East Kimberley Remotely Sensed ProductsThis web service contains a selection of remotely sensed raster products used in the Exploring for the Future (EFTF) East Kimberley Groundwater Project. Selected products were derived from LiDAR, Landsat (5, 7, and 8), and Sentinel-2 data. Datasets include: 1) mosaic 5 m digital elevation model (DEM) with shaded relief; 2) vegetation structure stratum and substratum classes; 3) Normalised Difference Vegetation Index (NDVI) 20th, 50th, and 80th percentiles; 4) Tasselled Cap exceedance summaries; 5) Normalised Difference Moisture Index (NDMI) and Normalised Difference Wetness Index (NDWI). Landsat spectral reflectance products can be used to highlight land cover characteristics such as brightness, greenness and wetness, and vegetation condition; Sentinel-2 datasets help to detect vegetation moisture stress or waterlogging; LiDAR datasets providing a five meter DEM and vegetation structure stratum classes for detailed analysis of vegetation and relief.satellite imageryLandsatNDVINormalised Difference Vegetation IndexTasselled Cap Exceedance SummaryLiDARDEMSentinel-2Vegetation Structure Stratum Classesurn:ogc:service:wcs2.0.11.1.11.1.0http://www.opengis.net/spec/WCS/2.0/conf/corehttp://www.opengis.net/spec/WCS_protocol-binding_get-kvp/1.0.1http://www.opengis.net/spec/WCS_protocol-binding_post-xml/1.0http://www.opengis.net/spec/WCS_service-extension_crs/1.0/conf/crs-gridded-coveragehttp://www.opengis.net/spec/GMLCOV/1.0/conf/gml-coveragehttp://www.opengis.net/spec/GMLCOV/1.0/conf/special-formathttp://www.opengis.net/spec/GMLCOV/1.0/conf/multiparthttp://www.opengis.net/spec/WCS_service-extension_scaling/1.0/conf/scalinghttp://www.opengis.net/spec/WCS_service-extension_crs/1.0/conf/crshttp://www.opengis.net/spec/WCS_service-extension_interpolation/1.0/conf/interpolationhttp://www.opengis.net/spec/WCS_service-extension_interpolation/1.0/conf/interpolation-per-axishttp://www.opengis.net/spec/WCS_service-extension_interpolation/1.0/conf/nearest-neighborhttp://www.opengis.net/spec/WCS_service-extension_interpolation/1.0/conf/linearhttp://www.opengis.net/spec/WCS_service-extension_interpolation/1.0/conf/cubichttp://www.opengis.net/spec/WCS_service-extension_range-subsetting/1.0/conf/record-subsettingNONE© Commonwealth of Australia (Geoscience Australia) 2024. This product is released under the Creative Commons Attribution 4.0 International Licence. http://creativecommons.org/licenses/by/4.0/legalcodeGeoscience AustraliaClient Services+61 2 6249 9111+61 2 6249 9999GPO Box 378CanberraACT2601Australiaclientservices@ga.gov.auXMLapplication/gml+xmlimage/jpegimage/pngimage/tiffimage/tiff;application=geotifftext/plainhttp://www.opengis.net/def/crs/EPSG/0/28352http://www.opengis.net/def/crs/EPSG/0/7852http://www.opengis.net/def/crs/EPSG/0/32752http://www.opengis.net/def/crs/EPSG/0/3857http://www.opengis.net/def/crs/EPSG/0/4283http://www.opengis.net/def/crs/EPSG/0/7844http://www.opengis.net/def/crs/EPSG/0/4326http://www.opengis.net/def/interpolation/OGC/1/nearest-neighborhttp://www.opengis.net/def/interpolation/OGC/1/linearhttp://www.opengis.net/def/interpolation/OGC/1/cubicEast Kimberley 2017 DEM 5mEast Kimberley LiDAR Digital Elevation Model (DEM) mosaic raster at 5 m spatial resolution was resampled from orthometric 1m mosaic DEM to 5m using cubic convolution value assigning methodin ArcGIS. LiDAR data was acquired by AAM Pty Ltd in June 2017 using Optech Galaxy LiDAR unit. Geoscience Australia Elevation team carried out post processing, classification, production, and delivery of all released datasets.LiDARDigital Elevation ModelDEMek-raster__KimberleyEast2017_DEM_fst_5mRectifiedGridCoverage428000.0 8232000.0544000.0 8358000.0128.32709482346954 -15.991538034748825129.41122623677128 -14.851417499978732East Kimberley 2017 DEM 5m HillshadeEast Kimberley LiDAR Digital Elevation Model (DEM) shaded relief raster, representing ground surface illuminated at 45 degree altitude with North West azimuth, and 10 times vertical exaggeration at 5m spatial resolution. LiDAR data was acquired by AAM Pty Ltd in June 2017 using Optech Galaxy LiDAR unit. Geoscience Australia Elevation team carried out post processing, classification, production, and delivery of all released datasets.LiDARDigital Elevation ModelDEMhillshadeshaded reliefek-raster__KimberleyEast2017_DEM_fst_5m_HillshadeRectifiedGridCoverage428000.0 8232000.0544000.0 8358000.0128.32709482346954 -15.991538034748825129.41122623677128 -14.851417499978732NDVI 20th Percentile Band 1East Kimberley NDVI 20th percentile for dry season (April to October) 1987-2018. NDVI was calculated for each Landsat surface reflectance observation and the 20th percentile was calculated for each pixel.satellite imageryNDVINormalised Difference Vegetation IndexLandsatek-raster__NDVI_20thPercentile_Band_1RectifiedGridCoverage324120.5794645462 8233637.824867175626141.5255939632 8442635.01960618127.35657142134511 -15.976611671046943130.17875939103305 -14.081650941532367NDVI 50th Percentile Band 2East Kimberley NDVI 50th percentile for 1987-2018. NDVI was calculated for each Landsat surface reflectance observation within the temporal and spatial query and the 20th, 50th and 80th percentile were calculated for each pixel.satellite imageryNDVINormalised Difference Vegetation IndexLandsatek-raster__NDVI_50thPercentile_Band_2RectifiedGridCoverage324120.5794645462 8233637.824867175626141.5255939632 8442635.01960618127.35657142134511 -15.976611671046943130.17875939103305 -14.081650941532367NDVI 80th Percentile Band 3The Normalised Difference Vegetation Index (NDVI) percentiles include 20th, 50th, and 80th for dry seasons (April to October) 1987 to 2018 and were derived from the Landsat 5,7 and 8 data stored in Digital Earth Australia (see Geoscience Australia, 2019). NDVI was calculated for each Landsat surface reflectance observation and the 20th, 50th and 80th percentiles were calculated for each pixel. East Kimberley NDVI 80th percentile for dry season (April to October) 1987-2018. NDVI was calculated for each Landsat surface reflectance observation and the 80th percentile was calculated for each pixel. Geoscience Australia, 2019. Earth Observation Archive. Geoscience Australia, Canberra. http://dx.doi.org/10.4225/25/57D9DCA3910CD.satellite imageryNDVINormalised Difference Vegetation IndexLandsatek-raster__NDVI_80thPercentile_Band_3RectifiedGridCoverage324120.5794645462 8233637.824867175626141.5255939632 8442635.01960618127.35657142134511 -15.976611671046943130.17875939103305 -14.081650941532367Sentinel-2 NDMINormalised Difference Moisture Index (NDMI) is used to detect vegetation moisture stress or waterlogging. NDMI is calculated as (NIR – SWIR)/(NIR + SWIR). Multi-colour ramp image with linear histogram stretched values, showing distribution of the vegetation and irrigated crops leaf moisture from low: -1 to high: 1.Surface MoistureSentinel-2Normalised Difference Moisture IndexNDMIek-raster__EK_Sen2_NDMIRectifiedGridCoverage-423860.0 -1704490.0-247220.0 -1564930.0128.062357207346 -16.007460383189255129.72593624192984 -14.697936751223999Sentinel-2 NDMI ClassifiedNormalised Difference Moisture Index (NDMI) is used to detect vegetation moisture stress or waterlogging. NDMI raster with 20 discrete colours for each defined class interval of 0.1 is showing distribution of the surface or leaf moisture in vegetation and irrigated crops as values between -1 (dry) to 1 (water). Waterlogged areas correspond to class values from 0.2 to 0.4.Surface MoistureSentinel-2Normalised Difference Moisture IndexNDMIek-raster__EK_Sen2_NDMI_ClassifiedRectifiedGridCoverage-423860.0 -1704490.0-247220.0 -1564930.0128.062357207346 -16.007460383189255129.72593624192984 -14.697936751223999Sentinel-2 NDWINormalised Difference Water Index (NDWI) is used to detect surface moisture and delineate water bodies. NDWI is calculated as (Green-NIR) / (Green+NIR). Multi-colour ramp image with the standard deviation histogram stretched values, showing distribution of the surface moisture from low: -1 to high: 1. Positive values indicate waterlogged areas.Surface MoistureSentinel-2Normalised Difference Water IndexNDWIek-raster__EK_Sen2_NDWIRectifiedGridCoverage-423860.0 -1704490.0-247220.0 -1564930.0128.062357207346 -16.007460383189255129.72593624192984 -14.697936751223999Sentinel-2 NDWI ClassifiedNormalised Difference Water Index (NDWI) is used to detect surface moisture and delineate water bodies. NDWI is calculated as (Green-NIR) / (Green+NIR). NDWI raster with 20 discrete colours for each defined class interval of 0.1 is showing distribution of the surface moisture as values from -1 (dry) to 1 (water). Positive values indicate waterlogged areas. Water bodies usually get values higher than 0.2.Surface MoistureSentinel-2Normalised Difference Water IndexNDWIek-raster__EK_Sen2_NDWI_ClassifiedRectifiedGridCoverage-423860.0 -1704490.0-247220.0 -1564930.0128.062357207346 -16.007460383189255129.72593624192984 -14.697936751223999TC Wetness Brightness Greenness Exceedances SummaryThe Tasselled Cap brightness, greenness and wetness statistics are linear combinations of Landsat bands and were calculated using the coefficients presented in Crist (1985). This dataset shows the percentage of observations that each pixel exceeded a particular threshold of brightness, greenness and wetness as well as the mean and standard deviation of these metrics. These surface reflectance products can be used to highlight vegetation characteristics such as wetness and greenness, and land cover. Tasselled Cap Exceedance Summary include brightness, greenness and wetness as a composite image and were derived from the Landsat 5, 7 and 8 data stored in Digital Earth Australia (see Geoscience Australia, 2019). Tasselled Cap brightness, greenness and wetness coefficients (see Crist, 1985) were calculated for period 1987 to 2018. Brightness, greenness and wetness exceedance was identified where the respective coefficient exceeded a particular threshold. The mean and standard deviation statistics of brightness, greenness and wetness were calculated on pixel basis for the available time series.satellite imageryLandsatTassel Capwetnessbrightnessgreennessek-raster__TC_Exceedances_SummaryRectifiedGridCoverage324120.5794645462 8233637.824867175626141.5255939632 8442635.01960618127.35657142134511 -15.976611671046943130.17875939103305 -14.081650941532367Vegetation Structure Stratum ClassesThe Vegetation Structure Stratum classes dataset was derived from Vegetation Height Model (VHM) and Fractional Cover Model (FCM) LiDAR products. The National Vegetation Information System framework was used to classify vegetation height and canopy/cover density into (sub-)stratum, growth forms, and structural formation classes. The classifications contain descriptions and spatial extents of the vegetation types for the East Kimberley LiDAR survey area. The displayed classifications include 19 dominant structural formation classes for lower-, mid-, and upper stratum. High resolution LiDAR imagery, including Digital Elevation Model (DEM), Canopy Height Model (CHM), Vegetation Height Model (VHM), Vegetation Cover Model (VCM) and Fractional Cover Model (FCM) surfaces were acquired for the East Kimberley area in June 2017. All the data were released in 2019 (Geoscience Australia, 2019).Vegetation Structure StratumLiDARvegetation heightcanopy densityek-raster__VegetationStructure_StratumRectifiedGridCoverage427999.9999999993 8232000.0543999.9999999993 8358000.0128.32709482346954 -15.991503998602402129.41122623677128 -14.851417499978732Vegetation Structure SubStratum ClassesThe Vegetation Structure SubStratum classes dataset was derived from Vegetation Height Model (VHM) and Fractional Cover Model (FCM) LiDAR products. The National Vegetation Information System framework was used to classify vegetation height and canopy/cover density into (sub-)stratum, growth forms, and structural formation classes. The classifications contain descriptions and spatial extents of the vegetation types for the East Kimberley LiDAR survey area. The displayed classification include 43 dominant sub-structural formation classes for lower-, mid-, and upper stratum. High resolution LiDAR imagery, including Digital Elevation Model (DEM), Canopy Height Model (CHM), Vegetation Height Model (VHM), Vegetation Cover Model (VCM) and Fractional Cover Model (FCM) surfaces were acquired for the East Kimberley area in June 2017. All the data were released in 2019 (Geoscience Australia, 2019).Vegetation Structure SubStratumLiDARvegetation heightcanopy densityek-raster__VegetationStructure_SubStratumRectifiedGridCoverage427999.9999999993 8232000.0543999.9999999993 8358000.0128.32709482346954 -15.991538034748825129.41122623677128 -14.851417499978732