datasets
Training and evaluation data, with the modality, task and licence stated up front. Listed live from the Hugging Face Hub.
remote_sensing_VQA_multilingual
Remote Sensing VQA — Multilingual
A multilingual counterfactual MCQ dataset built from remote sensing / satellite imagery.
Each row contains a satellite image, two captions (original vs counterfactual), and a multiple-choice question probing whether a VLM follows the image or the misleading text.
Languages
Language
Code
Rows
English
en
50
Hindi
hi
50
Urdu
ur
50
Telugu
te
50
Bahasa Indonesia
id
50
Columns
Column
Type… See the full description on the dataset page: https://huggingface.co/datasets/apart-global-south-hack/remote_sensing_VQA_multilingual.remote-sensing-VQA-benchmark
Adapting Multimodal Large Language Models to Domains via Post-Training (EMNLP 2025)
This repos contains the remote sensing visual instruction tasks for evaluating MLLMs in our paper: On Domain-Specific Post-Training for Multimodal Large Language Models.
The main project page is: Adapt-MLLM-to-Domains
1. Download Data
You can load datasets using the datasets library:
from datasets import load_dataset
# Choose the task name from the list of available tasks
task_name… See the full description on the dataset page: https://huggingface.co/datasets/AdaptLLM/remote-sensing-VQA-benchmark.remote-sensing-VQAremote-sensing-visual-instructions
Adapting Multimodal Large Language Models to Domains via Post-Training (EMNLP 2025)
This repos contains the remote-sensing visual instructions for post-training MLLMs in our paper: On Domain-Specific Post-Training for Multimodal Large Language Models.
The main project page is: Adapt-MLLM-to-Domains
Data Information
Using our visual instruction synthesizer, we generate visual instruction tasks based on the image-caption pairs from NWPU-Captions, RSICD, RSITMD… See the full description on the dataset page: https://huggingface.co/datasets/AdaptLLM/remote-sensing-visual-instructions.RemoteSensingCorpusopenearthmap-paris
Description
This dataset is a subset of the OpenEarthMap Land Cover Mapping Data, originally available here:
https://open-earth-map.org/overview_oem.html
The original dataset was subsampled to just contain the region of paris.
The dataset is composed of RGB images and associated annotated components.
Credits
Full dataset available on Zenodo:
https://zenodo.org/records/7223446
@inproceedings{xia2023openearthmap,
title={Openearthmap: A benchmark dataset for global… See the full description on the dataset page: https://huggingface.co/datasets/remote-sensing-ense3-grenoble-inp/openearthmap-paris.modis-snow-coverage
Description
This is a set of images taken by the MODIS sensor in the year 2013.
For each folder the dataset contain:
Modimlab_date_reproj2.tif: Fused image. 7 bands at 250m
Cloud_date_reproj2.tif: Cloud mask (1: cloud, 0: no cloud)
Wholesnow_ date_reproj2.tif: Fractional snow cover obtained by MODImLAB
Ndsi_date_reproj.tif: Fractional snow fraction based on NDSI
Spot_degrade_date.mat: Fractional snow cover based on Spot acquisitions at the same date and resampled to 250m… See the full description on the dataset page: https://huggingface.co/datasets/remote-sensing-ense3-grenoble-inp/modis-snow-coverage.Land-Use-Cover-Remote-Sensing-Dataset
Land Use Cover Remote Sensing Dataset
The current agricultural sector faces rapid depletion of land resources and environmental changes. Especially against the backdrop of global climate change, efficient monitoring of land use has become particularly important. Existing remote sensing datasets are mostly focused on urban areas with insufficient attention to agricultural land coverage, leading to a lack of data support for agricultural planning and environmental assessment. This… See the full description on the dataset page: https://huggingface.co/datasets/Mobiusi/Land-Use-Cover-Remote-Sensing-Dataset.remote_sensing_VQA_multilingualeurope-unsdg-chlorophyll-a-anomaly-remote-sensing-en-mar-chlanmsatellite_remote_sensing_change_detection