The CCD-Plugin uses Google Earth Engine to get Landsat or Sentinel2 datasets and run the Continuous Change Detection (CCDC) algorithm to analyze the trends and breakpoints of change over multi-year time series at a given coordinate.
Earth Observation Data Access Gateway
Remote-sensing opensource python library reading optical and SAR sensors, loading and stacking bands, clouds, DEM and spectral indices in a sensor-agnostic way.
This is a Science and Technology Society (STS) of Sarasota-Manatee Counties that shows the data from a series of NASA STELLA-Q2 Spectrometer readings on a number of vegetative species with calculations of NDVI to differentiate species using Decision Tree logic and Knn from the mean end member data.
A Python package for interactive geospatial analysis and visualization with Google Earth Engine.
The Science and Technology Society of Sarasota-Manatee Counties use Landsat data to calculate Normalized Difference Vegetative Index (NDVI) from Landsat NIR and Red Bands and Panchromatic Normalized Difference Vegetative Index (PNDVI) from Panchromatic and NIR Bands to assess the health of Mangrove Forests in Sarasota Bay
We have created a few Jupyter Notebooks to use NASA PACE data featuring GeoSpatial's HyperCoast software used to download, view and process the PACE data.
GRASS GIS Addon to remove clouds (e.g. Sentinel-2, Landsat), aiming at filling raster gaps using r.series and r.series.lwr and aggregates temporally the maps of a space time raster dataset by a user defined granularity using t.rast.aggregate
Awesome Spectral Indices for the Google Earth Engine JavaScript API (Code Editor).
A ninja python package that unifies the Google Earth Engine ecosystem.
A list of all the scale and offset parameters for each raster dataset in Google Earth Engine.
A collection of Imagery Explorer web applications developed by Esri's ArcGIS Living Atlas team
Atmospheric correction processor for high spatial resolution multispectral satellite images
An interactive toolbox for downloading satellite imagery, applying image segmentation models, mapping shoreline positions and more. The mapping extension for CoastSat and Zoo.
Pipeline for remotely sensed imagery. The pipeline processes satellite imagery alongside auxiliary data in multiple steps to arrive at a set of trend files related to land-cover changes.
Repository for Digital Earth Australia Jupyter Notebooks: tools and workflows for geospatial analysis with Open Data Cube and Xarray
Satellite image time series in R
Field-scale groundwater pumping estimation using OpenET
Awesome Spectral Indices in Julia
A ready-to-use curated list of Spectral Indices for Remote Sensing applications.
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