#landuse — Public Fediverse posts on home.social

ˈdälfən™🐬 💥 🌊 @[email protected] · 2026-09-06 · 20:37 UTC

"Data centers represent 27% of development sites in the U.S. this year. It’s the second-highest category after apartment buildings..."

Land prices are up 79% from last year.

And "home builders cannot bid in that market, because a builder’s land budget is capped by what home buyers can afford. A data center operator faces no such constraint. The result is ... no homes at all."

#USA #AI #DataCenters #LandUse #housing #farming
---
https://www.cnbc.com/2026/09/06/ai-data-centers-are-transforming-rural-land-markets-fueling-backlash.html

#usa #ai #datacenters #landuse #housing #farming

ˈdälfən™🐬 💥 🌊 @dalfen · 2026-09-06 · 20:37 UTC

"Data centers represent 27% of development sites in the U.S. this year. It’s the second-highest category after apartment buildings..."

Land prices are up 79% from last year.

And "home builders cannot bid in that market, because a builder’s land budget is capped by what home buyers can afford. A data center operator faces no such constraint. The result is ... no homes at all."

#USA #AI #DataCenters #LandUse #housing #farming
---
https://www.cnbc.com/2026/09/06/ai-data-centers-are-transforming-rural-land-markets-fueling-backlash.html

#usa #ai #datacenters #landuse #housing #farming

ˈdälfən™🐬 💥 🌊 @[email protected] · 2026-09-06 · 20:37 UTC

"Data centers represent 27% of development sites in the U.S. this year. It’s the second-highest category after apartment buildings..."

Land prices are up 79% from last year.

And "home builders cannot bid in that market, because a builder’s land budget is capped by what home buyers can afford. A data center operator faces no such constraint. The result is ... no homes at all."

#USA #AI #DataCenters #LandUse #housing #farming
---
https://www.cnbc.com/2026/09/06/ai-data-centers-are-transforming-rural-land-markets-fueling-backlash.html

#usa #ai #datacenters #landuse #housing #farming

ˈdälfən™🐬 💥 🌊 @[email protected] · 2026-09-06 · 20:37 UTC

"Data centers represent 27% of development sites in the U.S. this year. It’s the second-highest category after apartment buildings..."

Land prices are up 79% from last year.

And "home builders cannot bid in that market, because a builder’s land budget is capped by what home buyers can afford. A data center operator faces no such constraint. The result is ... no homes at all."

#USA #AI #DataCenters #LandUse #housing #farming
---
https://www.cnbc.com/2026/09/06/ai-data-centers-are-transforming-rural-land-markets-fueling-backlash.html

#farming #housing #landuse #datacenters #ai #usa

ˈdälfən™🐬 💥 🌊 @[email protected] · 2026-09-06 · 20:37 UTC

"Data centers represent 27% of development sites in the U.S. this year. It’s the second-highest category after apartment buildings..."

Land prices are up 79% from last year.

And "home builders cannot bid in that market, because a builder’s land budget is capped by what home buyers can afford. A data center operator faces no such constraint. The result is ... no homes at all."

#USA #AI #DataCenters #LandUse #housing #farming
---
https://www.cnbc.com/2026/09/06/ai-data-centers-are-transforming-rural-land-markets-fueling-backlash.html

#usa #ai #datacenters #landuse #housing #farming

💧🌏 Greg Cocks @[email protected] · 2026-09-02 · 07:33 UTC

The Radiative Effects Of Water Vapour From Terrestrial Evapotranspiration
--
https://doi.org/10.1088/1748-9326/adde72 <-- shared paper/letter
--
https://zenodo.org/records/15413219 | https://zenodo.org/records/15416936 <-- shared open data, for “Model information and output for "The radiative effects…” ”
--
https://doi.org/10.1007/s11269-025-04191-w <-- shared paper
--
H/T @jan Umsonst | Earth System Nerd
“Water vapour accounts for roughly 50% of the modern greenhouse effect. Over continental regions, evapotranspiration (ET) is often limited by water availability. In this study, [the authors] spatially quantify how much of the total atmospheric water vapour evaporated most recently from land and calculate the relative contribution of that water vapour to the atmospheric radiative budget. Using a combination of tracer-enabled Earth system model simulations and radiative transfer calculations, [they were] able to explicitly quantify the 3D distribution of terrestrial vs. oceanic water vapour, and the spatial contribution of each to the surface and top of atmosphere radiative budgets. [They found] that over many continental regions, more than half of the total column-integrated water vapour originates from land ET, and that this vapour contributes up to 30 W/m² of longwave radiation into the surface in the annual mean (about 10% of the total). Understanding how terrestrial ET impacts the base-state of water vapour distribution and the water vapour greenhouse effect is critical to understanding how and where changes in terrestrial ET, driven by climate change, land use, etc, will modify the radiative properties of the atmosphere and thus the climate system…”
#water #hydrology #greehouseeffect #highperformancecomputing #HPC #evapotranspiration #Radiative #WaterVapour #spatial #spatialanalysis #spatiotemporal #atmosphere #model #modeling #earthsystemmodelling #terrestrial #oceanic #vapour #climatechange #landuse #changes #climatesystem

#water #hydrology #greehouseeffect #highperformancecomputing #hpc #evapotranspiration

💧🌏 Greg Cocks @[email protected] · 2026-08-14 · 03:26 UTC

Impact Of Urbanization Driven Land Use And Land Cover Change On Ecological Environmental Quality In Rupandehi Nepal Assessed Using The Remote Sensing Ecological Index
--
https://doi.org/10.1007/s44288-026-00650-y <-- shared paper
--
https://kathmandupost.com/money/2026/02/18/rupandehi-s-continued-urban-sprawl-comes-at-a-cost-for-agriculture-in-the-periphery <-- shared media article
--
H/T@ Gaurav Parajulim
“[The authors] studied how the ecological quality of Nepal's Rupandehi District has changed over three decades (1993–2023), using satellite imagery and the Remote Sensing Ecological Index (RSEI) to track the health of the landscape year by year and to understand how urbanization-driven land use change has reshaped it.
What [they] found tells a nuanced story: as Butwal and Bhairahawa grew and built-up land expanded, ecological quality shifted in ways that a single number can't capture, some areas recovered, others declined, and the patterns rarely moved in a straight line…”
--
“Rapid urbanization and population growth are major drivers of land use and land cover (LULC) change and can substantially alter ecological environmental quality (EEQ). This study assessed the spatiotemporal dynamics of LULC and their effect on EEQ in Rupandehi District, Nepal, over a 30-year period (1993–2023). Four ecological indicators representing greenness, wetness, dryness, and heat were derived from Landsat imagery in Google Earth Engine (GEE), and LULC was classified using a Support Vector Machine (SVM). The Remote Sensing Ecological Index (RSEI) was then constructed from these indicators using Principal Component Analysis (PCA) in ArcGIS Pro, and its spatial structure was examined using global and local spatial autocorrelation. The mean RSEI followed a non-linear trajectory, rising from 0.59 in 1993 to 0.635 in 2004, declining to 0.55 in 2013, and recovering to 0.67 in 2023, indicating an overall improvement in EEQ with a temporary mid-period decline. Over the same period, built-up areas expanded substantially and agricultural land declined, whereas forest cover fluctuated but showed a slight net increase by 2023, and barren land decreased markedly. Higher EEQ was concentrated in the forested northern hills, while lower values occurred in the urban centers of Butwal and Bhairahawa, closely matching the spatial pattern of LULC change. The results indicate that ecological quality reflects the combined influence of all land cover classes rather than any single class. This study provides a transferable and reproducible workflow for long-term ecological assessment based on openly available Landsat data, with the analysis code shared in a public repository, offering practical guidance for sustainable land management and environmentally responsible urban development...”
#GIS #spatial #mapping #RemoteSensing #GIS #RSEI #EnvironmentalMonitoring #Nepal #Research #GoogleEarthEngine #ArcGIS #EcologicalQuality #spatialautocorrelation #ecology #environment #earthobservation #RemoteSensingEcologicalIndex #landscape #urbanisation #urban #development #landuse #change #spatialanalysis #spatiotemporal

#gis #spatial #mapping #remotesensing #rsei #environmentalmonitoring

Alexander J. Stein @[email protected] · 2026-08-13 · 16:42 UTC

Adherence to an adapted Planetary Health Diet (more fruits & #legumes; less #dairy, red #meat, animal fats & added #sugar) in China was linked to reduced GHG #emissions, water use & #landuse, as well as lower risk of all-cause mortality: doi.org/10.1007/s003... #environment #health #footprint

#legumes #dairy #meat #sugar #emissions #landuse

Eric Maugendre about carbon @[email protected] · 2026-08-09 · 18:42 UTC

From Ireland Land Use Review latest report: “sustainable land use requires very significant change”.

Explanations by Caroline O'Doherty:
"Agriculture is the main polluter of waterways, half of which fail to meet minimum environmental standards.
"It is responsible for 38 per cent of national emissions – the largest of any sector.
"It is the number one pressure on wildlife and natural habitats, 90 per cent of which are in poor condition."

By subscription: https://www.irishtimes.com/life-style/2026/08/09/how-irelands-land-is-used-and-why-it-has-to-change/
Archived: https://archive.ph/Al4qw#selection-2163.0-2177.107

#landUse #viability #property #sustainability #water #publicHealth #biomethane #tillage #forestry #Ireland #emissions #agriculture #footprint #GHG #methane #globalHeating #agribusiness #meat #cattle #climateChange #dairy

#dairy #climatechange #cattle #meat #agribusiness #globalheating

💧🌏 Greg Cocks @[email protected] · 2026-07-28 · 05:07 UTC

Busy Beavers - The Turbidity Signature Of Ecosystem Engineers At Work
--
https://doi.org/10.1002/hyp.70661 <-- shared paper
--
H/T @alan Puttock
“Beavers are the quintessential ecosystem engineers. In slow-flowing streams, they create complex wetlands with ponds by building dams and canals that can positively impact biodiversity, hydrology and water quality. These activities can interchangeably capture or release sediment along the watercourse. To date this has not been quantified at the resolution of rainfall events or beaver activity. This study used 15-min frequency, sustained monitoring upstream and downstream of a newly establishing beaver wetland to measure episodic changes in water turbidity at an event resolution. Monitoring showed no significant differences between upstream and downstream turbidity over 160 days when the first pair of beavers, known not to be building dams or canals, were resident. Shortly after introduction of another beaver pair, however, dam building, burrows and canal excavations were quickly observed, resulting in the creation of a complex beaver wetland between 2021 and 2024. Monitoring over 375 days during this period showed significant differences. Downstream turbidity was significantly higher overall than upstream: 13.1 Nephelometric Turbidity Units (NTU) compared to 4.2 NTU. Stochastic spikes in downstream turbidity during the study period not recorded upstream were associated with dam building and burrowing. Overall, there was no significant difference in turbidity loads, which was at least partially explained by a reduction in discharge downstream, particularly in higher flows, during the dam building period. This demonstrates a complex system with the trapping of influent sediment, the storing of water and the periodic release of beaver wetland sediment leading to net balance in loads. These results help provide context for other studies which have used temporally discrete sampling campaigns rather than continuous high-frequency monitoring. They provide a unique insight into the downstream impacts of a rapidly developing beaver wetland over its first three and a half years in a landscape that hasn't had beavers for over 400 years…"
#hydromorphic #water #hydrology #dam #beaverdam #waterquality #biodiversity #ecology #benefits #NatureBasedSolutions #Wetlands #Ecology #Biodiversity #EnvironmentalScience #Wildlife #Ecosystem #bioviversity #conservation #restoration #landscaperecovery #floodmanagement #FloodMitigation #flooding #energy #floodrisk #sustainability #wetlands #hydrography #dams #impoundment #deadwood #waterresources #landscapeengineer #benefits #vegetation #ecology #ecosystem #riversystemsstabilisation #naturalwaterregulation #resilience #valleysreborn #fisheries #invertebrates #extremeweather #floodflows #sediment #baseflow #drought #landmanagement #naturalsystems #landuse #monitoring #spatialanalysis #spatiotemporal

#hydromorphic #water #hydrology #dam #beaverdam #waterquality

Eric Maugendre about carbon @[email protected] · 2026-07-27 · 20:46 UTC

#Mining sub-Saharan Africa is expanding rapidly. This poses a key threat to tropical forests.

"For every hectare of direct deforestation due to the mine footprint, mining triggers, on average, 34 hectares of additional offsite loss within five years through ancillary activities, including agriculture and settlements. Mines extracting cobalt and copper—key energy transition minerals—caused the highest amount of additional deforestation."

Morton et al. (2026). "Mining triggers extensive additional deforestation in sub-Saharan Africa" https://doi.org/10.1038/s41586-026-10551-2 🧩 🧵

#extraction #landscape #pollution #cobalt #copper #gold #climateChange #rivers #deforestation #soil #carbon #causality #land #footprint #forests #landLoss #landUse #Africa #Congo #DRC #Centrafrique #Zambia #ZA #SouthAfrica

#southafrica #za #zambia #centrafrique #drc #congo

John Poole @[email protected] · 2026-07-26 · 23:30 UTC

Lehigh County Controller Mark Pinsley recommends requiring new data centers to cover their eventual decommissioning costs. That makes absolute sense: taxpayers should not inherit the cost of dismantling abandoned industrial infrastructure.

Video:
https://www.instagram.com/reel/DbOMvv0jlAt/

Provision text:
https://salemdata.net/CityOfSalem/other/BradfordCounty_Decommissioning_Provision_Corrected.txt

#DataCenter #DataCenters #Decommissioning #TaxpayerProtection #LocalGovernment #PublicPolicy #LandUse #EnergyPolicy #Accountability #SalemOR

#datacenter #datacenters #decommissioning #taxpayerprotection #localgovernment #publicpolicy

Alexander J. Stein @[email protected] · 2026-07-23 · 15:43 UTC

#Sugar is produced in high volumes and often consumed as empty calories in #confectionery products—40% of which in Europe, where related GHG #emissions are 3m tons CO₂eq and #landuse is 250k ha. Reallocation of land from sugar crops could improve #environment & human health: doi.org/10.1007/s410...

Land Use and Greenhouse Gas Em...

#sugar #confectionery #emissions #landuse #environment

💧🌏 Greg Cocks @[email protected] · 2026-07-14 · 03:14 UTC

Mapping Multifunctionality In Remote Patagonian Forest Landscapes Reveals High-Value Ecosystems Beyond Protected Areas
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https://doi.org/10.1038/s43247-026-03515-x <-- shared paper
--
H/T @Peter Potapov | Researcher at the World Resources Institute (WRI)
“This paper is] a strong example of multifunctionality analysis applied to conservation planning. The study mapped six ecosystem functions, including carbon storage, nutrient availability, water regulation, erosion control, habitat quality, and ecological connectivity. [The author] combined satellite data, field soil sampling, and spatial modeling for this comprehensive analysis.
Two findings stand out.
1. Old-growth forests had the highest multifunctionality index of any land cover type.
2. 78.5% of the top multifunctionality hotspots fall outside the region's protected areas, even though PAs already cover more than 54% of the territory.
Together, these results make a clear case for expanding conservation of the remaining Intact Forest Landscapes and primary forests in Patagonia and elsewhere…”
--
“Remote forest landscapes provide critical references for understanding ecosystem functions (EFs) under low anthropogenic pressure, yet their capacity to sustain multiple EFs simultaneously remains poorly understood. [They] assessed landscape multifunctionality in western Patagonia by integrating satellite indicators, field data, and spatial modeling. Six EFs (carbon storage, nutrient availability, water regulation, erosion control, habitat quality, and ecological connectivity) were mapped, and their spatial relationships and hotspot distribution within and outside protected areas (PAs) were analyzed. Old-growth and secondary forests showed the highest functional performance. Strong synergies (ρ ≥ 0.6) between carbon storage and nutrient availability covered >50% of the landscape, whereas strong trade-offs (ρ ≤ –0.6) were spatially limited ( < 6%). Notably, 78% of multifunctionality hotspots occurred outside PAs, indicating that high-functional-value areas extend beyond formal conservation boundaries. These findings reveal spatial mismatches between multifunctionality and protection status and provide a replicable framework for integrating multifunctionality into conservation planning under global change…”
#Patagonia #chile #aysen #coyhaique #landcover #mapping #spatial #spatialpatterns #spatiotemporal #spatialanalysis #forest #vegetation #oldgrowth #secondgrowth #shrubland #grassland #steppe #ecosystem #habitat #nutrients #water #hydrology #erosion #multifunctionality #multifunctionalityanalysis #protectedareas #landuse #conservationplanning #conservation #ecology #carbonstorage #nutrientavailability #waterregulation #erosioncontrol #habitatquality #ecologicalconnectivity #remotesensing #satellite #earthobservation #modeling

#patagonia #chile #aysen #coyhaique #landcover #mapping

💧🌏 Greg Cocks @[email protected] · 2026-07-14 · 03:00 UTC

Eager Beavers - Rodents Engineer Czech Wetland Project After Years Of Human Delay [ecosystem engineers]
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https://www.theguardian.com/world/2025/feb/11/beavers-save-czech-taxpayers-by-flooding-ex-army-training-site <-- shared technical media article
--
https://en.wikipedia.org/wiki/Beaver-engineered_dam_in_the_Czech_Republic <-- shared wiki technical page
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https://phys.org/news/2025-02-fine-beavers-czech-treasury-million.html <-- shared technical article
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https://youtu.be/GSTw8qmBP4Y?si=XK2Iy2pAltW91flj <-- shared video (Czech)
--
H/T @ScienceGirl
"We don't expect any conflict with the beaver in the next 10 years," ~ Bohumil Fiser from the Czech Nature Conservation Agency
--
“For seven years, planners struggled to complete a $1.2 million wetland restoration project in the Brdy region of the Czech Republic. The goal was to build a dam that would improve water management and bring back valuable wetland habitat, but the project remained trapped in a maze of permits and approvals.
Then a family of eight Eurasian beavers did what engineers had planned… without permits, machinery, or a budget.
The beavers built a network of dams in almost the exact area chosen for the proposed project, naturally restoring the wetland system officials had spent years trying to create. After seeing the results, authorities decided there was little point continuing with the original human-built dam.
Although some reports suggested the beavers completed the work overnight, experts say their construction likely took several weeks. The reason it seemed sudden is that the animals quietly worked away until their finished dams became impossible to miss.
Beavers are known as “ecosystem engineers” because their behaviour can reshape entire environments. By cutting trees and blocking streams, they create ponds and wetlands that support countless species, including fish, amphibians, insects, birds, and mammals.
Their wetlands also act as natural water reservoirs, helping during droughts, reducing flood risks, filtering water, storing carbon, and keeping landscapes wetter during wildfires…
Once heavily hunted across Europe, beaver populations have been recovering thanks to conservation efforts, proving that sometimes nature can solve problems humans spend years trying to fix…"
#water #hydrology #KlabavaRiver #Czech #BrdyRegion #protected #CzechRepublic #armytraining #military #beaver #Eurasianbeavers #dam #beaverdam #waterquality #restoration #biodiversity #crayfish #wetland #ecology #benefits #Beavers #NatureBasedSolutions #Wetlands #Ecology #Biodiversity #Agroforestry #EnvironmentalScience #Conservation #Wildlife #Ecosystem #bioviversity #conservation #restoration #landscaperecovery #EcosystemEngineers #nature #floodmanagement #FloodMitigation #flood #flooding #energy #floodrisk #sustainability #wetlands #hydrography #dams #impoundment #deadwood #waterresources #landscapeengineer #agriculture #benefits #vegetation #ecology #ecosystem #riversystemsstabilisation #naturalwaterregulation #resilience #drought #wildfire #valleysreborn #slowdetermination #fisheries #invertebrates #extremeweather #floodflows #sediment #baseflow #drought #landmanagement #naturalsystems #landuse #ecosystemengineers #watermanagement

#water #hydrology #klabavariver #czech #brdyregion #protected

Alexander J. Stein @[email protected] · 2026-07-08 · 17:13 UTC

With 17 Mha of UK land used for #agriculture and 11 Mha agricultural land abroad linked to food & feed #imports, the land #footprint of these imports should be an important focus when evaluating #environment consequences of UK food consumption: doi.org/10.1371/jour... #FoodSecurity #Trade #LandUse

Global land footprint of UK fo...

#agriculture #imports #footprint #environment #foodsecurity #trade

💧🌏 Greg Cocks @[email protected] · 2026-06-09 · 15:13 UTC

On The Use Of Rainfall Time Series For Regional Landslide Prediction By Means Of Functional Regression
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https://doi.org/10.1016/j.enggeo.2026.108860 <-- shared paper
--
#rainfallinduced #landslide #Functionalregression #Japan #Earlywarningsystem #Spacetimeprediction #spatialanalysis #spatiotemporal #massmovement #engineeringgeology #geomorphology #hydrogeomorphology #geomorphometry #remotesensing #geostatistics #model #modeling #mechanics #rainfall #threshold #precipitation #water #hydrology #risk #hazard #hazardassessment #terrain #landscape #landform #landuse #geology #soil #lithology #functionalGeneralizedAdditiveModel #FGAM #prediction #casestudy #AI #LLM

#rainfallinduced #landslide #functionalregression #japan #earlywarningsystem #spacetimeprediction

DoomsdaysCW @[email protected] · 2026-06-07 · 17:13 UTC

Legacy of #Indigenous #stewardship of #camas dates back more than 3,500 years, #OSU study finds

May 20, 2024

Excerpt: CORVALLIS, Ore. — "An #Oregon State University study found evidence that Indigenous groups in the #PacificNorthwest were intentionally harvesting edible #CamasBulbs at optimal stages of the plant’s maturation as far back as 3,500 years ago.

"The findings contribute to the growing body of research around #TraditionalEcologicalKnowledge and practices, demonstrating the care and specificity with which Indigenous groups have been stewarding and cultivating natural resources for millennia.

"Camas is an #ecological and cultural keystone, meaning it is a species that many other organisms depend on and that features prominently within many cultural practices.

" 'If you think about #salmon as being a charismatic species that people are very familiar with, camas is kind of the plant equivalent,' said Molly Carney, an assistant professor of anthropology in OSU’s College of Liberal Arts and lead author on the study. 'It is one of those species that really holds up greater #ecosystems, a fundamental species which everything is related to.'

"An eye-catching blue flower that grows widely throughout the Pacific Northwest, camas is referred to in Indigenous calendars across the region, with the plant’s growth stages used as a sort of seasonal benchmark. It is often included in traditional #FirstFood ceremonies, in which tribal communities mark the coming of spring with the first #SalmonRun or the first #EdibleRoots after a long winter, Carney said.

"Camas bulbs must be baked for two to three days to render them edible. Once soft, the bulbs taste a bit like sweet potato, Carney said. Traditional baking was done in underground ovens using heated rocks."

#SolarPunkSunday #LandUse
#IndigenousFoods #CulturalPreservation
#NativeAmericanHistory #IndigenousStewardship #IndigenousHistory #TraditionalFoods
#TraditionalFoodSources #KeystoneSpecies #PNW #TEK

#indigenous #stewardship #camas #osu #oregon #pacificnorthwest

Eric Maugendre about carbon @[email protected] · 2026-06-03 · 16:45 UTC

"The authors report that the occurrence of extensive deforestation in tandem with climate change will cause the remaining rainforest to lose resilience at global-warming levels of or slightly higher than 1.5 °C — rather than 4 °C — above pre-industrial levels".

Wunderling, N., Sakschewski, B., Rockström, J. et al. "Deforestation-induced drying lowers Amazon climate threshold." (2026). https://doi.org/10.1038/s41586-026-10456-0

#droughts #deforestation #landGrab #landUse #landUseChange #forests #forest #carbon #carbonSinks #carbonSink #footprint #Brazil #beef #cattle #Amazon #Amazonia #climateChange

#climatechange #amazonia #amazon #cattle #beef #brazil

Panethos @[email protected] · 2026-06-01 · 08:00 UTC

A comprehensive list of the tallest water towers [vodárenské věže] of Czechia

Provided below is a comprehensive working list of the tallest water towers (vodárenské věže) of Czechia. Currently, the compendium includes 285 water towers for which the height is known. The year completed is known for a number of others. As additional data is discovered, the list will be updated accordingly.

As has been. seen previously with water towers in Kuwait, Belgium, and elsewhere, the water tank is not necessarily set at the apex of the tower itself. Regardless, the height is measured to the top of the structure, whether the tank is placed specifically there or not.

Peace/Mír!

Translations:

Nova = New
Novy = New
Věž = Tower
Věže = Towers
Vodárenská = Waterworks
Vodárenské = Waterworks
Vodojem = Reservoir
Vrch = Hill

Dvůr Králové nad Labem (1941) = 80 m/262.5 feet (water tank is set on the chimney at 30 m)

Dvur Kralove nad Labem – Source: vezovevodojemy.cz

2. Nymburk (1917) = 73 m/239.5 feet (water tank set on the chimney at 35 m)

3. Ostrava-Kunčice (1972) = 71.2 m/233.6 feet

4. Choceň (1929) = 70 m/229.7 feet (water tank set on the chimney at 30 m)

5. Borovany (1988) = 65.4 m/214.6 feet

Borovany – Source: vezovevodojemy.cz

6-7. Dobrovice (1912) = 65 m/213.3 feet (water tank is set on the chimney at 35 m) and Roudnice nad Labem (1949) – (water tank is set on the chimney at ? m)

Dobrovice – Source: vezovevodojemy.cz

8. Teplice-Nová (1989) = 63 m/206.7 feet

Teplice-Nová – Source: visitteplice.com

9-10. Olomouc-Nová Ulic (1973) and Přelouč (1932) = 62 m/203.4 feet

11. Práčov Vodárenská (1953) = 57.9 m/190 feet

12. Třinec-Staré Město = 54.6 m/179.1 feet

13. Staromestske (1577): Prague = 53 m/173.9 feet

14-16. Plzeň Brewery (1907); Kladno-Dubí; and Liberec-Vratislavice nad Nisou (1919) = 52 m/170.6 feet

17. Kladno-Rozdělov (1958) = 51 m/167.3 feet

18-21. Děvín (1977): Prague; Břest; Kolín (1922) – (tank is set on the chimney at 25 m); Libiš (1946); = 50 m/164 feet

22. Stonava (1976) = 48 m/157.5 feet

23. Ostrava-Svinov (1910) = 47.5 m/155.8 feet

24-29. Šítkov (1591): Prague; Bohunovice; Chropyně (2020); Prague-Ruzyně (1935); Ostrava-Kunčice (1997); and Prague-Čakovice (ca 1971) = 47 m/154.2 feet

30. Hradec Králové (1935)= 46 m/150.9 feet

Hradec Králové (water tank is where the clock is located) – Source: vezovevodojemy.cz

31-35. Breclav (1927); Hrady (1908); Kolín (1930); Poděbrady (1930); and Libčice nad Vltavou (1921) = 45 m/147.6 feet

36. Ceske Budejovice (1882) = 44.3 m/145.3 feet

Ceske Budejovice – Source: outdooractive.com

37-38. Bohumín-Starý (1963) and Sudkov (1908) – (tank is set on the chimney at 25 m) = 44 m/144.4 feet

39. Dolní Lutyně (1966)= 43.6 m/143 feet

40-41. Kbley Airport (1930): Prague and Chudeřice (1916) = 43 m/141.1 feet

Kbley – Source: cs.wikipedia.org

42. Bohnice (1909): Prague = 42.6 m/139.8 feet

43. Chrast (1929) = 42.5 m/139.4 feet

Chrast – Source: vezovevodojemy.cz

44-46. Poděbrady (1929); Vršovická (1907): Prague; and Libeň (1904): Prague – now a duplex dwelling = 42.2 m/138.4 feet

47-52. Praha-Michle (1907): Prague; Novomlýnská (1660): Prague; Třeboň-Kotěrova (1909); Praha-Bubeneč (1888) Prague; Praha-Vysočany (1935) Prague; and Bílina-Chudeřice (1917) = 42 m/137.8 feet

Novomlýnská (New Mill) – Source: verliefdoppraag.nl/blog

53. Ostrava-Vítkovice (1962) = 41 m/134.5 feet

54-55. Kladno-Rozdělov (1933): and Kladno = 40.6 m/133.2 feet

56. Břeclav (1927) = 40.2 m/131.9 feet

Břeclav – Source: vezovevodojemy.cz

57-59. Vinohradská (1882): Prague – being converted into a water education center; Litovel-Nasobůrky (1917) – (tank is set on the chimney at 21 m) ; and Mělník (1948) (tank is set on the chimney at 25 m) = 40 m/131.2 feet

Litovel-Nasoburky – Source: vezovevodojemy.cz

60. Karviná (1929) = 39.4 m/129.3 feet

61-63. Bohumín-Novy (1935); Bohumín-Pudlov (1961); and Albrechtice (1993) = 39 m/127.9 feet

64. Letné (1888): Prague = 38.3 m/125.6 feet

65. Ostrava-Muglinov x 2 (1985) = 38.2 m/125.3 feet

66-69. Hradec Králové-Třebeš (1936); Pečky (1932); Ostrava-Mariánské Hory (1928); and Petřvald (1987) = 38 m/124.7 feet

70. Soběšovice-Pitrov (1985) = 37.5 m/123 feet

71. Petřvald (2009) = 37.1 m/121.7 feet

72-75. Nymburk (1903); Meziměstí; Opava-Předměstí; and Třeboň (1909) = 37 m/121.4 feet

76. Pardubice-Semtín (1923) = 36.8 m/120.7 feet

77. Louny (1936) = 36.5 m/119.7 feet

78. Praha-Vinohrady (1891): Prague = 36.4 m/119.4 feet

79-80. Holešov (2009) and Vítkov (1977) = 36 m/118.1 feet

81. Opava-Vlaštovičky (1995) = 35.7 m/117.1 feet

82. Ostrava-Zábřeh-Hulváky (1971) = 35.5 m/116.5 feet

83-86. Týniště nad Orlicí (1928) – now a museum; Kojetice; Ostrava-Kunčice (1981); and Velký Osek = 35 m/114.8 feet

87. Skřipov (1999) = 34.9 m/114.5 feet

88. Jaroměř (1928)= 34.8 m/114.2 feet

89. Hranice (1968) = 34.6 m/113.5 feet

90-92. Petržilkovská (Lesser Town) (1562): Prague; Jaroměř-Josefov (1913); and Uherské Hradiště (1917) = 34 m/111.5 feet

93. Holasovice (1999) = 33.5 m/109.9 feet

94. Děčín-Rozbělesy (~1968) = 33.1 m/108.6 feet

95-97. Suchý Vrch (1932); Cvikov (1933); and Velká Polom (1974) = 33 m/108.3 feet

98-99. Český Těšín-Koňákov (1992) and Těrlicko-Horní Těrlicko (1992) = 32.4 m/106.3 feet

100-104. Hněvošice (1988); Hněvošice (1984); Chlebičov (1988); “Orion Chocolate” (1985): Slavkov; and Šumvald (2020) = 32 m/104.5 feet

105. Holasovice-Kamenec (2002) = 31.9 m/104.7 feet

106. Panenský Týnec (1996) = 31.7 m/104 feet

107. Třebom = 31. 5 m/103.3 feet

108. Slaný = 31.2 m/102.4 feet

109-111. Ledčice (1991); Orličky (1932); Vilémov-Zahorany (1920) – (tank set on chimney at 15.5 m) = 31 m/101.7 feet

112. Petřvald (1954) = 30.6 m/100.4 feet

113. Vráž (1935) = 30.4 m/99.7 feet

114. Opava-Předměstí (1968): = 30.3 m/99.4 feet

115-116. Budčeves and Cvikov-Lindava (2013) = 30+ m/98.4 feet

117-122. Ohrazenice (2019) – also employs solar power; Brno-Kohoutovice (1973): Brno; Benátky nad Jizerou “Venice Tank” (1930); Hrušov (1984); Kozmice (1995); Staňkov-Krchleby; and Terezín (1936) = 30 m/98.4 feet

Ohrazenice – Source: researchgate.net

123. Nymburk (1950) = 29.4 m/96.5 feet

124-125. Tuřany and Ústí nad Labem (1928) = 29 m/95.1 feet

126-128. Bohumín-Pudlov (1961); Dobřany (1876); and Řepiště (1988) = 28.5 m/93.5 feet

129-134. Bělá pod Bezdězem (1926); Dobřany (1907); Kouřim (1930); Ostrava-Kunčice (1952); Ostrava-Kunčice (1960); and Spálov (1978) = 28 m/91.9 feet

135-136. Opařany (1901) and Rybník (1934) = 27.9 m/91.5 feet

137. Veselí nad Lužnicí (1935) = 27.1 m/88.9 feet

138. Dvůr Králové nad Labem (1985) = 27 m/88.6 feet

139-140. Lučina (1958) and Roudnice nad Labem (1928) = 26.6 m/87.3 feet

141. Buštěhrad (1933) = 26.5 m/86.9 feet

142-144. Opařany (~1901); České Velenice; and Svatý Mikuláš-Sulovice (2013) = 26.3 m/86.3 feet

145. Horní Bukovina (1935) = 26.2 m/86 feet

146-147. Mladá Boleslav (1896) and Přerov (1943) = 26 m/85.3 feet

148. Hradec nad Moravicí-Jakubčovice (1994) = 25.9 m/85 feet

149-150. Niměřice-Horní Cetno (1925) and Pardubice-Pardubičky (1907) = 25.5 m/83.7 feet

151. Lázně Bohdaneč (1911) = 25.3 m/83 feet

152-157. Kostelíček: Třebíč – now an observation tower; Chotěboř (1879); Hodonín; Kraslice (1904); Staré Město (1953); and Vysoké nad Jizerou (1931) = 25 m/82 feet

Kralice – Source: upload.wikimedia.org

158. Borovany (1931) = 24.9 m/81.7 feet

159-160. Náměšť na Hané (1987) and Višňová (1920) = 24.7 m/81 feet

161. Studénka (1939) = 24.4 m/80 feet

162. Oslavany (1913) = 24.2 m/79.4 feet

163. Chrašický (1755): Chrast = 24 m+/78.7 feet

164-169. Zamberk (late 16th Century); Praha-Běchovice (1939): Prague; Peruc (1928); Rosice (1927); Strašnov (1984); and Sychrov Castle (1891) = 24 m/78.7 feet

Sychrov – Source: vezovevodojemy.cz

170. Cerhenice (2014) = 23+ m/75.5 feet

171-172. Praha-Holešovice (1895): Prague and Sázava = 23 m/75.5 feet

173. Velešín (1930) = 22.7 m/74.5 feet

174-176. Dašice (1921); Františkov nad Ploučnicí (1911); Potštejn (1920); and Vratimov (1931) = 22 m/72.2 feet

178-179. Týnec nad Labem (1921) and Bezno (1914) = 21.8 m/71.5 feet

180. Peruc (1928) = 21.4 m/70.2 feet

181-184. Kladruby nad Labem (1925) – now an observation tower; Vratimov (1931); Praha-Uhříněve: Prague; and Olomouc-Pavlovičky (1935) = 21 m/68.9 feet

185. Bílá Hlína (1934) = 20.9 m/68.6 feet

186-191. Jaroměř (1928); Letovic (1911)’: Třebíč (1936) – now a water museum and lookout; Hevlín (1969); Ostrava-Moravská Ostrava (1903); and Trhové Sviny-Něch (1927)= 20 m/65.6 feet

Třebíč – Source: http://www.visittrebic.eu

192. Bechyně-Senožy (1926) = 19.5m/64 feet

193-194. Frýdek-Místek (1998) and Hradec nad Moravicí-Domoradovice (1984) = 19.4 m/63.6 feet

195. Čavisov (2008) = 19.3 m/63.3 feet

196-201. Česká Třebová-Parník (1895); Horní Kruty (1927); Chrudim (1913); Mladá Boleslav-Čejetice (1923); Rabštejnská Lhota-Rabštejn (1975) and Valašské Meziříčí-Krásno nad Bečvou (1930) = 19 m/62.3 feet

202. Starý Bydžov (1998) = 18.5 m/60.7 feet

203-204. Máslovice (1935) and Opava-Předměstí (1892) = 18.4 m/60.4 feet

205-209. Benátky nad Jizerou (1932); Mečeříž (1913); Frýdek-Místek-Lískovec (1973); Most-Kopisty; and Opava-Předměstí (1911) = 18 m/59.1 feet

210-212. Budišovice (1982); Olšany (1930); and Uhlířov = 17.9 m/58.7 feet

212. Suchá Lhota (1929) = 17.7 m/58.1 feet

214-215. Česká Lípa (1892) and Měnín-Jalovisko (1926) = 17.5 m/57.4 feet

216. Podbořany (1923) = 17.3 m/56.8 feet

217. Řepníky-Popovec (1930) = 17 m/55.8 feet

218. Václavovice (1977) = 16.9 m/55.4 feet

219. Chocnějovice-Rostkov (1923) = 16.5 m/54.1 feet

220-221. Bělá pod Bezdězem-Bezdedice (1930) and Hlučín (1913) = 16.2 m/53.1 feet

222-229. Heřmanova Huť (1908); Malé Všelisy (1912); Bělá pod Bezdězem-Hlínoviště (1927); České Budějovice (1870); Chotěboř (1871); Koleč (1873); Ostrava-Moravská Ostrava (1911); and Velké Všelisy-Malé Všelisy (1912) = 16 m/52.5 feet

230. Pardubice (1899) = 15.9 m/52.2 feet

231-233. Bohumín-Novy Bohumín (1908); Stěbořice (1974); and Uhlířov = 15.8 m/51.8 feet

234-235. Hostín (1932) and Návsí (1889) = 15.7 m/51.5 feet

236. Ostrava-Slezská Ostrava (1909) = 15.5 m/50.9 feet

237. Heřmanova Huť-Dolní Sekyřany (1909) = 15.4 m/50.5 feet

238. Březová-Jančí (1974) = 15.2 m/49.9 feet

239-241. Hlučín Křinec-Zábrdovice (1912); Lovosice (1897); and Turnov (1929) = 15 m/49.2 feet

242. Skalice nad Svitavou (1910) = 14.6 m/47.9 feet

243. Pardubice-Dražkovice (1900) = 14.4 m/47.2 feet

244-245. Nechanice-Lubno and Olomouc-Hodolany = 14.3 m/46.9 feet

246-247. Hořičky (1925) and Kobyly-Kojecko (1925) = 14 m/45.9 feet

248-249. Čerčany (1898) and Turnov (1939) = 13.8 m/45.3 feet

250. Nová Ves nad Lužnicí = 13.6 m/44.6 feet

251-252. Chrastava (1905) and Mikulov (1920s) = 13.5 m/44.3 feet

253. Jaroměř (1901) = 13.4 m/44 feet

254. Hlučín-Darkovičky (1954) = 13.3 m/43.6 feet

255-257. Holany-Loubí (1911); Hradec Králové-Pražské Předměstí (1931); and Veselí nad Lužnicí (1887) = 13 m/42.6 feet

258. Kobyly-Sedlisko (1923) = 12.9 m/42.3 feet

259-260. Rakovník (1917) and Ročov (1960) = 12.5 m/41 feet

261-267. Hodkovice nad Mohelkou (1859); Chrudim; Kanina (1913); Kolín-Zibohlavy (1927); Krupka; Nové Město nad Metují (1875); Štědrá (1898); and Zabrušany-Želénky (1934) = 12 m/39.4 feet

268-269. Moravská Třebová (1889) and Třeboň (1899) = 11.9 m/39 feet

270-273. Branná (1888); Nebužely (1925); Olomouc-Bělidla (1868); and Velká Kraš-Hukovice (1896) = 11.7 m/38.4 feet

274-275. Jizerní Vtelno and Vápenná (1896) = 11.6 m/38.1 feet

276. Malá Morávka (1901) = 11.5 m/37.7 feet

277-279. Lhotky; Měchenice (1897) and Třebívlice (1898) = 11.4 m/37.4 feet

280-282. Dobruška (1908); Senice na Hané (1943); and Třebovice (1889) = 11 m/36.1 feet

283-284. Kovanec (1909) and Novosedly (1948) = 10.9 m/35.8 feet

285. Přerov-Lověšice (1909) = 10.8 m/35.4 feet

286. Poběžovice (1900) = 10.6 m/34.8 feet

287. Ledeč nad Sázavou (1903) = 10.5 m/34.4 feet

288. Blatná (1899) = 10.4 m/34.1 feet

289. Vlašim (1895) = 10.2 m/33.5 feet

290-294. Spikaly (1914); Katusice-Spikaly (1914); Kutná Hora (1905); Osečany (1927); and Strakonice-Dražejo = 10 m/32.8 feet

Need more information:

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Postupice-Nová Ves
Pracejovice (1926)
Prague-Horni Pocernice
Praha-Hostivař
Praha-Smíchov (1990)
Praha-Uhříněves
Prachovice
Prazska Street (1532): Plzeň
Předměřice nad Labem
Premyslovice
Premyslovice 2
Přibice
Přibyslav
Prostějov
Protivanov
Prušánky
Pustá Dobrá
Rabštejnská Lhota
Račiněves
Radíkov (1976)
Radkov
Radkovy
Radosov
Radslavice
Rakovník
Ralsko-Ploužnice
Ralsko-Ploužnice 2
Rapšach
Rasošky
Rebešovice
Řečany nad Labem
Řitka
Roblín
Rohozec
Rokycany
Rokytovec (1935)
Roztoky
Rychnovek-Zvole
Šachov
Šanov (2020)
Sázava
Sázava 2
Šebířov
Sedlice (2005)
Sedlisko
Ševětín
Skalsko
Skuhrov
Slabce
Slapy
Slatina u Velvar
Slatiny
Slavkov
Slavkov u Brna
Slezská Ostrava x 2
Slezské Pavlovice
Slezské Rudoltice x 2
Smiřice
Sobotka
Sobotka-Staňkova Lhota
Sobotovice (2000)
Špičky
Stará Červená Voda
Stará Lysá
Štarnov
Starovičky
Stařeč “Orion Chocolate”
Štěchovice
Štěpánkovice
Štěpánov-Moravská Huzová
Štětí-Chcebuz
Strachotice
Strachotice-Micmanice
Stochov (1950)
Strakov
Stratov (1976)
Stráž-Souměř
Strážnice
Střelice
Strenice
Stříbrná Skalice
Strmilov (1984)
Struhařov
Studénka-Butovice
Studénka 2
Studeněves
Suchdol nad Lužnicí
Suchdol nad Lužnicí (2003)
Suchdol nad Odrou
Suchohrdly
Sudice (1963)
Šumná
Šumvald 2
Šumvald 3
Švábenice
Svatý Mikuláš
Svéradice
Světec-Chotějovice
Sviadnov
Sviny
Sychrov Castle (1891)
Tabor Vodárenská Věž (1502): Tabor
Tasovice
Teplá-Kladruby u Beranova
Teplá-Beranov
Teplice-Řetenice (2007)
Teplice-Řetenice 2
Terezín-Nové Kopisty (1987)
Terlico
Těšetice
Těškovice (1988)
Tísek
Tišnov (1952)
Tištín
Třebeň-Lesina
Třebeň-Nový Drahov
Třebešice (2011)
Třebíč Hospital (1936)
Třeboň-Břilice
Třebonín
Trhový Štěpánov-Střechov nad Sázavou
Trnávka
Trstěnice
Trusnov
Tuchoměřice-Kněžívka (1989)
Tuchoraz (1980)
Tuřany (1957)
Tutleky
Týnec
Týnec nad Labem 2
Týniště (1927)
Uherské Hradiště
Uherský Ostroh
Uherský Ostroh-Ostrožské Předměstí
Újezd-Haukovice
Úlibice
Únanov
Úněšov
Únětice
Uničov
Uničov-Brníčko
Uničov-Střelice
Ústí
Ústí nad Labem-Neštěmice
Ústí nad Orlicí-Knapovec
Vacenovice
Vacenovice 2
Velenice (1994)
Valtice
Valtrovice
Varnsdorf (1898)
Varnsdorf 2
Velemyšleves-Minice
Velká Chmelištná
Velké Albrechtice
Velké Bílovice
Velké Heraltice
Velké Všelisy
Velký Karlov
Velky-Osek 2
Velký Týnec
Velký Týnec 2
Vesce
Velešín
Velichovky
Věrovany
Verušičky-Luka
Veselí nad Mora
Veselí nad Mora 2
Větrušice
Veze Bohumin
Vidim (1903)
Vintířov
Višňová 2
Vítězná-Kocléřov
Vlastiboř-Záluží
Vlčice
Vlkaneč
Vodárenská věž v Chrustenicích
Vodárenská věž v Duchcově (1911): Duchcově (at Engel’s Glass Works)
Vodárenská věž (Mělník)
Vodárenské věže, Kobeřice x 2
Vodárenská věž Ostrava-Hladnov (1909)
Vodojem Hořičky (1907)
Vodojem Kojetice
Vodojem Kostelec nad Labem
Vodárna Křinec
Vodojem (Nový Dvůr)
Vodojem (Poděbrady)
Vodojem u Sklárny
Vodojem, Tištín
Vodojem Třebeš
Vodojem (Zruč Senec)
Vraclav
Vranín
Vranovice
Vrátkov
Vražné
Vrbátky-Dubany
Vrbátky-Štětovice
Vrbovec
Všelibice-Vrtky (1987)
Výškov-Třískolupy
Vyskytná nad Jihlavou-Hlávkov
Vysoká 2
Vysoké Chvojno
Vysoké Mýto (1768 as a water tower)
Vyžlovka
Žabčice
Zábřeh
Zákupy (1711)
Zákupy-Brenná
Zaloňov
Zálužice-Stekník
Zápy
Zápy (1990)
Žáravice
Zašová
Žatec
Žatec 2
Závada
Žďár
Žďár nad Sázavou-Město Žďár
Zdětín
Zdětín 2
Žebrák
Želatovice
Želeč
Zeleneč
Zemědělské družstvo
Zhoř
Zibohlavy (1927)
Zlatníky-Hodkovice
Žleby
Žleby-Markovice
Zlín-Salaš
Zlonice
Znojmo (1948)
Zruč-Senec (2013)
Zvěrkovice

SOURCES:

#cities #CzechRepublic #Czechia #Europe #geography #history #industry #landUse #preservation #reuse #statistics #tourism #towers #travel #vodárenskéVěže #waterTowers

#cities #czechrepublic #czechia #europe #geography #history

Panethos @[email protected] · 2026-05-28 · 08:00 UTC

Czechia’s mighty chimney-mounted water towers

While studying the water towers (vodárenské věže) of Czechia (formerly Czech Republic) an impressive collection of water towers built as a part of industrial chimneys was identified. Images of the nine (9) remaining historical sentinels (of the original 20) are provided below along with a brief background history. The tremendous resource for the data and images contained within this post is the www.vezovevodojemy.cz website.

Sites of the nine (9) remaining chimney water towers of Czechia – Map created by maps.google.com

Two (2) of these chimneys have been beautifully maintained or restored, as depicted in the first two images below. Hopefully, in time, the other towers can be cared for so they are preserved for future generations to marvel.

Peace/Mír!

Litovel-Nasoburky (1917) = 40 meters/131.2 feet tall (water tank is set at 21 meters). Serves the Litovel Food Factory (now Alibona). The 35 cubic meter.9,246 gallon water tank is still in operation, so both it and the chimney receive routine care and maintenance.

Litovel-Nasoburky – Source: vezovevodojemy.cz Litovel-Nasoburky – Source: vezovevodojemy.cz

Dobrovice (1912) = 65 meters/213.3 feet tall (water tank is set on the chimney at 35 m). The tank holds 35 cubic meters/9,246 gallons of water. The structure serves/d the Prince Alexandra of Thurn & Taxis sugar factory. The chimney is still in use, but the water tank is no longer.

Dobrovice – Source: vezovevodojemy.cz Dobrovice in 1927 – Source: vezovevodojemy.cz

Dvur Kralove nad Labem (1941) = 80 meters/262.5 feet tall (water tank is set at 30 meters). The tank held 300 cubic meters/79,252 gallons of water. Served the former mechanical weaving mill factory. The water tank ceased operations in 2007

Dvur Kralove nad Labem – Source: vezovevodojemy.cz Dvůr Králové nad Labem in 1944 – Source: vezovevodojemy.cz

Choceň (1929) = 70 meters/229.7 feet tall (water tank set on the chimney at 30 meters). The tank holds 80 cubic meters/22,134 gallons of water. The tower/tank served a spinning and weaving mill which continues in operation, though the tower and tank are primarily used for communications today.

Choceň – Source: vezovevodojemy.cz Choceň in 1937 – Source: vezovevodojemy.cz

Mělník (1956) = 40 meters/131.2 feet tall (water tank is set at 25 meters). The tank holds 35 cubic meters/9,246 gallons of water. The tower/tank serves the Association for Chemical and Metallurgical Production. Originally a zinc oxide facility, the factory now produces frits and glazes. The chimney and water tank are both still in operation.

Mělník – Source: vezovevodojemy.cz

Nymburk (1917) = 73 meters/239.5 feet tall (water tank is set at 35 meters). The tank holds 80 m3/21,134 gallons of water. Served the railway workshop of the North-Western Railway. The water tower and chimney have been disused since the 1970s when the taller concrete chimney (see image) was completed

Nymburk – Source: vezovevodojemy.cz Nymburk in 1974 – Source: vezovevodojemy.cz

Kolín (1922) = 50 meters/164 feet tall (the water tank is set at 25 meters). The water tank holds 100 cubic meters/26,417 gallons of water. Located at a fertilizer factory. Operation of the chimney and water tank ceased in 1997

Kolín – Source: vezovevodojemy.cz

Libčice nad Vltavou (1921) = 45 meters/147.6 feet tall (water tank set at 25 meters). Serves the Libšice Ironworks. The tank holds 150 cubic meters/39,625 gallons of water. The chimney was shut down in 1992, but the water tank is still used.

Libčice nad Vltavou – Source: vezovevodojemy.cz Libčice nad Vltavou in 1921 – Source: vezovevodojemy.cz

Slaný (ca 1925) = 50 meters/164 feet tall (water tank set at 29 meters). The tank holds 150 cubic meters/39,635 gallons of water. Served the Slaný Engineering Works. Both the chimney and the water tank ceased being used in the late 1980s.

Slaný – Source: vezovevodojemy.cz Slaný in 1935 – Source: vezovevodojemy.cz Close-up view of the Slaný water tank – Source: vezovevodojemy.cz

SOURCE: http://www.vezovevodojemy.cz

#chimneys #cities #Czechia #Europe #geography #history #industry #landUse #tourism #towers #travel #waterTowers

#chimneys #cities #czechia #europe #geography #history

Panethos @[email protected] · 2026-05-21 · 07:00 UTC

Working list: Tallest water towers of Taiwan

Listed below are the tallest water towers of the island of Taiwan. The number of towers is somewhat limited by the more recent use of elevated topography to store and supply water in cities like Taipei.

From an interesting historical standpoint, there are several water towers on the list dating from the 1930s that were constructed during Japanese occupation of Taiwan (1895-1945).

As more information is located on other water towers in Taiwan, the data will be added. Peace!

“Soaring” South Water Tower: Taichung/Central Taiwan Science Park = 76 m/249.3 feet

Source: maps.google.com

2. Huwei Township Water Tower (1930): Gong’an Village = 50.5 m/165.7 feet

3. “Sailing” West Water Tower (2005): Taichung/Central Taiwan Science Park ~ 47 m/154.2 feet

Sailing Water Tower – Source: common.wikimedia,org

4. Water Tower Park (1960s): Kaohsiung = 38 m/124.7 feet

Water Tower Park – Source: en.wikipedia.org

5. Puzi Waterway Distribution Tower (1933): Puzi City = 35 m/114.8 feet

Puzi Tower – Source: yy.idv.tw

6. Gangshan Water Tower (1938): Kaohsiung = 31 m/101.7 feet

7. Old Okayama Water Tower (1937): Kaohsiung = 30+m/98.4 feet

8. Beingang Water Tower (1930s): = 20 m/65.6 feet

9. Dapeng Bay Seaplane Water Tower (1938): Dapeng Bay ~ 20 m/65.6 feet

10. Magong Water Tower (1960): Magong City = 17 m/55.8 feet

More information needed:

Chenggong Station Water Tower
Chengkungling Water Tower
Daya Operations Station Water Tower
Fishing Harbor Water Tower
Gaomei Wetlands Water Tower: Taichung
Huajiang Water Tower (1960s or 1970s): Taipei
Jianshan Reservoir Water Tower
Mingde Water Tower
Nangang Water Tower
Seawater Station Water Tower: Pingtung
Tianmu New Village Water Tower
Waisungkai Water Tower: Taipei
Wan Guo Water Tower: Taipei
Wanhua Water Tower
Wonju Station Water Tower
Yilan Park Water Tower
Yiwu Water Tower: Wubei

Fishing Harbor Water Tower – Source: hippostcard.com

SOURCES:

#Asia #cities #Formosa #history #landUse #planning #statistics #Taiwan #towers #travel #waterTowers

#asia #cities #formosa #history #landuse #planning

💧🌏 Greg Cocks @[email protected] · 2026-04-22 · 03:13 UTC

Detecting Land Use And Land Cover Changes And Quantifying Soil Erosion And Sediment Export Using GIS And Remote Sensing In The GERD Catchment, Ethiopia
--
https://doi.org/10.1016/j.iswcr.2026.100657 <-- shared paper
--
https://infonile.org/en/2023/05/battling-for-survival-along-the-warming-source-of-the-blue-nile/ <-- shared technical media article
--
https://doi.org/10.1007/978-3-031-65241-7_4 <-- shared technical book chapter
--
https://doi.org/10.3390/rs8121020 <-- shared 2016 paper
--
#landuse #landcover #RUSLE #model #soil #erosion #sedimentation #GERD #catchment #NorthAfrica #Ethiopia #AbbayBasin #sustainability #landmanagement #agriculture #farmland #foodsecurity #water #hydrogology #reservior #watermanagement #watersecurity #waterresources #catchment #GrandEthiopianRenaissanceDam #BlueNile #hydrography #impoundment #GIS #spatial #mapping #remotesensing #earthobservation #thematic #spatialanalysis #spatiotemporal #landsat #elevation #DEM #CHIRPS #rainfall #precipitation #LULC #AI #forest #grazing #grassland #field #crops #cropland #waterbodies #urban #biophysical #risk #hazard #mitigation #soilquality

#landuse #landcover #rusle #model #soil #erosion

💧🌏 Greg Cocks @[email protected] · 2026-04-21 · 02:44 UTC

Remote Sensing And Process Attribution Uncertainties In The Dharali Event [Himalayas, India]
--
https://doi.org/10.1038/s44304-026-00211-w <-- shared paper review
--
https://doi.org/10.1038/s44304-026-00191-x <-- shared paper that was reviewed
--
https://doi.org/10.1016/j.nhres.2025.11.001 <-- related shared paper
--
#Dharali #disaster #BhagirathiBasin #India #NorthernIndia #Himalayas #GIS #spatial #mapping #remotesensing #satellite #imagery #earthobservation #trigger #risk #hazard #damage #infrastructure #mountain #geomorphology #glacier #glacial #debrisflow #publicsafety #landuse #paraglacial #rainfall #precipitation #extremeweather #massmovement #landslide #spatialanalysis #spatiotemporal #Bhagirathi #River #water #hydrology #icepatchcollapse

#dharali #disaster #bhagirathibasin #india #northernindia #himalayas

Alexander J. Stein @[email protected] · 2026-03-26 · 11:41 UTC

Shifting to lower levels of meat consumption & biofuel production could help protect the climate, water resources & wildlife habitat while feeding more people. The solutions exist: drawdown.org/news/only-ha... #Agriculture #FoodSystem #LandUse #ClimateChange #FoodSecurity #Livestock #Meat #Biofuel

Only half of calories produced...

#agriculture #foodsystem #landuse #climatechange #foodsecurity #livestock

💧🌏 Greg Cocks @[email protected] · 2026-03-10 · 03:17 UTC

Vertical Land Motion And Human Exposure Across India's Coastal Regions
--
https://doi.org/10.1029/2025GL120539 <-- shared paper 🔗
--
https://www.indiaspend.com/climate-change/indias-coastal-cities-face-heavy-flooding-risk-due-to-sea-level-rise-970906 <-- shared media article 🔗
--
#SeaLevelRise #Subsidence #India #InSAR #radar #Postdoc #GIS #spatial #mapping #inSAR #LandSubsidence #remotesensing #coast #coastal #coastline #India #earthobservation #subsidence #rise #urban #city #SLR #ClimateChange #spatialanalysis #spatiotemporal #marine #ocean #water #hydrology #risk #hazard #humanimpacts #flood #flooding #model #modeling #floodrisk #infrastructure #damage #costs #economics #verticallandmotion #VLM #ESA #Sentinel #Ahmedabad #Chennai #Amaravathi #Kochi #Kakinada #Kolkata #deltas #estuary #demographics #population #coastalsubsidence #landuse #planning #mitigation #farmland #agriculture #foodsecurity #groundwater #pumping #extraction

#sealevelrise #subsidence #india #insar #radar #postdoc

Alexander J. Stein @[email protected] · 2026-02-20 · 17:53 UTC

#China: Modeling suggests that integrating #FoodSystem actions across supply chains, consumer demand & land management could, by 2060, reduce GHG emissions ~40%, improve diet quality ~25% and cut inequality ~20%: doi.org/10.1016/j.sc... #SupplyChains #Consumers #LandUse #Climate #Nutrition

Redirecting

#china #foodsystem #supplychains #consumers #landuse #climate

Panethos @[email protected] · 2026-02-18 · 11:00 UTC

Cataloging Black-owned record stores

As part of celebrating Black History Month, here’s a list of known Black-owned record stores in the United States and other places around the globe. The list includes those stores that are either fully or partially Black-owned.

Sadly, as with all variations of brick and mortar record retailers, the advent of streaming, digital downloading, and online retailers like Amazon.com has vastly decreased the number of Black-owned record stores. It was also noteworthy that several stores only recently identified in previously published stories/articles (in the past five years) were discovered to have now closed permanently.

Kudos to these business owners for weathering the economic, social, and technological challenges of owning and operating an independent record store in the 21st Century. Please feel free to forward any additions, corrections, or suggestions to this list.

Peace!

Inside Dorsey’s Record Shop since 1946 in Pittsburgh (Neil & Marcus Dorsey) – Source: post-gazette.com

________

Bantu Records: Johannesburg, South Africa

Baoulecore Archive Center (2023): Abidjan, Cote d’ Ivorie

Better Days Records (1998): Louisville, Kentucky

Black Circle Records: Charleston (Summerville), South Carolina

Black Star Vinyl (formerly Halsey & Lewis Records) (2017): Brooklyn, New York

Blessed Love Record Shop: Berlin, Germany

Brittany’s Record Shop (2018): Cleveland, Ohio

Conservatory Vintage & Vinyl (2019): Chicago (Flossmoor), illinois

Crates ATL (2025): Atlanta, Georgia

DBS Sounds (1994): Atlanta (Riverdale), Georgia

Della Soul Records (2021): Grand Rapids, Michigan

DJ’s Record Shop: Jacksonville, Florida

Dorsey’s Record Shop (1946): Pittsburgh (Homewood), Pennsylvania

Fivespace: San Diego, California

Forever Changes Vinyl Lounge (1971): Philadelphia (Phoenixville), Pennsylvania

Freshtopia (2019): Norfolk, Virginia

God’s Time: Accra, Ghana

Good Stuff Records: Houston, Texas

Gotwhatulike: Kansas City, Missouri

Home Rule Records (2018): Washington, D.C.

Jampac Records (1986): Charlotte (Monroe), North Carolina

JB’s Record Lounge (2017): Atlanta, Georgia

Kumanini Vinyls (2017); Busua, Ghana

Maestro Records: London (Peckham), England, U.K.

Memories of Soul: Newark, New Jersey

Moodies Records (1982): Bronx, New York

Moods Music (2000): Atlanta, Georgia

Music Planet (1981): Flint, Michigan

Needle to the Groove (2014): San Jose, California

Offbeat (2014): Jackson, Mississippi

Out of the Past Records (1968): Chicago, Illinois

Peaches Records (1975): New Orleans, Louisiana

PM Sounds (2019): Los Angeles (San Pedro), California

Poo-Bah Records (1971): Los Angeles (Pasadena), California

Pure Vinyl: London, England, U.K.

Recs N Threads: St. Louis, Missouri

Re-Runz Records (2016): Orlando, Florida

Retrofit Records (2011): Tallahassee, Florida

Rockers International Records: Kingston, Jamaica

Serious Sounds (1991): Houston, Texas

SOOK Vintage & Vinyl (2023): Philadelphia, Pennsylvania

Soulfolk’s Records & Tapes (2019): Nashville, Tennessee

Stokley’s Records: Valdosta, Georgia

Str33t Records (2021): Los Angeles (Alhambra), California

Supertone Records: Londont (Brixton), England, U.K.

The Jazzhole: Lagos, Nigeria

The Real Vinyl Guru/Stall 570 (1989): Nairobi, Kenya

The Record Track (1990): Chicago, Illinois

Urban Lights Music (1993): Twin Cities, Minnesota

Vinyl and Pages: Baltimore, Maryland

Della Soul Records – Source: Facebook.com

SOURCES:

#AfricanAmericans #albums #BlackHistoryMonth #BlackOwned #cities #fun #geography #history #landUse #music #recordStores #records #tourism #travel #vinyl

#africanamericans #albums #blackhistorymonth #blackowned #cities #fun

💧🌏 Greg Cocks @[email protected] · 2026-01-08 · 04:54 UTC

State of Public Outdoor Access Report 2026 [New Zealand]
--
https://www.herengaanuku.govt.nz/our-work/publications/state-of-public-access <-- shared report
--
"This inaugural State of Public Outdoor Access Report, which provides a comprehensive snapshot of public access to the outdoors across Aotearoa..."
--
#spatial #mapping #pocketmaps #app #parcels #catalogue #easement #comprise #cadastre #outdooraccess #PublicLand #PrivateLand #accomodation #NewZealand #recreation #landuse #landtypes #outdoorspaces #access #legislation #framework #reserves #authority #paperroads #cycleways #bicycle #hunting #fishing #coast #coastal #mountains #commission #reporting #government #tangatawhenua #indigenous #firstnation #maori #localcouncils #communitygroups #landowners #publicaccess #education #environment #restoration #support #respect #landrights #walkways #tramping #trails #hiking #camping #services #land
@HerengaāNukuAotearoa | #HerengaāNukuAotearoa | #OutdoorAccessCommission

#spatial #mapping #pocketmaps #app #parcels #catalogue

💧🌏 Greg Cocks @[email protected] · 2025-12-15 · 05:52 UTC

Geologically-Driven Migration of Landmines and Explosive Remnants of War - A Feature Focusing on the Western Balkans
-
https://doi.org/10.3390/geosciences13060178 <-- shared 2023 paper
--
https://www.kpbs.org/news/2014/05/20/balkan-floods-expose-deadly-mines-from-1990s <-- shared 2014 media example
--
[mechanics/process I know I (fortunately) don’t consider - but fascinating!]
#landmine #unexplodedordnance #explosiveordnance #abandonedexplosiveordnance #IED #improvisedexplosivedevice #military #minefield #war #publicsafety #flood #flooding #landslide #WesternBalkans #balkans #Bosnia #Herzegovina #Serbia #Croatia #stochastic #deterministic #model #modeling #war #battlefield #ordanance #injury #fatality #massmovement #landsurface #processes #engineeringgeology #geology #geology #soil #debrisflow #water #hydrology #risk #hazard #hydromorphology #morphology #geomorphometry #spatialanalysis #GIS #spatial #mapping #riskmapping #fieldsurvey #spatiotemporal #research #hazardmap #planning #polict #landuse #emergency #publichealth #riskmanagement

#landmine #unexplodedordnance #explosiveordnance #abandonedexplosiveordnance #ied #improvisedexplosivedevice

💧🌏 Greg Cocks @[email protected] · 2025-11-26 · 03:38 UTC

Surface Water Transitions 1984–2022 - A Global Dataset at Annual Resolution
--
https://doi.org/10.1038/s41597-025-06013-5 <-- shared paper
--
#water #hydrology #hydrospatial #globe #global #remotesensing #spatialanalysis #spatiotemporal #GIS #spatial #mapping #watertransition #river #stream #lake #coast #coastal #landsat #timeseries #WCD #WTTD #OTSU #NDWI #landuse #landcover #NLDI #soil #vegetation #forest #urban #industrial #advance #recession #wetland #engineered #agriculture #floodplain #deforestration #reservior #delta #model #modeling #surfacewater #change #seasonal #climate #annual #historic #recenthistory #waterresources #watermanagement #watersecurity

#water #hydrology #hydrospatial #globe #global #remotesensing

💧🌏 Greg Cocks @[email protected] · 2025-09-30 · 02:11 UTC

New USGS Map Offers An Interactive Look At The Rocks Beneath Our Feet
The Cooperative National Geologic Map is an interactive tool that builds on both cutting-edge technology and decades of mapping by geoscientists.
--
https://eos.org/articles/new-usgs-map-offers-an-interactive-look-at-the-rocks-beneath-our-feet <-- shared EOS-source technical article
--
https://ngmdb.usgs.gov/nationalgeology/#lat=37.0000&lng=-97.5000&zoom=5&theme=esurf&symbology=synthesis <-- shared @USGS resource
--
[recognising that I posted something similar earlier ~smile~]
#GIS #spatial #mapping #data #fedopendata #fedscience #geologicmap #geology #webmap #geologicdata #energy #minerals #mining #waterresources #hydrology #risk #hazard #landuse #infrastructure #planning #realestate #insurance #rock #sediment #mapunits #compilation #criticalminerals #economicgeology #nation #mobile #fieldwork #interactivewebtool #publicgood #online #state #federal #map #usecase #energy #resources #CooperativeNationalGeologicMap #USGS #mainland #CONUS
@USGS

#gis #spatial #mapping #data #fedopendata #fedscience

💧🌏 Greg Cocks @[email protected] · 2025-09-23 · 00:36 UTC

Occurrence And Tissue Distribution Of Per- And Polyfluoroalkyl Substances (PFAS) In Fishes From Waterbodies With Point And Non-Point Sources In Massachusetts, USA
--
https://doi.org/10.1016/j.aquatox.2025.107499 <-- shared paper
--
#GIS #spatial #mapping #spatialanalysis #Massachusetts #USA #PFAs #Largemouthbass #bass #Bandedkillifish #killifish #Pointsources #waterbody #Histology #Healthassessment #bioaccumulation #pfa #immunology #AshumetPond #SudburyRiver #pollution #contamination #toxicology #environmental #contaminants #PFOs #fish #fisheries #species #plasma #liver #muscle #cost #economics #publichealth #publicsafety #exposurepathways #testing #landuse #NLCD #recreationalfishing #angling #spatiotemporal #sediment
@USGS

#gis #spatial #mapping #spatialanalysis #massachusetts #usa

💧🌏 Greg Cocks @[email protected] · 2025-09-05 · 00:07 UTC

Thirty Years Of The U.S. National Land Cover Database [NLCD] - Impacts And Future Direction
--
https://doi.org/10.14358/PERS.25-00121R2 <-- shared paper
--
https://www.usgs.gov/centers/eros/science/annual-national-land-cover-database <-- shared #USGS Annual National Land Cover Database (open data)
--
https://www.usgs.gov/centers/eros/science/annual-national-land-cover-database <-- get the open NLCD data
--
#GIS #spatial #mapping #history #continuity #improvement #LandCover #Landuse #change #Landsat #NLCD #NationalLandCoverDatabase #earthobservation #remotesensing #landchange #monitoring #fedscience #publicgood #fedopendata #opendata #history #fedservice #MRLCC #USA #download #impervious #surface #forestcanopy #mosaics #accuracy #deeplearning #AI #research #landmanagement #agriculture #water #hydrology #cropland #biodiversity #conservation #urban #planning #publichealth #naturalhazard #assesment #risk #hazard #mitigation #national #nation #multiple #usecase
#USGS | #EROS

#usgs #gis #spatial #mapping #history #continuity

💧🌏 Greg Cocks @[email protected] · 2025-08-27 · 19:51 UTC

[USGS] Landsat At Work – Preparing Residents When Hurricanes Threaten
--
Landsat-Based National Land Cover Datasets (NCLD) Helps Predict Wind Risk To Homes And Other Structures
--
https://www.usgs.gov/centers/eros/news/landsat-work-preparing-residents-where-hurricanes-threaten <-- shared technical article
--
#GIS #spatial #mapping #remotesensing #landsat #satellite #fedopendata #publicgood #fedscience #risk #hazard #model #modeling #actuary #insurance #rates #appraisal #hurricane #naturaldisaster #infrastructure #damage #cost #economics #loss #NLCD #landcover #landuse #evulation #projection #Florida #residential #EROS #USGS #coast #coastline #computermodels #wind #surge #flood #flooding #USGS #NOAA #NASA #EROS #HurricaneLossProjectionMethodology

#gis #spatial #mapping #remotesensing #landsat #satellite

💧🌏 Greg Cocks @[email protected] · 2025-06-26 · 14:56 UTC

Barriers To Quantifying Human Alterations Of Global Floodplains And How We Can Overcome Them
--
https://doi.org/10.1016/j.crsus.2025.100433 <-- shared paper
--
#floodplains #floodplain #development #alterations #flood #flooding #risk #hazard #management #planning #humanimpacts #mitigation #GIS #spatial #mapping #remotesensing #landuse #spatialanalysis #monitoring #mitigation #humanimpacts #riverine #watersecurity #population #foodsecurity #waterquality #waterresources #degradation #damage #infrastructure #loss #cost #economics #extremeweather #climatechange #waterstorage #groundwater #watershed #water #hydrology #hydrography #naturaldisaster #spatiotemporal

#floodplains #floodplain #development #alterations #flood #flooding

💧🌏 Greg Cocks @[email protected] · 2025-06-19 · 20:27 UTC

Land Surface Heterogeneity And Tornado Occurrence - An Analysis Of Tornado Alley And Dixie Alley
--
https://doi.org/10.1080/19475705.2019.1583292 <-- shared paper
--
#GIS #spatial #mapping #NLCD #climatechange #severeweather #extremeweather #environment #slope #remotesensing #landcover #extremeweather #landcover #landuse #tornado #risk #hazard #damage #cost #economics #publicsafety #infrastructure #loss #USA #TornadoAlley #DixieAlley #landsurface #topography #vegetation #spatialanalysis #model #modeling #heterogeneity #variables #parameters #factors #geostatistics #statistics #EROS #fedscience

#gis #spatial #mapping #nlcd #climatechange #severeweather

💧🌏 Greg Cocks @[email protected] · 2025-05-08 · 19:48 UTC

Geospatial Services / Gateway – USDA NRCS [open data]
--
https://gdg.sc.egov.usda.gov/ <-- shared link to USDA NRCS Geospatial Data Gateway
--
#GIS #spatial #mapping #portal #download #spatialdata #opendata #remotesensing #earthobservation #NRCS #ISDA #FSA #FarmServiceAgenct #RuralDevelopment #agriculture #fedservice #fedscience #farming #farmers #soil #SSURGO #environmental #naturalresources #NaturalResourcesConservationService #TIGER #precipitation #temperature #conservation #easement #LiDAR #elevation #names #geography #geology #governmentunits #boundaries #watershed #hydrology #water #WBD #HUC #topo #imagery #roads #transportation #soils #SSURGO #USA #US #landcover #landuse #NLCD

#gis #spatial #mapping #portal #download #spatialdata

💧🌏 Greg Cocks @[email protected] · 2025-04-29 · 23:16 UTC

Landsat At Work – Better Wireless Communication - National Land Cover Database (NLCD), Based On Landsat, Helps Plan Clear Signal
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https://www.usgs.gov/centers/eros/news/landsat-work-a-path-better-wireless-communication <-- shared article
--
https://www.usgs.gov/landsat-missions <-- shared about Landsat
--
https://www.usgs.gov/centers/eros/science/annual-national-land-cover-database <-- shared about NLCD
--
#GIS #spatial #mapping #Landsat #remotesensing #satellite #earthobservation #fedscience #usecase #USGS #EROS #cellphone #mobilephone #telecommunications #communications #cost #benefit #wireless #towers #antennas #landcover #landuse #NLCD #radio #frequency #siting #lineofsight #clutter #economics #risk #hazard #signal #signalquality #USA #value #returnoninvestment
@USGS @USGS_EROS

#gis #spatial #mapping #landsat #remotesensing #satellite

💧🌏 Greg Cocks @[email protected] · 2025-04-29 · 04:18 UTC

Landslide Susceptibility Assessment In The Marin Khola Watershed Of The Sub Himalaya, Central Nepal
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https://doi.org/10.3126/jist.v30i1.76264 <-- shared paper
--
#GIS #spatial #mapping #geology #engineeringgeology #massmovement #landslides #Nepal #susceptibility #MarinKhola #watershed #InfoVal #Siwaliks #Himalayas #risk #hazard #cost #infrastructure #publicsafety #lossoflife #propertydamage #damage #geomorphology #water #hydrology #geomorphometry #casestudies #spatialanalysis #water #hydrology #factors #topography #geology #soil #landuse #landcover #model #modeling #accuracy

#gis #spatial #mapping #geology #engineeringgeology #massmovement

💧🌏 Greg Cocks @[email protected] · 2025-04-22 · 04:45 UTC

Modeling Future Land Cover And Water Quality Change In Minneapolis, MN, USA To Support Drinking Water Source Protection Decisions
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https://doi.org/10.1111/1752-1688.13109 <-- shared paper
--
#GIS #spatial #mapping #remotesensing #earthobservation #landsat #fedscience #landuse #landcover #waterquality #model #modeling #spatialanalysis #spatiotemporal #NLCD #Minneapolis #MississippiR #water #hydrology #watersecurity #waterresources #nitrates #phosphorus #cyanotoxins #Minnesota #trees #agriculture #pesticides #fertiliser #farming #potable #runoff #farming #FORESCE #urbanisation #urban #headwater #watershed #planning #urbanplanning #management #nitrogencycle #soil #watertreatment #sediment

#gis #spatial #mapping #remotesensing #earthobservation #landsat

💧🌏 Greg Cocks @[email protected] · 2025-04-22 · 04:24 UTC

A Framework For Understanding The Effects Of Subsurface Agricultural Drainage On Downstream Flows
--
https://doi.org/10.3133/sir20255023 <-- shared USGS publication
--
#water #hydrology #mapping #framework #model #modeling #fedscience #streamflow #subsurface #soil #drainage #agriculture #farming #landuse #landcover #GIS #spatial #tiledrainage #drains #flow #waterresources #runoff #peakflow #evapotranspiration #precipitation #USA
@USGS

#water #hydrology #mapping #framework #model #modeling

Lyle Solla-Yates @[email protected] · 2024-09-10 · 16:08 UTC

I see that my friend Andrew Knuppel's #uva Masters Thesis on the #history of #landuse regulations in #albemarlecounty is now available online here: https://libraetd.lib.virginia.edu/downloads/hm50ts46s?filename=KnuppelMUEP2020_AlbemarleWatershedMoments.pdf Recommended if you find yourself needing to understand what is happening across that huge and interesting area. #urbanplanning Thanks to Andrew for the kind shout out there. #equity #zoning #conservation

#uva #history #landuse #albemarlecounty #urbanplanning #equity

💧🌏 Greg Cocks @[email protected] · 2024-07-19 · 19:42 UTC

Flood Susceptibility Mapping Of Kathmandu Metropolitan City Using GIS-Based Multi-Criteria Decision Analysis
--
https://doi.org/10.1016/j.ecolind.2023.110653 <-- shared paper
--
#GIS #spatial #mapping #analyticalhierarchyprocess #floodhazardcriteria #floodpotentialzone #localadministrativeunit #Nepal #spatialanalysis #spatiotemporal #model #modeling #processmodeling #water #hydrology #flood #flooding #Kathmandu #distance #proximity #river #climatechange #extremeweather #precipitation #rainfall #monsoon #builtenvironments #impervious #impervioussurfaces #concrete #stormwater #drainage #economics #environment #infrastructure #damage #ecology #floodinnundation #urbanplanning #criteria #slope #elevation #drainagedensity #rainfall #landuse #landcover #distancefromriver #distance #topography #elevation #floodsusceptibility #floodprone #risk #hazard #mitigation #budgets #costs #policymakers

#gis #spatial #mapping #analyticalhierarchyprocess #floodhazardcriteria #floodpotentialzone

💧🌏 Greg Cocks @[email protected] · 2024-01-25 · 04:13 UTC

Spatially Balanced Sampling And Ground-Level Imagery For Vegetation Monitoring On Reclaimed Well Pads
--
https://doi.org/10.1111/rec.12956 <-- shared paper
--
#GIS #spatial #mapping #energy #oilandgas #oilandgasindustry #oilandgasexploration #wellpads #reclamation #spatialanalysis #naturalgas #development #northamerica #USWest #landuse #ownership #stakeholders #vegetation #metric #esosystem #SamplePoint #systematic #sampling #imageanalysis #remotesensing #spatialstatistics #monitoring #regulations #seeding #costs #naturalresources #standardprotocols #defensibility #costsavings #observerbias #GPS #camera #Wyoming #WY

#gis #spatial #mapping #energy #oilandgas #oilandgasindustry

Panethos @[email protected] · 2024-01-12 · 02:36 UTC

The following list identifies the longest escarpments on the planet. Escarpments are defined as follows:

Escarpment: “A steep slope or long cliff that results from erosion or faulting and separates two relatively level areas of differing elevations.”
Source: The American Heritage® Dictionary of the English Language, 5th Edition

If you have ever driven along the Ohio Turnpike near Cleveland, you have gone up/down the Portage Escarpment. Similarly, between Toronto and London Ontario, one would have to cross the Niagara Escarpment. In fact, Niagara Falls, on the New York/Ontario border, are literally a part of the Niagara Escarpment. The falls are where the elevation drops dramatically between Lake Erie (571 feet above sea level) on the upper side and Lake Ontario (243 feet above sea level) on the lower side of the escarpment. The Welland Canal was specifically built to bypass the falls and cross the escarpment.

Niagara Falls on the Niagara Escarpment -Source: driftwoodjournals.com

Similar examples of lengthy escarpments can be found worldwide on every continent including Antarctica. And the steepness/sheerness of them can vary too, as the Cody Scarp in northern Florida is comparatively quite mild. However, most escarpments are quite bold, rapidly rising to elevations well above the surrounding terrain. The sharp change can often be measured in hundreds or thousands of feet.

In several cases, hiking trails or scenic byways have been developed along or near the rim of these magnificent natural features, providing amazing visiting fr those trekking them. Blue Ridge Parkway, Mogollon Rim Road and Skyline Drive are examples of scenic byways while the Knobstone Trail in Indiana and the developing Mogollon Rim Trail in Arizona are hiking routes.

Knobstone Hiking Trail in Indiana – Source: Indianaoutfitters.com

For proposes of this post a minimum length of 10 miles was required and escarpments which are primarily situated underwater (ocean/sea/lake, etc.) are not included. Those shown in italics the author has seen or traveled across. Peace!

Great Escarpment of Southern Africa = 3,107 miles/5,000 km

Great Southern Africa Escarpment (gray line) – Source: reserachgate.net Drakensberg portion of the Great Southern Africa Escarpment in South
Africa – Source: alexnail.com

2. Great Escarpment (Oceania) = 2,200 miles/3,600 km

Great Australian Escarpment (red) – Source: researchgate.net

3. Grande Escarpa do Brasil (South America) = 1,600 miles/2,600 km

Source: sarthaks.com

4. Niagara Escarpment (North America) = 1,000 miles/1609 km

Niagara Escarpment – Source: Waterloo.ca

5. Atlantic Seaboard Fall Line (North America) = 900 miles/1,400 km

Fall Line (thicker red line) – Source: alchetron,com

6. Portage Escarpment (North America) ~ 653 miles/1051 km

Portage Escarpment – Source: kids.kiddle.co

7-8. Darling Scarp (Oceania) and Madagascar East Coast Escarpment (Africa) = 620 miles/1,000 km

9. Blue Ridge Escarpment (North America) = 550 miles/885 km

10. Tuwaiq Escarpment (Asia) = 500 miles/800 km

11. Zambezi Escarpment (Africa) = 497 miles/800 km

12. Manitoba/Pembina Escarpment (North America) = 419 miles/675 km

13-14. Sierra Escarpment (North America) = 400 miles/644 km Balcones Escarpment (North America) ~ 400 miles/644 km

Balcones and Caprock Escarpments in Texas – Source: weather.gov

15. Book Cliffs Escarpment (North America) = 250 miles/402 km *longest continuous escarpment in the world

16-17. Caprock Escarpment (North America) and Mogollon Rim (North America) = 200 miles/320 km

Source: i0wp.com

18. Usas Escarpment (Antarctica) = 199 miles/320 km

19. Roan Cliffs Escarpment (North America) = 190 miles/306 km – separate escarpment atop the Book Cliffs Escarpment

20. Allegheny Front (North America) = 180 miles/290 km

21. Western Andean Escarpment (South America) = 155 miles/250 km

22. North Downs Chalk Escarpment = 153 miles/246 km

23. Knobstone Escarpment (North America) = 150 miles/241 km

24. Nullarbor Scarp (Oceania) = 130 miles/210 km

25. Missouri Escarpment (North America) = 100 miles/161 km

26-27. Bandiagara Escarpment (Africa) and Vermillion-Echo Cliffs Escarpment (North America) = 90 miles/160 km

Clearly defined Vermillion Cliffs (left) and Echo Cliffs (right) – Source: maps.google.com

28. South Downs Chalk Escarpment (Europe) = 68 miles/110 km

29. Onondaga Escarpment (North America) = 62 miles/100km

30. Illawarra Escarpment (Oceania) = 57 miles/92 km

31-32. Lincoln/Trent Cliff (Europe) and Mescalero Ridge (North America) = 50 miles/80 km

33. Chiltern Escarpment (Europe) = 45 miles/72 km

34. Côte d’Or (Europe) = 30 miles/48 km

35. Catskills Escarpment (North America) = 24 miles/38 km

36. Palisades Escarpment (North America) = 20 miles/34 km

37. Wenlock Edge (Europe) = 19 miles/31 km

38. Chinese Wall Escarpment (North America) = 12 miles/19 km

Chinese Wall Escarpment in Montana – Source: pinterest.com

39-40. Duluth Escarpment (North America) and Black Mountain Escarpment (Europe) = 11 miles/18 km

Portions of the Niagara and Onondaga Escarpments in New York – Source: falzguy.com

Other Escarpments – More Information Needed

Cody Scarp (North America)
Elgeyo Escarpement (Africa)
Eardley Escarpment (North America) = 40+ km
Kaimai Escarpment (Oceania)
Muldraugh Hill Escarpment (North America)
Pottsville/Cumberland Escarpment (North America)
Sharon Escarpment (Asia)
Gotland–Saaremaa Klint (Europe) = 180+ km
Wulian Feng (Asia)

SOURCES:

https://panethos.wordpress.com/2024/01/11/natures-sheer-cliffs-the-worlds-longest-escarpments/

#bluffs #cliffs #ecology #ecosystems #environment #escarpments #geology #hiking #history #landUse #mountains #planning #rims #topology #travel

#bluffs #cliffs #ecology #ecosystems #environment #escarpments

BellingenNSW @[email protected] · 2023-10-01 · 21:31 UTC

Study demonstrates that "formalizing tenure for Indigenous lands reduced deforestation and/or increased reforestation"
https://academic.oup.com/pnasnexus/article/2/1/pgac287/7005261?login=false
#IndigenousRights #LandUse #conservation #NativeForests #Biodiversity #deforestation #extractivism #mining #IndustrialLogging

#biodiversity #indigenousrights #landuse #conservation #nativeforests #deforestation

💧🌏 Greg Cocks @[email protected] · 2023-04-17 · 23:05 UTC

Dynamic World, Near Real-Time Global 10 Metre Land Use Land Cover Mapping
--
https://doi.org/10.1038/s41597-022-01307-4 <-- shared paper
--
#GIS #spatial #mapping #landcover #processeddata #deeplearning #AI #landuse #remotesensing #global #timelag #automation #NRT #LULC #NLCD #satellite #Sentinel #Sentinel2 #DynamicWorld #NDVI #machinelearning #artificialintelligence #NearRealTime

#gis #spatial #mapping #landcover #processeddata #deeplearning

💧🌏 Greg Cocks @[email protected] · 2023-03-29 · 21:10 UTC

Elevation-Based Probabilistic Mapping Of Irregularly Flooded Wetlands Along The Northern Gulf Of Mexico Coast
--
https://www.sciencedirect.com/science/article/pii/S0034425723000020 <-- shared paper
--
https://doi.org/10.5066/P9MLO26U <-- open access to study’s data
--
#GIS #spatial #probablistic #mapping #coastal #wetlands #elevation #uncertainty #LiDAR #MonteCarloSimulation #spatialautocorrelation #gischat #flooded #flooding #GulfOfMexico #MHW #datum #tidal #ecosystem #wildlife #fish #habitat #erosion #protection #SLR #sealevelrise #climatechange #hydrospatial #extremestorms #stormsurge #management #mitigation #spatialanalysis #spatiotemporal #changecontrol #extremeweather #landuse #landcover #remotesensing #model #modeling #numericalmodeling #probabilisticmap #accuracy #precision #corrleation #errormetrics #statistics #geostatistics #opendata #water #hydrology #data #food #digital

#gis #spatial #probablistic #mapping #coastal #wetlands