CLI pipeline for Planet, Satellogic, Digital Globe & Google Earth Engine Imagery
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Updated
Nov 30, 2018 - Python
CLI pipeline for Planet, Satellogic, Digital Globe & Google Earth Engine Imagery
Python package to estimate Land Surface Temperatures from Google Earth Engine's Landsat imagery
Helper library to work with the Google Earth Engine Python API.
the workflow of google earth engine city extraction written in python with arcpy
Terrarium is a Python Package for geospatial manipulation and raster/vector generation for the GeoSentry 🌍 Platform powered by Google Earth Engine and Google Maps Platform.
Antalya/Cleopatra Beach Shoreline Change Detection with CoastSat (2013–2022)
Django (Python) backend for the Angular Satellite Analysis application
Simple app to calculate NDVI from Sentinel-2 satellite imagery using Google Earth Engine API.
JSON API to compute mismatch of pressure timeseries with ERA-5 on Google Earth Engine.
This repository contains the Python codes used in the short paper "Sensitivity of Land Surface Temperature to Emissivity Retrieved from Landsat 8 Data", submitted to the XXIV Brazilian Symposium on GeoInformatics.
Generate elevation plots using open-elevation API and Google Earth
This package assists with downloading Landsat and other satellite imagery data from google earth engine.
Remote Sensing data - Earth observation data
An account manager for the Earth Engine Python API
Mobile and native notifications for Earth Engine tasks
Simple Python script that generates (from a csv file containing lat and long coordinates) a txt file with each row corresponding to the definition in Javascript of a ee.Geometry.Point. Each ee.Geometry.Point can then be imported and visualized in the Code Editor of Google Earth Engine, instead of writing all of them manually
📦🐍 geefcc Python package to get forest cover change data from Google Earth Engine
Mapping vegetation communities in the Arctic-boreal wetlands of the Peace-Athabasca Delta using AVIRIS-NG hyperspectral data
Serverless Microservices for the GeoCore API, used internally for the core geospatial functionalities of the GeoSentry 🌍 Platform facilitated by the Terrarium package. The Services are built with Docker, stored on Artifact Registry, deployed on Cloud Run and discoverable with Service Directory.
Classify the vegetation coverage of Cocientas basin in La Guajira (Colombia) with a Random Forest model to get the total vegetation coverage and try to predict futer changes.
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