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gee-codes

gee-image-fusion

gee-scripts

gee-to-npy

Extract parcel-level Sentinel-1/Sentinel-2 time series from Google Earth Engine

gee_functions

gee_subset

Google Earth Engine subset script & library

gee_timeseries

Google Earth Engine time series with Savitzky-Golay filter

geeguide

Harmonization of Landsat and Sentinel 2 in Google Earth Engine, documentation and scripts

geospatial-machine-learning

A curated list of resources focused on Machine Learning in Geospatial Data Science.

geospatial-predictive-modeling

gis-and-remote-sensing-python

This is to practise GIS and remote sensing data with Python

global-cropland-mapping

using deep semantic segmentation networks for global multi-temporal cropland mapping from remote sensing big data

google-colab-geepy_palaeolandscape

google_earth_engine_notebook

A walkthrough of some Google Earth Engine Features, as well as using the data in TensorFlow

hands-on-time-series-analylsis-python

Source Code for 'Hands-on Time Series Analysis with Python' by B V Vishwas and Ashish Patel

hsi_classification

Classification for hyperspectral imagery

hydrolstm

LSTM Data and Model for Streamflow Forecasting

hyperspectral

Deep Learning for Land-cover Classification in Hyperspectral Images.

hyperspectral_image_analysis_simplified

The repository contains the implementation of different machine learning techniques such as classification and clustering on Hyperspectral and Satellite Imagery.

igarss2019-dl4sits

Machine learning for satellite image time series

igarss2020_code

imgseg4croptypemapping

Corn and Soybean Mapping model at 30 m resolution from Landsat 8/ Sentinel 2

jarvis

Personal Voice Assistant made with Python and has a cool looking GUI (Graphical User Interface)

keras-bi-lstm-timeseries

It‘s my graduation design, which is designed to restore missing values in remote-sensing images.

label-maker

Data Preparation for Satellite Machine Learning

land-cover-classification-using-sentinel-2-dataset

Application of deep learning on Satellite Imagery of Sentinel-2 satellite that move around the earth from June, 2015. This image patches can be trained and classified using transfer learning techniques.

land-cover-ethiopia-visualization

land-use-classification-using-encoder-decoder-lstm

Biweekly mapping of land use and land cover using MODIS time series (MOD13Q1) and LSTM Neural Networks.

land-use-land-cover-classification-of-satellite-images-using-deep-learning

This work discusses how high resolution satellite images are classified into various classes like cloud, vegetation, water and miscellaneous, using feed forward neural network. Open source python libraries like GDAL and keras were used in this work. This work is generic and can be used for satellite images of any resolution, but with MX band sensors.

landcover_rcnn

Code for spatially and temporally generalizable regional land cover mapping