home.social

#cropland — Public Fediverse posts

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

  1. 💧🌏 Greg Cocks @[email protected] ·

    GMIA-NEXT - Next-Generation Global Map of Irrigated Areas |
    --
    doi.org/10.21203/rs.3.rs-10085 <-- shared paper
    --
    zenodo.org/records/17627111 <-- shared open data
    --
    H/T @kyle Davis
    “Irrigation plays a critical role in global food production and climate adaptation and exercises profound influence over humanity's water use. Yet despite its critical importance, there is a persistent lack of understanding of fine-scale irrigation patterns across the planet, knowledge which is essential for informing global food security and sustainability targets. Utilizing either statistical downscaling or remote sensing approaches, existing global irrigation datasets are constrained by coarse spatial resolutions, a lack of timeliness, or varying robustness and reliability. To address this gap, here [they] integrate[d] multi-source Earth observation and environmental datasets and use[d] machine learning to develop a medium-resolution (30 metre) global irrigated area dataset for the 2023/24 growing season. Within existing cropland extent, we leverage a newly compiled set of georeferenced irrigated (N=230,683) and non-irrigated (N=153,194) ground-truth points and integrate seasonal vegetation metrics derived from Landsat 8/9 imagery with agroecological-zone information and hydroclimatic and topographic variables. [They] subsequently develop and evaluate two machine-learning frameworks, a continental Agro-Ecological Zone (AEZ) tile-based framework and a continental-scale framework, and apply the best-performing approach for each continent. Evaluation using held-out test samples yielded a global accuracy of 80.5 ± 2.1%. The resulting maps were also validated against independent global and national irrigation datasets and statistics, demonstrating broad agreement in the spatial distribution of irrigated areas. This approach is robust and reliable because it is built on a harmonized global ground-truth database, incorporates multiple predictors, and is rigorously validated using independent datasets. All code, ground-truth, and data products are freely and publicly available [link above] and can serve as a robust, scale-neutral, and fully reproducible framework for fine-resolution irrigation mapping. These advances provide the critical and long-needed foundation for near-real-time monitoring and early warning systems, and fine-scale land and water resource management…”
    #IrrigatedAreas #Mapping #GIS #spatial #mapping #spatialanalysis #spatiotemporal #global #irrigation #water #hydrology #hydrography #waterresources #farming #agriculture #opendata #remotesensing #earthobservation #geomorphometry #AI #machinelearning #LLM #model #modeling #WaterManagement #opendata #AgroEcologicalZone #AEZ #cropland #irrigatedareas #foodproduction #wateruse #humanimpacts #EarthObservation #remotesensing #earlywarning #monitoring #FoodandAgricultureOrganizationFAO #FAO
    @FAO - Food and Agriculture Organization

    #irrigatedareas #mapping #gis #spatial #spatialanalysis #spatiotemporal
  2. 💧🌏 Greg Cocks @GregCocks ·

    GMIA-NEXT - Next-Generation Global Map of Irrigated Areas |
    --
    doi.org/10.21203/rs.3.rs-10085 <-- shared paper
    --
    zenodo.org/records/17627111 <-- shared open data
    --
    H/T @kyle Davis
    “Irrigation plays a critical role in global food production and climate adaptation and exercises profound influence over humanity's water use. Yet despite its critical importance, there is a persistent lack of understanding of fine-scale irrigation patterns across the planet, knowledge which is essential for informing global food security and sustainability targets. Utilizing either statistical downscaling or remote sensing approaches, existing global irrigation datasets are constrained by coarse spatial resolutions, a lack of timeliness, or varying robustness and reliability. To address this gap, here [they] integrate[d] multi-source Earth observation and environmental datasets and use[d] machine learning to develop a medium-resolution (30 metre) global irrigated area dataset for the 2023/24 growing season. Within existing cropland extent, we leverage a newly compiled set of georeferenced irrigated (N=230,683) and non-irrigated (N=153,194) ground-truth points and integrate seasonal vegetation metrics derived from Landsat 8/9 imagery with agroecological-zone information and hydroclimatic and topographic variables. [They] subsequently develop and evaluate two machine-learning frameworks, a continental Agro-Ecological Zone (AEZ) tile-based framework and a continental-scale framework, and apply the best-performing approach for each continent. Evaluation using held-out test samples yielded a global accuracy of 80.5 ± 2.1%. The resulting maps were also validated against independent global and national irrigation datasets and statistics, demonstrating broad agreement in the spatial distribution of irrigated areas. This approach is robust and reliable because it is built on a harmonized global ground-truth database, incorporates multiple predictors, and is rigorously validated using independent datasets. All code, ground-truth, and data products are freely and publicly available [link above] and can serve as a robust, scale-neutral, and fully reproducible framework for fine-resolution irrigation mapping. These advances provide the critical and long-needed foundation for near-real-time monitoring and early warning systems, and fine-scale land and water resource management…”

    @FAO - Food and Agriculture Organization

    #irrigatedareas #mapping #gis #spatial #spatialanalysis #spatiotemporal
  3. 💧🌏 Greg Cocks @[email protected] ·

    Optical, Radar, And Hybrid Indices To Detect Farming Practices In Europe
    --
    doi.org/10.1016/j.rse.2026.115 <-- 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

    #sowing #harvest #tillage #tillagedetection #cropland #croplandmanagement
  4. 💧🌏 Greg Cocks @GregCocks ·

    Optical, Radar, And Hybrid Indices To Detect Farming Practices In Europe
    --
    doi.org/10.1016/j.rse.2026.115 <-- 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
  5. 💧🌏 Greg Cocks @[email protected] ·

    Optical, Radar, And Hybrid Indices To Detect Farming Practices In Europe
    --
    doi.org/10.1016/j.rse.2026.115 <-- 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

    #sowing #harvest #tillage #tillagedetection #cropland #croplandmanagement
  6. 💧🌏 Greg Cocks @[email protected] ·

    Optical, Radar, And Hybrid Indices To Detect Farming Practices In Europe
    --
    doi.org/10.1016/j.rse.2026.115 <-- 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

    #sowing #harvest #tillage #tillagedetection #cropland #croplandmanagement
  7. 💧🌏 Greg Cocks @[email protected] ·

    Optical, Radar, And Hybrid Indices To Detect Farming Practices In Europe
    --
    doi.org/10.1016/j.rse.2026.115 <-- 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

    #modeling #model #region #europe #growingseason #environmentalstewardship
  8. 💧🌏 Greg Cocks @[email protected] ·

    National-Scale Field Delineation In Mozambique Refines Our Understanding Of Cropland Distribution, Field Size, And Deforestation Actors.
    --
    doi.org/10.1088/1748-9326/ae5c <-- shared paper
    --
    philipperufin.github.io/blog/m <-- 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

    #foodsecurity #subsistence #smallholder #farms #farming #agriculture
  9. 💧🌏 Greg Cocks @GregCocks ·

    National-Scale Field Delineation In Mozambique Refines Our Understanding Of Cropland Distribution, Field Size, And Deforestation Actors.
    --
    doi.org/10.1088/1748-9326/ae5c <-- shared paper
    --
    philipperufin.github.io/blog/m <-- shared associated technical article from one of the paper’s authors
    --

    #foodsecurity #subsistence #smallholder #farms #farming #agriculture
  10. 💧🌏 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
  11. 💧🌏 Greg Cocks @GregCocks ·

    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
  12. 💧🌏 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
  13. 💧🌏 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
  14. 💧🌏 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

    #soilquality #mitigation #hazard #risk #biophysical #urban
  15. 💧🌏 Greg Cocks @[email protected] ·

    Map Reveals How America's Forests Have Changed Over Time
    --
    newsweek.com/america-forests-c <-- shared 2025 media article
    --
    doi.org/10.5194/essd-15-1005-2 <-- shared 2023 paper
    --
    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

    #gis #spatial #mapping #remotesensing #spatialanalysis #spatiotemporal
  16. 💧🌏 Greg Cocks @GregCocks ·

    Map Reveals How America's Forests Have Changed Over Time
    --
    newsweek.com/america-forests-c <-- shared 2025 media article
    --
    doi.org/10.5194/essd-15-1005-2 <-- shared 2023 paper
    --
    doi.org/10.5281/zenodo.7055086 <-- shared study datasets
    --

    #gis #spatial #mapping #remotesensing #spatialanalysis #spatiotemporal
  17. 💧🌏 Greg Cocks @[email protected] ·

    Map Reveals How America's Forests Have Changed Over Time
    --
    newsweek.com/america-forests-c <-- shared 2025 media article
    --
    doi.org/10.5194/essd-15-1005-2 <-- shared 2023 paper
    --
    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

    #gis #spatial #mapping #remotesensing #spatialanalysis #spatiotemporal
  18. 💧🌏 Greg Cocks @[email protected] ·

    Map Reveals How America's Forests Have Changed Over Time
    --
    newsweek.com/america-forests-c <-- shared 2025 media article
    --
    doi.org/10.5194/essd-15-1005-2 <-- shared 2023 paper
    --
    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

    #gis #spatial #mapping #remotesensing #spatialanalysis #spatiotemporal
  19. 💧🌏 Greg Cocks @[email protected] ·

    Map Reveals How America's Forests Have Changed Over Time
    --
    newsweek.com/america-forests-c <-- shared 2025 media article
    --
    doi.org/10.5194/essd-15-1005-2 <-- shared 2023 paper
    --
    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

    #biogeochemical #hydrology #climate #census #lulc #colonial
  20. EvoLand @[email protected] ·

    🌱 #EvoLand C5 candidate prototype develops high-resolution Gross Primary Productivity data (10-daily, 10 m) for #grassland and #cropland across Europe.

    🌡️ A key improvement is the refined drought and temperature stress component, which better captures the impact of extreme weather on vegetation productivity.

    🌐 Explore our website and see how to connect with the Results Portal and uncover more about C5 evo-land.eu/results-portal/

    @EU_HaDEA @EU_ENV @DLR @cnes

    #evoland #grassland #cropland
  21. 💧🌏 Greg Cocks @[email protected] ·

    Floodplain Mapping - An Age-Old Practice Updated For Today's Flooding Events
    --
    woolpert.com/news/blogs/floodp <-- shared technical blog post
    --
    [this post should not be considered an endorsement of this specific vendor, rather sharing an informative technical article]
    #GIS #spatial #mapping #opendata #model #modeling #flood #floodplain #flooding #3DHP #NHD #remotesensing #LiDAR #risk #hazard #water #hydrology #geohazard #river #terrace #elevation #climatechange #extremeweather #photogrammetry #property #infrastructure #mitigation #engineering #event #agriculture #storm #rainfall #precipitation #regulations #design #construction #seasonal #damage #cost #economics #cropland #lowlands #data #topography #geomorphology #geomorphometry
    @USGS @NOAA @nws

    #gis #spatial #mapping #opendata #model #modeling
  22. 💧🌏 Greg Cocks @GregCocks ·

    Floodplain Mapping - An Age-Old Practice Updated For Today's Flooding Events
    --
    woolpert.com/news/blogs/floodp <-- shared technical blog post
    --
    [this post should not be considered an endorsement of this specific vendor, rather sharing an informative technical article]

    @USGS @NOAA @nws

    #gis #spatial #mapping #opendata #model #modeling
  23. 💧🌏 Greg Cocks @[email protected] ·

    Floodplain Mapping - An Age-Old Practice Updated For Today's Flooding Events
    --
    woolpert.com/news/blogs/floodp <-- shared technical blog post
    --
    [this post should not be considered an endorsement of this specific vendor, rather sharing an informative technical article]
    #GIS #spatial #mapping #opendata #model #modeling #flood #floodplain #flooding #3DHP #NHD #remotesensing #LiDAR #risk #hazard #water #hydrology #geohazard #river #terrace #elevation #climatechange #extremeweather #photogrammetry #property #infrastructure #mitigation #engineering #event #agriculture #storm #rainfall #precipitation #regulations #design #construction #seasonal #damage #cost #economics #cropland #lowlands #data #topography #geomorphology #geomorphometry
    @USGS @NOAA @nws

    #gis #spatial #mapping #opendata #model #modeling
  24. 💧🌏 Greg Cocks @[email protected] ·

    Floodplain Mapping - An Age-Old Practice Updated For Today's Flooding Events
    --
    woolpert.com/news/blogs/floodp <-- shared technical blog post
    --
    [this post should not be considered an endorsement of this specific vendor, rather sharing an informative technical article]
    #GIS #spatial #mapping #opendata #model #modeling #flood #floodplain #flooding #3DHP #NHD #remotesensing #LiDAR #risk #hazard #water #hydrology #geohazard #river #terrace #elevation #climatechange #extremeweather #photogrammetry #property #infrastructure #mitigation #engineering #event #agriculture #storm #rainfall #precipitation #regulations #design #construction #seasonal #damage #cost #economics #cropland #lowlands #data #topography #geomorphology #geomorphometry
    @USGS @NOAA @nws

    #gis #spatial #mapping #opendata #model #modeling
  25. 💧🌏 Greg Cocks @[email protected] ·

    Floodplain Mapping - An Age-Old Practice Updated For Today's Flooding Events
    --
    woolpert.com/news/blogs/floodp <-- shared technical blog post
    --
    [this post should not be considered an endorsement of this specific vendor, rather sharing an informative technical article]
    #GIS #spatial #mapping #opendata #model #modeling #flood #floodplain #flooding #3DHP #NHD #remotesensing #LiDAR #risk #hazard #water #hydrology #geohazard #river #terrace #elevation #climatechange #extremeweather #photogrammetry #property #infrastructure #mitigation #engineering #event #agriculture #storm #rainfall #precipitation #regulations #design #construction #seasonal #damage #cost #economics #cropland #lowlands #data #topography #geomorphology #geomorphometry
    @USGS @NOAA @nws

    #geomorphometry #geomorphology #topography #data #lowlands #cropland
  26. 💧🌏 Greg Cocks @[email protected] ·

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

    #usgs #gis #spatial #mapping #history #continuity
  27. 💧🌏 Greg Cocks @GregCocks ·

    Thirty Years Of The U.S. National Land Cover Database [NLCD] - Impacts And Future Direction
    --
    doi.org/10.14358/PERS.25-00121 <-- shared paper
    --
    usgs.gov/centers/eros/science/ <-- shared Annual National Land Cover Database (open data)
    --
    usgs.gov/centers/eros/science/ <-- get the open NLCD data
    --

    |

    #usgs #gis #spatial #mapping #history #continuity
  28. 💧🌏 Greg Cocks @[email protected] ·

    Floodplain Mapping - An Age-Old Practice Updated For Today's Flooding Events
    --
    woolpert.com/news/blogs/floodp <-- shared technical blog post
    --
    [this post should not be considered an endorsement of this specific vendor, rather sharing an informative technical article]
    #GIS #spatial #mapping #opendata #model #modeling #flood #floodplain #flooding #3DHP #NHD #remotesensing #LiDAR #risk #hazard #water #hydrology #geohazard #river #terrace #elevation #climatechange #extremeweather #photogrammetry #property #infrastructure #mitigation #engineering #event #agriculture #storm #rainfall #precipitation #regulations #design #construction #seasonal #damage #cost #economics #cropland #lowlands #data #topography #geomorphology #geomorphometry
    #USGS #NOAA #NWS

    #gis #spatial #mapping #opendata #model #modeling
  29. 💧🌏 Greg Cocks @GregCocks ·

    Floodplain Mapping - An Age-Old Practice Updated For Today's Flooding Events
    --
    woolpert.com/news/blogs/floodp <-- shared technical blog post
    --
    [this post should not be considered an endorsement of this specific vendor, rather sharing an informative technical article]

    #gis #spatial #mapping #opendata #model #modeling
  30. 💧🌏 Greg Cocks @[email protected] ·

    Floodplain Mapping - An Age-Old Practice Updated For Today's Flooding Events
    --
    woolpert.com/news/blogs/floodp <-- shared technical blog post
    --
    [this post should not be considered an endorsement of this specific vendor, rather sharing an informative technical article]
    #GIS #spatial #mapping #opendata #model #modeling #flood #floodplain #flooding #3DHP #NHD #remotesensing #LiDAR #risk #hazard #water #hydrology #geohazard #river #terrace #elevation #climatechange #extremeweather #photogrammetry #property #infrastructure #mitigation #engineering #event #agriculture #storm #rainfall #precipitation #regulations #design #construction #seasonal #damage #cost #economics #cropland #lowlands #data #topography #geomorphology #geomorphometry
    #USGS #NOAA #NWS

    #gis #spatial #mapping #opendata #model #modeling
  31. 💧🌏 Greg Cocks @[email protected] ·

    Floodplain Mapping - An Age-Old Practice Updated For Today's Flooding Events
    --
    woolpert.com/news/blogs/floodp <-- shared technical blog post
    --
    [this post should not be considered an endorsement of this specific vendor, rather sharing an informative technical article]
    #GIS #spatial #mapping #opendata #model #modeling #flood #floodplain #flooding #3DHP #NHD #remotesensing #LiDAR #risk #hazard #water #hydrology #geohazard #river #terrace #elevation #climatechange #extremeweather #photogrammetry #property #infrastructure #mitigation #engineering #event #agriculture #storm #rainfall #precipitation #regulations #design #construction #seasonal #damage #cost #economics #cropland #lowlands #data #topography #geomorphology #geomorphometry
    #USGS #NOAA #NWS

    #gis #spatial #mapping #opendata #model #modeling
  32. 💧🌏 Greg Cocks @[email protected] ·

    Floodplain Mapping - An Age-Old Practice Updated For Today's Flooding Events
    --
    woolpert.com/news/blogs/floodp <-- shared technical blog post
    --
    [this post should not be considered an endorsement of this specific vendor, rather sharing an informative technical article]
    #GIS #spatial #mapping #opendata #model #modeling #flood #floodplain #flooding #3DHP #NHD #remotesensing #LiDAR #risk #hazard #water #hydrology #geohazard #river #terrace #elevation #climatechange #extremeweather #photogrammetry #property #infrastructure #mitigation #engineering #event #agriculture #storm #rainfall #precipitation #regulations #design #construction #seasonal #damage #cost #economics #cropland #lowlands #data #topography #geomorphology #geomorphometry
    #USGS #NOAA #NWS

    #nws #noaa #usgs #geomorphometry #geomorphology #topography
  33. :rss: Hacker News @[email protected] ·

    Most Illinois farmland is not owned by farmers
    chicagotribune.com/2025/06/01/
    #ycombinator #Illinois_farmland #farmland #farming #farmland_ownership #business #environment #crops #soybeans #corn #Illinois_farmers #cropland #cash_crops #farmers

    #ycombinator #illinois_farmland #farmland #farming #farmland_ownership #business
  34. :rss: Hacker News @[email protected] ·

    Most Illinois farmland is not owned by farmers
    chicagotribune.com/2025/06/01/
    #ycombinator #Illinois_farmland #farmland #farming #farmland_ownership #business #environment #crops #soybeans #corn #Illinois_farmers #cropland #cash_crops #farmers

    #ycombinator #illinois_farmland #farmland #farming #farmland_ownership #business
  35. Hacker News @[email protected] ·

    One-sixth of the planet's cropland has toxic levels of one or more metals

    english.elpais.com/science-tec

    #HackerNews #toxicmetals #cropland #pollution #environment #sustainability #agriculture

    #hackernews #toxicmetals #cropland #pollution #environment #sustainability
  36. Hacker News @[email protected] ·

    One-sixth of the planet's cropland has toxic levels of one or more metals

    english.elpais.com/science-tec

    #HackerNews #toxicmetals #cropland #pollution #environment #sustainability #agriculture

    #hackernews #toxicmetals #cropland #pollution #environment #sustainability
  37. Dragofix @[email protected] ·

    About 15% of world’s cropland polluted with toxic metals, say researchers theguardian.com/environment/20

    #environment #agriculture #crops #cropland #pollution

    #environment #agriculture #crops #cropland #pollution
  38. Dragofix @[email protected] ·

    About 15% of world’s cropland polluted with toxic metals, say researchers theguardian.com/environment/20

    #environment #agriculture #crops #cropland #pollution

    #environment #agriculture #crops #cropland #pollution
  39. Paolo Redaelli @[email protected] ·

    About 15% of World's #Cropland Polluted With #Toxic Metals, Say Researchers - #Slashdot

    Well, that is **really a BAD new**!!!

    news.slashdot.org/story/25/04/

    #cropland #toxic #slashdot
  40. Paolo Redaelli @[email protected] ·

    About 15% of World's #Cropland Polluted With #Toxic Metals, Say Researchers - #Slashdot

    Well, that is **really a BAD new**!!!

    news.slashdot.org/story/25/04/

    #cropland #toxic #slashdot
  41. 💧🌏 Greg Cocks @[email protected] ·

    Hydrogeologic Investigation, Framework, And Conceptual Flow Model Of The Antlers Aquifer, Southeastern Oklahoma, 1980–2022
    --
    doi.org/10.3133/sir20255013 <-- shared USGS publication
    --
    waterdata.usgs.gov/nwis <-- shared USGS National Water Information System (NWIS) database
    --
    doi.org/10.5066/P14C6QFS <-- shared associated USGS open data release
    --
    #GIS #spatial #mapping #fedscience #water #hydrology #wateresources #pump #pumping #groundwater #AntlersAquifer #aquifer #Oklahoma #model #flow #test #flowmodel #yield #wateruse #watersecurity #climate #weather #recharge #precipitation #rainfall #TDS #waterquality #ions #potentiometric #geology #monitoring #planning #regulatory #agriculture #farming #cropland #spatialanalysis #spatiotemporal #fedscience
    @USGS

    #gis #spatial #mapping #fedscience #water #hydrology
  42. 💧🌏 Greg Cocks @[email protected] ·

    Hydrogeologic Investigation, Framework, And Conceptual Flow Model Of The Antlers Aquifer, Southeastern Oklahoma, 1980–2022
    --
    doi.org/10.3133/sir20255013 <-- shared USGS publication
    --
    waterdata.usgs.gov/nwis <-- shared USGS National Water Information System (NWIS) database
    --
    doi.org/10.5066/P14C6QFS <-- shared associated USGS open data release
    --
    #GIS #spatial #mapping #fedscience #water #hydrology #wateresources #pump #pumping #groundwater #AntlersAquifer #aquifer #Oklahoma #model #flow #test #flowmodel #yield #wateruse #watersecurity #climate #weather #recharge #precipitation #rainfall #TDS #waterquality #ions #potentiometric #geology #monitoring #planning #regulatory #agriculture #farming #cropland #spatialanalysis #spatiotemporal #fedscience
    @USGS

    #gis #spatial #mapping #fedscience #water #hydrology
  43. 💧🌏 Greg Cocks @[email protected] ·

    Hydrogeologic Investigation, Framework, And Conceptual Flow Model Of The Antlers Aquifer, Southeastern Oklahoma, 1980–2022
    --
    doi.org/10.3133/sir20255013 <-- shared USGS publication
    --
    waterdata.usgs.gov/nwis <-- shared USGS National Water Information System (NWIS) database
    --
    doi.org/10.5066/P14C6QFS <-- shared associated USGS open data release
    --
    #GIS #spatial #mapping #fedscience #water #hydrology #wateresources #pump #pumping #groundwater #AntlersAquifer #aquifer #Oklahoma #model #flow #test #flowmodel #yield #wateruse #watersecurity #climate #weather #recharge #precipitation #rainfall #TDS #waterquality #ions #potentiometric #geology #monitoring #planning #regulatory #agriculture #farming #cropland #spatialanalysis #spatiotemporal #fedscience
    @USGS

    #gis #spatial #mapping #fedscience #water #hydrology
  44. 💧🌏 Greg Cocks @[email protected] ·

    Hydrogeologic Investigation, Framework, And Conceptual Flow Model Of The Antlers Aquifer, Southeastern Oklahoma, 1980–2022
    --
    doi.org/10.3133/sir20255013 <-- shared USGS publication
    --
    waterdata.usgs.gov/nwis <-- shared USGS National Water Information System (NWIS) database
    --
    doi.org/10.5066/P14C6QFS <-- shared associated USGS open data release
    --
    #GIS #spatial #mapping #fedscience #water #hydrology #wateresources #pump #pumping #groundwater #AntlersAquifer #aquifer #Oklahoma #model #flow #test #flowmodel #yield #wateruse #watersecurity #climate #weather #recharge #precipitation #rainfall #TDS #waterquality #ions #potentiometric #geology #monitoring #planning #regulatory #agriculture #farming #cropland #spatialanalysis #spatiotemporal #fedscience
    @USGS

    #spatiotemporal #spatialanalysis #cropland #farming #agriculture #regulatory
  45. 💧🌏 Greg Cocks @GregCocks ·

    Hydrogeologic Investigation, Framework, And Conceptual Flow Model Of The Antlers Aquifer, Southeastern Oklahoma, 1980–2022
    --
    doi.org/10.3133/sir20255013 <-- shared USGS publication
    --
    waterdata.usgs.gov/nwis <-- shared USGS National Water Information System (NWIS) database
    --
    doi.org/10.5066/P14C6QFS <-- shared associated USGS open data release
    --

    @USGS

    #gis #spatial #mapping #fedscience #water #hydrology
  46. CelloMom On Cars @[email protected] ·

    "Fertilizers that shed #microplastics are increasingly spreading on America’s #cropland, research shows, raising new worry about the soil contamination and safety of the US food supply.

    There are many types of slow release fertilizers, including those that are encapsulated with biodegradable materials, Salehi said. However, the plastic versions work well so the industry for now seems to be sticking with them, she added."

    theguardian.com/us-news/2025/m

    #microplastics #cropland
  47. CelloMom On Cars @[email protected] ·

    "Fertilizers that shed #microplastics are increasingly spreading on America’s #cropland, research shows, raising new worry about the soil contamination and safety of the US food supply.

    There are many types of slow release fertilizers, including those that are encapsulated with biodegradable materials, Salehi said. However, the plastic versions work well so the industry for now seems to be sticking with them, she added."

    theguardian.com/us-news/2025/m

    #microplastics #cropland
  48. Alexander J. Stein @[email protected] ·

    #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): doi.org/10.1073/pnas.240483912 #biodiversity #foodsecurity

    #agriculture #landuse #carbon #footprint #productivity #cropland
  49. 💧🌏 Greg Cocks @[email protected] ·

    Cropland Abandonment Between 1986 And 2018 Across The United States - Spatiotemporal Patterns And Current Land Uses
    --
    doi.org/10.1088/1748-9326/ad2d <-- shared paper
    --
    agdaily.com/crops/study-30-mil <-- 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

    #gis #spatial #mapping #spatiotemporal #usa #spatialanalysis
  50. 💧🌏 Greg Cocks @GregCocks ·

    Cropland Abandonment Between 1986 And 2018 Across The United States - Spatiotemporal Patterns And Current Land Uses
    --
    doi.org/10.1088/1748-9326/ad2d <-- shared paper
    --
    agdaily.com/crops/study-30-mil <-- shared media article
    --

    #gis #spatial #mapping #spatiotemporal #usa #spatialanalysis