#landcover — Public Fediverse posts

https://www.europesays.com/ie/689549/ An Early Look at Fall Color in Canada #EarthObservatory #Éire #IE #Ireland #LandCover #Landsat9 #Science #Space #Vegetation

An Early Look at Fall Color in Canada 🌎🛰️

#LandCover #Vegetation

▶️ 1 new picture from NASA (Website) https://commons.wikimedia.org/wiki/File:An_Early_Look_at_Fall_Color_in_Canada_%281320015_-_727%29.jpg

An Early Look at Fall Color in Canada 🌎🛰️

#LandCover #Vegetation

▶️ 1 new picture from NASA (Website) https://commons.wikimedia.org/wiki/File:An_Early_Look_at_Fall_Color_in_Canada_%281320015_-_727%29.jpg

An Early Look at Fall Color in Canada 🌎🛰️

#LandCover #Vegetation

▶️ 1 new picture from NASA (Website) https://commons.wikimedia.org/wiki/File:An_Early_Look_at_Fall_Color_in_Canada_%281320015_-_727%29.jpg

An Early Look at Fall Color in Canada 🌎🛰️

#LandCover #Vegetation

▶️ 1 new picture from NASA (Website) https://commons.wikimedia.org/wiki/File:An_Early_Look_at_Fall_Color_in_Canada_%281320015_-_727%29.jpg

An Early Look at Fall Color in Canada

As North America rode out a summer of remarkable heat, fall foliage and cool, crisp weather still seemed…
#Canada #EarthObservatory #LandCover #Landsat9 #Vegetation
https://www.europesays.com/canada/208380/

Crop-type classification across the US Midwest at 30 m, on Landsat via Earth Engine: corn vs soy vs everything else, at regional scale.
#RemoteSensing #Agriculture #EarthEngine #LandCover

Crop-type classification across the US Midwest at 30 m, on Landsat via Earth Engine: corn vs soy vs everything else, at regional scale.
#RemoteSensing #Agriculture #EarthEngine #LandCover

Crop-type classification across the US Midwest at 30 m, on Landsat via Earth Engine: corn vs soy vs everything else, at regional scale.
#RemoteSensing #Agriculture #EarthEngine #LandCover

Crop-type classification across the US Midwest at 30 m, on Landsat via Earth Engine: corn vs soy vs everything else, at regional scale.
#RemoteSensing #Agriculture #EarthEngine #LandCover

🌎 Brazil Landcover Map 2025 🇧🇷 🗺️ From the Amazon rainforest, Pantanal wetlands and Cerrado savannas to the Atlantic coast—mapped using ESRI Landcover 2025 by @impactobservatory & @Esri and CGIAR-SRTM DEM . #gischat #GIS #Cartography #Brazil #Landcover #RemoteSensing #Geospatial

🌎 Brazil Landcover Map 2025 🇧🇷 🗺️ From the Amazon rainforest, Pantanal wetlands and Cerrado savannas to the Atlantic coast—mapped using ESRI Landcover 2025 by @impactobservatory & @Esri and CGIAR-SRTM DEM . #gischat #GIS #Cartography #Brazil #Landcover #RemoteSensing #Geospatial

🌎 Brazil Landcover Map 2025 🇧🇷 🗺️ From the Amazon rainforest, Pantanal wetlands and Cerrado savannas to the Atlantic coast—mapped using ESRI Landcover 2025 by @impactobservatory & @Esri and CGIAR-SRTM DEM . #gischat #GIS #Cartography #Brazil #Landcover #RemoteSensing #Geospatial

🌎 Brazil Landcover Map 2025 🇧🇷 🗺️ From the Amazon rainforest, Pantanal wetlands and Cerrado savannas to the Atlantic coast—mapped using ESRI Landcover 2025 by @impactobservatory & @Esri and CGIAR-SRTM DEM . #gischat #GIS #Cartography #Brazil #Landcover #RemoteSensing #Geospatial

🌎 Brazil Landcover Map 2025 🇧🇷 🗺️ From the Amazon rainforest, Pantanal wetlands and Cerrado savannas to the Atlantic coast—mapped using ESRI Landcover 2025 by @impactobservatory & @Esri and CGIAR-SRTM DEM . #gischat #GIS #Cartography #Brazil #Landcover #RemoteSensing #Geospatial

🌎 Brazil Landcover Map 2025 🇧🇷 🗺️ From the Amazon rainforest, Pantanal wetlands and Cerrado savannas to the Atlantic coast—mapped using ESRI Landcover 2025 by @impactobservatory & @Esri and CGIAR-SRTM DEM . #gischat #GIS #Cartography #Brazil #Landcover #RemoteSensing #Geospatial

🌍 East Africa Landcover Map 2025 🇹🇿🇰🇪🇺🇬🇷🇼🇧🇮 🗺️ From the Great Lakes, forests and savannas to Kilimanjaro—mapped using ESRI Landcover 2025 by @impactobservatory & @Esri and CGIAR-SRTM DEM by @divagis. #GIS #Cartography #EAC #Landcover #RemoteSensing #Geospatial

🔥 Mapping Calgary's Fuel Continuity: Where Can Wildfire Actually Spread?

In a baseline, unsuppressed fire scenario ("apocalyptic scenario"), surface fires can only sustain a continuous front where vegetation forms an unbroken canopy or grassland corridor.

Using my 2025 Calgary Land Cover Model (v6.0), I isolated all vegetated pixels and calculated the spatial continuity and total area of every single contiguous fuel patch across the city:
🌾 The Nose Hill Island (~1,100 ha): A massive grassland fuel bed right in the city's heart.
🌲 River Corridors (Fish Creek Provincial Park & Bow Valley, 500–1,500 ha): Linear fuel superclusters acting as natural conduits.
🏙️ Urban Built-up Fragmentation: Inside established communities, the continuous network of asphalt, concrete, and roofing fractures vegetation into micro-patches (< 1 ha).

#GIS #RemoteSensing #EarthObservation #Calgary #SpatialDataScience #LandCover #MachineLearning #GreennessOfCalgary #Rstats #UrbanTrees #TreeCanopy #UrbanHealth #Wildfire

🔥 Mapping Calgary's Fuel Continuity: Where Can Wildfire Actually Spread?

In a baseline, unsuppressed fire scenario ("apocalyptic scenario"), surface fires can only sustain a continuous front where vegetation forms an unbroken canopy or grassland corridor.

Using my 2025 Calgary Land Cover Model (v6.0), I isolated all vegetated pixels and calculated the spatial continuity and total area of every single contiguous fuel patch across the city:
🌾 The Nose Hill Island (~1,100 ha): A massive grassland fuel bed right in the city's heart.
🌲 River Corridors (Fish Creek Provincial Park & Bow Valley, 500–1,500 ha): Linear fuel superclusters acting as natural conduits.
🏙️ Urban Built-up Fragmentation: Inside established communities, the continuous network of asphalt, concrete, and roofing fractures vegetation into micro-patches (< 1 ha).

#GIS #RemoteSensing #EarthObservation #Calgary #SpatialDataScience #LandCover #MachineLearning #GreennessOfCalgary #Rstats #UrbanTrees #TreeCanopy #UrbanHealth #Wildfire

🔥 Mapping Calgary's Fuel Continuity: Where Can Wildfire Actually Spread?

In a baseline, unsuppressed fire scenario ("apocalyptic scenario"), surface fires can only sustain a continuous front where vegetation forms an unbroken canopy or grassland corridor.

Using my 2025 Calgary Land Cover Model (v6.0), I isolated all vegetated pixels and calculated the spatial continuity and total area of every single contiguous fuel patch across the city:
🌾 The Nose Hill Island (~1,100 ha): A massive grassland fuel bed right in the city's heart.
🌲 River Corridors (Fish Creek Provincial Park & Bow Valley, 500–1,500 ha): Linear fuel superclusters acting as natural conduits.
🏙️ Urban Built-up Fragmentation: Inside established communities, the continuous network of asphalt, concrete, and roofing fractures vegetation into micro-patches (< 1 ha).

#GIS #RemoteSensing #EarthObservation #Calgary #SpatialDataScience #LandCover #MachineLearning #GreennessOfCalgary #Rstats #UrbanTrees #TreeCanopy #UrbanHealth #Wildfire

🔥 Mapping Calgary's Fuel Continuity: Where Can Wildfire Actually Spread?

In a baseline, unsuppressed fire scenario ("apocalyptic scenario"), surface fires can only sustain a continuous front where vegetation forms an unbroken canopy or grassland corridor.

Using my 2025 Calgary Land Cover Model (v6.0), I isolated all vegetated pixels and calculated the spatial continuity and total area of every single contiguous fuel patch across the city:
🌾 The Nose Hill Island (~1,100 ha): A massive grassland fuel bed right in the city's heart.
🌲 River Corridors (Fish Creek Provincial Park & Bow Valley, 500–1,500 ha): Linear fuel superclusters acting as natural conduits.
🏙️ Urban Built-up Fragmentation: Inside established communities, the continuous network of asphalt, concrete, and roofing fractures vegetation into micro-patches (< 1 ha).

#GIS #RemoteSensing #EarthObservation #Calgary #SpatialDataScience #LandCover #MachineLearning #GreennessOfCalgary #Rstats #UrbanTrees #TreeCanopy #UrbanHealth #Wildfire

🔥 Mapping Calgary's Fuel Continuity: Where Can Wildfire Actually Spread?

In a baseline, unsuppressed fire scenario ("apocalyptic scenario"), surface fires can only sustain a continuous front where vegetation forms an unbroken canopy or grassland corridor.

Using my 2025 Calgary Land Cover Model (v6.0), I isolated all vegetated pixels and calculated the spatial continuity and total area of every single contiguous fuel patch across the city:
🌾 The Nose Hill Island (~1,100 ha): A massive grassland fuel bed right in the city's heart.
🌲 River Corridors (Fish Creek Provincial Park & Bow Valley, 500–1,500 ha): Linear fuel superclusters acting as natural conduits.
🏙️ Urban Built-up Fragmentation: Inside established communities, the continuous network of asphalt, concrete, and roofing fractures vegetation into micro-patches (< 1 ha).

#GIS #RemoteSensing #EarthObservation #Calgary #SpatialDataScience #LandCover #MachineLearning #GreennessOfCalgary #Rstats #UrbanTrees #TreeCanopy #UrbanHealth #Wildfire

🔥 Calgary Urban Heat: How the Solid-to-Tree Ratio drives an 8°C gap

My Summer 2025 ML satellite analysis reveals a direct relationship between a community's built-to-canopy footprint and surface temperature (LST):

🌳 Cooling Refuges (~29.5–31°C): Roxboro, Rideau Park, Discovery Ridge, Eau Claire (mature canopies + river valleys).
🔥 Northeast Heat Dome (~37–38°C): Marlborough, Rundle, Temple (dense low-rise footprint, minimal mature canopy).
🏗️ New Suburbs: Seton, Redstone, Rangeview (canopy lag: fully built out, but young saplings need years to mature).

🌲 Urban trees are not decorative landscaping — they are critical municipal climate infrastructure.

#GIS #RemoteSensing #YYC #EarthObservation #Calgary #SpatialDataScience #LandCover #MachineLearning #Geoscience #GreennessOfCalgary #Rstats #UrbanTrees #TreeCanopy #UrbanHealth

🔥 Calgary Urban Heat: How the Solid-to-Tree Ratio drives an 8°C gap

My Summer 2025 ML satellite analysis reveals a direct relationship between a community's built-to-canopy footprint and surface temperature (LST):

🌳 Cooling Refuges (~29.5–31°C): Roxboro, Rideau Park, Discovery Ridge, Eau Claire (mature canopies + river valleys).
🔥 Northeast Heat Dome (~37–38°C): Marlborough, Rundle, Temple (dense low-rise footprint, minimal mature canopy).
🏗️ New Suburbs: Seton, Redstone, Rangeview (canopy lag: fully built out, but young saplings need years to mature).

🌲 Urban trees are not decorative landscaping — they are critical municipal climate infrastructure.

#GIS #RemoteSensing #YYC #EarthObservation #Calgary #SpatialDataScience #LandCover #MachineLearning #Geoscience #GreennessOfCalgary #Rstats #UrbanTrees #TreeCanopy #UrbanHealth

🔥 Calgary Urban Heat: How the Solid-to-Tree Ratio drives an 8°C gap

My Summer 2025 ML satellite analysis reveals a direct relationship between a community's built-to-canopy footprint and surface temperature (LST):

🌳 Cooling Refuges (~29.5–31°C): Roxboro, Rideau Park, Discovery Ridge, Eau Claire (mature canopies + river valleys).
🔥 Northeast Heat Dome (~37–38°C): Marlborough, Rundle, Temple (dense low-rise footprint, minimal mature canopy).
🏗️ New Suburbs: Seton, Redstone, Rangeview (canopy lag: fully built out, but young saplings need years to mature).

🌲 Urban trees are not decorative landscaping — they are critical municipal climate infrastructure.

#GIS #RemoteSensing #YYC #EarthObservation #Calgary #SpatialDataScience #LandCover #MachineLearning #Geoscience #GreennessOfCalgary #Rstats #UrbanTrees #TreeCanopy #UrbanHealth

🔥 Calgary Urban Heat: How the Solid-to-Tree Ratio drives an 8°C gap

My Summer 2025 ML satellite analysis reveals a direct relationship between a community's built-to-canopy footprint and surface temperature (LST):

🌳 Cooling Refuges (~29.5–31°C): Roxboro, Rideau Park, Discovery Ridge, Eau Claire (mature canopies + river valleys).
🔥 Northeast Heat Dome (~37–38°C): Marlborough, Rundle, Temple (dense low-rise footprint, minimal mature canopy).
🏗️ New Suburbs: Seton, Redstone, Rangeview (canopy lag: fully built out, but young saplings need years to mature).

🌲 Urban trees are not decorative landscaping — they are critical municipal climate infrastructure.

#GIS #RemoteSensing #YYC #EarthObservation #Calgary #SpatialDataScience #LandCover #MachineLearning #Geoscience #GreennessOfCalgary #Rstats #UrbanTrees #TreeCanopy #UrbanHealth

🔥 Calgary Urban Heat: How the Solid-to-Tree Ratio drives an 8°C gap

My Summer 2025 ML satellite analysis reveals a direct relationship between a community's built-to-canopy footprint and surface temperature (LST):

🌳 Cooling Refuges (~29.5–31°C): Roxboro, Rideau Park, Discovery Ridge, Eau Claire (mature canopies + river valleys).
🔥 Northeast Heat Dome (~37–38°C): Marlborough, Rundle, Temple (dense low-rise footprint, minimal mature canopy).
🏗️ New Suburbs: Seton, Redstone, Rangeview (canopy lag: fully built out, but young saplings need years to mature).

🌲 Urban trees are not decorative landscaping — they are critical municipal climate infrastructure.

#GIS #RemoteSensing #YYC #EarthObservation #Calgary #SpatialDataScience #LandCover #MachineLearning #Geoscience #GreennessOfCalgary #Rstats #UrbanTrees #TreeCanopy #UrbanHealth

🔥 The Green Illusion: Why Zoning-Level Analysis Changes the Picture

📊 Gross community statistics can be misleading. When measuring an entire neighborhood, large municipal parks and green buffers inflate the overall 'greenness' score.

❗ When we filter the data down exclusively to actual Residential Land Use Districts in established communities, the picture changes significant:
🔹 Unvegetated/Impervious surfaces (Solid) explode to ~80% (79.22%) of the total zoned area.
🔹 Vegetative classes collapse: Functional lawns and canopy cover are compressed into narrow margins (Lawn: 2.15%, Forest: 0.59%), with community-level sparsed trees (Park) accounting for only 17.87%.

☝️ Moving from macro-boundaries to parcel-level zoning exposes the true physical density of Calgary’s residential footprint.

#GIS #RemoteSensing #EarthObservation #Calgary #SpatialDataScience #LandCover #MachineLearning #Geoscience #GreennessOfCalgary #Rstats #YYC #DataScience #Urban #Sentinel

🔥 The Green Illusion: Why Zoning-Level Analysis Changes the Picture

📊 Gross community statistics can be misleading. When measuring an entire neighborhood, large municipal parks and green buffers inflate the overall 'greenness' score.

❗ When we filter the data down exclusively to actual Residential Land Use Districts in established communities, the picture changes significant:
🔹 Unvegetated/Impervious surfaces (Solid) explode to ~80% (79.22%) of the total zoned area.
🔹 Vegetative classes collapse: Functional lawns and canopy cover are compressed into narrow margins (Lawn: 2.15%, Forest: 0.59%), with community-level sparsed trees (Park) accounting for only 17.87%.

☝️ Moving from macro-boundaries to parcel-level zoning exposes the true physical density of Calgary’s residential footprint.

#GIS #RemoteSensing #EarthObservation #Calgary #SpatialDataScience #LandCover #MachineLearning #Geoscience #GreennessOfCalgary #Rstats #YYC #DataScience #Urban #Sentinel

🔥 The Green Illusion: Why Zoning-Level Analysis Changes the Picture

📊 Gross community statistics can be misleading. When measuring an entire neighborhood, large municipal parks and green buffers inflate the overall 'greenness' score.

❗ When we filter the data down exclusively to actual Residential Land Use Districts in established communities, the picture changes significant:
🔹 Unvegetated/Impervious surfaces (Solid) explode to ~80% (79.22%) of the total zoned area.
🔹 Vegetative classes collapse: Functional lawns and canopy cover are compressed into narrow margins (Lawn: 2.15%, Forest: 0.59%), with community-level sparsed trees (Park) accounting for only 17.87%.

☝️ Moving from macro-boundaries to parcel-level zoning exposes the true physical density of Calgary’s residential footprint.

#GIS #RemoteSensing #EarthObservation #Calgary #SpatialDataScience #LandCover #MachineLearning #Geoscience #GreennessOfCalgary #Rstats #YYC #DataScience #Urban #Sentinel

🔥 The Green Illusion: Why Zoning-Level Analysis Changes the Picture

📊 Gross community statistics can be misleading. When measuring an entire neighborhood, large municipal parks and green buffers inflate the overall 'greenness' score.

❗ When we filter the data down exclusively to actual Residential Land Use Districts in established communities, the picture changes significant:
🔹 Unvegetated/Impervious surfaces (Solid) explode to ~80% (79.22%) of the total zoned area.
🔹 Vegetative classes collapse: Functional lawns and canopy cover are compressed into narrow margins (Lawn: 2.15%, Forest: 0.59%), with community-level sparsed trees (Park) accounting for only 17.87%.

☝️ Moving from macro-boundaries to parcel-level zoning exposes the true physical density of Calgary’s residential footprint.

#GIS #RemoteSensing #EarthObservation #Calgary #SpatialDataScience #LandCover #MachineLearning #Geoscience #GreennessOfCalgary #Rstats #YYC #DataScience #Urban #Sentinel

🔥 The Green Illusion: Why Zoning-Level Analysis Changes the Picture

📊 Gross community statistics can be misleading. When measuring an entire neighborhood, large municipal parks and green buffers inflate the overall 'greenness' score.

❗ When we filter the data down exclusively to actual Residential Land Use Districts in established communities, the picture changes significant:
🔹 Unvegetated/Impervious surfaces (Solid) explode to ~80% (79.22%) of the total zoned area.
🔹 Vegetative classes collapse: Functional lawns and canopy cover are compressed into narrow margins (Lawn: 2.15%, Forest: 0.59%), with community-level sparsed trees (Park) accounting for only 17.87%.

☝️ Moving from macro-boundaries to parcel-level zoning exposes the true physical density of Calgary’s residential footprint.

#GIS #RemoteSensing #EarthObservation #Calgary #SpatialDataScience #LandCover #MachineLearning #Geoscience #GreennessOfCalgary #Rstats #YYC #DataScience #Urban #Sentinel

Glacial ridges line Björkö in Finland's Kvarken Archipelago

#CoastalEnvironment #LandMonitoring #Landcover #MarineEnvironment

▶️ 1 new picture from EU Space https://commons.wikimedia.org/wiki/File:Glacial_ridges_line_Bj%C3%B6rk%C3%B6_in_Finland%27s_Kvarken_Archipelago_%28Copernicus_2026-08-09%29.webp

Glacial ridges line Björkö in Finland's Kvarken Archipelago

#CoastalEnvironment #LandMonitoring #Landcover #MarineEnvironment

▶️ 1 new picture from EU Space https://commons.wikimedia.org/wiki/File:Glacial_ridges_line_Bj%C3%B6rk%C3%B6_in_Finland%27s_Kvarken_Archipelago_%28Copernicus_2026-08-09%29.webp

Glacial ridges line Björkö in Finland's Kvarken Archipelago

#CoastalEnvironment #LandMonitoring #Landcover #MarineEnvironment

▶️ 1 new picture from EU Space https://commons.wikimedia.org/wiki/File:Glacial_ridges_line_Bj%C3%B6rk%C3%B6_in_Finland%27s_Kvarken_Archipelago_%28Copernicus_2026-08-09%29.webp

Glacial ridges line Björkö in Finland's Kvarken Archipelago

#CoastalEnvironment #LandMonitoring #Landcover #MarineEnvironment

▶️ 1 new picture from EU Space https://commons.wikimedia.org/wiki/File:Glacial_ridges_line_Bj%C3%B6rk%C3%B6_in_Finland%27s_Kvarken_Archipelago_%28Copernicus_2026-08-09%29.webp

How does physical vegetation compare to administrative park maps?

In a new article by LiveWire Calgary, I shared technical insights from my 10-meter machine learning land cover classification model.

🛰️ Satellites map physical ground reality, not property boundaries. Multispectral land cover data reveals continuous fine fuel pathways (grass, brush, and canopy) extending across unmanaged ravines and private lots right up to residential property lines at Calgary's Wildland-Urban Interface.

🔗 Read the full article: https://livewirecalgary.com/2026/08/06/calgary-wildfire-campaign-high-risk-areas-map-gaps/

#GIS #RemoteSensing #EarthObservation #Calgary #SpatialDataScience #LandCover #WUI #MachineLearning #Geoscience #GreennessOfCalgary #LiveWireCalgary

How does physical vegetation compare to administrative park maps?

In a new article by LiveWire Calgary, I shared technical insights from my 10-meter machine learning land cover classification model.

🛰️ Satellites map physical ground reality, not property boundaries. Multispectral land cover data reveals continuous fine fuel pathways (grass, brush, and canopy) extending across unmanaged ravines and private lots right up to residential property lines at Calgary's Wildland-Urban Interface.

🔗 Read the full article: https://livewirecalgary.com/2026/08/06/calgary-wildfire-campaign-high-risk-areas-map-gaps/

#GIS #RemoteSensing #EarthObservation #Calgary #SpatialDataScience #LandCover #WUI #MachineLearning #Geoscience #GreennessOfCalgary #LiveWireCalgary

How does physical vegetation compare to administrative park maps?

In a new article by LiveWire Calgary, I shared technical insights from my 10-meter machine learning land cover classification model.

🛰️ Satellites map physical ground reality, not property boundaries. Multispectral land cover data reveals continuous fine fuel pathways (grass, brush, and canopy) extending across unmanaged ravines and private lots right up to residential property lines at Calgary's Wildland-Urban Interface.

🔗 Read the full article: https://livewirecalgary.com/2026/08/06/calgary-wildfire-campaign-high-risk-areas-map-gaps/

#GIS #RemoteSensing #EarthObservation #Calgary #SpatialDataScience #LandCover #WUI #MachineLearning #Geoscience #GreennessOfCalgary #LiveWireCalgary

How does physical vegetation compare to administrative park maps?

In a new article by LiveWire Calgary, I shared technical insights from my 10-meter machine learning land cover classification model.

🛰️ Satellites map physical ground reality, not property boundaries. Multispectral land cover data reveals continuous fine fuel pathways (grass, brush, and canopy) extending across unmanaged ravines and private lots right up to residential property lines at Calgary's Wildland-Urban Interface.

🔗 Read the full article: https://livewirecalgary.com/2026/08/06/calgary-wildfire-campaign-high-risk-areas-map-gaps/

#GIS #RemoteSensing #EarthObservation #Calgary #SpatialDataScience #LandCover #WUI #MachineLearning #Geoscience #GreennessOfCalgary #LiveWireCalgary

https://www.europesays.com/africa/365789/ The Paradox of Lençóis Maranhenses National Park #EarthObservatory #LandCover #Landsat9 #Namibia #vegetation

The Paradox of Lençóis Maranhenses National Park 🌎🛰️

#LandCover #Topography #Vegetation

▶️ 1 new picture from NASA (Website) https://commons.wikimedia.org/wiki/File:The_Paradox_of_Len%C3%A7%C3%B3is_Maranhenses_National_Park_%281273633_-_lencois_oli_20260608%29.jpg

The Paradox of Lençóis Maranhenses National Park 🌎🛰️

#LandCover #Topography #Vegetation

▶️ 1 new picture from NASA (Website) https://commons.wikimedia.org/wiki/File:The_Paradox_of_Len%C3%A7%C3%B3is_Maranhenses_National_Park_%281273633_-_lencois_oli_20260608%29.jpg

The Paradox of Lençóis Maranhenses National Park 🌎🛰️

#LandCover #Topography #Vegetation

▶️ 1 new picture from NASA (Website) https://commons.wikimedia.org/wiki/File:The_Paradox_of_Len%C3%A7%C3%B3is_Maranhenses_National_Park_%281273633_-_lencois_oli_20260608%29.jpg

The Paradox of Lençóis Maranhenses National Park 🌎🛰️

#LandCover #Topography #Vegetation

▶️ 1 new picture from NASA (Website) https://commons.wikimedia.org/wiki/File:The_Paradox_of_Len%C3%A7%C3%B3is_Maranhenses_National_Park_%281273633_-_lencois_oli_20260608%29.jpg

https://www.europesays.com/ie/621178/ The Paradox of Lençóis Maranhenses National Park #EarthObservatory #Éire #IE #Ireland #LandCover #Landsat9 #Science #Vegetation

🌍 Saudi Arabia Landcover Map 2025 🇸🇦 🗺️
From vast deserts to the Asir Mountains — Saudi Arabia’s land cover mapped using ESRI Landcover 2025 by @impactobservatory &
@esri
and CGIAR-SRTM DEM by
@divagis
.
#GIS #Cartography #SaudiArabia #Landcover #Desert #Asir #RemoteSensing

🌍 Saudi Arabia Landcover Map 2025 🇸🇦 🗺️
From vast deserts to the Asir Mountains — Saudi Arabia’s land cover mapped using ESRI Landcover 2025 by @impactobservatory &
@esri
and CGIAR-SRTM DEM by
@divagis
.
#GIS #Cartography #SaudiArabia #Landcover #Desert #Asir #RemoteSensing

🌍 Saudi Arabia Landcover Map 2025 🇸🇦 🗺️
From vast deserts to the Asir Mountains — Saudi Arabia’s land cover mapped using ESRI Landcover 2025 by @impactobservatory &
@esri
 and CGIAR-SRTM DEM by
@divagis
.
#GIS #Cartography #SaudiArabia #Landcover #Desert #Asir #RemoteSensing

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

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

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

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

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

Neighbourhood colours of Basel: Basel-Stadt’s Statistical Office turns #landcover into art with “#Quartierfarben”, an interactive tool that maps each neighbourhood’s mix of green space, traffic, water and buildings and lets you turn it into a downloadable postcard. Built in the...
https://spatialists.ch/posts/2026/07/09-neighbourhood-colours-of-basel/ #GIS #GISchat #geospatial #SwissGIS

Neighbourhood colours of Basel: Basel-Stadt’s Statistical Office turns #landcover into art with “#Quartierfarben”, an interactive tool that maps each neighbourhood’s mix of green space, traffic, water and buildings and lets you turn it into a downloadable postcard. Built in the...
https://spatialists.ch/posts/2026/07/09-neighbourhood-colours-of-basel/ #GIS #GISchat #geospatial #SwissGIS

Neighbourhood colours of Basel: Basel-Stadt’s Statistical Office turns #landcover into art with “#Quartierfarben”, an interactive tool that maps each neighbourhood’s mix of green space, traffic, water and buildings and lets you turn it into a downloadable postcard. Built in the...
https://spatialists.ch/posts/2026/07/09-neighbourhood-colours-of-basel/ #GIS #GISchat #geospatial #SwissGIS

Neighbourhood colours of Basel: Basel-Stadt’s Statistical Office turns #landcover into art with “#Quartierfarben”, an interactive tool that maps each neighbourhood’s mix of green space, traffic, water and buildings and lets you turn it into a downloadable postcard. Built in the...
https://spatialists.ch/posts/2026/07/09-neighbourhood-colours-of-basel/ #GIS #GISchat #geospatial #SwissGIS

Neighbourhood colours of Basel: Basel-Stadt’s Statistical Office turns #landcover into art with “#Quartierfarben”, an interactive tool that maps each neighbourhood’s mix of green space, traffic, water and buildings and lets you turn it into a downloadable postcard. Built in the...
https://spatialists.ch/posts/2026/07/09-neighbourhood-colours-of-basel/ #GIS #GISchat #geospatial #SwissGIS

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