The scripts used for the Honours Thesis project of Angus Kennedy, 2024.
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Updated
Aug 7, 2024 - R
The scripts used for the Honours Thesis project of Angus Kennedy, 2024.
PYthon Models for AgeNt-based resource GAthering (pyMANGA): Describing vegetation population dynamics based on first principles
The PEOPLE-ER Wetland and Wetness Trends tool provides a flexible, powerful set of EO data analytics tools to support wetland ER assessment. The tool provides methods for high-resolution satellite EO data time series analysis to enable monitoring of surface water dynamics and wetness trends in natural to heavily modified wetland ecosystems.
Datasets of the monthly waterbird counts at Sabaki and Mida.
sensitivity analysis of the tool used to assess the surface area impacted by agricultural drainage for the protection of wetlands.
Mapping surface water and wetland hydrological dynamics using Google Earth Engine
Visualization project to show the potential of wetlands to mitigate climate change based on multiple open data sources
Wetland change detection using Landsat time-series imagery
This repository contains the code associated with the Journal of American Water Resources Association article Depressional Runoff Cascades of the Des Moines Lobe of Iowa (Green and Crumpton, 2023). DOI: 10.1111/1752-1688.13103
Here are the codes for the "3DUNetGSFormer: A deep learning pipeline for complex wetland mapping using generative adversarial networks and Swin transformer" paper.
Repository for analysis of classified drone imagery from Kooragang wetlands
Wetland modeling using clustering techniques.
The Beaver-Flood Event Detector (B-FED) is a Google Earth Engine script created by the Spring 2020 MA Massachusetts Water Resources team. It uses NASA Earth Observations, a MassGIS wetland polygon layer, citizen science Global Biodiversity Information Facility (GBIF) Data and remote sensing methodology to detect flooding events that are likely c…
The Wetland Extent Tool (WET) was developed by the 2019 Spring JPL Great Lakes Water Resources team for wetland mapping in Minnesota using Sentinel-1 C-SAR, Landsat 8 OLI, and a LiDAR-derived Topographic Wetness Index (TWI) in Google Earth Engine.
Global typologies of coastal wetland status to inform conservation and management.
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