There are 0 repository under wetlands topic.
Mapping wetland hydrological dynamics using Google Earth Engine (GEE)
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
Here are the codes for the "3DUNetGSFormer: A deep learning pipeline for complex wetland mapping using generative adversarial networks and Swin transformer" paper.
PYthon Models for AgeNt-based resource GAthering (pyMANGA): Describing vegetation population dynamics based on first principles
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.
Supporting code for the paper 'Connections Matter: National Classification Links Wetlands with Stream Water Quality'
The repo contains the data for the Grailville Wetlands Project
Wetland change detection using Landsat time-series imagery
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 caused by beavers in Massachusetts, USA. The objective of this kit is to have an algorithm with conditional statements to determine for a given year if flooding, based on spectral signatures, caused by beavers has occurred. This is then filtered for a wetland layer and then inlaid with citizen science data of beaver observations from GBIF. The correlation of having flooding, along with reported beaver observations acts as a validation for the tool. B-FED is divided into three scripts: preprocessing, analysis, and visualization.
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.
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."
Datasets of the monthly waterbird counts at Sabaki and Mida.
Global typologies of coastal wetland status to inform conservation and management.
Visualization project to show the potential of wetlands to mitigate climate change based on multiple open data sources
sensitivity analysis of the tool used to assess the surface area impacted by agricultural drainage for the protection of wetlands.
The scripts used for the Honours Thesis project of Angus Kennedy, 2024.
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
Code, data and manuscript for "Fernández-Pascual, E. & Correia-Álvarez., E. (2021). Mire microclimate: groundwater buffers temperature in waterlogged versus dry soils. International Journal of Climatology." https://doi.org/10.1002/joc.6893
Wetland modeling using clustering techniques.
PYthon Models for AgeNt-based resource GAthering (pyMANGA): Describing vegetation population dynamics based on first principles
Trait database of aquatic invertebrate traits assigned at the genus level for taxa found in floodplain wetlands of the Wolastoq | Saint John River, New Brunswick, Canada
Data and code used for the paper titled, "Heterogenous runoff trends in peatland-dominated basins throughout the circumpolar North."
This assignment focuses on mapping the wetlands of the Ohio region in the USA using machine learning (ML) techniques. By integrating active, passive satellite images and ML algorithms, the goal was to delineate wetlands.
This app "Greek Wetland Kerkini Tour" has real informations and images. It is a guide to travel at lake Kerkini. Project "Tour Guide app"created with Android Studio when learning on udacity.com with EU scholarship by Google on "Android Basic Nanodegree Programme" course.
Metadata for NWI analysis of nearest NHD feature