Winning Solutions from Crop Type Detection Competition at CV4A workshop, ICLR 2020
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Updated
May 29, 2020 - Jupyter Notebook
Winning Solutions from Crop Type Detection Competition at CV4A workshop, ICLR 2020
An information model for spatially-discrete, feature-based earth observations.
An acquisition and processing toolkit for open access phenology data.
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.
Saraswati is a robust, multi-channel audio recording, transmission and storage system
☂️🛰️ 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.
Flask application to create an overview of SAR datasets & to visualize time series data of individual pixels
A comprehensive collection of global earth science and geospatial datasets 🌍
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 t…
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