Mapping wetland hydrological dynamics using Google Earth Engine (GEE)
Mapping surface water and wetland hydrological dynamics using Google Earth Engine
Open Virginia GIS is a repository of gis data mapping the Commonwealth of Virginia, its localities, features, demographics, etc. Census data, state data, and locality data included....eventually standalone will automagic all of this
PYthon Models for AgeNt-based resource GAthering (pyMANGA): Describing vegetation population dynamics based on first principles
Here are the codes for the "3DUNetGSFormer: A deep learning pipeline for complex wetland mapping using generative adversarial networks and Swin transformer" paper.
An ArcGIS toolbox for wetland hydrology
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.
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…
Wetland change detection using Landsat time-series imagery
Supplemental files accompanying McTigue, N.D., Q.A. Walker, & C.A. Currin (2021) "Refining estimates of greenhouse gas emissions from salt marsh “blue carbon” erosion and decomposition."
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.
Bilingual conservation education website on Spoon-billed Sandpiper habitat, Yellow Sea migration ecology, and coastal development. DKU Environment101 group project.
A tutorial introducing the TOPMODEL-based wetland and peatland model DYPTOP.
Benchmarking Sentinel-1 SAR feature groups (intensity, indices, textures) for floodplain woody vegetation classification, including preprocessing, modeling, evaluation, and SHAP interpretability workflows.
Global typologies of coastal wetland status to inform conservation and management.
Downscale dynamic coarse-resolution groundwater depth simulations and observations to predict fine-resolution stream and wetland dynamics
Pipeline for analysing audio files for bird identification using BirdNET
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