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761

MODIS LST monthly daytime and nighttime low (0.05), median (0.50) and high (0.95) temperatures for year 2019 at 1-km

by Hengl, T., Parente, L.
Published 2021
“... To download and compute with maps using Cloud-Optimized-GeoTIFF see this tutorial . If you discover a bug...”

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Dataset
Select result number 762
762

MODIS LST monthly daytime and nighttime low (0.05), median (0.50) and high (0.95) temperatures for year 2001 at 1-km

by Hengl, T., Parente, L.
Published 2021
“... To download and compute with maps using Cloud-Optimized-GeoTIFF see this tutorial . If you discover a bug...”

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Dataset
Select result number 763
763

MODIS LST monthly daytime and nighttime low (0.05), median (0.50) and high (0.95) temperatures for year 2001 at 1-km

by Hengl, T., Parente, L.
Published 2021
“... To download and compute with maps using Cloud-Optimized-GeoTIFF see this tutorial . If you discover a bug...”

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Dataset
Select result number 764
764

MODIS LST monthly daytime and nighttime low (0.05), median (0.50) and high (0.95) temperatures for year 2002 at 1-km

by Hengl, T., Parente, L.
Published 2021
“... To download and compute with maps using Cloud-Optimized-GeoTIFF see this tutorial . If you discover a bug...”

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Dataset
Select result number 765
765

MODIS LST monthly daytime and nighttime low (0.05), median (0.50) and high (0.95) temperatures for year 2002 at 1-km

by Hengl, T., Parente, L.
Published 2021
“... To download and compute with maps using Cloud-Optimized-GeoTIFF see this tutorial . If you discover a bug...”

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Dataset
Select result number 766
766

MODIS LST monthly daytime and nighttime low (0.05), median (0.50) and high (0.95) temperatures for year 2003 at 1-km

by Hengl, T., Parente, L.
Published 2021
“... To download and compute with maps using Cloud-Optimized-GeoTIFF see this tutorial . If you discover a bug...”

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Dataset
Select result number 767
767

MODIS LST monthly daytime and nighttime low (0.05), median (0.50) and high (0.95) temperatures for year 2003 at 1-km

by Hengl, T., Parente, L.
Published 2021
“... To download and compute with maps using Cloud-Optimized-GeoTIFF see this tutorial . If you discover a bug...”

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Dataset
Select result number 768
768

MODIS LST monthly daytime and nighttime low (0.05), median (0.50) and high (0.95) temperatures for year 2004 at 1-km

by Hengl, T., Parente, L.
Published 2021
“... To download and compute with maps using Cloud-Optimized-GeoTIFF see this tutorial . If you discover a bug...”

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Dataset
Select result number 769
769

MODIS LST monthly daytime and nighttime low (0.05), median (0.50) and high (0.95) temperatures for year 2004 at 1-km

by Hengl, T., Parente, L.
Published 2021
“... To download and compute with maps using Cloud-Optimized-GeoTIFF see this tutorial . If you discover a bug...”

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Dataset
Select result number 770
770

MODIS LST monthly daytime and nighttime low (0.05), median (0.50) and high (0.95) temperatures for year 2016 at 1-km

by Hengl, T., Parente, L.
Published 2021
“... To download and compute with maps using Cloud-Optimized-GeoTIFF see this tutorial. If you discover a bug...”

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Dataset
Select result number 771
771

MODIS LST monthly daytime and nighttime low (0.05), median (0.50) and high (0.95) temperatures for year 2015 at 1-km

by Hengl, T., Parente, L.
Published 2021
“... To download and compute with maps using Cloud-Optimized-GeoTIFF see this tutorial. If you discover a bug...”

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Dataset
Select result number 772
772

Soil organic carbon stock in kg/m2 for 5 standard depth intervals (0–10, 10–30, 30–60, 60–100 and 100–200 cm) at 250 m resolution

by Tomislav Hengl, Ichsani Wheeler
Published 2018
“...: https://openlandmap.org If you discover a bug, artifact or inconsistency in the maps, or if you have a...”

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Dataset
Select result number 773
773

Soil organic carbon stock (0–30 cm) in kg/m2 time-series 2001–2015 based on the land cover changes

by Ichsani Wheeler, Hengl, Tomislav
Published 2018
“... If you discover a bug, artifact or inconsistency in the maps, or if you have a question please use some...”

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Dataset
Select result number 774
774

Soil water content (volumetric %) for 33kPa and 1500kPa suctions predicted at 6 standard depths (0, 10, 30, 60, 100 and 200 cm) at 250 m resolution

by Tomislav Hengl, Surya Gupta
Published 2019
“...://landgis.opengeohub.org If you discover a bug, artifact or inconsistency in the LandGIS maps, or if you have a question...”

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Dataset
Select result number 775
775

MOD17A2H version 6 Gross Primary Productivity (GPP) global mosaics at 500 m resolution and difference 2000-2017

by Hengl, Tomislav
Published 2018
“.... Antartica is not included. If you discover a bug, artifact or inconsistency in the maps, or if you have a...”

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Dataset
Select result number 776
776

Global DEM derivatives at 250 m, 1 km and 2 km based on the MERIT DEM

by Hengl, Tomislav
Published 2018
“.... To access and visualize maps use: OpenLandMap.org If you discover a bug, artifact or inconsistency...”

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Dataset
Select result number 777
777

Predicted USDA soil great groups at 250 m (probabilities)

by Hengl, Tomislav, Nauman, Travis
Published 2018
“.... To access and visualize maps use: https://landgis.opengeohub.org If you discover a bug, artifact...”

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Dataset
Select result number 778
778

Predicted USDA soil suborders at 250 m (probabilities)

by Hengl, Tomislav, Nauman, Travis
Published 2019
“...: OpenLandMap.org If you discover a bug, artifact or inconsistency in the maps, or if you have a question please use...”

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Dataset
Select result number 779
779

Predicted USDA soil suborders at 250 m (probabilities)

by Hengl, Tomislav, Nauman, Travis
Published 2019
“...: OpenLandMap.org If you discover a bug, artifact or inconsistency in the maps, or if you have a question please use...”

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Dataset
Select result number 780
780

GBIF Occurrence Download

by Occdownload Gbif.Org
Published 2018
“.... 1 records from BugGuide - Identification, Images, & Information For Insects, Spiders & Their Kin...”

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Dataset