earth-observations
There are 1 repository under earth-observations topic.
radiantearth / crop-type-detection-ICLR-2020
Winning Solutions from Crop Type Detection Competition at CV4A workshop, ICLR 2020
Language:Jupyter Notebook 66- Language:TSQL 58
earthobservations / phenodata
An acquisition and processing toolkit for open access phenology data.
Language:Python 24KMarkert / rastersmith
RasterSmith is a package to preprocess different NASA Earth observing satellite data products into common resolution, spatial reference, and format for easy analysis and processing across sensors.
Language:Python 12hiveeyes / saraswati
Saraswati is a robust, multi-channel audio recording, transmission and storage system
Language:Python 10- Language:Python 5
anniebritton / NASA-Extreme-Weather-Geohealth-Research
☂️🛰️ This work is for a NASA-funded project using Earth observations to improve methods available for estimating the health damages of extreme weather events in Texas.
Language:R 4nansencenter / py-thesaurus-interface
An interface to metadata conventions for geospatial data
Language:Python 2emanuelespiritowork / gee-standalone-projects
Projects of remote sensing with Google Earth Engine scripts
Language:JavaScript 0Scripts of useful functions in Google Earth Engine for remote sensing geospatial data analysis
Language:JavaScript 0maawoo / S1GRASS-Webapp
Flask application to create an overview of SAR datasets & to visualize time series data of individual pixels
Language:Python 0javedali99 / geospatial-and-earth-science-data
A comprehensive collection of global earth science and geospatial datasets 🌍
jdilger / SAVeTrEE
SAVeTrEE is a script within Google Earth Engine for classifying areas of vegetation mortality. It prompts the user for a year, duration, and spectral index for which a mortality map should be produced, then fits a trend line to an imagery time sequence of vegetative spectral index values calculated from Landsat multispectral data. The slope of the trend line, as well as the spectral index values, are used in determining the final classification of each pixel within the study area. Classification categories are: 1) Growing 2) Mortality (declining) 3) Stable Vegetation and 4) Stable Barren.
