ArcGIS Python Toolbox for Search & Download of Sentinel-2 data (L1C/TOA, L2A/BOA) via DHuS (Copernicus Open Access Hub a.k.a. SciHub, or CODE-DE).
-
Updated
Aug 17, 2018 - Python
ArcGIS Python Toolbox for Search & Download of Sentinel-2 data (L1C/TOA, L2A/BOA) via DHuS (Copernicus Open Access Hub a.k.a. SciHub, or CODE-DE).
Flood mapping and damage assessment in GEE
Using various indices such as NDVI, CCCI, and NDWI to identify waterways in satellite images
This repo contains implementations of water classification methods to detect small proglacial streams in High Mountain Asia (HMA) using high-resolution PlanetScope imagery.
Geospatial analysis on Google's infrastructure, Google Earth Engine.
Tools for extracting and preparing Digital Earth Australia Satellite Multi-Spectral Images for use in Deep Learning Machine models.
NDWI index was applied for the Landsat 8 images around the İznik Lake.
This repo includes the a detailed comparison of different vegetation indices (like NDVI, EVI, SAVI, NDWI) between landsat 8 and new landsat 9 satellite.
A novel Lansat 8 processing tool for automated NDWI analysis.
The script calculates 3 indices for WorldView2 data. The NDVI, the NDWI and the Built-Up Index.
TapiRiver-Analysis-GEE: Analyzing Tapi River's water quality, turbidity, and width variations using satellite imagery and Google Earth Engine (GEE) to support sustainable water management and urban planning. 🚀🌊
R/terra scripts computing multispectral vegetation and water indices (NDVI, GNDVI, IPVI, NDWI, OSAVI) from Landsat 8 OLI/TIRS surface reflectance over the Khartoum region of Sudan for 2013/2018/2022, plus a GMT study-area map. Lemenkova & Debeir (2023), J. Imaging 9(5):98.
Graphical tool for merging Landsat bands
IndexRidge Sentinel-derived GeoTIFF workflow samples — free mini sample, bundles, and QGIS/rasterio downloads
Multi-sensor Landsat pipeline in Google Earth Engine + Python: Otsu surface-water delineation, landscape-fragmentation metrics, and Mann-Kendall/Sen's-slope trend analysis
Flood-water detection from Sentinel-2 imagery using NDWI thresholding and Random Forest classification in Google Earth Engine, with a case study of Swat, Pakistan.
My works at PRESIDENTAL DIGITAL TRANSFORMATION OFFICE
To associate your repository with the ndwi topic, visit your repo's landing page and select "manage topics."