Top 3 most popular datasets released in the last 6 months

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News & Information
Topic: 
Announcement

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We are continually adding new datasets and other resources to SEED, with 18 added in the last 6 months of 2024.  Of these new resources, the top three most popular were:The Earth Observation Water Toolkit, built on Google Earth Engine (GEE), features a set of Python scripts…
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We are continually adding new datasets and other resources to SEED, with 18 added in the last 6 months of 2024.  Of these new resources, the top three most popular were:

  1. The Earth Observation Water Toolkit, built on Google Earth Engine (GEE), features a set of Python scripts that enable users to extract time-series data of water surface areas from Landsat and Sentinel-2 imagery. This tool automates the extraction of water surface area for input waterbody polygons and comes with comprehensive documentation for setting up and running the process.

     

  2. High Ecological Value Aquatic Ecosystem (HEVAE) Instream Value of Freshwater Rivers in NSW dataset. This dataset is a significant resource for anyone interested in water management, ecology, or conservation, providing detailed insights into the instream values of river reaches across NSW.

     

  3. The NSW Joint Private Works Schemes. This first-of-its-kind dataset provides comprehensive resources and mapped boundaries for the management of Private Water Trusts and Private Water Corporations in New South Wales.

Join the conversation and let us know where you have used our data!

 

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Last Reply 1 year ago

J

Jane

Keywords

ecology
modelling
surface water
water utilities
spatial data

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Overview

The link points to a GitHub repository. This code repository presents an efficient Google Earth Engine (GEE)-based algorithm to mapping water surface area time-series in waterbodies from Landsat and Sentinel-2. Detailed documentation is contained to run the tool on a set of input waterbodies. The GitHub repository contains a set of Python scripts to automatically extract time-series of water surface area for a set of input polygons. _NB: Google Earth Engine project is needed to run this toolkit._ Image: Example Interactive Map ![example_interactive_map_resized]( https://github.com/u...
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The link points to a GitHub repository. This code repository presents an efficient Google Earth Engine (GEE)-based algorithm to mapping water surface area time-series in waterbodies from Landsat and Sentinel-2. Detailed documentation is contained to run the tool on a set of input waterbodies. The GitHub repository contains a set of Python scripts to automatically extract time-series of water surface area for a set of input polygons. _NB: Google Earth Engine project is needed to run this toolkit._ Image: Example Interactive Map ![example_interactive_map_resized]( https://github.com/user-attachments/assets/4485b25d-35d2-4af1-8de0-89e40a08f1e6)
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Open linked dataset

Dataset Resources

Download

Data Quality Statement

Data quality statement for Earth Observation-Water Toolkit

Download PDF file, View dataset on SEED
GitHub Repository link to Earth Observation Water Toolkit

GitHub Repository link to Earth Observation Water Toolkit

Download URL file, View dataset on SEED
Metadata Statement - Questionnaire.pdf

Metadata Statement associated with the Earth Observation Water Toolkit.pdf

Download PDF file, 457876 mb View dataset on SEED