Printed from the TERN Data Discovery portalhttp://portal.tern.org.au/green-accumulation-index-nsw/22015
155.214844,-28.046126 155.214844,-37.764924 140.537109,-37.764924 140.537109,-28.046126 155.214844,-28.04612622015
The Landsat-derived fractional cover layer gives the amount of bare ground, green vegetation, and dead vegetation for each pixel on a specific date. The landscape of NSW undergoes a large variation in greenness throughout the seasonal and drought cycles. Information about the variation in greenness can be useful for a variety of mapping and planning tasks. Areas of green vegetation are important for native species habitat and human recreation activities. Green areas in the landscape are often related to the availability of near surface water or recent inundation, such as bogs, swamps and mires. These green areas are important for native plants and animals as locations of food and water in dry times. The green fraction has been analysed for a sequence of images to show how long an area stays green following a greening event, such as grass growth in response to rainfall. The map of green accumulation for NSW was created from Landsat images from 1988 to 2012. Areas exhibiting the highest values are the areas of NSW that respond with high green cover for a long period after a greening event.
This work was funded by Local Land Services and completed by the Joint Remote Sensing Research Program and the NSW Office of Environment and Heritage. Thank you to the United States Geological Survey provided access to Landsat data.
The maps are intended for rural landscapes in areas with low woody vegetation cover and are suited to many applications including: - property planning - vegetation maps - local government planning - risk assessment - native vegetation mapping - habitat identification and mapping
From 1988-01-01 To 2012-01-01
How to cite this collection:
Office of Environment and Heritage (2011-2019), New South Wales (2015): Green Accumulation Index - NSW. Version 1.0.0. Terrestrial Ecosystem Research Network (TERN). Dataset. https://doi.org/10.25901/xhz0-m787
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