#himalayas — Public Fediverse posts

Chinese national rescued from Nepal tunnel

A Chinese national was pulled alive from a tunnel in Nepal ten ‌days after a wall of ice, rock and mud tore through a Himalayan valley, killing more than 1,300 people. #nepal #environment #himalayas #mudslides #china #tibet #climatechange #glacier #asia #News #Reuters #Newsfeed Read the story here: 👉 Subscribe: Keep up with the latest news from around the world: Follow Reuters on Facebook: Follow Reuters on X: Follow Reuters…

https://fllics.com/en/video/chinese-national-rescued-from-nepal-tunnel/

Nepal floods highlight growing glacier risks in warming Himalayas https://news.mongabay.com/short-article/2026/08/nepal-floods-highlight-growing-glacier-risks-in-warming-himalayas/

#Nepal #Himalaya #Himalayas #glaciers #environment #flood #floods #flooding

Flood And Landslide Susceptibility Assessment And Multi Hazard Interaction Mapping Using Machine Learning And GIS For Sustainable Settlement Planning In Nepal
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https://doi.org/10.1007/s44288-026-00670-8 <-- shared paper
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H/T @Narayan Thapa | Earth Data Modeling
“Nepal lies within an active seismic zone and is influenced by most dynamic climatic systems in the world. It faces compounding floods and landslide threats. Impacts are worst where multi-hazard interactions create spatially linked corridors. Despite frequent co-occurrence, national-scale assessments remain limited. This study presents machine learning and GIS-based approach to map nationwide susceptibility to floods, landslides, and identify their potential interaction zones, and delineate critical multi-hazard flow zones through spatial adjacency analysis. Using Google Earth Engine, the Random Forest model integrates topographic, climatic, environmental, and hydrological datasets to overcome subjective expert-driven methods. The model achieved strong predictive accuracy (AUC: 0.84 for floods, 0.85 for landslides). The results showed 19% of Nepal’s lowlands are medium to very highly susceptible to inundation, threatening approximately 900,000 people and over 3.4 million buildings; whilst in the hilly terrains, 40% is susceptible to slope-failure endangering 200,000 people and about 0.6 million buildings. K-means clustering followed by spatial adjacency analysis identified four spatial zonation: 81% of national area as low-hazard zone, 9% as flood-only zone, 5% as landslide-only zone, and 5% as interaction zones. Critical multi-hazard flow zone covering 7,588 km² represents spatially connected corridors linking interaction zones to downstream flood-prone populated areas, affecting 88 km² built-up land and 1,722 km² cropland. These zones represent susceptibility-based spatial connectivity rather than physically simulated cascading processes. These findings support recommendations for risk-informed land-use planning, resilient infrastructure development and climate adaptation aligned to sustainable development and investment risk screening…”
#GIS #spatial #mapping #GoogleEarthEngine #MachineLearning #RemoteSensing #GeospatialAI #DisasterRiskReduction #MultiHazard #ClimateAdaptation #climatechange #extremeweather #LandUsePlanning #SustainableDevelopment #InfrastructurePlanning #RiskAssessment #NaturalHazards #Nepal #EarthObservation #HinduKushHimalaya #HKH #HinduKush #Himalayas #risk #hazard #assessment #national #regional #spatialanalysis #spatiotemporal #massmovement #landslide #assessment #mitigation #water #hydrology #flood #flooding #sustainability

Compound Hydrogeomorphic Cascades And Rapid Upstream To Downstream Hazard Coupling In The Eastern Himalaya
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https://doi.org/10.1038/s41598-026-52915-8 <-- shared paper
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https://doi.org/10.1007/s11600-022-00943-z <-- shared paper
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H/T @Kuldeep Dutta | Geology-Earth Science
“… In hilly regions transitioning rapidly to low gradient alluvial plains, localized hydrometeorological triggers can instantly scale into devastating basin wide disasters. This study dissects the September 2020 cascading hazard in parts of the Arunachal Pradesh-Assam corridor to quantify the rapid coupling between upstream hillslopes and downstream floodplains.
Check out the [attached graphical abstract figure] for an integrated visual workflow of the entire disaster continuum from hillslope failure to floodplain transformation...”
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“Extreme precipitation in the Eastern Himalaya is increasingly associated with coupled hillslope-floodplain hazards. This study examines the 17th-18th September 2020 rainfall event in Arunachal Pradesh initiating landslides and its downstream impacts in Assam, India, using multi-sensor satellite data and long-term rainfall records. Sentinel-2 imagery was used to map landslides and debris flows, Sentinel-1 SAR data to delineate flood extent, and IMD gridded rainfall (1996–2020) to analyse rainfall spell characteristics. The event triggered widespread slope failures, localized landslide damming, and a subsequent breach, generating sediment-laden flows that inundated ~ 100 km² of the Dhemaji floodplain. A backscatter-derived Relative Flood Volume Index (RFVI) indicates spatial variability in inundation intensity, although it does not represent absolute flood volume. Rainfall analysis suggests that antecedent wetness from preceding spells preconditioned slopes, while peak daily rainfall (> 170 mm day−1) initiated landsliding. Power-law scaling shows negligible dependence of intensity on duration (R2 ≈ 0.0004), whereas cumulative rainfall exhibits a stronger relationship with duration (R2 ≈ 0.54). These results indicate distinct roles of rainfall intensity and accumulation in controlling landslide initiation and downstream flooding, respectively, highlighting the importance of compound rainfall forcing in rapid hydrogeomorphic cascades…”
#EarthScience #RemoteSensing #Himalayas #NaturalHazards #ClimateChange #ScientificReports #GeospatialAnalysis #DisasterMitigation #Landslide #trigger #Flooding #massmovement #extremeweather #engineeringgeology #floodplain #innundation #hillslope #fluvial #pluvial #alluvial #sediment #sedimentation #hydrometeorology #ArunachalPradesh #Assam #India #Brahmaputra #risk #hazard #geology #engineeringgeology #remotesensing #earthobservation #spatialanalysis #spatiotemporal #disaster #hydrogeomorphology #workflow

Compound Hydrogeomorphic Cascades And Rapid Upstream To Downstream Hazard Coupling In The Eastern Himalaya
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https://doi.org/10.1038/s41598-026-52915-8 <-- shared paper
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https://doi.org/10.5194/esurf-13-1281-2025 <-- shared paper
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https://doi.org/10.1007/s11069-025-07766-3 <-- shared paper
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[I recognise that the photo is instead for the floods, etc in Lubra, Nepal - but felt it better showed the hydrogeomorphical setting (sic) for the 'casual' post viewer...]
H/T @Kuldeep Dutta
“In hilly regions transitioning rapidly to low gradient alluvial plains, localized hydrometeorological triggers can instantly scale into devastating basin wide disasters. This study dissects the September 2020 cascading hazard in parts of the Arunachal Pradesh-Assam corridor to quantify the rapid coupling between upstream hillslopes and downstream floodplains…”
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“Extreme precipitation in the Eastern Himalaya is increasingly associated with coupled hillslope-floodplain hazards. This study examines the 17th-18th September 2020 rainfall event in Arunachal Pradesh initiating landslides and its downstream impacts in Assam, India, using multi-sensor satellite data and long-term rainfall records. Sentinel-2 imagery was used to map landslides and debris flows, Sentinel-1 SAR data to delineate flood extent, and IMD gridded rainfall (1996–2020) to analyse rainfall spell characteristics. The event triggered widespread slope failures, localized landslide damming, and a subsequent breach, generating sediment-laden flows that inundated ~ 100 km2 of the Dhemaji floodplain. A backscatter-derived Relative Flood Volume Index (RFVI) indicates spatial variability in inundation intensity, although it does not represent absolute flood volume. Rainfall analysis suggests that antecedent wetness from preceding spells preconditioned slopes, while peak daily rainfall (> 170 mm/day/) initiated landsliding. Power-law scaling shows negligible dependence of intensity on duration (R² ≈ 0.0004), whereas cumulative rainfall exhibits a stronger relationship with duration (R² ≈ 0.54). These results indicate distinct roles of rainfall intensity and accumulation in controlling landslide initiation and downstream flooding, respectively, highlighting the importance of compound rainfall forcing in rapid hydrogeomorphic cascades...”
#EarthScience #RemoteSensing #Himalayas #NaturalHazards #ClimateChange #ScientificReports #GeospatialAnalysis #DisasterMitigation #Landslide #Flooding #alluvial #fluvial #water #hydrology #hydrography #flood #flooding #spatialanalysis #spatiotemporal #mountain #plain #hydrometeorological #hydrogeomorphology #ArunachalPradesh #Assam #India #hillslope #floodplain #rainfall #precipitation #extremeweather #engineeringgeology #massmovement #landslide #debrisflow #risk #hazard #monitoring #GIS #spatial #mapping #remotesensing #satellite #Sentinel #sedimentation #humanimpacts #infrastructure #damage #cost #economics #public #safety #model #modeling #downstream

Permafrost Distribution, Degradation, And Potential Mass Movement Cascades In The Western Himalaya Using Machine Learning And Numerical Models
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https://doi.org/10.1038/s44304-026-00217-4 <-- shared paper
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https://doi.org/10.1038/s41598-025-22051-w <-- shared (earlier) paper
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https://doi.org/10.1080/2150704X.2025.2488532 <-- shared (earlier) paper
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H/T @abhinav Alangadan
“Can we develop a first-order understanding of permafrost degradation and glacial lakes exposed to degradation-induced mass movements in the Himalaya?
[The authors] tried to address this question. The study [first link above] integrates machine learning, statistical modeling, and numerical modeling to investigate high-resolution permafrost distribution, potential degradation, and associated mass-movement hazards in the Kinnaur district of Himachal Pradesh, India.
Using rock glaciers as proxies, [they] generated a high-resolution permafrost distribution using machine learning, while potential degradation zones were delineated using the 0°C isotherm as a first-order indicator. [They] further identified glacial lakes located near potentially degrading permafrost zones and reconstructed their bathymetry. A detailed scenario-based GLOF process-chain simulation was then carried out for Kashang Lake using r.avaflow and HEC-RAS.
[Their] results indicate that seven glacial lakes in #Kinnaur are located close to potentially degrading permafrost zones. The simulations further show that a potential GLOF from Kashang Lake could inundate critical downstream infrastructure, including nearly 11 km of National Highway 5…”
#permafrost #distribution #GIS #spatial #mapping #Himalayas #India #Kinnaur #HimachalPradesh #KashangLake #massmovement #engineeringgeology #machinelearning #AI #model #modeling #numericalmodel #glaciallakes #glaciet #glacial #glaciallakeoutburstflood #GLOF #cryosphere #geostatistics #rockglaciers #GeoAI #bathymetry #processchainsimulation #HECRAS #avaflow #risk #hazard #mitigation #riskassessment #infrastructure #HEP #publicsafety #downstream #avalanche

💁🏻‍♀️ TIL: 🏔️❄️ Roughly the size of #HongKong, #Sagarmatha National Park in north-east #Nepal contains Mount #Everest, the highest #mountain on #Earth.

Established in 1976 and declared a #UNESCO World Heritage Site in 1979, the #park spans 1,148 square km of #glaciers, river #valleys, and #forests. It hosts 28 #mammal species and over 150 #birds, including snow #leopards, red #pandas, Himalayan #tahr, and bar-headed #geese.

👉 https://www.discoverwildlife.com/animal-facts/sagarmatha-national-park

#himalayas #everest #unesco #snowleopard #redpanda #wildlife #conservation #mountains #biodiversity #nature #geography

What Are Some Popular Trekking Destinations in the Himalayan Region?

https://indiasafaristrends.wordpress.com/2026/06/07/what-are-some-popular-trekking-destinations-in-the-himalayan-region/

Hanging Glaciers In Himalaya Reveal Rising Avalanche Risk
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https://www.nature.com/articles/d44151-026-00072-2 <-- shared technical article
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https://doi.org/10.1038/s44304-026-00205-8 <-- shared paper
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#GIS #spatial #mapping #risk #hazard #monitoring #engineeringgeology #naturalhazard #Himalaya #Himalayas #Alaknanda #basin #Garhwal #India #ice #cryosphere #massmovement #avalanche #glacier #hangingglacier #cryosphere #remotesensing #spatialanalysis #spatiotemporal #sentinel2 #DEM #elevation #model #modeling #GlabTop2 #unstable #hanging #BadrinathMana #impact #infrastructure #damage #HEP #urbanisation #development #population #publicsafety #demographics #glacialretreat #melting #Chamoli #disaster #earlywarningsystems #Himalayan #glaciers #instability #warming #climatechange #riskassessment #riskclassification #framework #avaflow #runout #downstream #downslope #water #hydrology #planning #policy #mitigation #geomorphology #geomorphometry

Remote Sensing And Process Attribution Uncertainties In The Dharali Event [Himalayas, India]
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https://doi.org/10.1038/s44304-026-00211-w <-- shared paper review
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https://doi.org/10.1038/s44304-026-00191-x <-- shared paper that was reviewed
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https://doi.org/10.1016/j.nhres.2025.11.001 <-- related shared paper
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#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

A Red Pierrot (Talicada nyseus) butterfly. Dehradun India.

As per Sanjay Sondhi of Titli Trust, the Red Pierrot was not seen in this region till some years ago. The theory being that this butterfly may have arrived with the boom in Kalanchoe, the host plant, of the Red Pierrot.

Whatever reason this is a beautiful butterfly, both closed wings, or open wings.

#entomology #IndiasNature #butterfly #lepidoptera #TalicudaNyseus #RedPierrot #Himalayas #Dehradun #nature

https://en.wikipedia.org/wiki/Talicada_nyseus

Ice-Patch Collapse And Early-Warning Implications From A Himalayan Flash Flood - Emerging Cryo-Hydrological Hazards Under Deglaciation
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https://doi.org/10.1038/s44304-026-00191-x
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https://youtu.be/zZXER7DocfY?si=lYOE_a6YwigP3-mB
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#GIS #spatial #mapping #glacier #glacial #cryosphere #risk #hazard #flood #flooding #flashflood #earthobservation #cryohydrology #ice #snow #water #hydrogy #Himalaya #Himalayan #extremeweather #monitoring #risk #hazard #forecasting #DharaliFlashFlood #CryosphereScience #Deglaciation #EarlyWarning #RemoteSensing #Himalayas #NaturalHazards #ClimateChange #GlacierResearch #OpenScience #highmountain #mountain #slope #steepness #erosion #fluvial #nivation #Uttarakhand #India #SrikantaGlacier #DEM #elevation #satellite #chronology #reconstruction #ablation #debris #sedimentation #debrisflow #meltwater #debris #surge #massmovement #engineeringgeology #cryospherichazard #terrain #spatialanalysis #spatiotemporal #earlywarning #naturalhazard #channel #topography #geography #hydrogeomorphology #geomorphology #Dharali

Improving Forest Loss Mapping In Nepal Using Landtrendr Time-Series And Machine Learning
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https://doi.org/10.1016/j.rsase.2025.101864 <-- share paper
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“HIGHLIGHTS:
• ViT-based forest mask, multispectral ensemble LandTrendr and terrain shadow mask.
• District-level RF/XGBoost model training with expert-weighted validation.
• Outperformed GFC and REDD + AI benchmarks in accuracy and F1 performance.
• RF excelled in High Mountains/Himalayas; XGBoost in the lower Mountain regions.
• NBR contributed the most; snow-impacted forest loss uncertainty was observed..."
#Forestdisturbance #forest #disturbance #remotesensing #LandTrendr #workflow #timeseries #ViT #RF #XGBoost #GEE #Nepal #ForestNepal #spatial #GIS #mapping #earthobservation #landsat #Himalayas #mountains #alpine #vegetation #AI #multispectral #monitoring #spatialanalysis #spatiotemporal #loss #change #machinelearning #NDR #conservation #planning #policy #mitagion #ecology #Karnali #Bagmati, #Darchula #Siwalik #GlobalForestChange #Degradation

Indian Towns with a European Vibe: Explore Charm, Luxury, and Culture in 2026–2027

https://indiasafaristrends.wordpress.com/2025/08/25/indian-towns-with-a-european-vibe-explore-charm-luxury-and-culture-in-2025-2026/

The most turbulent flight routes on each continent:

🇦🇷 Mendoza → 🇨🇱 Santiago (South America)
🇳🇵 Kathmandu → 🇨🇳 Lhasa (Asia)
🇺🇸 Albuquerque → 🇺🇸 Denver (North America)
🇫🇷 Nice → 🇨🇭 Geneva (Europe)
🇿🇦 Durban → 🇿🇦 Johannesburg (Africa)
🇳🇿 Christchurch → 🇳🇿 Wellington (Oceania)

Turbulence is not random.

From the Andes and Himalayas to the Rockies and Alps, certain flight paths are consistently rough due to towering mountains, shifting wind patterns, and powerful jet streams. These are the forces behind every bump and jolt in the sky. 🏔️✈️🌪️

#Turbulence #Flight #TurbulentFlightRoutes #Himalayas #Andes #Rockies #TurbulentRoutes #CAT #ClearAirTurbulence #Alps #Lhasa #Kathmandu #Mendoza #Santiago #Randomness #Random #Mountains #ToweringMountains #JetStreams #FlightPaths #Aerospace #Airplane #Aeroplane

This c1790 ad #Pahari #IndianMiniaturePainting from #Kangra #HimachalPradesh from the family workshop of #Nainsukh of #Guler depicts the Musical Mode 'Natanarayan #Raga'

Now at Rietberg Museum, this was last displayed at their 2024 exhibition " #Ragamala : Images for all Seasons"

#shivratri2025
#Hindu God Lord #Shiva

#Hinduism #Religion #artoftheday #IndianHeritage #IndianFestivals #Art #Heritage #Paintings #History #IndianHistory #MastoArt #Histodons #Himalayas

आंदोलन भी एक प्रकार का राष्ट्रधर्म - सोनम वांगचुक।

https://aliyesha.com/sub/articles/news/display/uk_activism_a_national_duty_wangchuk

#uttarakhand #dehradun #india #news #press #environment #himalayas #pashmina #solarenergy #ladhak #3idiots

Enjoy tracker free reading with us. #privacy #privacymatters

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
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#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

Himalayas Formation May Have Destroyed At Least 30% Of Continental Crust In Collision Zone
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https://phys.org/news/2024-11-himalayas-formation-destroyed-continental-crust.html <-- shared technical article
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https://doi.org/10.1016/j.epsl.2024.119070 <-- shared paper
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#geology #structuralgeology #model #modeling #numericmodeling #geochemistry #mountainbuilding #orogeny #Himalayas #continentalcrust #platetectonics #continents #EuropeanAlps #ZagrosMountains #mantle #subsumed #deformation #erosion #thickening #extrusion #massbalance #calculations #delamination #topography #lithosphere

The Changing Ecology Of A High Himalayan Valley - Challenges To The Sustainable Development Of The Kanchenjunga Conservation Area, Eastern Nepal
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https://doi.org/10.3390/su16062434 <-- shared paper
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#GIS #spatial #mapping #geology #geomorphology #infrastructure #change #Kanchenjunga #conservationarea #Nepal #sustainability #roads #adventuretourism #climatechange #wildlife #humanimpact #mountains #history #development #remotesensing #MPA #impactassessment #social #environment #glaciallakeoutburstflood #GLOF #Himalayas

Climate Change Impact Assessment On The Hydrological Regime Of The Kaligandaki Basin, Nepal
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https://doi.org/10.1016/j.scitotenv.2017.12.332 <-- shared paper
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“HIGHLIGHTS
• The rise in temperature and increase in precipitation is projected in future in Kaligandaki River basin.
• The water availability in the basin is not likely to decrease during this century.
• The change in water balance in the upper sub-basins of Kaligandaki River is higher.
• The output from this research could be beneficial for water resources management..."
#GIS #spatial #mapping #Nepal #Kaligandaki #riverbasin #basin #river #hydrology #model #modeling #numericmodeling #climatechange #temperature #precipitation #ET ##waterresources #water #watersecurity #waterbalance #impactassessment #humanimpacts #freshwater #HinduKush #himalayas #SWAT #prediction #projection #cimip5 #gcm #waterbalance #snowmelt #evapotranspiration #spatialanalysis #spatiotemporal

New Geological Study Rewrites History Of The World's Highest Peaks
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https://www.forbes.com/sites/davidbressan/2023/08/15/new-geological-study-rewrites-history-of-the-worlds-highest-peaks/ <-- shared media article
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https://doi.org/10.1038/s41561-023-01243-x <-- shared paper
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#GIS #spatial #mapping #remotesensing #uplift #Himalayas #tibet #model #modeling #research #uplift #sampling #hydrothermal #oxygenisotopes #India #Eurasia #mountains #geology #structuralgeology #TibetanPlateau #palaeoaltimetry #palaeoelevation #geodynamic #palaeoclimate #GangdeseArc #subduction #lithosphere #continentalcollision

I brought my teeny little #Platypod on this trip and figured I wouldn't use it much but this morning I popped my 85mm on the "tripod" and did a few "hires mode" shots.

Still amazes me just how much detail you can get from a 24MP sensor, building a 96MP RAW file.

Also amazes me just how cold it get on the rooftop of our guesthouse at 6am in November!

#Nepal #Annapurnas #Himalayas #LumixS5 #Lumix #CaptureDontClimb #NoLoveLikeSnowLove #JustLuckyToBeHere #Photography #Fotografie