Datasets › Fine-Grained Grass Segmentation Dataset
Fine-Grained Grass Segmentation Dataset
The dataset was created using high-resolution (8 m) satellite imagery from the Gaofen series (Gaofen-2 and Gaofen-6), captured in 2019 over Maduo County, China, located in the Yellow River source area. This region is known for its high-altitude, alpine grasslands, and complex terrain, with coordinates between 33°50'–35°40' N latitude and 96°50'–99°20' E longitude.
We collected two 13,872 × 13,150-pixel images from Gaofen-6 and two 7,300 × 6,905-pixel images from Gaofen-2, all containing red, green, and blue spectral bands. These images provide critical information for fine-grained grass extraction.
Labeling was assisted by the X-AnyLabeling tool, supplemented with manual refinements to ensure high accuracy. Grassland coverage was classified into five levels, based on national grassland survey standards:
- Low coverage (<10%)
- Medium-low coverage (10%–25%)
- Medium coverage (25%–50%)
- Medium-high coverage (50%–75%)
- High coverage (>75%)
The final dataset comprises 1,151 pairs of 256×256 patches, split into training and testing sets with an 8:2 ratio. This dataset, with its detailed and accurate labeling, is a valuable resource for advancing remote sensing applications, particularly in ecologically sensitive and high-altitude regions like the Yellow River source area.
Benchmarks archive 2025-07-28
All 1 leaderboard whose dataset resolves to this page shown (sort by any header). "First row" is the archive's own first row at snapshot, in the archive's row order; nothing here re-ranks and metric direction is not asserted.
| First row (archive order) | Paper | Code | ||||
|---|---|---|---|---|---|---|
| Semantic Segmentation | Fine-Grained Grass Segmentation Dataset | D2LS mIoU 51.96 | Dynamic Dictionary Learning for Remote Sensing Image Segmentation | XavierJiezou/D2LS | 10 | Compare |
Papers archive 2025-07-28
10 shown of 10 papers with a leaderboard row on this dataset's benchmarks, newest first. The archive's own "papers using this dataset" list was never published, so this is the benchmark-backed subset; the archive's count for this dataset is 10. The Syntology column is from Syntology's graph (read 2026-09-24), stated per sample; it is not part of any archive number.
| Date | Samples run Syntology | |||
|---|---|---|---|---|
| Dynamic Dictionary Learning for Remote Sensing Image Segmentation | 1 | 1 | 9 Mar 2025 | ran 9 of 12 samples (3 unverified; 12 pointer-only for licence) |
| Knowledge Transfer and Domain Adaptation for Fine-Grained Remote Sensing Image Segmentation | 1 | 1 | 9 Dec 2024 | not harvested |
| SFA-Net: Semantic Feature Adjustment Network for Remote Sensing Image Segmentation | 1 | 1 | 3 Sep 2024 | not harvested |
| DINOv2: Learning Robust Visual Features without Supervision | 26 | 1 | 14 Apr 2023 | ran 21 of 46 samples (25 unverified; 12 pointer-only for licence) |
| Masked-attention Mask Transformer for Universal Image Segmentation | 7 | 1 | 2 Dec 2021 | ran 2 of 8 samples (6 unverified) |
| SegFormer: Simple and Efficient Design for Semantic Segmentation with Transformers | 28 | 1 | 31 May 2021 | ran 48 of 86 samples (38 unverified; 15 pointer-only for licence) |
| Encoder-Decoder with Atrous Separable Convolution for Semantic Image Segmentation | 78 | 1 | 7 Feb 2018 | ran 43 of 72 samples (29 unverified; 40 pointer-only for licence) |
| Pyramid Scene Parsing Network | 67 | 1 | 4 Dec 2016 | ran 7 of 29 samples (22 unverified; 5 pointer-only for licence) |
| U-Net: Convolutional Networks for Biomedical Image Segmentation | 487 | 1 | 18 May 2015 | ran 510 of 757 samples (247 unverified; 426 pointer-only for licence) |
| Fully Convolutional Networks for Semantic Segmentation | 51 | 1 | 14 Nov 2014 | ran 3 of 4 samples (1 unverified; 4 pointer-only for licence) |
Dataset loaders archive 2025-07-28
No loader listed in the archive.
Tasks archive 2025-07-28
License archive 2025-07-28
Apache-2.0
Modalities archive 2025-07-28
No modality tagged.
Languages archive 2025-07-28
No language tagged.
Variants archive 2025-07-28
- Fine-Grained Grass Segmentation Dataset
1 variant name, as the archive lists them.
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