carsCARS is a dedicated and open source 3D tool to produce Digital Surface Models from satellite imaging by photogrammetry.
Stars: ✭ 147 (+539.13%)
satproc🛰️ Python library and CLI tools for processing geospatial imagery for ML
Stars: ✭ 27 (+17.39%)
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trends.earthtrends.earth - measure land change
Stars: ✭ 69 (+200%)
ee extraA ninja python package that unifies the Google Earth Engine ecosystem.
Stars: ✭ 42 (+82.61%)
LoveDA[NeurIPS2021 Poster] LoveDA: A Remote Sensing Land-Cover Dataset for Domain Adaptive Semantic Segmentation
Stars: ✭ 111 (+382.61%)
pylandtempAlgorithms for computing global land surface temperature and emissivity from NASA's Landsat satellite images with Python.
Stars: ✭ 110 (+378.26%)
dfc2020 baselineSimple Baseline for the IEEE GRSS Data Fusion Contest 2020
Stars: ✭ 44 (+91.3%)
DSMSCN[MultiTemp 2019] Official Tensorflow implementation for Change Detection in Multi-temporal VHR Images Based on Deep Siamese Multi-scale Convolutional Neural Networks.
Stars: ✭ 63 (+173.91%)
sarbianWe’ve built a plug’n play Operation System (based on Debian Linux) with all the freely and openly available SAR processing software. No knowledge of installation steps needed, just download and get started with SAR data processing. SARbian is free for use in research, education or operational work.
Stars: ✭ 49 (+113.04%)
Intro-RIntro to R training material delivered in a 2 day format
Stars: ✭ 33 (+43.48%)
FormaleSystemeUnterlagen zur Vorlesung "Formale Systeme", Fakultät Informatik, TU Dresden
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speckle2voidSpeckle2Void: Deep Self-Supervised SAR Despeckling with Blind-Spot Convolutional Neural Networks
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massive-change-detectionQGIS 2 plugin for applying change detection algorithms on high resolution satellite imagery
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whiteboxguiAn interactive GUI for WhiteboxTools in a Jupyter-based environment
Stars: ✭ 94 (+308.7%)
Start majaTo process a Sentinel-2 time series with MAJA cloud detection and atmospheric correction processor
Stars: ✭ 47 (+104.35%)
HSI-Traditional-to-Deep-ModelsPytorch and Keras Implementations of Hyperspectral Image Classification -- Traditional to Deep Models: A Survey for Future Prospects.
Stars: ✭ 72 (+213.04%)
badsDemo codes, tutorials, and exercises for the master lecture Business Analytics and Data Science offered by the Chair of Information Systems at the Humboldt-University of Berlin
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deepsumDeepSUM: Deep neural network for Super-resolution of Unregistered Multitemporal images (ESA PROBA-V challenge)
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SAR2SARSAR2SAR: a self-supervised despeckling algorithm for SAR images - Notebook implementation usable on Google Colaboratory
Stars: ✭ 23 (+0%)
deeprivera deep-learning-based river centerline extraction model
Stars: ✭ 25 (+8.7%)
workshop-materialsPresented hardware reverse engineering workshops since 2019
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deepwatermapa deep model that segments water on multispectral images
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rsMoveRemote Sensing for Movement Ecology
Stars: ✭ 25 (+8.7%)
advanced-pandasPandas is a powerful tool for data exploration and analysis (including timeseries).
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TheoLogVorlesungsunterlagen "Theoretische Informatik und Logik", Fakultät Informatik, TU Dresden
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ChangeOSChangeOS: Building damage assessment via Deep Object-based Semantic Change Detection - (RSE 2021)
Stars: ✭ 33 (+43.48%)
Intermediate-RIntermediate R training material delivered in a 2 day format
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pylandsatSearch, download, and preprocess Landsat imagery 🛰️
Stars: ✭ 49 (+113.04%)
spectralAwesome Spectral Indices for the Google Earth Engine JavaScript API (Code Editor).
Stars: ✭ 68 (+195.65%)
course-materialsStudy material (slides, documents, etc) for the Web Applications I course (Politecnico di Torino, 2019/2020)
Stars: ✭ 23 (+0%)
ExtendedMorphologicalProfilesRemote sensed hyperspectral image classification with Spectral-Spatial information provided by the Extended Morphological Profiles
Stars: ✭ 32 (+39.13%)
gskyDistributed Scalable Geospatial Data Server
Stars: ✭ 23 (+0%)
pytorch-psetaePyTorch implementation of the model presented in "Satellite Image Time Series Classification with Pixel-Set Encoders and Temporal Self-Attention"
Stars: ✭ 117 (+408.7%)
awesome-spectral-indicesA ready-to-use curated list of Spectral Indices for Remote Sensing applications.
Stars: ✭ 357 (+1452.17%)
biodivMapRbiodivMapR: an R package for α- and β-diversity mapping using remotely-sensed images
Stars: ✭ 18 (-21.74%)
eodagEarth Observation Data Access Gateway
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ChangeDetectionRepositoryThis repository contains some python code of some traditional change detection methods or provides their original websites, such as SFA, MAD, and some deep learning-based change detection methods, such as SiamCRNN, DSFA, and some FCN-based methods.
Stars: ✭ 311 (+1252.17%)
earthengine-py-examplesA collection of 300+ examples for using Earth Engine and the geemap Python package
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piradarRadar using Red Pitaya for RF: using Raspberry Pi 3 for quad-core radar signal processing
Stars: ✭ 59 (+156.52%)
GGHLThis is the implementation of GGHL (A General Gaussian Heatmap Label Assignment for Arbitrary-Oriented Object Detection)
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MHCLNDeep Metric and Hash Code Learning Network for Content Based Retrieval of Remote Sensing Images
Stars: ✭ 30 (+30.43%)
spyndexAwesome Spectral Indices in Python.
Stars: ✭ 56 (+143.48%)
Python-for-Remote-Sensingpython codes for remote sensing applications will be uploaded here. I will try to teach everything I learn during my projects in here.
Stars: ✭ 20 (-13.04%)
CRC4DockerPython scripts for the textbook "Image Analysis, Classification and Change Detection in Remote Sensing, Fourth Revised Edition"
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RivWidthCloudPaperA Google Earth Engine based algorithm that extracts river centerlines and widths from satellite images
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moveVisAn R package providing tools to visualize movement data (e.g. from GPS tracking) and temporal changes of environmental data (e.g. from remote sensing) by creating video animations.
Stars: ✭ 104 (+352.17%)
modapeMODIS Assimilation and Processing Engine
Stars: ✭ 19 (-17.39%)
dea-coastlinesExtracting tidally-constrained annual shorelines and robust rates of coastal change from freely available Earth observation data at continental scale
Stars: ✭ 24 (+4.35%)
forestoolsTools for detecting deforestation and forest degradation
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