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NEON Lidar (light detection and ranging data) for grand mesa colorado. NEON will provide free lidar data for 30 years over all of its core sites.
Aerial shot of a cityscape in West Kalimantan, Indonesia.
Photo by Yayan Indriatmoko/CIFOR
If you use one of our photos, please credit it accordingly and let us know. You can reach us through our Flickr account or at: cifor-mediainfo@cgiar.org and m.edliadi@cgiar.org
Reference: APAAME_20221103_FB-0415
Photographer: Firas Bqa'in
Credit: APAAME
Copyright: Creative Commons Attribution-Noncommercial-NoDerivative Works
Reference: APAAME_20221103_FB-0311
Photographer: Firas Bqa'in
Credit: APAAME
Copyright: Creative Commons Attribution-Noncommercial-NoDerivative Works
Reference: APAAME_20221103_FB-0351
Photographer: Firas Bqa'in
Credit: APAAME
Copyright: Creative Commons Attribution-Noncommercial-NoDerivative Works
The Global Summer Land Surface Temperature (LST) Grids, 2013, part of the Satellite-Derived Environmental Indicators collection, estimate daytime (1:30 p.m.) maximum temperature and nighttime (1:30 a.m.) minimum temperature in degrees Celsius at a spatial resolution of ~1km during summer months of the northern and southern hemispheres for the year 2013. The LST grids are produced using the Aqua Level-3 Moderate Resolution Imaging Spectroradiometer (MODIS) Version 5 global daytime and nighttime LST 8-day composite data product (MYD11A2). See more information at dx.doi.org/10.7927/H408638T.
Classification of a portion of LandSat imagery from Path 90 Row 79 (around Lake Wivenhoe and the Somerset reservoir, between Brisbane and Toowoomba in southern Queensland), using bands 1,2,3,4,5 & 7. It was performed in ERMapper.
Unsupervised classification is an exercise in point-cluster delineation, each point corresponding to a pixel in the image. In this case, because six wavelength bands were used, clustering was analysed in 6 dimensions. ISODATA is an iterative algorithm, repeatedly merging and re-dividing classes it has previously created, to arrive at an optimally distinct and robust collection of point clusters.
Correspondence between the classes it comes up with and human-conceived land cover type classes is not guaranteed, as in this case. To get round this, the algorithm can be asked to erect many more classes than are envisaged for human use, and then hopefully it is possible to selectively combine ISODATA classes that are more-or-less subsets of a particular human-conceived cover type class.
The class that I have coloured blue was the one that principally corresponded to open water, but it also included areas of particularly dark, lush vegetation, both natural forest and certain arable fields. This probably happened because of green algae (and hence chlorophyll) in the freshwater bodies.
Reference: APAAME_20221103_FB-0239
Photographer: Firas Bqa'in
Credit: APAAME
Copyright: Creative Commons Attribution-Noncommercial-NoDerivative Works
Trends in Global Freshwater Availability from the Gravity Recovery and Climate Experiment (GRACE), 2002–2016, part of the Satellite-Derived Environmental Indicators Collection, is a global gridded data set at a spatial resolution of 0.5 degrees that presents trends (rate of change measured in centimeters per year) in freshwater availability based on data obtained from 2002 to 2016 by NASA GRACE. Terrestrial water availability is the sum of groundwater, soil moisture, snow and ice, surface waters, and wet biomass, expressed as an equivalent height of water.
Harvard forest is a NEON core site. NEON will provide free lidar data for 30 years over all of its core sites.
Trends in Global Freshwater Availability from the Gravity Recovery and Climate Experiment (GRACE), 2002–2016, part of the Satellite-Derived Environmental Indicators Collection, is a global gridded data set at a spatial resolution of 0.5 degrees that presents trends (rate of change measured in centimeters per year) in freshwater availability based on data obtained from 2002 to 2016 by NASA GRACE. Terrestrial water availability is the sum of groundwater, soil moisture, snow and ice, surface waters, and wet biomass, expressed as an equivalent height of water.
Reference: APAAME_20221115_FBal-165
Photographer: Fadi Bala'wi
Credit: APAAME
Copyright: Creative Commons Attribution-Noncommercial-NoDerivative Works
The Global Development Potential Indices are part of the Land Use Land Cover collection. The data set contains 13 sector-level Development Potential Indices (DPIs) for sectors related to renewable energy (concentrated solar power, photovoltaic solar, wind, hydropower), fossil fuels (coal, conventional and unconventional oil and gas), mining (metallic, non-metallic), and agriculture (crop, biofuels expansion). Each DPI is a 1-km spatially-explicit, global land suitability map that has been validated using locations of planned development as well as examined for uncertainty and sensitivity. This map displays the DPI for photovoltaic solar power, grouped into six 6 classes ranging from very low to very high.
The Global Annual PM2.5 Grids from MODIS, MISR and SeaWiFS Aerosol Optical Depth (AOD), 1998-2019, V4.GL.03 consists of annual concentrations (micrograms per cubic meter) of all composition ground-level fine particulate matter (PM2.5). This data set combines AOD retrievals from multiple satellite algorithms including NASA MODerate resolution Imaging Spectroradiometer Collection 6.1 (MODIS C6.1), Multi-angle Imaging SpectroRadiometer Version 23 (MISRv23), MODIS Multi-Angle Implementation of Atmospheric Correction Collection 6 (MAIAC C6), and the Sea-Viewing Wide Field-of-View Sensor (SeaWiFS) Deep Blue Version 4. The GEOS-Chem chemical transport model is used to relate this total column measure of aerosol to near-surface PM2.5 concentration. Geographically Weighted Regression (GWR) is used with global ground-based measurements from the World Health Organization (WHO) database to predict and adjust for the residual PM2.5 bias per grid cell in the initial satellite-derived values. This map represents percent change in concentrations of all composition ground-level fine particulate matter from 1998 to 2019 using 5-year averages.
Reference: APAAME_20221123_RHB-0297
Photographer: Robert Bewley
Credit: APAAME
Copyright: Creative Commons Attribution-Noncommercial-NoDerivative Works
Reference: APAAME_20221123_RHB-0283
Photographer: Robert Bewley
Credit: APAAME
Copyright: Creative Commons Attribution-Noncommercial-NoDerivative Works
Reference: APAAME_20221123_FB-0394
Photographer: Firas Bqa'in
Credit: APAAME
Copyright: Creative Commons Attribution-Noncommercial-NoDerivative Works
Trends in Global Freshwater Availability from the Gravity Recovery and Climate Experiment (GRACE), 2002–2016, part of the Satellite-Derived Environmental Indicators Collection, is a global gridded data set at a spatial resolution of 0.5 degrees that presents trends (rate of change measured in centimeters per year) in freshwater availability based on data obtained from 2002 to 2016 by NASA GRACE. Terrestrial water availability is the sum of groundwater, soil moisture, snow and ice, surface waters, and wet biomass, expressed as an equivalent height of water.
Reference: APAAME_20221123_RHB-0276
Photographer: Robert Bewley
Credit: APAAME
Copyright: Creative Commons Attribution-Noncommercial-NoDerivative Works
Reference: APAAME_20221103_BT-0316
Photographer: Bashar Tabbah
MAP&LENS
Credit: APAAME
Copyright: Creative Commons Attribution-Noncommercial-NoDerivative Works
Reference: APAAME_20221123_FB-0395
Photographer: Firas Bqa'in
Credit: APAAME
Copyright: Creative Commons Attribution-Noncommercial-NoDerivative Works
Reference: APAAME_20221123_RHB-0278
Photographer: Robert Bewley
Credit: APAAME
Copyright: Creative Commons Attribution-Noncommercial-NoDerivative Works
Reference: APAAME_20221103_RHB-0358
Photographer: Robert Bewley
Credit: APAAME
Copyright: Creative Commons Attribution-Noncommercial-NoDerivative Works
Alone in the desert
while purple expands
towards equality
mindsets scanned
Still a long way to go.
@CopernicusEU #Sentinel2 2022-06-21
Saudi Arabia.
Reference: APAAME_20221103_RHB-0407
Photographer: Robert Bewley
Credit: APAAME
Copyright: Creative Commons Attribution-Noncommercial-NoDerivative Works
Reference: APAAME_20221103_RHB-0293
Photographer: Robert Bewley
Credit: APAAME
Copyright: Creative Commons Attribution-Noncommercial-NoDerivative Works
Reference: APAAME_20221123_RHB-0289
Photographer: Robert Bewley
Credit: APAAME
Copyright: Creative Commons Attribution-Noncommercial-NoDerivative Works
Reference: APAAME_20221123_RHB-0158
Photographer: Robert Bewley
Credit: APAAME
Copyright: Creative Commons Attribution-Noncommercial-NoDerivative Works
The flow direction layer, generated from the digital elevation model, is very similar looking to hillshading. It can be used as input to generate a flow accumulation layer, which models surface water run-off coalescing into watercourses.
This image shows the value of playing around with different visual representations of elevation data. You can see the clusters of small cinder-cones near the left edge of the image, but also, there seem to be one or two partially formed craters immediately west of Lake Barrine, which is a maar (a lake formed after a phreatomagmatic explosion, i.e. an eruption caused by explosive generation of steam from groundwater coming into contact with hot magma).
The German word maar is etymologically related to the old English word mere, and to the Latin mare, and simply means lake.
The Global Development Potential Indices are part of the Land Use Land Cover collection. The data set contains 13 sector-level Development Potential Indices (DPIs) for sectors related to renewable energy (concentrated solar power, photovoltaic solar, wind, hydropower), fossil fuels (coal, conventional and unconventional oil and gas), mining (metallic, non-metallic), and agriculture (crop, biofuels expansion). Each DPI is a 1-km spatially-explicit, global land suitability map that has been validated using locations of planned development as well as examined for uncertainty and sensitivity. This map displays the DPI for concentrated solar power, grouped into six 6 classes ranging from very low to very high.