{"payload":{"pageCount":134,"repositories":[{"type":"Public","name":"s2p","owner":"GRSEB9S","isFork":true,"description":"Satellite Stereo Pipeline","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":65,"license":"GNU Affero General Public License v3.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2021-10-18T15:04:46.331Z"}},{"type":"Public","name":"raster-functions","owner":"GRSEB9S","isFork":true,"description":"A curated set of lightweight but powerful tools for on-the-fly image processing and raster analysis in ArcGIS.","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":81,"license":"Apache License 2.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2021-06-20T02:42:35.502Z"}},{"type":"Public","name":"s2p-1","owner":"GRSEB9S","isFork":true,"description":"This repository is not maintained, please use https://github.com/centreborelli/s2p instead.","allTopics":[],"primaryLanguage":{"name":"C","color":"#555555"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":77,"license":"GNU Affero General Public License v3.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2021-06-17T19:37:44.775Z"}},{"type":"Public","name":"awesome-multimodal-remote-sensing-classification","owner":"GRSEB9S","isFork":true,"description":"List of datasets, papers, and codes related to multimodal/multisource/multisensor remote sensing classification","allTopics":[],"primaryLanguage":null,"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":12,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2021-06-14T03:56:38.015Z"}},{"type":"Public","name":"awesome-datascience","owner":"GRSEB9S","isFork":true,"description":"📝 An awesome Data Science repository to learn and apply for real world problems.","allTopics":[],"primaryLanguage":null,"pullRequestCount":0,"issueCount":0,"starsCount":1,"forksCount":5765,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2021-04-30T15:37:02.561Z"}},{"type":"Public","name":"custom-scripts","owner":"GRSEB9S","isFork":true,"description":"A repository of custom scripts to be used with Sentinel Hub","allTopics":[],"primaryLanguage":{"name":"JavaScript","color":"#f1e05a"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":293,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2021-03-26T07:42:43.258Z"}},{"type":"Public","name":"Cloud-Net-A-semantic-segmentation-CNN-for-cloud-detection","owner":"GRSEB9S","isFork":true,"description":"A semantic segmentation CNN for cloud detection","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":26,"license":"GNU General Public License v3.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2021-01-14T06:21:37.342Z"}},{"type":"Public","name":"95-Cloud-An-Extension-to-38-Cloud-Dataset","owner":"GRSEB9S","isFork":true,"description":"A huge dataset for binary segmentation of clouds in satellite images","allTopics":[],"primaryLanguage":null,"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":7,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2021-01-14T05:34:45.944Z"}},{"type":"Public","name":"classification-app-frontend","owner":"GRSEB9S","isFork":true,"description":"","allTopics":[],"primaryLanguage":{"name":"JavaScript","color":"#f1e05a"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":1,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2021-01-05T11:53:06.844Z"}},{"type":"Public","name":"cuFSDAF","owner":"GRSEB9S","isFork":true,"description":"cuFSDAF is an enhanced FSDAF algorithm parallelized using GPUs. In cuFSDAF, the TPS interpolator is replaced by a modified Inverse Distance Weighted (IDW) interpolator. Besides, computationally intensive procedures are parallelized using the Compute Unified Device Architecture (CUDA), a parallel computing framework for GPUs. Moreover, an adaptiv…","allTopics":[],"primaryLanguage":{"name":"C++","color":"#f34b7d"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":8,"license":"GNU General Public License v3.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-12-28T08:16:05.648Z"}},{"type":"Public","name":"big_data_and_urban_computing_course","owner":"GRSEB9S","isFork":true,"description":"Course materials for big data and urban computing (2020 fall semester).","allTopics":[],"primaryLanguage":null,"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":13,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-12-23T09:33:25.456Z"}},{"type":"Public","name":"Open-Space-Cellular_Automata","owner":"GRSEB9S","isFork":true,"description":" A spatio-temporal approach based on Cellular Automata (CA) for simulating the spatial dynamics of open spaces (include urban green spaces, parks, squares, trails, courtyards, and other natural spaces), by considering a set of spatial data that represents the infrastructural and socio-economic factors, namely the OS-CA (Open Space Cellular Autom…","allTopics":[],"primaryLanguage":null,"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":9,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-12-11T10:29:09.513Z"}},{"type":"Public","name":"Patch-generating_Land_Use_Simulation_Model","owner":"GRSEB9S","isFork":true,"description":"The PLUS model integrates a rule mining framework based on Land Expansion Analysis Strategy (LEAS) and a CA model based on multi-type Random Patch Seeds (CARS), which was used to understand the drivers of land expansion and project landscape dynamics.","allTopics":[],"primaryLanguage":null,"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":39,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-11-29T03:55:58.998Z"}},{"type":"Public","name":"raster-deep-learning","owner":"GRSEB9S","isFork":true,"description":"ArcGIS built-in python raster functions for deep learning to get you started fast.","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":86,"license":"Apache License 2.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-11-20T19:45:42.202Z"}},{"type":"Public","name":"elevation-gp-python","owner":"GRSEB9S","isFork":true,"description":"ArcGIS elevation analysis tool that allows you to set up an in-house viewshed geoprocessing service.","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":7,"license":"Apache License 2.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-11-18T19:43:55.384Z"}},{"type":"Public","name":"GeoCA","owner":"GRSEB9S","isFork":true,"description":"Geographical Simulation Application via Cellular Automata (GeoCA)","allTopics":[],"primaryLanguage":null,"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":9,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-11-08T16:55:10.619Z"}},{"type":"Public","name":"eo-flow","owner":"GRSEB9S","isFork":true,"description":"Collection of TensorFlow 2.0 code for Earth Observation applications","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":28,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-10-27T10:38:38.516Z"}},{"type":"Public","name":"Mixed_Cell_Cellullar_Automata","owner":"GRSEB9S","isFork":true,"description":"The Mixed-Cell Cellullar Automata (MCCA) provides a new approach to enable more dynamic mixed landuse modeling to move away from the analysis of static patterns. One of the biggest advantages of mixed-cell CA models is the capability of simulating the quantitative and continuous changes of multiple landuse components inside cells.","allTopics":[],"primaryLanguage":null,"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":12,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-10-16T09:48:01.453Z"}},{"type":"Public","name":"SuperCugersMappingSystem","owner":"GRSEB9S","isFork":true,"description":"Surveying and Mapping System for error adjustment of SUPERCUGERS team","allTopics":[],"primaryLanguage":{"name":"C++","color":"#f34b7d"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":2,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-10-16T08:28:48.783Z"}},{"type":"Public","name":"Realistic_Land_Parcel_Subdivision_APP","owner":"GRSEB9S","isFork":true,"description":"","allTopics":[],"primaryLanguage":{"name":"Batchfile","color":"#C1F12E"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":3,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-10-16T05:41:11.577Z"}},{"type":"Public","name":"cuSTSG","owner":"GRSEB9S","isFork":true,"description":"cuSTSG is a GPU-enabled spatial-temporal Savitzky-Golay (STSG) program based on the Compute Unified Device Architecture (CUDA). Firstly, the cosine similarity between time-series data of adjacent years is used to identify similar years without land cover type changes, hence to exclude the years with inaccurate quality flags from generating NDVI …","allTopics":[],"primaryLanguage":{"name":"Cuda","color":"#3A4E3A"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":5,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-09-07T12:12:43.031Z"}},{"type":"Public","name":"geemap","owner":"GRSEB9S","isFork":true,"description":"A Python package for interactive mapping with Google Earth Engine, ipyleaflet, and ipywidgets","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":1,"forksCount":1064,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-09-04T15:52:26.727Z"}},{"type":"Public","name":"earthengine-py-notebooks","owner":"GRSEB9S","isFork":true,"description":"A collection of 360+ Jupyter Python notebook examples for using Google Earth Engine with interactive mapping","allTopics":[],"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":403,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-07-21T02:12:05.804Z"}},{"type":"Public","name":"TorchCRF","owner":"GRSEB9S","isFork":true,"description":"An Inplementation of CRF (Conditional Random Fields) in PyTorch 1.0","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":11,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-07-05T05:11:49.349Z"}},{"type":"Public","name":"38-Cloud-A-Cloud-Segmentation-Dataset","owner":"GRSEB9S","isFork":true,"description":"This data set includes Landsat 8 images and their manually extracted pixel-level ground truths for cloud detection.","allTopics":[],"primaryLanguage":{"name":"MATLAB","color":"#e16737"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":37,"license":"Apache License 2.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-06-30T22:18:30.082Z"}},{"type":"Public","name":"mask-to-polygons","owner":"GRSEB9S","isFork":true,"description":"Routines for extracting and working with polygons from semantic segmentation masks","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":9,"license":"Apache License 2.0","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-06-30T02:27:00.550Z"}},{"type":"Public","name":"awesome-satellite-imagery-datasets","owner":"GRSEB9S","isFork":true,"description":"🛰️ List of satellite image training datasets with annotations for computer vision and deep learning","allTopics":[],"primaryLanguage":null,"pullRequestCount":0,"issueCount":0,"starsCount":1,"forksCount":635,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-06-18T15:29:37.297Z"}},{"type":"Public","name":"dfc2019","owner":"GRSEB9S","isFork":true,"description":"2019 IEEE GRSS Data Fusion Contest data, baselines, and metrics","allTopics":[],"primaryLanguage":{"name":"Python","color":"#3572A5"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":56,"license":"MIT License","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-06-16T11:22:55.439Z"}},{"type":"Public","name":"Py4Geo","owner":"GRSEB9S","isFork":true,"description":"Satellite Image Analytics and Earth Data Science Experiments in Python","allTopics":[],"primaryLanguage":{"name":"Jupyter Notebook","color":"#DA5B0B"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":11,"license":null,"participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-06-11T05:54:07.105Z"}},{"type":"Public","name":"ISIS3","owner":"GRSEB9S","isFork":true,"description":"Integrated Software for Imagers and Spectrometers v3. ISIS3 is a digital image processing software package to manipulate imagery collected by current and past NASA and International planetary missions.","allTopics":[],"primaryLanguage":{"name":"C++","color":"#f34b7d"},"pullRequestCount":0,"issueCount":0,"starsCount":0,"forksCount":164,"license":"Other","participation":null,"lastUpdated":{"hasBeenPushedTo":true,"timestamp":"2020-06-05T23:33:36.552Z"}}],"repositoryCount":4017,"userInfo":null,"searchable":true,"definitions":[],"typeFilters":[{"id":"all","text":"All"},{"id":"public","text":"Public"},{"id":"source","text":"Sources"},{"id":"fork","text":"Forks"},{"id":"archived","text":"Archived"},{"id":"template","text":"Templates"}],"compactMode":false},"title":"Repositories"}