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#precipitation — Public Fediverse posts

Live and recent posts from across the Fediverse tagged #precipitation, aggregated by home.social.

  1. That wx & music girl ☮️&💜 @[email protected] ·

    Here's today's forecast map and today's high temperature map. Check out the NWS site for more National Forecast Maps www.weather.gov/forecastmaps
    #weather #wx #Forecast #precipitation #Temperature #TheOutPost

    #weather #wx #forecast #precipitation #temperature #theoutpost
  2. That wx & music girl ☮️&💜 @[email protected] ·

    Here's today's forecast map and today's high temperature map. Check out the NWS site for more National Forecast Maps www.weather.gov/forecastmaps
    #weather #wx #Forecast #precipitation #Temperature #TheOutPost

    #weather #wx #forecast #precipitation #temperature #theoutpost
  3. That wx & music girl ☮️&💜 @[email protected] ·

    Here's today's forecast map and today's high temperature map. Check out the NWS site for more National Forecast Maps www.weather.gov/forecastmaps
    #weather #wx #Forecast #precipitation #Temperature #TheOutPost

    #theoutpost #temperature #precipitation #forecast #wx #weather
  4. That wx & music girl ☮️&💜 @[email protected] ·

    Here's today's forecast map and today's high temperature map. Check out the NWS site for more National Forecast Maps www.weather.gov/forecastmaps
    #weather #wx #Forecast #precipitation #Temperature #TheOutPost

    #weather #wx #forecast #precipitation #temperature #theoutpost
  5. 💧🌏 Greg Cocks @[email protected] ·

    Mapping Flood Agents In The Northern Pantanal Wetland Using Multiple Spatio-Temporal GIS And Remote Sensing Techniques
    --
    doi.org/10.1007/s13157-026-020 <-- shared paper
    --
    H/T @renato Gatto de Morais | Geógrafo | Mestre em Recursos Hídricos | Doutorando em Geografia
    “Combining MODIS data, TRMM, river discharge, a digital terrain model, and multinomial logistic regression, [the authors] identified three predominant classes of flood origin: local rainfall, bank overflow, and mixed areas. The model achieved a Nagelkerke Pseudo-R² of 0.63 and a classification accuracy of up to 81.2% (10-fold cross-validation). To the best of [their] knowledge, this is the first explicit approach to mapping flood agents for this wetland, a component that has historically remained unmapped despite its recognized influence on habitats and biodiversity…”
    --
    “The mapping of functional hydrologic units is crucial for enhancing our understanding of flooding and hydroecological processes in large wetlands. These units are typically defined by flooding frequency, duration, and magnitude, but another important hydrologic characteristic is the origin of flooding, known as the flood agent. This study presents an empirical framework utilizing remote sensing and GIS procedures for modeling flood agents in the northern Pantanal wetland. Eleven spatial data layers were derived from multi-year MODIS flood maps, daily rainfall estimates from the TRMM 3B42 grid, in situ discharge data, the BEST Digital Terrain Model, and a hydrographic network layer. These layers were tested for their predictive power in a multinomial logistic regression mapping model. Model performance metrics, along with qualitative validation of mapping outcomes using in situ flooding measurements, and vegetation and soil data from field test sites, support the plausibility of the proposed mapping scheme. However, they also highlight the challenges of flood agent mapping in large tropical wetlands…”
    #GIS #spatial #mapping #MODIS #TRMM #riverdischarge #digitalterrainmodel #multinomiallogisticregression #geostatistics #Pantanal #Cuiaba #Brazil #water #hydrology #spatialanalysis #spatiotemporal #remotesensing #earthobservation #flood #flooding #source #type #floodagent #tropical #wetland #habitat #biodiversity #ecosystem #hydrologicunit #hydroecology #model #modeling #rainfall #precipitation #weather #climate #discharge #network #metrics

    #gis #spatial #mapping #modis #trmm #riverdischarge
  6. 💧🌏 Greg Cocks @[email protected] ·

    Mapping Flood Agents In The Northern Pantanal Wetland Using Multiple Spatio-Temporal GIS And Remote Sensing Techniques
    --
    doi.org/10.1007/s13157-026-020 <-- shared paper
    --
    H/T @renato Gatto de Morais | Geógrafo | Mestre em Recursos Hídricos | Doutorando em Geografia
    “Combining MODIS data, TRMM, river discharge, a digital terrain model, and multinomial logistic regression, [the authors] identified three predominant classes of flood origin: local rainfall, bank overflow, and mixed areas. The model achieved a Nagelkerke Pseudo-R² of 0.63 and a classification accuracy of up to 81.2% (10-fold cross-validation). To the best of [their] knowledge, this is the first explicit approach to mapping flood agents for this wetland, a component that has historically remained unmapped despite its recognized influence on habitats and biodiversity…”
    --
    “The mapping of functional hydrologic units is crucial for enhancing our understanding of flooding and hydroecological processes in large wetlands. These units are typically defined by flooding frequency, duration, and magnitude, but another important hydrologic characteristic is the origin of flooding, known as the flood agent. This study presents an empirical framework utilizing remote sensing and GIS procedures for modeling flood agents in the northern Pantanal wetland. Eleven spatial data layers were derived from multi-year MODIS flood maps, daily rainfall estimates from the TRMM 3B42 grid, in situ discharge data, the BEST Digital Terrain Model, and a hydrographic network layer. These layers were tested for their predictive power in a multinomial logistic regression mapping model. Model performance metrics, along with qualitative validation of mapping outcomes using in situ flooding measurements, and vegetation and soil data from field test sites, support the plausibility of the proposed mapping scheme. However, they also highlight the challenges of flood agent mapping in large tropical wetlands…”
    #GIS #spatial #mapping #MODIS #TRMM #riverdischarge #digitalterrainmodel #multinomiallogisticregression #geostatistics #Pantanal #Cuiaba #Brazil #water #hydrology #spatialanalysis #spatiotemporal #remotesensing #earthobservation #flood #flooding #source #type #floodagent #tropical #wetland #habitat #biodiversity #ecosystem #hydrologicunit #hydroecology #model #modeling #rainfall #precipitation #weather #climate #discharge #network #metrics

    #gis #spatial #mapping #modis #trmm #riverdischarge
  7. 💧🌏 Greg Cocks @[email protected] ·

    Mapping Flood Agents In The Northern Pantanal Wetland Using Multiple Spatio-Temporal GIS And Remote Sensing Techniques
    --
    doi.org/10.1007/s13157-026-020 <-- shared paper
    --
    H/T @renato Gatto de Morais | Geógrafo | Mestre em Recursos Hídricos | Doutorando em Geografia
    “Combining MODIS data, TRMM, river discharge, a digital terrain model, and multinomial logistic regression, [the authors] identified three predominant classes of flood origin: local rainfall, bank overflow, and mixed areas. The model achieved a Nagelkerke Pseudo-R² of 0.63 and a classification accuracy of up to 81.2% (10-fold cross-validation). To the best of [their] knowledge, this is the first explicit approach to mapping flood agents for this wetland, a component that has historically remained unmapped despite its recognized influence on habitats and biodiversity…”
    --
    “The mapping of functional hydrologic units is crucial for enhancing our understanding of flooding and hydroecological processes in large wetlands. These units are typically defined by flooding frequency, duration, and magnitude, but another important hydrologic characteristic is the origin of flooding, known as the flood agent. This study presents an empirical framework utilizing remote sensing and GIS procedures for modeling flood agents in the northern Pantanal wetland. Eleven spatial data layers were derived from multi-year MODIS flood maps, daily rainfall estimates from the TRMM 3B42 grid, in situ discharge data, the BEST Digital Terrain Model, and a hydrographic network layer. These layers were tested for their predictive power in a multinomial logistic regression mapping model. Model performance metrics, along with qualitative validation of mapping outcomes using in situ flooding measurements, and vegetation and soil data from field test sites, support the plausibility of the proposed mapping scheme. However, they also highlight the challenges of flood agent mapping in large tropical wetlands…”
    #GIS #spatial #mapping #MODIS #TRMM #riverdischarge #digitalterrainmodel #multinomiallogisticregression #geostatistics #Pantanal #Cuiaba #Brazil #water #hydrology #spatialanalysis #spatiotemporal #remotesensing #earthobservation #flood #flooding #source #type #floodagent #tropical #wetland #habitat #biodiversity #ecosystem #hydrologicunit #hydroecology #model #modeling #rainfall #precipitation #weather #climate #discharge #network #metrics

    #gis #spatial #mapping #modis #trmm #riverdischarge
  8. 💧🌏 Greg Cocks @[email protected] ·

    Mapping Flood Agents In The Northern Pantanal Wetland Using Multiple Spatio-Temporal GIS And Remote Sensing Techniques
    --
    doi.org/10.1007/s13157-026-020 <-- shared paper
    --
    H/T @renato Gatto de Morais | Geógrafo | Mestre em Recursos Hídricos | Doutorando em Geografia
    “Combining MODIS data, TRMM, river discharge, a digital terrain model, and multinomial logistic regression, [the authors] identified three predominant classes of flood origin: local rainfall, bank overflow, and mixed areas. The model achieved a Nagelkerke Pseudo-R² of 0.63 and a classification accuracy of up to 81.2% (10-fold cross-validation). To the best of [their] knowledge, this is the first explicit approach to mapping flood agents for this wetland, a component that has historically remained unmapped despite its recognized influence on habitats and biodiversity…”
    --
    “The mapping of functional hydrologic units is crucial for enhancing our understanding of flooding and hydroecological processes in large wetlands. These units are typically defined by flooding frequency, duration, and magnitude, but another important hydrologic characteristic is the origin of flooding, known as the flood agent. This study presents an empirical framework utilizing remote sensing and GIS procedures for modeling flood agents in the northern Pantanal wetland. Eleven spatial data layers were derived from multi-year MODIS flood maps, daily rainfall estimates from the TRMM 3B42 grid, in situ discharge data, the BEST Digital Terrain Model, and a hydrographic network layer. These layers were tested for their predictive power in a multinomial logistic regression mapping model. Model performance metrics, along with qualitative validation of mapping outcomes using in situ flooding measurements, and vegetation and soil data from field test sites, support the plausibility of the proposed mapping scheme. However, they also highlight the challenges of flood agent mapping in large tropical wetlands…”
    #GIS #spatial #mapping #MODIS #TRMM #riverdischarge #digitalterrainmodel #multinomiallogisticregression #geostatistics #Pantanal #Cuiaba #Brazil #water #hydrology #spatialanalysis #spatiotemporal #remotesensing #earthobservation #flood #flooding #source #type #floodagent #tropical #wetland #habitat #biodiversity #ecosystem #hydrologicunit #hydroecology #model #modeling #rainfall #precipitation #weather #climate #discharge #network #metrics

    #metrics #network #discharge #climate #weather #precipitation
  9. 💧🌏 Greg Cocks @GregCocks ·

    Mapping Flood Agents In The Northern Pantanal Wetland Using Multiple Spatio-Temporal GIS And Remote Sensing Techniques
    --
    doi.org/10.1007/s13157-026-020 <-- shared paper
    --
    H/T @renato Gatto de Morais | Geógrafo | Mestre em Recursos Hídricos | Doutorando em Geografia
    “Combining MODIS data, TRMM, river discharge, a digital terrain model, and multinomial logistic regression, [the authors] identified three predominant classes of flood origin: local rainfall, bank overflow, and mixed areas. The model achieved a Nagelkerke Pseudo-R² of 0.63 and a classification accuracy of up to 81.2% (10-fold cross-validation). To the best of [their] knowledge, this is the first explicit approach to mapping flood agents for this wetland, a component that has historically remained unmapped despite its recognized influence on habitats and biodiversity…”
    --
    “The mapping of functional hydrologic units is crucial for enhancing our understanding of flooding and hydroecological processes in large wetlands. These units are typically defined by flooding frequency, duration, and magnitude, but another important hydrologic characteristic is the origin of flooding, known as the flood agent. This study presents an empirical framework utilizing remote sensing and GIS procedures for modeling flood agents in the northern Pantanal wetland. Eleven spatial data layers were derived from multi-year MODIS flood maps, daily rainfall estimates from the TRMM 3B42 grid, in situ discharge data, the BEST Digital Terrain Model, and a hydrographic network layer. These layers were tested for their predictive power in a multinomial logistic regression mapping model. Model performance metrics, along with qualitative validation of mapping outcomes using in situ flooding measurements, and vegetation and soil data from field test sites, support the plausibility of the proposed mapping scheme. However, they also highlight the challenges of flood agent mapping in large tropical wetlands…”

    #gis #spatial #mapping #modis #trmm #riverdischarge
  10. 💧🌏 Greg Cocks @[email protected] ·

    Can Himalayan Crops Help Secure The Future Of Food?
    (Exploring how genomic diversity, traditional crops, and regional cooperation can strengthen climate resilience and food security across the Hindu Kush Himalaya [HKH])
    --
    substack.com/home/post/p-20744 <-- shared technical post
    --
    openlibrary.substack.com/ <-- shared Substack, “Open Library on Green Economy”
    --
    adaptationwithoutborders.org/k <-- shared technical article, “Shifting cooperation in the [HKH]”
    --
    icimod.org/who-we-are/the-hind <-- background on the HKH, International Centre for Integrated Mountain Development (ICIMOD)
    --
    doi.org/10.48130/cas-0026-0003 <-- shared paper
    --
    [not at all my technical area - but fascinating, including the spatial component #alldataisspatial]
    H/T @jeevan Labh
    “As we navigate the intensifying impacts of the 2026 El Niño, the vulnerability of our global food systems require careful evaluation. With this year’s erratic weather patterns driving severe, prolonged droughts in some regions and unseasonal, devastating floods in others, the climate crisis is proving that it is not a distant threat; it is happening right now, in our fields and on our plates.
    This crisis is more visible in the Hindu Kush Himalaya (HKH) region. Often called the “water tower of Asia,” this vast mountain range sustains 240 million people across eight countries and provides essential ecosystem services to nearly 2 billion people downstream. When glaciers melt at accelerated rates and monsoons become unpredictable, the narrative often focuses solely on the mountain communities. But the truth is much broader: a disrupted harvest in the high hills of Nepal or Bhutan creates a domino effect. It leads to displaced populations, reduced agricultural output flowing into the Indus, Ganges, and Brahmaputra basins, and ultimately, skyrocketing food prices for families living in the sprawling downstream plains.
    The climate crisis respects no borders and recognizes no difference between altitude and sea level. Because this problem affects us all, the solution must protect us all. Fortunately, the means to overcome this challenge are already in our hands, locked within the ancient seeds of the mountains…”
    ## #GreenEconomy #economy #monoculture #agriculture #farming #crop #cropland #HinduKushHimalaya #himalaya #mountain #HKH #spatial #mapping #elevation #climatechange #foodsecurity #food #extremeweather #weather #ElNiño #drought #rainfall #precipitation #snowmelt #climatecrisis #mountainrange #water #hydrology #ecosystem #glacier #moonsoons #community #harvest #Nepal #Bhutan #watersheds #watersecurity #risk #hazard #waterresources #genes #genomicdiversity #cooperation

    #alldataisspatial #greeneconomy #economy #monoculture #agriculture #farming
  11. 💧🌏 Greg Cocks @[email protected] ·

    Can Himalayan Crops Help Secure The Future Of Food?
    (Exploring how genomic diversity, traditional crops, and regional cooperation can strengthen climate resilience and food security across the Hindu Kush Himalaya [HKH])
    --
    substack.com/home/post/p-20744 <-- shared technical post
    --
    openlibrary.substack.com/ <-- shared Substack, “Open Library on Green Economy”
    --
    adaptationwithoutborders.org/k <-- shared technical article, “Shifting cooperation in the [HKH]”
    --
    icimod.org/who-we-are/the-hind <-- background on the HKH, International Centre for Integrated Mountain Development (ICIMOD)
    --
    doi.org/10.48130/cas-0026-0003 <-- shared paper
    --
    [not at all my technical area - but fascinating, including the spatial component #alldataisspatial]
    H/T @jeevan Labh
    “As we navigate the intensifying impacts of the 2026 El Niño, the vulnerability of our global food systems require careful evaluation. With this year’s erratic weather patterns driving severe, prolonged droughts in some regions and unseasonal, devastating floods in others, the climate crisis is proving that it is not a distant threat; it is happening right now, in our fields and on our plates.
    This crisis is more visible in the Hindu Kush Himalaya (HKH) region. Often called the “water tower of Asia,” this vast mountain range sustains 240 million people across eight countries and provides essential ecosystem services to nearly 2 billion people downstream. When glaciers melt at accelerated rates and monsoons become unpredictable, the narrative often focuses solely on the mountain communities. But the truth is much broader: a disrupted harvest in the high hills of Nepal or Bhutan creates a domino effect. It leads to displaced populations, reduced agricultural output flowing into the Indus, Ganges, and Brahmaputra basins, and ultimately, skyrocketing food prices for families living in the sprawling downstream plains.
    The climate crisis respects no borders and recognizes no difference between altitude and sea level. Because this problem affects us all, the solution must protect us all. Fortunately, the means to overcome this challenge are already in our hands, locked within the ancient seeds of the mountains…”
    ## #GreenEconomy #economy #monoculture #agriculture #farming #crop #cropland #HinduKushHimalaya #himalaya #mountain #HKH #spatial #mapping #elevation #climatechange #foodsecurity #food #extremeweather #weather #ElNiño #drought #rainfall #precipitation #snowmelt #climatecrisis #mountainrange #water #hydrology #ecosystem #glacier #moonsoons #community #harvest #Nepal #Bhutan #watersheds #watersecurity #risk #hazard #waterresources #genes #genomicdiversity #cooperation

    #alldataisspatial #greeneconomy #economy #monoculture #agriculture #farming
  12. 💧🌏 Greg Cocks @[email protected] ·

    Can Himalayan Crops Help Secure The Future Of Food?
    (Exploring how genomic diversity, traditional crops, and regional cooperation can strengthen climate resilience and food security across the Hindu Kush Himalaya [HKH])
    --
    substack.com/home/post/p-20744 <-- shared technical post
    --
    openlibrary.substack.com/ <-- shared Substack, “Open Library on Green Economy”
    --
    adaptationwithoutborders.org/k <-- shared technical article, “Shifting cooperation in the [HKH]”
    --
    icimod.org/who-we-are/the-hind <-- background on the HKH, International Centre for Integrated Mountain Development (ICIMOD)
    --
    doi.org/10.48130/cas-0026-0003 <-- shared paper
    --
    [not at all my technical area - but fascinating, including the spatial component #alldataisspatial]
    H/T @jeevan Labh
    “As we navigate the intensifying impacts of the 2026 El Niño, the vulnerability of our global food systems require careful evaluation. With this year’s erratic weather patterns driving severe, prolonged droughts in some regions and unseasonal, devastating floods in others, the climate crisis is proving that it is not a distant threat; it is happening right now, in our fields and on our plates.
    This crisis is more visible in the Hindu Kush Himalaya (HKH) region. Often called the “water tower of Asia,” this vast mountain range sustains 240 million people across eight countries and provides essential ecosystem services to nearly 2 billion people downstream. When glaciers melt at accelerated rates and monsoons become unpredictable, the narrative often focuses solely on the mountain communities. But the truth is much broader: a disrupted harvest in the high hills of Nepal or Bhutan creates a domino effect. It leads to displaced populations, reduced agricultural output flowing into the Indus, Ganges, and Brahmaputra basins, and ultimately, skyrocketing food prices for families living in the sprawling downstream plains.
    The climate crisis respects no borders and recognizes no difference between altitude and sea level. Because this problem affects us all, the solution must protect us all. Fortunately, the means to overcome this challenge are already in our hands, locked within the ancient seeds of the mountains…”
    ## #GreenEconomy #economy #monoculture #agriculture #farming #crop #cropland #HinduKushHimalaya #himalaya #mountain #HKH #spatial #mapping #elevation #climatechange #foodsecurity #food #extremeweather #weather #ElNiño #drought #rainfall #precipitation #snowmelt #climatecrisis #mountainrange #water #hydrology #ecosystem #glacier #moonsoons #community #harvest #Nepal #Bhutan #watersheds #watersecurity #risk #hazard #waterresources #genes #genomicdiversity #cooperation

    #alldataisspatial #greeneconomy #economy #monoculture #agriculture #farming
  13. 💧🌏 Greg Cocks @[email protected] ·

    Can Himalayan Crops Help Secure The Future Of Food?
    (Exploring how genomic diversity, traditional crops, and regional cooperation can strengthen climate resilience and food security across the Hindu Kush Himalaya [HKH])
    --
    substack.com/home/post/p-20744 <-- shared technical post
    --
    openlibrary.substack.com/ <-- shared Substack, “Open Library on Green Economy”
    --
    adaptationwithoutborders.org/k <-- shared technical article, “Shifting cooperation in the [HKH]”
    --
    icimod.org/who-we-are/the-hind <-- background on the HKH, International Centre for Integrated Mountain Development (ICIMOD)
    --
    doi.org/10.48130/cas-0026-0003 <-- shared paper
    --
    [not at all my technical area - but fascinating, including the spatial component #alldataisspatial]
    H/T @jeevan Labh
    “As we navigate the intensifying impacts of the 2026 El Niño, the vulnerability of our global food systems require careful evaluation. With this year’s erratic weather patterns driving severe, prolonged droughts in some regions and unseasonal, devastating floods in others, the climate crisis is proving that it is not a distant threat; it is happening right now, in our fields and on our plates.
    This crisis is more visible in the Hindu Kush Himalaya (HKH) region. Often called the “water tower of Asia,” this vast mountain range sustains 240 million people across eight countries and provides essential ecosystem services to nearly 2 billion people downstream. When glaciers melt at accelerated rates and monsoons become unpredictable, the narrative often focuses solely on the mountain communities. But the truth is much broader: a disrupted harvest in the high hills of Nepal or Bhutan creates a domino effect. It leads to displaced populations, reduced agricultural output flowing into the Indus, Ganges, and Brahmaputra basins, and ultimately, skyrocketing food prices for families living in the sprawling downstream plains.
    The climate crisis respects no borders and recognizes no difference between altitude and sea level. Because this problem affects us all, the solution must protect us all. Fortunately, the means to overcome this challenge are already in our hands, locked within the ancient seeds of the mountains…”
    ## #GreenEconomy #economy #monoculture #agriculture #farming #crop #cropland #HinduKushHimalaya #himalaya #mountain #HKH #spatial #mapping #elevation #climatechange #foodsecurity #food #extremeweather #weather #ElNiño #drought #rainfall #precipitation #snowmelt #climatecrisis #mountainrange #water #hydrology #ecosystem #glacier #moonsoons #community #harvest #Nepal #Bhutan #watersheds #watersecurity #risk #hazard #waterresources #genes #genomicdiversity #cooperation

    #cooperation #genomicdiversity #genes #waterresources #hazard #risk
  14. 💧🌏 Greg Cocks @GregCocks ·

    Can Himalayan Crops Help Secure The Future Of Food?
    (Exploring how genomic diversity, traditional crops, and regional cooperation can strengthen climate resilience and food security across the Hindu Kush Himalaya [HKH])
    --
    substack.com/home/post/p-20744 <-- shared technical post
    --
    openlibrary.substack.com/ <-- shared Substack, “Open Library on Green Economy”
    --
    adaptationwithoutborders.org/k <-- shared technical article, “Shifting cooperation in the [HKH]”
    --
    icimod.org/who-we-are/the-hind <-- background on the HKH, International Centre for Integrated Mountain Development (ICIMOD)
    --
    doi.org/10.48130/cas-0026-0003 <-- shared paper
    --
    [not at all my technical area - but fascinating, including the spatial component ]
    H/T @jeevan Labh
    “As we navigate the intensifying impacts of the 2026 El Niño, the vulnerability of our global food systems require careful evaluation. With this year’s erratic weather patterns driving severe, prolonged droughts in some regions and unseasonal, devastating floods in others, the climate crisis is proving that it is not a distant threat; it is happening right now, in our fields and on our plates.
    This crisis is more visible in the Hindu Kush Himalaya (HKH) region. Often called the “water tower of Asia,” this vast mountain range sustains 240 million people across eight countries and provides essential ecosystem services to nearly 2 billion people downstream. When glaciers melt at accelerated rates and monsoons become unpredictable, the narrative often focuses solely on the mountain communities. But the truth is much broader: a disrupted harvest in the high hills of Nepal or Bhutan creates a domino effect. It leads to displaced populations, reduced agricultural output flowing into the Indus, Ganges, and Brahmaputra basins, and ultimately, skyrocketing food prices for families living in the sprawling downstream plains.
    The climate crisis respects no borders and recognizes no difference between altitude and sea level. Because this problem affects us all, the solution must protect us all. Fortunately, the means to overcome this challenge are already in our hands, locked within the ancient seeds of the mountains…”
    ##

    #alldataisspatial #greeneconomy #economy #monoculture #agriculture #farming
  15. 💧🌏 Greg Cocks @[email protected] ·

    Detecting Land Use And Land Cover Changes And Quantifying Soil Erosion And Sediment Export Using GIS And Remote Sensing In The GERD Catchment, Ethiopia
    --
    doi.org/10.1016/j.iswcr.2026.1 <-- shared paper
    --
    infonile.org/en/2023/05/battli <-- shared technical media article
    --
    doi.org/10.1007/978-3-031-6524 <-- shared technical book chapter
    --
    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
  16. 💧🌏 Greg Cocks @[email protected] ·

    Detecting Land Use And Land Cover Changes And Quantifying Soil Erosion And Sediment Export Using GIS And Remote Sensing In The GERD Catchment, Ethiopia
    --
    doi.org/10.1016/j.iswcr.2026.1 <-- shared paper
    --
    infonile.org/en/2023/05/battli <-- shared technical media article
    --
    doi.org/10.1007/978-3-031-6524 <-- shared technical book chapter
    --
    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
  17. 💧🌏 Greg Cocks @[email protected] ·

    Detecting Land Use And Land Cover Changes And Quantifying Soil Erosion And Sediment Export Using GIS And Remote Sensing In The GERD Catchment, Ethiopia
    --
    doi.org/10.1016/j.iswcr.2026.1 <-- shared paper
    --
    infonile.org/en/2023/05/battli <-- shared technical media article
    --
    doi.org/10.1007/978-3-031-6524 <-- shared technical book chapter
    --
    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