#landuse — Public Fediverse posts

"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

"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

"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

"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

"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

A status on land use change worldwide:

"The area used for growing crops grew significantly from 2001 to 2024. Temporary crops (such as wheat, rice and maize) increased by 104 million ha, or 11 percent, reaching 1 081 million ha. Permanent crops (such as cocoa, oil palm and coffee) grew by 59 million ha, reaching 194 million ha in 2024, an increase of over 43 percent."

The leaders in cropland expansion were in Africa (+78 million ha) and South America (+35 million ha).
The leaders in cropland contraction were in Northern America (−26 million ha).

https://openknowledge.fao.org/items/fbfbe167-5026-4aa1-b985-2468507d5dc1

#FAO #foodSovereignty #agriculture #crops #land #landUse #LULUCF #trade #internationalTrade #cashCrops #exports

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

Mapping Multifunctionality In Remote Patagonian Forest Landscapes Reveals High-Value Ecosystems Beyond Protected Areas
--
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

Mapping Multifunctionality In Remote Patagonian Forest Landscapes Reveals High-Value Ecosystems Beyond Protected Areas
--
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

Mapping Multifunctionality In Remote Patagonian Forest Landscapes Reveals High-Value Ecosystems Beyond Protected Areas
--
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

Mapping Multifunctionality In Remote Patagonian Forest Landscapes Reveals High-Value Ecosystems Beyond Protected Areas
--
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

Mapping Multifunctionality In Remote Patagonian Forest Landscapes Reveals High-Value Ecosystems Beyond Protected Areas
--
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

Eager Beavers - Rodents Engineer Czech Wetland Project After Years Of Human Delay [ecosystem engineers]
--
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
--
https://phys.org/news/2025-02-fine-beavers-czech-treasury-million.html <-- shared technical article
--
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

Optical, Radar, And Hybrid Indices To Detect Farming Practices In Europe
--
https://doi.org/10.1016/j.rse.2026.115553 <-- shared paper
--
“HIGHLIGHTS:
• [they] compare[d] Sentinel-1 and Sentinel-2 time series to detect farming practices.
• HyBRIS index is introduced, temporally weighting BSI and VH/VV into a daily index.
• Time-series minima and maxima are used to predict sowing, harvest, and tillage.
• Validation is performed across several years, crop types, and European locations.
• Phenology detection is improved compared to HRL-Cropland.
ABSTRACT: Arable farming practices dictate both crop cycles and soil dynamics, and are central to agriculture's environmental impact and its mitigation. Sowing and harvesting mark the beginning and end of the growing season, while tillage modifies soil structure during the dormant period. Although well-established methods exist for delineating the growing season using phenology and optical data, the detection of farming practices, particularly tillage, remains underexplored. This study investigates the strengths of radar and optical data to retrieve sowing, harvest, and tillage dates at the field level, and proposes a novel Hybrid Bare Soil Radar Index (HyBRIS). Based on Sentinel-1 and Sentinel-2, HyBRIS merges optical and radar data into a single index using a temporally weighted mean. Local minima and maxima of the time series are used to detect farming practices across European sites. Validation is carried out against a reference dataset comprising 238 fields in 11 EU countries, including 462 sowing, 374 harvest, and 388 tillage events covering more than 40 crop types over 8 years. Compared to the Copernicus High Resolution Layer Croplands product (HRL-Cropland), the proposed method based on HyBRIS time series improved sowing and harvest dates detection (MAE 26 and 23 days, respectively). Additionally, this method enabled tillage dates estimation during dormant periods (MAE = 28 days), but tended to overestimate the number of tillage events (producer's accuracy = 97%, user's accuracy = 70%). Incorporating soil moisture data is advised for reducing false positives. The results highlight the potential of optical, radar, and hybrid indices for monitoring agricultural management and supporting environmental stewardship…”
#Sowing #Harvest #tillage #tillagedetection #cropland #CroplandManagement #remotesensing #earthobservation #sentinel #Copernicus #cropland #satellite #optical #radar #sensor #landuse #landcover #landsurface #phenology #agricultural #monitoring #GIS #spatial #mapping #spatialanalysis #spatiotemporal #arable #farming #agriculture #soil #substrate #environment #sustainability #environmentalstewardship #growingseason #Europe #region #model #modeling

The #EnvironmentalCost of #ArtificialIntelligence: #Carbon, #Water, and #LandFootprints

#AI’s rapid growth drives huge energy, water, and land use, raising environmental and equity challenges across its global infrastructure.

Date Published 3 Jun 2026

UNU-INWEH Report: Aczel, M., Chamanara, S., Matin, M., Farsi, A., Marwala, T., Madani, K. (2026).

"This report, Environmental Cost of Artificial Intelligence: Carbon, Water and Land Footprints, by the #UnitedNationsUniversity Institute for Water, Environment and Health ( #UNU - #INWEH ) on its 30th anniversary, examines one of the most underexplored consequences of AI’s rapid expansion: the environmental footprints of the energy required to power it. As artificial intelligence becomes embedded in economies, public services, research, communication, and everyday life, it depends on a growing physical infrastructure of #datacenters, advanced #chips, #CoolingSystems, #ElectricityGrids, #WaterResources, land, and #CriticalMineral supply chains. The report shows that AI is not only a digital technology, but also a material system with measurable #EnvironmentalCosts.

"The report moves beyond a carbon-only lens by quantifying the carbon, water, and land footprints associated with the electricity used to train, deploy, and operate AI systems at scale. Its central finding is that AI’s environmental costs depend not only on how much electricity is used, but also on where that electricity is generated and which energy sources power it. Every kilowatt-hour used by AI carries carbon, water, and land implications, and these footprints do not always move in the same direction: low-carbon electricity is not automatically low-water or low-land. The report also shows that AI’s footprint is shaped by both major infrastructure trends, including the rapid growth of data centers, and everyday use patterns, including model choice, output length, modality, and the growing use of text, image, and video generation.

"Importantly, the report frames AI’s environmental footprint as a governance and justice challenge, not only a technical problem. The benefits of AI often flow across borders and sectors, while the environmental burdens of data center siting, electricity demand, water withdrawals, #LandUse, MineralExtraction, and #EWaste can be concentrated in specific communities and regions. To address these risks, the report calls for a responsible AI ecosystem grounded in transparency, efficiency by design, equity and #EnvironmentalJustice, lifecycle responsibility, global cooperation, and sustainable use. By making AI’s carbon, water, and land footprints visible and comparable, the report provides a practical basis for integrating AI into energy, climate, water, and land-use planning, ensuring that innovation advances without shifting environmental costs onto vulnerable communities."

Download PDF:
https://unu.edu/inweh/collection/environmental-cost-of-AIs-Enrgy-Use-Carbon-water-and-land-footprints

#AIBoom #Electricity #Hyperscale #BigTech #BigData #CarbonFootprint #EnvironmentalRacism #EnvironmentalDegradation #NoisePollution #LightPollution #WaterIsLife #AIAgents #BotTraffic #GreenSpaces #Farmland #Prairies #Woodland #TechGiants #ProtectNature #NoDatacenters #EnergyConsumption #USPol #WorldPol #Datacentres
#DatacenterMoratoriums

The #EnvironmentalCost of #ArtificialIntelligence: #Carbon, #Water, and #LandFootprints

#AI’s rapid growth drives huge energy, water, and land use, raising environmental and equity challenges across its global infrastructure.

Date Published 3 Jun 2026

UNU-INWEH Report: Aczel, M., Chamanara, S., Matin, M., Farsi, A., Marwala, T., Madani, K. (2026).

"This report, Environmental Cost of Artificial Intelligence: Carbon, Water and Land Footprints, by the #UnitedNationsUniversity Institute for Water, Environment and Health ( #UNU - #INWEH ) on its 30th anniversary, examines one of the most underexplored consequences of AI’s rapid expansion: the environmental footprints of the energy required to power it. As artificial intelligence becomes embedded in economies, public services, research, communication, and everyday life, it depends on a growing physical infrastructure of #datacenters, advanced #chips, #CoolingSystems, #ElectricityGrids, #WaterResources, land, and #CriticalMineral supply chains. The report shows that AI is not only a digital technology, but also a material system with measurable #EnvironmentalCosts.

"The report moves beyond a carbon-only lens by quantifying the carbon, water, and land footprints associated with the electricity used to train, deploy, and operate AI systems at scale. Its central finding is that AI’s environmental costs depend not only on how much electricity is used, but also on where that electricity is generated and which energy sources power it. Every kilowatt-hour used by AI carries carbon, water, and land implications, and these footprints do not always move in the same direction: low-carbon electricity is not automatically low-water or low-land. The report also shows that AI’s footprint is shaped by both major infrastructure trends, including the rapid growth of data centers, and everyday use patterns, including model choice, output length, modality, and the growing use of text, image, and video generation.

"Importantly, the report frames AI’s environmental footprint as a governance and justice challenge, not only a technical problem. The benefits of AI often flow across borders and sectors, while the environmental burdens of data center siting, electricity demand, water withdrawals, #LandUse, MineralExtraction, and #EWaste can be concentrated in specific communities and regions. To address these risks, the report calls for a responsible AI ecosystem grounded in transparency, efficiency by design, equity and #EnvironmentalJustice, lifecycle responsibility, global cooperation, and sustainable use. By making AI’s carbon, water, and land footprints visible and comparable, the report provides a practical basis for integrating AI into energy, climate, water, and land-use planning, ensuring that innovation advances without shifting environmental costs onto vulnerable communities."

Download PDF:
https://unu.edu/inweh/collection/environmental-cost-of-AIs-Enrgy-Use-Carbon-water-and-land-footprints

#AIBoom #Electricity #Hyperscale #BigTech #BigData #CarbonFootprint #EnvironmentalRacism #EnvironmentalDegradation #NoisePollution #LightPollution #WaterIsLife #AIAgents #BotTraffic #GreenSpaces #Farmland #Prairies #Woodland #TechGiants #ProtectNature #NoDatacenters #EnergyConsumption #USPol #WorldPol #Datacentres
#DatacenterMoratoriums

The #EnvironmentalCost of #ArtificialIntelligence: #Carbon, #Water, and #LandFootprints

#AI’s rapid growth drives huge energy, water, and land use, raising environmental and equity challenges across its global infrastructure.

Date Published 3 Jun 2026

UNU-INWEH Report: Aczel, M., Chamanara, S., Matin, M., Farsi, A., Marwala, T., Madani, K. (2026).

"This report, Environmental Cost of Artificial Intelligence: Carbon, Water and Land Footprints, by the #UnitedNationsUniversity Institute for Water, Environment and Health ( #UNU - #INWEH ) on its 30th anniversary, examines one of the most underexplored consequences of AI’s rapid expansion: the environmental footprints of the energy required to power it. As artificial intelligence becomes embedded in economies, public services, research, communication, and everyday life, it depends on a growing physical infrastructure of #datacenters, advanced #chips, #CoolingSystems, #ElectricityGrids, #WaterResources, land, and #CriticalMineral supply chains. The report shows that AI is not only a digital technology, but also a material system with measurable #EnvironmentalCosts.

"The report moves beyond a carbon-only lens by quantifying the carbon, water, and land footprints associated with the electricity used to train, deploy, and operate AI systems at scale. Its central finding is that AI’s environmental costs depend not only on how much electricity is used, but also on where that electricity is generated and which energy sources power it. Every kilowatt-hour used by AI carries carbon, water, and land implications, and these footprints do not always move in the same direction: low-carbon electricity is not automatically low-water or low-land. The report also shows that AI’s footprint is shaped by both major infrastructure trends, including the rapid growth of data centers, and everyday use patterns, including model choice, output length, modality, and the growing use of text, image, and video generation.

"Importantly, the report frames AI’s environmental footprint as a governance and justice challenge, not only a technical problem. The benefits of AI often flow across borders and sectors, while the environmental burdens of data center siting, electricity demand, water withdrawals, #LandUse, MineralExtraction, and #EWaste can be concentrated in specific communities and regions. To address these risks, the report calls for a responsible AI ecosystem grounded in transparency, efficiency by design, equity and #EnvironmentalJustice, lifecycle responsibility, global cooperation, and sustainable use. By making AI’s carbon, water, and land footprints visible and comparable, the report provides a practical basis for integrating AI into energy, climate, water, and land-use planning, ensuring that innovation advances without shifting environmental costs onto vulnerable communities."

Download PDF:
https://unu.edu/inweh/collection/environmental-cost-of-AIs-Enrgy-Use-Carbon-water-and-land-footprints

#AIBoom #Electricity #Hyperscale #BigTech #BigData #CarbonFootprint #EnvironmentalRacism #EnvironmentalDegradation #NoisePollution #LightPollution #WaterIsLife #AIAgents #BotTraffic #GreenSpaces #Farmland #Prairies #Woodland #TechGiants #ProtectNature #NoDatacenters #EnergyConsumption #USPol #WorldPol #Datacentres
#DatacenterMoratoriums

The #EnvironmentalCost of #ArtificialIntelligence: #Carbon, #Water, and #LandFootprints

#AI’s rapid growth drives huge energy, water, and land use, raising environmental and equity challenges across its global infrastructure.

Date Published 3 Jun 2026

UNU-INWEH Report: Aczel, M., Chamanara, S., Matin, M., Farsi, A., Marwala, T., Madani, K. (2026).

"This report, Environmental Cost of Artificial Intelligence: Carbon, Water and Land Footprints, by the #UnitedNationsUniversity Institute for Water, Environment and Health ( #UNU - #INWEH ) on its 30th anniversary, examines one of the most underexplored consequences of AI’s rapid expansion: the environmental footprints of the energy required to power it. As artificial intelligence becomes embedded in economies, public services, research, communication, and everyday life, it depends on a growing physical infrastructure of #datacenters, advanced #chips, #CoolingSystems, #ElectricityGrids, #WaterResources, land, and #CriticalMineral supply chains. The report shows that AI is not only a digital technology, but also a material system with measurable #EnvironmentalCosts.

"The report moves beyond a carbon-only lens by quantifying the carbon, water, and land footprints associated with the electricity used to train, deploy, and operate AI systems at scale. Its central finding is that AI’s environmental costs depend not only on how much electricity is used, but also on where that electricity is generated and which energy sources power it. Every kilowatt-hour used by AI carries carbon, water, and land implications, and these footprints do not always move in the same direction: low-carbon electricity is not automatically low-water or low-land. The report also shows that AI’s footprint is shaped by both major infrastructure trends, including the rapid growth of data centers, and everyday use patterns, including model choice, output length, modality, and the growing use of text, image, and video generation.

"Importantly, the report frames AI’s environmental footprint as a governance and justice challenge, not only a technical problem. The benefits of AI often flow across borders and sectors, while the environmental burdens of data center siting, electricity demand, water withdrawals, #LandUse, MineralExtraction, and #EWaste can be concentrated in specific communities and regions. To address these risks, the report calls for a responsible AI ecosystem grounded in transparency, efficiency by design, equity and #EnvironmentalJustice, lifecycle responsibility, global cooperation, and sustainable use. By making AI’s carbon, water, and land footprints visible and comparable, the report provides a practical basis for integrating AI into energy, climate, water, and land-use planning, ensuring that innovation advances without shifting environmental costs onto vulnerable communities."

Download PDF:
https://unu.edu/inweh/collection/environmental-cost-of-AIs-Enrgy-Use-Carbon-water-and-land-footprints

#AIBoom #Electricity #Hyperscale #BigTech #BigData #CarbonFootprint #EnvironmentalRacism #EnvironmentalDegradation #NoisePollution #LightPollution #WaterIsLife #AIAgents #BotTraffic #GreenSpaces #Farmland #Prairies #Woodland #TechGiants #ProtectNature #NoDatacenters #EnergyConsumption #USPol #WorldPol #Datacentres
#DatacenterMoratoriums

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."

Read more:
https://news.oregonstate.edu/news/legacy-indigenous-stewardship-camas-dates-back-more-3500-years-osu-study-finds

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

Erin Brockovich Asks Americans For Help As She Launches Data Center Map
--
https://www.newsweek.com/erin-brockovich-asks-americans-for-help-as-she-launches-data-center-map-11989813 <-- shared media article
--
https://brockovichdatacenter.com/ <-- shared Brockovich AI Data Center Reporting web site
--
https://youtu.be/fp5ozQraKf4?si=7qu3g77iVVD3GGFJ <-- shared media video, @cbs Sunday Morning, “Nationwide boom in AI data centers stirs resistance”
--
#GIS #spatial #mapping #USA #nation #AI #datacenters #waterresources #utilities #energyconsumption #water #hydrology #hydrography #watermanagement #community #humanimpacts #costs #economics #ewaste #noise #risk #hazard #electricity #localcommunities #taxbreaks #cooling #energy #highenergyusage #infrastructure #landuse #environment #ecology #public #skepticism #environmentalimpact #scalability #growth #Virginia #Utah #Texas #Ohio #Arizona #Georgia
#ErinBrockovichFoundation #ErinBrockovich

Carving out 12 million cubic yards of rock for a toll road eyesore?

The Pennsylvania Turnpike Commission wants to eliminate the Allegheny Tunnels along the Pennsylvania Turnpike (Interstates 70/76) through Allegheny Mountain in Somerset County, Pennsylvania. The tunnels would be replaced with a massive road cut (a.k.a. ‘the Gray Cut’) that would be 250 feet deep, 1,000 feet wide and would require the excavation of 12 million cubic yards of earth and rock. That is not an engineering accomplishment, that’s a plan for a future eyesore.

A recent calculation (confirmed by using Google’s gemini.ai) has shown that 12 million cubic yards of rock would fill an entire football field to the height of a bit more than 5,600 feet…more than a mile high and nearly four Empire State Buildings tall. It would also be the tallest mountain/structure in the Commonwealth of Pennsylvania. Even a natural conical pile of this material would be approximately 1,100 feet high. Where exactly does the Turnpike Commission plan to dump all this material?

Reasons cited for the proposed Gray Cut

The Pennsylvania Turnpike Commission has noted that the cost of upgrading the tunnels would be approximately double that of the Gray Cut. They indicate it is also needed due to anticipated future traffic, improved safety (particularly related to accidents within the tunnels), maintenance costs for the tunnels, and the current need for hazardous cargo loads to bypass the tunnels. According to the turnpike’s website, the preliminary design phase is currently ongoing and is expected to be completed in 2028. If approved for construction, actual work would begin in 2033.

In regards to the cost comparison between the cut and tunnel improvements/upgrades, what never seems to be included in the calculations are the intangible benefits associated with the scenery, wildlife, ecosystems, water resources, culture, history, and lifestyles that would negatively impacted by this project.

“Look Doris, someday you’re going to find that your way of facing this realistic world just doesn’t work. And when you do, don’t overlook those lovely intangibles. You’ll discover they’re the only things that are worthwhile.”

– Fred from Miracle on 34th Street per imdb.com

In addition, many other tunnels across the nation ban hazardous materials. Exactly why is this being used as a reason to build this project here? Maybe manufacturers should be transporting such dangerous stuff on trains instead of trucks on highways? Or perhaps, it should just be an accepted cost of doing business.

Lastly, “anticipated future traffic” can be a tricky calculation. All too often, past data is used to guesstimate futures trends. In reality, unforeseen events can alter those calculations. Unforeseen events like gas prices now hovering around $4.50+ per gallon, with diesel prices running even higher. There are a litany of other things that could change the traffic dynamics – migration patterns, birthrates, car ownership rates, inflation, cyclical economic changes, war, and climate change to name a few.

If this project is being proposed just so the PA Turnpike can better compete with I-80 to the north and I-68 to the south, then that is a very poor reason to cause the extent of anticipated negative impacts listed below. It should be noted that neither I-80 nor I-68 have tunnels nor tolls. The Sideling Hill Cut west of Hancock, Maryland on I-68 is 340 feet deep and 720 feet wide. The much ballyhooed geological display at the site was closed 18 years after completion due to budget cuts. – en.wikipedia.org and mgs.md.gov

In addition, rockfall fencing needed to be added along both sides of the highway in the Sideling Hill Cut in 2023.

Anticipated negative impacts

Not only would such a massive trench leave a permanent disfiguring scar across this scenic mountainous landscape, but it would also have the following negative impacts, as noted by Citizens to Save Allegheny Mountain:

“The proposed Gray Cut would destroy critical wildlife habitats, disrupt migration patterns, and endanger species that rely on the unspoiled wilderness of the Allegheny Mountain.”

“The natural springs and deep wells that provide clean water to nearby communities and are at risk of being polluted or permanently altered by the construction.”

“The project will lead to the removal of forest stand and the displacement of massive amounts of soil and sediment that can never be reestablished or replaced.”

“This irreversible destruction…will also reduce recreational opportunities and threaten traditions such as hunting and fishing opportunities, which are vital to the region’s outdoor lifestyle.”

“The proposed construction will fragment these habitats, making it difficult for wildlife to find food, shelter, and mates.”

“The Gray Cut project jeopardizes these efforts [previous and current restoration efforts along the Stonycreek River Watershed].

“Beyond the Stonycreek River, other neighboring watersheds, including the Raystown Branch of the Juniata River and the Indian Lake Watersheds, are also at risk due to the Allegheny Mountain Tunnel’s unique location at a triple watershed divide.”

“Construction activities associated with the turnpike expansion will significantly increase the risk of soil erosion and sedimentation in nearby streams and rivers.”

“The increased runoff from paved surfaces carries pollutants such as oil, heavy metals, and other toxic substances into water bodies, further impacting the health of our waterways within the Stonycreek River watershed.”

“The noise, dust, and heavy machinery involved in this large-scale construction project would disrupt the lives of local residents and visitors who cherish the peace and quiet of the mountain.”

“The project will disrupt local communities by affecting the water supply for residents who rely on wells and natural springs. The potential contamination of these water sources poses serious health risks, particularly for those who rely on them for daily use.”

“The long-term environmental and social costs far outweigh any short-term economic gains.”

Other impacts not mentioned by Citizen to Save the Allegheny Mountain on their website, include, but are not limited to:

• Increased risk of animal vehicle collisions with the loss of the mountain’s natural wildlife crossing over the turnpike. This may lead to the future need of constructing a new wildlife crossing.

• “Drivers on the proposed highway would lose the tunnel’s protection from the worst of the weather near the turnpike’s highest point, 2,600 feet above sea level, where fog, icing and high winds are frequent hazards.” – penncapital-star.com

• The potential for microclimate changes in weather patterns as a result of the cut. According to google.gemini.ai, these could include: wind-channeling through the cut; alteration to the rain shadow on the east side of the mountain; creation of a cold air sink at the bottom of the cut increasing the likelihood of fog and frost; and disruption to wind patterns along the mountainside.

• The loss of the historic highway tunnels, first built in 1940 and expanded in 1965.

Steps one can take

If you feel this proposed project should go back to the drawing board, consider other alternatives, or be scrapped for upgrading the tunnels, please consider contacting Citizens to Save the Allegheny Mountain through the following links:

• https://savealleghenymountain.com

• https://www.facebook.com/profile.php?id=61565316543351

The organization’s website includes a petition one can sign along with space to provide comments.

Peace!

National-Scale Field Delineation In Mozambique Refines Our Understanding Of Cropland Distribution, Field Size, And Deforestation Actors.
--
https://doi.org/10.1088/1748-9326/ae5cb4 <-- shared paper
--
https://philipperufin.github.io/blog/mozfields-2023/ <-- shared associated technical article from one of the paper’s authors
--
#foodsecurity #subsistence #smallholder #farms #farming #agriculture #crops #Mozambique #subSaharan #Africa #GIS #spatial #mapping #remotesensing #earthobservation #policy #planning #cropland #spatialanalysis #spatiotemporal #field #deforestation #countrywide #landuse #sustainability #delineation #satellite #SPOT #model #modeling #deeplearning #AI #machinelearning #survey #GeoAI #spatialdata

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

How Ordnance Survey Supports Agriculture And Land Management Through Innovation And Trusted, Authoritative Data [UK]
--
https://www.ordnancesurvey.co.uk/insights/supporting-agriculture-and-land-management <-- shared technical article
--
https://youtu.be/BQReQyr3Xv0?si=6ov42Fe94epDBfBh <-- shared video, ‘CNH supports farmers with driverless tractors using OS technology’
--
https://www.ordnancesurvey.co.uk/products/os-ngd <-- shared link to the OS National Geographic Database open spatial data portal
--
#OrdnanceSurvey #OS #agency #OSNet #GPS #navigation #routing #safety #security #location #locating #GIS #spatial #mapping #precisionagriculture #farmers #farming #UK #Britain #England #Scotland #Wales #NorthernIreland #agriculture #production #food #foodsecurity #geospatial #farming #locationdata #tractor #SeeABetterPlace #mechanisation #automation #driverless #landuse #landuseframework #defra #spatialdata #opendata #OSNationalGeographicDatabase #API #downloads #Geovation #LandApp #OkoAg #SoilBenchmark #sustainable #environment
@OrdnanceSurvey @Defra @CNH

Drivers Of Forest Disturbance In Southeast Asia [incl. spatial analysis]
--
https://doi.org/10.1016/j.jag.2026.105220 <-- shared paper 🔗
--
https://github.com/shijuanchen/SEA_forest_dis <-- shared GitHub ‘data repository 🔗
--
#GIS #spatial #mapping #spatialanalysis #spatiotemporal #forest #vegetation #Forestdisturbance #Forestdegradation #Deforestation #remotesensing #SoutheastAsia #Asia #tropicalforests #timeseriesanalysis #geostatistics #disturbance #clearing #planting #agriculture #earthobservation #imagery #CCDC #changedetection #landcover #landuse #change #plantation #cultivation #slashandburn #planning #mitigation #catalogue #conservation #management #landmanagement #machinelearning #imageanalysis #AI

Map Reveals How America's Forests Have Changed Over Time
--
https://www.newsweek.com/america-forests-change-over-time-2041291 <-- shared 2025 media article
--
https://doi.org/10.5194/essd-15-1005-2023 <-- shared 2023 paper
--
https://doi.org/10.5281/zenodo.7055086 <-- shared study datasets
--
#GIS #spatial #mapping #remotesensing #spatialanalysis #spatiotemporal #copernicus #CONUS #USA #forest #model #modeling #landuse #landcover #change #forestland #agriculture #urban #development #cities #industry #vegetation #America #humanimpacts #settlement #decline #cropland #pasture #grassland #grazing #reforestation #deforestation #urbanization #conservation #ecosystems #logging #mining #railroad #infrastructure #forestcover #NLDI #farmland #colonial #LULC #census #climate #hydrology #biogeochemical

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

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

Landslide Susceptibility Assessment In The Marin Khola Watershed Of The Sub Himalaya, Central Nepal
--
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

💡 Innovative ideas in the field of spatial #SustainabilityTransformation research? We invite leading scientists to apply for an #IOER_Fellow|ship to jointly advance the spatial sustainability sciences. 📅 Apply until 12 May 2025! Learn more 👉🏻 https://www.ioer.de/en/career/ioer-fellowship

#LivableFuture #CircularEconomy #ClimateAdaption #LandUse #GeoData

@S4F @NFDI @BERD_NFDI @nfdi4earth @konsortswd

💡 Innovative ideas in the field of spatial #SustainabilityTransformation research? We invite leading scientists to apply for an #IOER_Fellow|ship to jointly advance the spatial sustainability sciences. 📅 Apply until 12 May 2025! Learn more 👉🏻 https://www.ioer.de/en/career/ioer-fellowship

#LivableFuture #CircularEconomy #ClimateAdaption #LandUse #GeoData

@S4F @NFDI @BERD_NFDI @nfdi4earth @konsortswd

💡 Innovative ideas in the field of spatial #SustainabilityTransformation research? We invite leading scientists to apply for an #IOER_Fellow|ship to jointly advance the spatial sustainability sciences. 📅 Apply until 12 May 2025! Learn more 👉🏻 https://www.ioer.de/en/career/ioer-fellowship

#LivableFuture #CircularEconomy #ClimateAdaption #LandUse #GeoData

@S4F @NFDI @BERD_NFDI @nfdi4earth @konsortswd

💡 Innovative ideas in the field of spatial #SustainabilityTransformation research? We invite leading scientists to apply for an #IOER_Fellow|ship to jointly advance the spatial sustainability sciences. 📅 Apply until 12 May 2025! Learn more 👉🏻 https://www.ioer.de/en/career/ioer-fellowship

#LivableFuture #CircularEconomy #ClimateAdaption #LandUse #GeoData

@S4F @NFDI @BERD_NFDI @nfdi4earth @konsortswd

Local Food

Can public institutions procure food locally? How do land grabs impact local food movements? What are the local food discourses in Canada? What are the ethical considerations of eating locally?

https://canadianfoodstudies.uwaterloo.ca/index.php/cfs/search/index?query=%22Local+Food%22&dateFromYear=&dateFromMonth=&dateFromDay=&dateToYear=&dateToMonth=&dateToDay=&authors=

#Read all you want! #OpenAccess
#Share generously! #KnowledgeSharing
#Grow your understanding of #Food
#Repeat

#FoodProcurement #LocalFood #LandGrabbing #LandUse #CapeBreton #Discourse #Ecological #EthicalConsumption #EthicalFood #OrganicFood #Caring #Canada

A Methodology For The Multitemporal Analysis Of Land Cover Changes And Urban Expansion Using Synthetic Aperture Radar (SAR) Imagery - A Case Study Of The Aburrá Valley In Colombia
--
https://doi.org/10.3390/rs17030554 <-- shared paper
--
#GIS #spatial #mapping #SyntheticApertureRadar #SAR #remotesensing #multitemporalanalysis #landcover #landcoverchange #clustering #kurtosis #fuzzylogic #kernelbasedmethod #machinelearning #spatialanalysis #spatiotemporal #geostatistics #model #modeling #AburráValley #Columbia #urban #urbanexpansion #population #growth #topography #monitoring #satellite #sentinel #valley #landuse #distribution #infrastructure #building #roads #naturalresources #environmental #conservation #monitoring #multitemporal

#Agriculture is a key driver of #landuse change and terrestrial #carbon & biodiversity loss. But its environment #footprint can be reduced by sustained #productivity growth: Globally, historic crop improvement (1961-2015) resulted net in less #cropland expansion, lower GHG #emissions, and more plant & animal species being saved from extinction (plus the higher #yields generally lowered commodity prices of staple crops): https://doi.org/10.1073/pnas.2404839122 #biodiversity #foodsecurity

Cropland Abandonment Between 1986 And 2018 Across The United States - Spatiotemporal Patterns And Current Land Uses
--
https://doi.org/10.1088/1748-9326/ad2d12 <-- shared paper
--
https://www.agdaily.com/crops/study-30-million-acres-cropland-abandoned-since-1980s <-- shared media article
--
#GIS #spatial #mapping #spatiotemporal #USA #spatialanalysis #crops #cropland #abandoned #remotesensing #landsat #imagery #CONUS #AI #USDA #OgallalaAquifer #GoogleEarthEngine #CNN #machinelearning #irrigation #ConservationReserveProgram #landuse #landcover #planning #management #economics

More Faults, More Resolution, More Features - The New Zealand Active Faults Database Webmap Gets A Major Upgrade
--
https://www.gns.cri.nz/news/more-faults-more-resolution-more-features-the-nz-active-faults-database-webmap-gets-a-major-upgrade/ <-- shared technical article
--
https://data.gns.cri.nz/af/ <-- New Zealand Active Faults home page/ webmap
--
#GIS #spatial #mapping #spatiotemporal #fault #faulting #NewZealand #earthquake #geology #risk #hazard #groundsurface #webmap #record #database #surfacetrace #geomorphology #geomorphmetry #NZAFD #infrastructure #earthquakeengineering #engineeringgeology #planning #urbanplanning #regulations #geotechnical #landuse #permits #slip #frequency #riskassessment #GNS
@gnsscience

More Faults, More Resolution, More Features - The New Zealand Active Faults Database Webmap Gets A Major Upgrade
--
https://www.gns.cri.nz/news/more-faults-more-resolution-more-features-the-nz-active-faults-database-webmap-gets-a-major-upgrade/ <-- shared technical article
--
https://data.gns.cri.nz/af/ <-- New Zealand Active Faults home page/ webmap
--
#GIS #spatial #mapping #spatiotemporal #fault #faulting #NewZealand #earthquake #geology #risk #hazard #groundsurface #webmap #record #database #surfacetrace #geomorphology #geomorphmetry #NZAFD #infrastructure #earthquakeengineering #engineeringgeology #planning #urbanplanning #regulations #geotechnical #landuse #permits #slip #frequency #riskassessment #GNS
@gnsscience

More Faults, More Resolution, More Features - The New Zealand Active Faults Database Webmap Gets A Major Upgrade
--
https://www.gns.cri.nz/news/more-faults-more-resolution-more-features-the-nz-active-faults-database-webmap-gets-a-major-upgrade/ <-- shared technical article
--
https://data.gns.cri.nz/af/ <-- New Zealand Active Faults home page/ webmap
--
#GIS #spatial #mapping #spatiotemporal #fault #faulting #NewZealand #earthquake #geology #risk #hazard #groundsurface #webmap #record #database #surfacetrace #geomorphology #geomorphmetry #NZAFD #infrastructure #earthquakeengineering #engineeringgeology #planning #urbanplanning #regulations #geotechnical #landuse #permits #slip #frequency #riskassessment #GNS
@gnsscience

More Faults, More Resolution, More Features - The New Zealand Active Faults Database Webmap Gets A Major Upgrade
--
https://www.gns.cri.nz/news/more-faults-more-resolution-more-features-the-nz-active-faults-database-webmap-gets-a-major-upgrade/ <-- shared technical article
--
https://data.gns.cri.nz/af/ <-- New Zealand Active Faults home page/ webmap
--
#GIS #spatial #mapping #spatiotemporal #fault #faulting #NewZealand #earthquake #geology #risk #hazard #groundsurface #webmap #record #database #surfacetrace #geomorphology #geomorphmetry #NZAFD #infrastructure #earthquakeengineering #engineeringgeology #planning #urbanplanning #regulations #geotechnical #landuse #permits #slip #frequency #riskassessment #GNS
@gnsscience

More Faults, More Resolution, More Features - The New Zealand Active Faults Database Webmap Gets A Major Upgrade
--
https://www.gns.cri.nz/news/more-faults-more-resolution-more-features-the-nz-active-faults-database-webmap-gets-a-major-upgrade/ <-- shared technical article
--
https://data.gns.cri.nz/af/ <-- New Zealand Active Faults home page/ webmap
--
#GIS #spatial #mapping #spatiotemporal #fault #faulting #NewZealand #earthquake #geology #risk #hazard #groundsurface #webmap #record #database #surfacetrace #geomorphology #geomorphmetry #NZAFD #infrastructure #earthquakeengineering #engineeringgeology #planning #urbanplanning #regulations #geotechnical #landuse #permits #slip #frequency #riskassessment #GNS
@gnsscience

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

Today our article "#Landuse and #landcover as a conditioning factor in landslide #susceptibility: a #literaturereview" was accepted to be published in #Landslides, the leading journal on this subject.

This article is a part of my PhD thesis focused on landslide susceptibility and the influence of spatial heterogeneity and #LUCC.

I am very happy to end 2022 with this news!

Thank you to all the collaborators!!