From Terrestrial Ecosystem Research Network
JSON RDF ISO19115-3 XML

Water Count Time Series - Landsat, DES Algorithm, Queensland

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Created 20/10/2024

Updated 21/01/2025

JSON RDF ISO19115-3 XML

This dataset indicates the presence and persistence of water across Queensland between 1988 and 2022. Water is one of the world’s most important resources as it’s critical for human consumption, agriculture, the persistence of flora and fauna species and other ecosystem services. Information about the spatial distribution and prevalence of water is necessary for a range of business, modelling, monitoring, risk assessment, and conservation activities. The water count product is based on water index and water masks for Queensland (Danaher & Collett 2006) and represents the proportion of observations with water present across the Landsat time series as a fraction of total number of possible observations for the period 1 Jan 1988 to 31 Dec 2022. The product has two bands where band 1 is the number of times water was present across the time series, and band 2 is the count of unobscured (i.e. non-null) input pixels, or number of total observations for that pixel. Cloud, cloud-shadow, steep slopes and topographic shadow can obscure the ability to count water presence.

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Title Water Count Time Series - Landsat, DES Algorithm, Queensland
Language eng
Licence notspecified
Landing Page https://devweb.dga.links.com.au/data/dataset/cad68351-8639-4999-b8ea-50985cc89095
Contact Point
Environment Protection Authority (EPA) Victoria
lisa.collett@des.qld.gov.au
Reference Period 01/01/1988
Geospatial Coverage {"type": "Polygon", "coordinates": [[[138.0, -29.2], [154.0, -29.2], [154.0, -9.5], [138.0, -9.5], [138.0, -29.2]]]}
Data Portal data.gov.au

Data Source

This dataset was originally found on data.gov.au "Water Count Time Series - Landsat, DES Algorithm, Queensland". Please visit the source to access the original metadata of the dataset:
https://devweb.dga.links.com.au/data/dataset/water-count-time-series-landsat-des-algorithm-queensland

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No duplicate datasets found.