Remote Sensing Data Analysis in R 🛰
[RSE 2022] Cross-sensor domain adaptation for high-spatial resolution urban land-cover mapping: from airborne to spaceborne imagery
An implementation of Deeplabv3plus in TensorFlow2 for semantic land cover segmentation
R package to support Remote Sensing oriented field work
Land Cover Prediction from Satellite Imagery Using Machine Learning Techniques
Submeter Datasets (HiCity-LC) and Land-Cover Maps (HiCity-Map) by MCAE
32 satellite imagery maps of Sri Lanka from 2017-2024, ranging from normal RGB, to high contrast versions, to gridded land cover / land use mapped by our in-house machine learning models.
Ressource pédagogique : Télédétection spatiale sur logiciel libre
R package to support land cover classification and water management in the Central Asia Basin (SAB)
Compendium for "A Scalable Clustering-Based Method for Vegetation Mapping in Large Areas Using Satellite Image Time Series" — SOM + HCA/DTW clustering pipeline for SITS, applied to secondary-vegetation classification in TerraClass Cerrado 2024.
Detecting and visualizing land cover change using ArcGIS Pro in the Brazil state Rondonia between year 2020 and 1992.
Harmonize classification raster files using Latent Dirichlet Allocation
Automating Land Use and Land Cover Mapping Using Computer Vision and Satellite Imagery, Cameroon
Forest monitoring, reporting, and verification (MRV) materials
Leveraging U-Net and Selective Feature Extraction for Land Cover Classification Using Remote Sensing Imagery [Scientific Reports, 2025]
Geospatial AI for deforestation detection and LULC mapping using Prithvi-EO v2 foundation models on Sentinel-2 satellite imagery from Lahore & Gujranwala, Pakistan. Includes LoRA fine-tuning, zero-shot inference, and change detection.
This project screens New York State for utility-scale solar and wind siting on a statewide ~10 km grid. It combines 2018–2025 hourly weather, land cover, transmission access, developability filters, machine-learning resource models, seasonal hybrid suitability, and risk into a composite score that ranks sites for clean-energy investment.
A land use and land cover map of New York City using QGIS.
Fork of MortenTabaka/Semantic-segmentation-of-LandCover.ai-dataset. An implementation of Deeplabv3plus in TensorFlow2 for semantic land cover segmentation
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