huangjingyuan7's Stars
yformer/EfficientSAM
EfficientSAM: Leveraged Masked Image Pretraining for Efficient Segment Anything
seanyx/RivWidthCloudPaper
A Google Earth Engine based algorithm that extracts river centerlines and widths from satellite images
sentinel-hub/water-observatory-backend
Monitoring water levels of lakes and reservoirs using satellite imagery
ICESAT-2HackWeek/ICESat2_hackweek_tutorials
Combined repository for final tutorial material from 2019 ICESat-2 HackWeek at the Univeristy of Washington
Agri-Hub/Deep-Learning-for-Cloud-Gap-Filling-on-Normalized-Difference-Vegetation-Index
A CNN-RNN based model that identifies correlations between optical and SAR data and exports dense Normalized Difference Vegetation Index (NDVI) time-series of a static 6-day time resolution and can be used for Events Detection tasks
myeungun/SAR-water-segmentation
Jowekk/SAR-Image-Recognition
This is a CNN for Polarimetric SAR Image Classification
ThomasWangWeiHong/Water-Body-Extraction-from-Very-High-Spatial-Resolution-Remote-Sensing-Data-Based-on-FCNs
Python implementation of Convolutional Neural Network (CNN) proposed in academia
vhertel/radar-based-flood-mapping
This repository contains a Jupyter Notebook for automatic flood extent mapping using space-based information.
MWieland/s1s2_water
S1S2-Water: A global dataset for semantic segmentation of water bodies from Sentinel-1 and Sentinel-2 satellite images
CNES/ALCD
The Active Learning for Cloud Detection (ALCD) software enables to generate reference cloud masks which may be used to validate operational cloud masks, such as those generated by MAJA. The reference cloud masks are generated interactively using an iterative active learning procedure which enables to generate an accurate reference cloud mask in less than two hours. ALCD works on linux systems and relyes on the OTB library. It also requires a GIS software such as QGIS. The tool was written by Louis Baetens during a training period at CESBIO, funded by CNES, under supervision of Olivier Hagolle.
GieziJo/cvpr23-earthvision-CNN-LSTM-Inundation
dagdelenvolkan/Extraction-Water-Areas-from-Sentinel-2A
A Python library for extraction water areas as shapefile extension from Sentinel 2A Satellite Images.
JoshuaBillson/Waterbody-Detection-Via-Deep-Learning
Source code for the paper, "Water Body Extraction from Sentinel-2 Imagery with Deep Convolutional Networks and Pixelwise Category Transplantation".
Oussamaaat/sentinel-down-clip
sentinel-down-clip is a Jupyter Notebook that simplifies the process of querying, downloading, clipping and processing Sentinel satellite data. With its intuitive interface and comprehensive functionalities, it enables easy access to Sentinel data for various applications, including machine learning and deep learning.
dr-lizhiwei/SeamlessFloodMapper
Seamless Flood Mapping Using Harmonized Landsat and Sentinel-2 Data
nbiswasuw/rat-reservoir_assessment_tool
This repository is dedicated to use for the Reservoir Assessment Tool (RAT)- Global monitoring and assessment of reservoirs
sv2441/Water-body-segmentation-in-Satellite-Images
hyunholee26/Short-term-water-level-prediction-in-the-river-using-LSTM-with-MC-dropout
short term river level prediction using LSTM with MC dropout
MinhVu25/Surface_Water_Dynamics_2023
This script aims to determine the most suitable threshold for surface water extraction from Sentinel-1 image and provide a fully automatic processing chain for detecting, monitoring surface water and mapping water dynamics.
twrighta/Dissertation
Physical Geography Undergraduate Dissertation 2023 - University of Leeds. Using Multivariate Multistep LSTMs to generate river discharge forecasts on the River Aire, Leeds, UK.
xinluo2018/radar-altimetry-tool
Toolbox for sentinel-3 altimetry level2 product processing.
eduardosteps/sentinelsat_imagery_download
Este projeto foi desenvolvido por Eduardo Passos, com o objetivo de realizar o download em lote (batch) de imagens do satélite Sentinel 2, da Agência Espacial Europeia (ESA), utilizando a biblioteca Sentinelsat.
ericslevenson/arctic-surface-water
Code in support of satellite remote sensing of daily to inter-annual surface water variability across the Arctic.
rbdxyxk/hhu_flood
Shilianghe Reservoir Flood Forecasting System.
santosh-dhungana/RankingofGRPS
Ranking of Gridded Precipitation Products against observed station rainfall data using mean rainfall and 5 extreme indices by employing Entropy-Compromise Programming and categorical indices.
MelissaSchwab/Simplistic-water-body-masking-with-dynamic-Otsu-thresholding
SanchitMinocha/Experimental-Multi-sensor-Reservoir-Area-Estimation
This project aims at estimating water area of a reservoir in Texas, US using landsat-8, sentinel-1 and sentinel-2 scenes. The scripts are written in python and use Google Earth Engine (GEE) for processing.
beingdeepshah/MODIS_VIIRS_GWR_Codes
The code to extract data for VIIRS C2 and C3 products with the sample data are attached here.
freakinaman/WaterBody-detection-using-satellite-images
This repository contains code for detecting water bodies in images using machine learning. Images are preprocessed and features are extracted using Local Binary Patterns (LBP). A Random Forest Classifier is trained on the features to classify images as water or non-water. The trained model is used to detect water in example images.