Forest
Datasets
All datasets matching “Forest”ukraine-forest-change-detection
Satellite Forest Change Detection Dataset
This dataset contains paired multispectral satellite image tiles and binary
change masks for forest change detection. Each valid sample is a triplet:
A: image at the first time point
B: image at the second time point
label: change mask for the same tile and period
The data is organized into train, val, and test splits. Each split has
the same directory structure:
train/
A/
B/
label/
val/
A/
B/
label/
test/
A/
B/
label/… See the full description on the dataset page: https://huggingface.co/datasets/Moriae/ukraine-forest-change-detection.IndustryCorpus2_agriculture_forestry_animal_husbandry_fishery
IndustryCorpus2: Agriculture & Fisheries
This repository contains the IndustryCorpus2: Agriculture & Fisheries domain subset of BAAI/IndustryCorpus2.
Refer to the parent dataset card for data construction, intended use, limitations,
and licensing details.
Citation
If you use this dataset in your work, please cite IndustryCorpus2:
@misc{shi2024industrycorpus2,
title = {IndustryCorpus2},
author = {Xiaofeng Shi and Lulu Zhao and Hua Zhou and Donglin Hao}… See the full description on the dataset page: https://huggingface.co/datasets/BAAI/IndustryCorpus2_agriculture_forestry_animal_husbandry_fishery.ForestPersons
ForestPersons Dataset
Dataset Summary
ForestPersons is a large-scale dataset designed for missing person detection in forested environments under search-and-rescue scenarios. The dataset simulates realistic field conditions with varied poses (standing, sitting, lying) and visibility levels (20, 40, 70, 100). Images were captured using RGB sensors at ground and low-altitude perspectives.
Links
Paper: OpenReview (ICLR 2026)
Dataset:
RGB (Visible)
IR (Thermal) –… See the full description on the dataset page: https://huggingface.co/datasets/etri/ForestPersons.kontext-bench
Kontext Bench
Kontext Bench is a benchmark for image editing models consisting of source images paired with image editing instructions and category tags.
The benchmark comprises 1026 unique image-prompt pairs derived from 108 base images from diverse sources. It spans five core tasks: local instruction editing, global instruction editing, text editing, style reference, and character reference. We found that the scale of the benchmark provides a good balance between reliable human… See the full description on the dataset page: https://huggingface.co/datasets/black-forest-labs/kontext-bench.FireDetectionDataset-flame-forest-flameye-wildfire
FlamEye — Wildfire Detection Dataset
A merged, deduplicated, and augmented dataset for real-time wildfire detection (fire and smoke) from CCTV/surveillance cameras. Built to train YOLOv8m for early-stage fire detection.
Classes
ID
Name
0
fire
1
smoke
Dataset Statistics
Split
Images
Train
~10,929
Validation
~3,000
Test
~1,500
Sources
Dataset
Source
Notes
D-Fire
Kaggle
Class IDs remapped:… See the full description on the dataset page: https://huggingface.co/datasets/baizhanquan/FireDetectionDataset-flame-forest-flameye-wildfire.ssl4eo_eu_forest
SSL4EO-EU-Forest
Sentinel-2 winter scene
tree (green) segmentation
Sentinel-2 summer scene
tree (green) segmentation
Introduction
The dataset is an add-on to the globally sampled SSL4EO-S12 pre-training dataset (https://doi.org/10.1109/MGRS.2023.3281651) where v1.1 is available at https://huggingface.co/datasets/embed2scale/SSL4EO-S12-v1.1 with downstream tasks… See the full description on the dataset page: https://huggingface.co/datasets/dm4eo/ssl4eo_eu_forest.