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This product is released under the Creative Commons Attribution 4.0 International Licence. http://creativecommons.org/licenses/by/4.0/legalcode text/xml image/png application/atom+xml application/geopackage+sqlite3 application/json;type=utfgrid application/pdf application/rss+xml application/vnd.google-earth.kml+xml application/vnd.google-earth.kml+xml;mode=networklink application/vnd.google-earth.kmz image/geotiff image/geotiff8 image/gif image/jpeg image/png; mode=8bit image/svg+xml image/tiff image/tiff8 image/vnd.jpeg-png image/vnd.jpeg-png8 text/html; subtype=openlayers text/html; subtype=openlayers2 text/html; subtype=openlayers3 text/plain application/vnd.ogc.gml text/xml application/vnd.ogc.gml/3.1.1 text/xml; subtype=gml/3.1.1 text/html application/json XML INIMAGE BLANK JSON This web service provides access to gridded data produced by Geoscience Australia from studies of Australian groundwater and hydrogeological systems. EPSG:3577 EPSG:4283 EPSG:4326 EPSG:3857 EPSG:20248 EPSG:20249 EPSG:20250 EPSG:20251 EPSG:20252 EPSG:20253 EPSG:20254 EPSG:20255 EPSG:20256 EPSG:20257 EPSG:20258 EPSG:28348 EPSG:28349 EPSG:28350 EPSG:28351 EPSG:28352 EPSG:28353 EPSG:28354 EPSG:28355 EPSG:28356 EPSG:28357 EPSG:28358 EPSG:32748 EPSG:32749 EPSG:32750 EPSG:32751 EPSG:32752 EPSG:32753 EPSG:32754 EPSG:32755 EPSG:32756 EPSG:32757 EPSG:32758 EPSG:3110 EPSG:3111 EPSG:3112 EPSG:3031 EPSG:3032 EPSG:3308 EPSG:3107 CRS:84 127.35631114229716 147.9681839177344 -31.992542877195405 -13.583790289980561 This layer group 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. EPSG:28352 127.35631114229716 130.17894612754455 -16.008484521672735 -14.081650945471928 Landsat derived products highlighting vegetation characteristics such as wetness and greenness, and land cover. Tasselled Cap Exceedance Summary includes wetness, brightness, and greenness as a composite image. Normalised Difference Vegetation Index (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. NDVI percentiles are for dry seasons 1987 to 2018. satellite imagery EPSG:28352 127.3565714213451 130.17875939103303 -15.976611676730265 -14.081650945471928 text/html ek-raster:NDVI_20thPercentile_Band_1 East 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 imagery NDVI Normalised Difference Vegetation Index Landsat EPSG:28352 CRS:84 127.35657142134511 130.17875939103305 -15.976611671046943 -14.081650941532367 text/html ek-raster:NDVI_50thPercentile_Band_2 East 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 imagery NDVI Normalised Difference Vegetation Index Landsat EPSG:28352 CRS:84 127.35657142134511 130.17875939103305 -15.976611671046943 -14.081650941532367 text/html ek-raster:NDVI_80thPercentile_Band_3 The 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 imagery NDVI Normalised Difference Vegetation Index Landsat EPSG:28352 CRS:84 127.35657142134511 130.17875939103305 -15.976611671046943 -14.081650941532367 text/html ek-raster:TC_Exceedances_Summary The 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 imagery Landsat Tassel Cap wetness brightness greenness EPSG:28352 CRS:84 127.35657142134511 130.17875939103305 -15.976611671046943 -14.081650941532367 text/html East Kimberley LiDAR Products contains Vegetation Structure classes derived from Vegetation Height Model (VHM) and Fractional Cover Model (FCM) LiDAR datasets, and Elevation mosaic raster with shaded relief image at 5m spatial resolution. EPSG:28352 128.32709482346954 129.41122623677128 -15.991538040447248 -14.851417504585068 text/html text/html ek-raster:VegetationStructure_Stratum The 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 Stratum LiDAR vegetation height canopy density EPSG:28352 CRS:84 128.32709482346954 129.41122623677128 -15.991503998602402 -14.851417499978732 text/html ek-raster:VegetationStructure_SubStratum The 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 SubStratum LiDAR vegetation height canopy density EPSG:28352 CRS:84 128.32709482346954 129.41122623677128 -15.991538034748825 -14.851417499978732 text/html ek-raster:KimberleyEast2017_DEM_fst_5m East 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. LiDAR Digital Elevation Model DEM EPSG:28352 CRS:84 128.32709482346954 129.41122623677128 -15.991538034748825 -14.851417499978732 text/html ek-raster:KimberleyEast2017_DEM_fst_5m_Hillshade East 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. LiDAR Digital Elevation Model DEM hillshade shaded relief EPSG:28352 CRS:84 128.32709482346954 129.41122623677128 -15.991538034748825 -14.851417499978732 text/html The East Kimberley Surface Moisture products group layer contains classified and visually enhanced derivatives of the Sentinel-2 satellite sensor ‘geo-median’ dataset. A weighted geometric median statistic has been applied to Sentinel-2 dataset to derive median reflectance dataset from time series data collected from 2015 to 2018 (Roberts et al., 2017). The Normalised Difference Moisture Index (NDMI; Gao, 1996) and Normalised Difference Water Index (NDWI; McFeeters, 1996) were calculated from the median reflectance. These datasets have been classified and visually enhanced to detect vegetation moisture stress or water-logging and show distribution of moisture. NDMI is used to detect vegetation moisture stress or waterlogging, as NDWI is used to detect surface/soil moisture and delineate water bodies. Layers of classified indices between -1 to 1, and multi-colour ramp stretch images show distribution of moisture from low: -1 to high: 1. For example, positive NDWI values indicate waterlogged areas while waterbodies typically correspond with values greater than 0.2. Waterlogged areas also correspond to NDMI values of 0.2 to 0.4. Surface Moisture Sentinel-2 Normalised Difference Moisture Index NDMI Normalised Difference Water Index NDWI EPSG:3577 128.02120156427134 129.7494686455228 -16.047001324058282 -14.657818167147704 text/html text/html ek-raster:EK_Sen2_NDMI Normalised 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 Moisture Sentinel-2 Normalised Difference Moisture Index NDMI EPSG:3577 CRS:84 128.062357207346 129.72593624192984 -16.007460383189255 -14.697936751223999 text/html ek-raster:EK_Sen2_NDMI_Classified Normalised 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 Moisture Sentinel-2 Normalised Difference Moisture Index NDMI EPSG:3577 CRS:84 128.062357207346 129.72593624192984 -16.007460383189255 -14.697936751223999 text/html ek-raster:EK_Sen2_NDWI Normalised 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 Moisture Sentinel-2 Normalised Difference Water Index NDWI EPSG:3577 CRS:84 128.062357207346 129.72593624192984 -16.007460383189255 -14.697936751223999 text/html ek-raster:EK_Sen2_NDWI_Classified Normalised 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 Moisture Sentinel-2 Normalised Difference Water Index NDWI EPSG:3577 CRS:84 128.062357207346 129.72593624192984 -16.007460383189255 -14.697936751223999 text/html This layer group contains groundwater Tasselled Cap percentile grids derived from Landsat imagery over the South Nicholson - Georgina region, used in the assessment of groundwater dependent ecosystems (GDEs). groundwater hydrogeology remote sensing landsat tasselled cap groundwater dependent ecosystem GDE grids South Nicholson Basin Georgina Basin Exploring For The Future EFTF EPSG:3577 130.43129114522927 142.1734501810812 -25.362536552120105 -13.583790289980561 text/html sng_gde_grids:GSN_Tasselled_Cap_1987_2022_CVgreen50pc The Tasselled Cap greenness 50th percentile Coefficient of Variation (CV) dataset was created using data extracted from Digital Earth Australia to help identify and characterise groundwater dependent ecosystems (GDE) in the South Nicholson-Georgina basins study area. The Tasselled Cap greenness 50th CV represents the amount of variation between a wet and dry period with low CV values indicating a potential GDE, for the timeframe between 1987 and 2022. However, a low CV value could also indicate a permanent waterbody or bare ground, so should be used in conjunction with other datasets. More information and source data can be obtained from https://pid.geoscience.gov.au/dataset/ga/149293. EFTF South Nicholson Basin Georgina Basin Remote Sensing Landsat Tasselled Cap Ground Water Dependent Ecosystem GDE Northern Territory NT Queensland QLD EPSG:3577 CRS:84 130.43129114522927 142.1734501810812 -25.356530021367018 -13.583790289980561 text/html sng_gde_grids:GSN_Tasselled_Cap_1987_2022_CombinedGreenWet The Tasselled Cap greenness and wetness 10th percentiles were extracted from Digital Earth Australia to help identify and characterise groundwater dependent ecosystems (GDE) in the South Nicholson-Georgina basins study area. The Tasselled Cap greenness and wetness 10th percentiles represent the lowest 10% of values and is considered to represent the least green/driest period for the timeframe between 1987 and 2022. These datasets were each classified into nine classes and combined where the first number of the resulting two-digit code represents greenness and the second value represents wetness. A potential GDE is most likely when both digits are above four. E.g., a code of 89 represents an area that is well above average in both greenness and wetness and has a higher probability of being a GDE than a code of 63, which is only above average in greenness (but is still a potential GDE). More information and source data can be obtained from https://pid.geoscience.gov.au/dataset/ga/149293. EFTF South Nicholson Basin Georgina Basin Remote Sensing Landsat Tasselled Cap Ground Water Dependent Ecosystem GDE Northern Territory NT Queensland QLD EPSG:3577 CRS:84 130.43129114522927 142.1734501810812 -25.356530021367018 -13.583790289980561 text/html sng_gde_grids:GSN_Tasselled_Cap_1987_2022_greenness The Tasselled Cap greenness 10th percentiles were extracted from Digital Earth Australia to help identify and characterise groundwater dependent ecosystems (GDE) in the South Nicholson-Georgina basins study area. The Tasselled Cap greenness 10th percentile represent the lowest 10% of values and is considered to represent the least green period for the timeframe between 1987 and 2022. These datasets were each classified into nine classes where a code of 9 represents an area that is well above average in greenness. More information and source data can be obtained from https://pid.geoscience.gov.au/dataset/ga/149293. EFTF South Nicholson Basin Georgina Basin Remote Sensing Landsat Tasselled Cap Ground Water Dependent Ecosystem GDE Northern Territory NT Queensland QLD EPSG:3577 CRS:84 130.43129114522927 142.1734501810812 -25.356530021367018 -13.583790289980561 text/html sng_gde_grids:GSN_Tasselled_Cap_1987_2022_wetness The Tasselled Cap wetness 10th percentiles were extracted from Digital Earth Australia to help identify and characterise groundwater dependent ecosystems (GDE) in the Upper Darling region of NSW. The Tasselled Cap wetness 10th percentiles represent the lowest 10% of values and is considered to represent the driest period for the timeframe between 1987 and 2022. These datasets were each classified into nine classes where a code of 9 represents an area that is well above average in wetness. More information and source data can be obtained from https://pid.geoscience.gov.au/dataset/ga/149293. EFTF South Nicholson Basin Georgina Basin Remote Sensing Landsat Tasselled Cap Ground Water Dependent Ecosystem GDE Northern Territory NT Queensland QLD EPSG:3577 CRS:84 130.43129114522927 142.1734501810812 -25.356530021367018 -13.583790289980561 text/html This layer group consists of groundwater raster products for the Upper Burdekin region, including; inferred relative groundwater recharge potential derived from weightings assigned to qualitative estimates of relative permeability based on mapped soil type and surface geology; Normalised Difference Vegetation Index (NDVI) used to map vegetation with potential access to groundwater in the basalt provinces, and; inferred base surfaces of geological provinces. EPSG:28355 143.43308521034288 146.40909730451713 -20.517156847722866 -17.64969341779984 This layer group contains Normalised Difference Vegetation Index (NDVI) raster layers that map vegetation with potential access to groundwater in basalt provinces of the Upper Burdekin region. EPSG:28355 143.50914704027124 146.3102339859782 -20.216645634009467 -17.706512850831498 text/plain ub-gw-rasters:UB_McBride_NDVI Normalised Difference Vegetation Index (NDVI) was used to map vegetation with potential access to groundwater in the McBride basalt province in the Upper Burdekin. The vegetation classifications in this layer are a product of the median dry and wet NDVI calculated for the end of the dry season and end of the wet season for all available cloud-free Landsat imagery between 1987 and 2018. Dry NDVI values were subtracted from wet NDVI values to show the difference over time. Both dry NDVI and NDVI difference were classified and the classified datasets were then combined with the first number of the two digit code corresponding to the dry NDVI class and the second digit corresponding to the NDVI difference class. Links to the ‘Exploring for the Future – Hydrogeological summary of the McBride and Nulla basalt provinces, North Queensland’ report containing further information on how the data were classified, and a file download for the full dataset used to generate this classification, are available at http://pid.geoscience.gov.au/dataset/ga/135648. Upper Burdekin Groundwater Groundwater Dependent Vegetation Normalised Difference Vegetation Index NDVI vegetation density vegetation vigour EPSG:28355 CRS:84 143.53605111755618 145.37128225383205 -18.95471603088902 -17.706512843260963 text/plain ub-gw-rasters:UB_Nulla_NDVI Normalised Difference Vegetation Index (NDVI) was used to map vegetation with potential access to groundwater in the McBride basalt province in the Upper Burdekin. The vegetation classifications in this layer are a product of the median dry and wet NDVI calculated for the end of the dry season and end of the wet season for all available cloud-free Landsat imagery between 1987 and 2018. Dry NDVI values were subtracted from wet NDVI values to show the difference over time. Both dry NDVI and NDVI difference were classified and the classified datasets were then combined with the first number of the two digit code corresponding to the dry NDVI class and the second digit corresponding to the NDVI difference class. Links to the ‘Exploring for the Future – Hydrogeological summary of the McBride and Nulla basalt provinces, North Queensland’ report containing further information on how the data were classified, and a file download for the full dataset used to generate this classification, are available at http://pid.geoscience.gov.au/dataset/ga/135648. Upper Burdekin Groundwater Groundwater Dependent Vegetation Normalised Difference Vegetation Index NDVI vegetation density vegetation vigour EPSG:28355 CRS:84 144.4857931098585 146.30393469855963 -20.216645623237348 -19.28403939636536 This layer group contains rasters that map inferred relative groundwater recharge potential within basalt provinces of the Upper Burdekin region. EPSG:28355 143.43308521034288 146.40909730451713 -20.517156847722866 -17.64969341779984 ub-gw-rasters:McBride_Basalt_Potential_Recharge Inferred relative groundwater recharge potential within the McBride Basalt Province. Recharge potential categories are derived from weightings assigned to qualitative estimates of relative permeability based on mapped soil type and surface geology. McBride Basalt Upper Burdekin Volcanic Province Groundwater Permeability Potential Recharge EPSG:28355 CRS:84 143.46807744485864 145.31748222331646 -18.92157406266374 -17.64969341029561 ub-gw-rasters:Nulla_Basalt_Potential_Recharge Inferred relative groundwater recharge potential within the Nulla Basalt Province. Recharge potential categories are derived from weightings assigned to qualitative estimates of relative permeability based on mapped soil type and surface geology. Nulla Basalt Upper Burdekin Volcanic Province Groundwater Permeability Potential Recharge EPSG:28355 CRS:84 144.40798634037088 146.40395388616722 -20.517156836534138 -19.162062517030808 This layer group contains rasters of the base surfaces of basalt provinces in the Upper Burdekin region. EPSG:28355 143.551623720566 145.24087695585914 -18.86953952921935 -17.714871054023195 ub-gw-rasters:McBride_Basalt_Inferred_Base This is a raster representing the base surface (mAHD) of the McBride Basalt Province. The surface has been inferred from sparse available data, dominated by private water bore records. This interpretation is based on bore strata and drilling logs, the ground surface elevation at the edges of the province, and surface topography. Iterative processes were used to produce an interpretation with positive thickness within areas of outcropping basalt, and to reflect likely topographic shapes. The resultant model is just one possible base of basalt, based on sparse input data (no uncertainty has been presented); other models are possible. This model has been produced for visualisation purposes and should not be considered a definitive depth prediction dataset. McBride Basalt Upper Burdekin Volcanic Province base surface Exploring for the Future EFTF EPSG:28355 CRS:84 143.551623720566 145.2408769558591 -18.869539520229885 -17.714871046442877 ub-gw-rasters:Nulla_Basalt_Inferred_Base This is a raster representing the base surface (mAHD) of the Nulla Basalt Province. The surface has been inferred from sparse available data, dominated by private water bore records. This interpretation is based on bore strata and drilling logs, the ground surface elevation at the edges of the province, and surface topography. Iterative processes were used to produce an interpretation with positive thickness within areas of outcropping basalt, and to reflect likely topographic shapes. The resultant model is just one possible base of basalt, based on sparse input data (no uncertainty has been presented); other models are possible. This model is for visualisation purposes and should not be considered a definitive depth prediction dataset. Nulla Basalt Upper Burdekin Volcanic Province base surface Exploring for the Future EFTF EPSG:28355 CRS:84 144.52504292433662 146.28796952367028 -20.237344745026782 -19.320084133010877 This layer group consists of Tasselled Cap percentile grids generated from the processing by Digital Earth Australia (2023) of Landsat satellite imagery acquired between 1987 and 2022 to identify potential groundwater dependent ecosystems (GDEs) for the upper Darling River floodplain in NSW. groundwater hydrogeology remote sensing landsat tasselled cap groundwater dependent ecosystem grids EFTF EPSG:3577 142.841939844437 147.9681839177344 -31.992542877195405 -29.001546790334466 text/html ud_gde_grids:UD_CV_Green_pc50_1987_2022 The Tasselled Cap greenness 50th percentile Coefficient of Variation (CV) dataset was created using data extracted from Digital Earth Australia to help identify and characterise groundwater dependent ecosystems (GDE) in the Upper Darling region of NSW. The Tasselled Cap greenness 50th CV represents the amount of variation between a wet and dry period with low CV values indicating a potential GDE, for the timeframe between 1987 and 2022. However, a low CV value could also indicate a permanent waterbody or bare ground, so should be used in conjunction with other datasets. remote sensing Landsat Tasselled Cap Ground Water Dependent Ecosystem GDE Floodplain New South Wales NSW EFTF Upper Darling EPSG:3577 CRS:84 142.841939844437 147.96818391773436 -31.992542877195397 -29.001546790334473 text/html ud_gde_grids:UD_CombinedGreenWet_pc10_1987_2022 The Tasselled Cap greenness and wetness 10th percentiles were extracted from Digital Earth Australia to help identify and characterise groundwater dependent ecosystems (GDE) in the Upper Darling region of NSW. The Tasselled Cap greenness and wetness 10th percentiles represent the lowest 10% of values and is considered to represent the least green/driest period for the timeframe between 1987 and 2022. These datasets were each classified into nine classes and combined where the first number of the resulting two-digit code represents greenness and the second value represents wetness. A potential GDE is most likely when both digits are above four. E.g., a code of 89 represents an area that is well above average in both greenness and wetness and has a higher probability of being a GDE than a code of 63, which is only above average in greenness (but is still a potential GDE). EFTF Upper Darling Remote Sensing Landsat Tasselled Cap Ground Water Dependent Ecosystem GDE New South Wales NSW EPSG:3577 CRS:84 142.841939844437 147.96818391773436 -31.992542877195397 -29.001546790334473 text/html ud_gde_grids:UD_ScaledGreenWet_pc10_1987_2022 The Tasselled Cap greenness and wetness 10th percentiles were extracted from Digital Earth Australia to help identify and characterise groundwater dependent ecosystems (GDE) in the Upper Darling region of NSW. The Tasselled Cap greenness and wetness 10th percentiles represent the lowest 10% of values and is considered to represent the least green/driest period for the timeframe between 1987 and 2022. These datasets were scaled and then added together, with the higher values correlating to areas of above average greenness and wetness, indicating potential GDEs. EFTF Upper Darling Remote Sensing Landsat Tasselled Cap Groundwater Dependent Ecosystem GDE Upper Darling Floodplain New South Wales NSW Groundwater EPSG:3577 CRS:84 142.841939844437 147.96818391773436 -31.992542877195397 -29.001546790334473 text/html gw_grids:UD_CV_Green_pc50_1987_2022 The Tasselled Cap greenness 50th percentile Coefficient of Variation (CV) dataset was created using data extracted from Digital Earth Australia to help identify and characterise groundwater dependent ecosystems (GDE) in the Upper Darling region of NSW. The Tasselled Cap greenness 50th CV represents the amount of variation between a wet and dry period with low CV values indicating a potential GDE, for the timeframe between 1987 and 2022. However, a low CV value could also indicate a permanent waterbody or bare ground, so should be used in conjunction with other datasets. remote sensing Landsat Tasselled Cap Ground Water Dependent Ecosystem GDE Floodplain New South Wales NSW EFTF Upper Darling EPSG:3577 CRS:84 142.841939844437 147.9681839177344 -31.992542877195405 -29.001546790334466 text/html gw_grids:UD_CombinedGreenWet_pc10_1987_2022 The Tasselled Cap greenness and wetness 10th percentiles were extracted from Digital Earth Australia to help identify and characterise groundwater dependent ecosystems (GDE) in the Upper Darling region of NSW. The Tasselled Cap greenness and wetness 10th percentiles represent the lowest 10% of values and is considered to represent the least green/driest period for the timeframe between 1987 and 2022. These datasets were each classified into nine classes and combined where the first number of the resulting two-digit code represents greenness and the second value represents wetness. A potential GDE is most likely when both digits are above four. E.g., a code of 89 represents an area that is well above average in both greenness and wetness and has a higher probability of being a GDE than a code of 63, which is only above average in greenness (but is still a potential GDE). EFTF Upper Darling Remote Sensing Landsat Tasselled Cap Ground Water Dependent Ecosystem GDE New South Wales NSW EPSG:3577 CRS:84 142.841939844437 147.9681839177344 -31.992542877195405 -29.001546790334466 text/html gw_grids:UD_ScaledGreenWet_pc10_1987_2022 The Tasselled Cap greenness and wetness 10th percentiles were extracted from Digital Earth Australia to help identify and characterise groundwater dependent ecosystems (GDE) in the Upper Darling region of NSW. The Tasselled Cap greenness and wetness 10th percentiles represent the lowest 10% of values and is considered to represent the least green/driest period for the timeframe between 1987 and 2022. These datasets were scaled and then added together, with the higher values correlating to areas of above average greenness and wetness, indicating potential GDEs. EFTF Upper Darling Remote Sensing Landsat Tasselled Cap Groundwater Dependent Ecosystem GDE Upper Darling Floodplain New South Wales NSW Groundwater EPSG:3577 CRS:84 142.841939844437 147.9681839177344 -31.992542877195405 -29.001546790334466 text/html