Datasets:

paeslemesa
/

matchgeodem

+cff-version: 1.1.1
+message: "If you use this dataset, please cite it using the metadata from this file."
+type: dataset
+title: "MatchGeo: Multi-City Digital Elevation Model Dataset for Local Feature Matching"
+abstract: "A Digital Elevation Model (DEM) dataset aggregating high-resolution elevation data from 13 distinct environments across 6 continents. Designed for training and benchmarking local feature matching algorithms in urban and natural terrain analysis."
+authors:
+  - family-names: "Correa"
+    given-names: "S. P. L. P."
+    email: "sabrina.correa@ufv.br"
+    affiliation: "Universidade Federal de Viçosa"
+  - family-names: "Pazini Pedro"
+    given-names: "Daniele Fernanda"
+    affiliation: "Universidade Federal do Rio Grande do Norte"
+  - family-names: "Oliveira"
+    given-names: "H. N."
+    affiliation: "Universidade Federal de Viçosa"
+  - family-names: "Belton"
+    given-names: "D."
+    affiliation: "Curtin University of Technology"
+  - family-names: "Ivánová"
+    given-names: "I."
+    affiliation: "Curtin University of Technology"
+  - family-names: "Santos"
+    given-names: "A. de Paula"
+    affiliation: "Universidade Federal de Viçosa"
+repository-code: "https://github.com/paeslemesa/matchgeo"
+url: "https://doi.org/10.5281/zenodo.21229785"
+doi: "10.5281/zenodo.21229785"
+version: 1.1
+date-released: 2026-06-26
+keywords:
+  - digital elevation model
+  - DEM
+  - DSM
+  - local feature matching
+  - geospatial dataset
+  - urban terrain
+  - cross-domain matching
+  - computer vision
+  - GeoTIFF
+  - LiDAR
+  - photogrammetry
+  - Structure-from-Motion
+  - satellite stereophotogrammetry
+license: CC-BY-4.0
+preferred-citation:
+  type: dataset
+  title: "MatchGeo: Digital Elevation Model Dataset for Local Feature Matching"
+  authors:
+    - family-names: "Correa"
+      given-names: "S. P. L. P."
+    - family-names: "Pazini Pedro"
+      given-names: "Daniele Fernanda"
+    - family-names: "Oliveira"
+      given-names: "H. N."
+    - family-names: "Belton"
+      given-names: "D."
+    - family-names: "Ivánová"
+      given-names: "I."
+    - family-names: "Santos"
+      given-names: "A. de Paula"
+  year: 2026
+  doi: "10.5281/zenodo.21229785"
+  url: "https://doi.org/10.5281/zenodo.21229785"

DATASET_DESCRIPTION.md ADDED Viewed

	@@ -0,0 +1,452 @@

+# MatchGeo Dataset — Version 1.1
+## 1. Dataset Overview
+| Attribute | Details |
+|---|---|
+| **Title** | MatchGeo: Multi-region Digital Elevation Model Dataset for Local Feature Matching |
+| **Version** | 1.1 |
+| **Release Date** | 2026-05-11 |
+| **Authors / Creators** | Correa, S. P. L. P.; Pazini Pedro, D. F.; Oliveira, H. N.; Belton, D.; Ivánová, I.; Santos, A. de Paula |
+| **Contact** | sabrina.correa@ufv.br |
+| **Persistent Identifier (DOI)** | [10.5281/zenodo.21229785](https://doi.org/10.5281/zenodo.21229785) |
+| **Keywords** | digital elevation model, DEM, DSM, local feature matching, geospatial dataset, urban terrain, cross-domain matching, computer vision, GeoTIFF, LiDAR, photogrammetry, Structure-from-Motion, satellite stereophotogrammetry |
+| **Related Publication** | In preparation |
+| **Repository** | [Zenodo](https://doi.org/10.5281/zenodo.21229785) · [Hugging Face](https://huggingface.co/datasets/paeslemesa/matchgeo) |
+---
+## 2. Description
+MatchGeo is a curated, multi-region Digital Elevation Model (DEM) dataset designed for training and benchmarking local feature matching algorithms in urban and natural terrain analysis. It aggregates high-resolution elevation data from **13 distinct environments** across 6 continents to support research in cross-domain local feature detection and matching under varying acquisition methods, climates, terrain types, and urban morphologies.
+The dataset provides standardized **256x256 pixel GeoTIFF patches** with handcrafted ground truth annotations for two cities, enabling systematic evaluation of both intra-region and inter-region model generalization.
+### Geographic & Temporal Scope
+| Region | Country | Temporal Coverage | Spatial Coverage | Terrain Type |
+|---|---|---|---|---|
+| Antarctic Peninsula (ATA_MV) | Antarctica | 2009–2024 | Peninsula | Polar, ice |
+| São Paulo (BRA_SP) | Brazil | 2020 | Municipal (1,544 km²) | Tropical, urban |
+| Wutai Shan (CHN_WS) | China | 2021 | Regional | Mountainous |
+| El Hierro (ESP_EH) | Canary Islands (Spain) | 2022–2025 | Regional | Volcanic, coastal |
+| Lahti Lake (FIN_LM) | Finland | 2020–2026 | Regional | Temperate, country |
+| Bonn (GER_BN) | Germany | 2016–2018 | City limits | Temperate, country |
+| Sinabung Volcano (IDN_SV) | Indonesia | 2018 | 16.07 km² | Volcanic, tropical |
+| Almaty City (KAZ_AC) | Kazakhstan | 2017 | 304.28 km² | Semi-arid, urban |
+| Wadi Al-Akhdar (KSA_WA) | Saudi Arabia | 2016 | 1,200 km² | Desert, graben |
+| Hebron Fault (NAM_HF) | Namibia | 2017 | Regional | Arid, fault zone |
+| Kapiti Coast (NZL_KP) | New Zealand | 2010–2025 | Regional | Coastal, temperate, country |
+| Tarlac (PHL_TA) | Philippines | 2014–2017 | Regional | Tropical, flat |
+| Grand Canyon (USA_GC) | United States | 2020–2026 | Regional | Desert, canyon |
+### Purpose & Use Cases
+- Training and benchmarking local feature detectors and descriptors on geospatial elevation data
+- Cross-domain generalization studies (LiDAR vs. photogrammetry vs. satellite, temperate vs. tropical vs. desert)
+- Urban terrain analysis and change detection
+- Evaluation of matching robustness across sensor modalities and terrain types
+- Benchmarking for computer vision models on non-RGB data
+---
+## 3. Content & Schema
+### 3.1 Files Included
+| Filename / Folder | Description | Approx. Size |
+|---|---|---|
+| `data/ATA_MV/` | Antarctic Peninsula tiles + metadata | 138.3 MB |
+| `data/BRA_SP/` | São Paulo tiles + annotations + metadata | 105.34 MB |
+| `data/CHN_WS/` | Wutai Shan tiles + metadata | 206.08 MB |
+| `data/ESP_EH/` | El Hierro tiles + metadata | 422.49 MB |
+| `data/FIN_LM/` | Lahti Lake tiles + metadata | 45.97 MB |
+| `data/GER_BN/` | Bonn tiles + annotations + metadata | 333.24 MB |
+| `data/IDN_SV/` | Sinabung Volcano tiles + metadata | 34.98 MB |
+| `data/KAZ_AC/` | Almaty City tiles + metadata | 128.00 MB |
+| `data/KSA_WA/` | Wadi Al-Akhdar tiles + metadata | 556.85 MB |
+| `data/NAM_HF/` | Hebron Fault tiles + metadata | 115.24 MB |
+| `data/NZL_KP/` | Kapiti Coast tiles + metadata | 362.23 MB |
+| `data/PHL_TA/` | Tarlac tiles + metadata | 64.10 MB |
+| `data/USA_GC/` | Grand Canyon tiles + metadata | 138.27 MB |
+| `splits/` | Train / validation / test split manifests (CSV) | 1.6 MB |
+| `manifest.json` | Central machine-readable catalog (JSON-LD) | 7.2 KB |
+| `README.md` | High-level project documentation | 12.5 KB |
+| `DATASET_DESCRIPTION.md` | This file | 126.0 KB |
+| `LICENSE` | Full CC BY 4.0 legal text | 14.2 KB |
+### 3.2 Per-region File Structure
+Each region folder follows this structure:
+```
+<REGION_ID>/
+├── <REGION_ID>.tif                  # Merged DEM (BigTIFF, tiled, DEFLATE)
+├── <REGION_ID>_extent.geojson       # Bounding polygon of full coverage
+├── <REGION_ID>_tiles.geojson        # Tile index (grid of all 256x256 patches)
+├── metadata/
+│   └── <REGION_ID>_metadata.json    # ISO 19115-2 + OGC 23-008r3 metadata
+├── annotations/                     # Only for labelled cities (BRA_SP, GER_BN)
+│   └── <REGION_ID>_###_###.json     # Keypoint annotations per tile
+└── tiles/
+    └── <REGION_ID>_###_###.tif      # 256x256 pixel patches
+```
+### 3.3 Data Dictionary
+| Variable / Field | Data Type | Description | Units / Format | Nullable | Example |
+|---|---|---|---|---|---|
+| `tile_id` | string | Unique identifier for each 256x256 patch | — | No | `GER_BN_001_010` |
+| `region` | string | Source region code | — | No | `GER_BN` |
+| `geometry` | GeoTIFF raster | Elevation patch | 256x256 px, float32 | No | — |
+| `crs` | string | Coordinate reference system | EPSG code | No | `EPSG:25832` |
+| `resolution` | float | Ground sample distance | meters | No | `1.0` |
+| `acquisition_method` | string | Data acquisition technique | — | No | `airborne_lidar` |
+| `acquisition_year` | integer | Year of data capture | year | No | `2017` |
+| `elevation_min` | float | Minimum elevation in patch | meters | Yes | `42.3` |
+| `elevation_max` | float | Maximum elevation in patch | meters | Yes | `156.8` |
+| `elevation_mean` | float | Mean elevation in patch | meters | Yes | `98.4` |
+| `elevation_std` | float | Standard deviation of elevation | meters | Yes | `12.1` |
+| `annotated` | boolean | Whether patch has handcrafted ground truth | — | No | `true` |
+| `n_annotations` | integer | Number of verified point annotations in patch | count | Yes | `127` |
+| `split` | string | Dataset split assignment | — | No | `train` |
+| `difficulty` | string | Difficulty tag for stratification | — | Yes | `easy` |
+---
+## 4. Methodology & Provenance
+### 4.1 Data Sources
+All raw data were obtained from open municipal, national, or research portals and are redistributed under terms compatible with CC BY 4.0.
+| City | Source Dataset | Provider | Method | Resolution | Year | CRS | License / Terms |
+|---|---|---|---|---|---|---|---|
+| **ATA_MV** | REMA | Polar Geospatial Center / University of Minnesota | Satellite stereophotogrammetry | 1.0 m | 2009–2024 | EPSG:3031 | CC BY 4.0 |
+| **BRA_SP** | GeoSampa MDS 2020 | Prefeitura de São Paulo (PMSP) / SMUL / GEOINFO | Airborne LiDAR (Optech ORION H300) | **0.5 m** | 2020 | EPSG:31983 | Open municipal data |
+| **CHN_WS** | Wutai Shan / Yingwang Shan 2021 | Zhou, C. / OpenTopography | UAV SfM (DJI Phantom 4) | 1.0 m | 2021 | EPSG:32649 | OpenTopography terms |
+| **ESP_EH** | PNOA-LiDAR 3ª Cobertura | CNIG / Instituto Geográfico Nacional | Airborne LiDAR | 0.5 m | 2022–2025 | EPSG:3040 | CC BY 4.0 |
+| **FIN_LM** | Elevation Model 2 m | Maanmittauslaitos (NLS Finland) | Airborne LiDAR + photogrammetry | 2.0 m | 2020–2026 | EPSG:3067 | CC BY 4.0 |
+| **GER_BN** | Digitales Oberflächenmodell (DOM) | Geobasis NRW / Bezirksregierung Köln | Airborne LiDAR | 1.0 m | 2016–2018 | EPSG:25832 | Open data |
+| **IDN_SV** | Sinabung Volcano 2018 | Carr, B. / OpenTopography | UAS SfM (DJI Matrice 210) | 0.87 m | 2018 | EPSG:32647 | OpenTopography terms |
+| **KAZ_AC** | Almaty City 2017 | Amey et al. / OpenTopography | Pleiades Tristereo | 1.0 m | 2017 | EPSG:32643 | OpenTopography terms |
+| **KSA_WA** | Wadi-al-Akhdar 2016 | Matthieu et al. / OpenTopography | SPOT 6 Stereo | 1.6 m | 2016 | EPSG:32637 | OpenTopography terms |
+| **NAM_HF** | Hebron Fault 2017 | Salomon et al. / UCT / OpenTopography | WorldView-3 Stereo | 0.53 m | 2017 | EPSG:32733 | OpenTopography terms |
+| **NZL_KP** | NZ LiDAR 1m DEM | LINZ | Airborne LiDAR | 1.0 m | 2010–2025 | EPSG:2193 | CC BY 4.0 |
+| **PHL_TA** | LiPAD | UP Diliman TCAGP / DREAM / DOST | Airborne LiDAR | 1.0 m | 2014–2017 | EPSG:32651 | Open data |
+| **USA_GC** | USGS 3DEP DEM | U.S. Geological Survey | LiDAR | 0.5 m | 2020–2026 | EPSG:6341 | Public Domain |
+### 4.2 Processing Pipeline
+All cities were processed through a standardized PDAL pipeline with region-specific adaptations:
+1. **Acquisition & Download** — Raw data retrieved from source portals in native CRS and resolution.
+2. **Preprocessing (region-specific)**:
+   - **BRA_SP**: Ground classification via `filters.smf` (scalar=1.25, slope=0.15, threshold=0.5, window=16.0)
+   - **CHN_WS**: Noise removal (`filters.range` Classification![7:7]) + statistical outlier removal (mean_k=6, multiplier=2.0)
+   - **IDN_SV, KSA_WA, NAM_HF**: Statistical outlier removal (mean_k=6, multiplier=2.0)
+   - **Others**: Direct rasterization
+3. **Rasterization** — PDAL `writers.gdal` with:
+   - `output_type`: `max` (DSM: highest point per cell)
+   - `data_type`: `float32`
+   - `nodata`: `-9999`
+   - `gdalopts`: `COMPRESS=DEFLATE|TILED=YES|BIGTIFF=YES`
+   - `resolution`: City-specific (see table above)
+4. **Patch Extraction** — Non-overlapping 256x256 pixel patches extracted using a regular grid (no resampling).
+5. **Quality Control** — Outlier removal based on elevation range checks, CRS validation, and visual inspection.
+6. **Annotation (BRA_SP, GER_BN)** — Handcrafted point-level annotations in normalized coordinates.
+7. **Stratified Splitting** — 80% train / 10% validation / 10% test (planned; to be stratified by region and difficulty).
+8. **Packaging & Metadata** — Per-region ISO 19115-2 metadata; central JSON-LD manifest; archived on Zenodo with DOI.
+### 4.3 Software & Tools
+- Python 3.10.20
+- PDAL 2.6.0 (point cloud processing)
+- GDAL / rasterio (geospatial I/O and reprojection)
+- NumPy / pandas (tabular metadata management)
+- Custom annotation and patch-generation scripts
+---
+## 5. Access & Licensing
+### 5.1 Availability
+| Repository | URL | Access Type |
+|---|---|---|
+| **Zenodo (Primary)** | [https://doi.org/10.5281/zenodo.21229785](https://doi.org/10.5281/zenodo.21229785) | Open, DOI-backed, permanent |
+| **Hugging Face Datasets** | [https://huggingface.co/datasets/paeslemesa/matchgeo](https://huggingface.co/datasets/paeslemesa/matchgeo) | Open, streaming loader available |
+- **Total Size**: ~12.5 GB
+- **File Formats**: Cloud Optimized GeoTIFF - COG (`.tif`), GeoJSON (`.geojson`), metadata JSON, split manifests CSV
+- **Access Type**: Open access, no registration required
+### 5.2 License
+This dataset is released under the **Creative Commons Attribution 4.0 International License (CC BY 4.0)**.
+You are free to:
+- **Share** — copy and redistribute the material in any medium or format
+- **Adapt** — remix, transform, and build upon the material for any purpose, even commercially
+Under the following terms:
+- **Attribution** — You must give appropriate credit, provide a link to the license, and indicate if changes were made.
+The full legal text is provided in the [`LICENSE`](LICENSE) file and at [https://creativecommons.org/licenses/by/4.0/legalcode](https://creativecommons.org/licenses/by/4.0/legalcode).
+### 5.3 Terms of Use & Source Attribution
+When using this dataset, your publication or product must include:
+1. **Dataset citation** (see [Section 8: Citation](#8-citation))
+2. **Original source acknowledgments** (per region):
+   - *ATA_MV: Data derived from REMA © Polar Geospatial Center / University of Minnesota*
+   - *BRA_SP: Data derived from GeoSampa © Prefeitura de São Paulo*
+   - *CHN_WS: Data derived from OpenTopography dataset by Zhou, C. (DOI: 10.5069/G98C9TGT)*
+   - *ESP_EH: Data derived from PNOA-LiDAR © CNIG / Instituto Geográfico Nacional*
+   - *FIN_LM: Data derived from Maanmittauslaitos © National Land Survey of Finland*
+   - *GER_BN: Data derived from Geobasis NRW © Bezirksregierung Köln*
+   - *IDN_SV: Data derived from OpenTopography dataset by Carr, B. (DOI: 10.5069/G8988568)*
+   - *KAZ_AC: Data derived from OpenTopography dataset by Amey et al. (DOI: 10.5069/G9H41PMP)*
+   - *KSA_WA: Data derived from OpenTopography dataset by Matthieu et al. (DOI: 10.5069/G9V40SDZ)*
+   - *NAM_HF: Data derived from OpenTopography dataset by Salomon et al. (DOI: 10.5069/G9W957BC)*
+   - *NZL_KP: Data derived from LINZ © Land Information New Zealand*
+   - *PHL_TA: Data derived from LiPAD © UP Diliman TCAGP / DREAM Program*
+   - *USA_GC: Data derived from USGS 3DEP © U.S. Geological Survey*
+---
+## 6. Interoperability & Technical Details
+### 6.1 Standards & Formats
+| Aspect | Standard / Value |
+|---|---|
+| **Raster format** | Cloud Optimized GeoTIFF (BigTIFF variant, OGC 23-008r3 compliant) |
+| **Internal tiling** | 256 × 256 pixels |
+| **Pixel depth** | Float32 |
+| **Patch dimensions** | 256 × 256 pixels |
+| **Coordinate systems** | Region-specific UTM (see Section 4.1) |
+| **Metadata standard** | ISO 19115-2 + OGC 23-008r3 |
+| **Encoding** | UTF-8 for all text and tabular files |
+| **Compression** | DEFLATE |
+| **NoData value** | -9999 |
+### 6.2 OGC GeoTIFF Compliance (23-008r3)
+All GeoTIFFs comply with OGC 23-008r3 and contain the following required keys:
+| Key | Status | Source |
+|---|---|---|
+| GTModelTypeGeoKey | ✅ | PDAL `override_srs` |
+| GTRasterTypeGeoKey | ✅ | GDAL default (PixelIsArea) |
+| ProjectedCSTypeGeoKey | ✅ | EPSG code embedded |
+| GeogGeodeticDatumGeoKey | ✅ | Derived from EPSG |
+| GeogAngularUnitsGeoKey | ✅ | Degree (default) |
+| ProjLinearUnitsGeoKey | ✅ | Meter (default) |
+| PixelScale | ✅ | GDAL writer |
+| TiePoint | ✅ | Upper-left corner coordinate |
+| BigTIFF | ✅ | `BIGTIFF=YES` |
+| Tiled | ✅ | `TILED=YES` |
+| Compression | ✅ | `COMPRESS=DEFLATE` |
+| NoData | ✅ | `nodata=-9999` |
+> **Note on vertical CRS**: The GeoTIFFs encode 2D projected CRS (EPSG codes) with elevation as pixel values. A vertical CRS is not explicitly embedded in the GeoTIFF GeoKeys; vertical datum information is documented in per-region `metadata.json` files.
+### 6.3 Controlled Vocabularies
+- **GCMD Keywords**: `EARTH SCIENCE > LAND SURFACE > TOPOGRAPHY > TERRAIN ELEVATION > DIGITAL ELEVATION/TERRAIN MODEL (DEM)`
+- **ISO Topic Category**: `elevation`
+- **INSPIRE Theme**: `Elevation`
+### 6.4 Data Splits
+| Split | Proportion | Stratification |
+|---|---|---|
+| Train | 80% | By region and difficulty |
+| Validation | 10% | By region and difficulty |
+| Test | 10% | By region and difficulty |
+Explicit **intra-region** and **inter-region** test subsets are planned for future releases.
+---
+## 7. Quality Assurance & Known Limitations
+### 7.1 Validation
+- Bonn annotations were verified by multiple annotators.
+- Elevation ranges were cross-checked against known region topographies.
+- CRS consistency was validated using GDALinfo and automated assertions.
+### 7.2 Known Biases & Limitations
+| Issue | Description | Mitigation / Status |
+|---|---|---|
+| **Geographic bias** | Dense annotation only in GER_BN and BRA_SP; others unlabelled | v1.1 separates labelled/unlabelled; future releases will add annotations |
+| **Temporal mismatch** | Data spans 2009–2026 across cities | Documented; users should account for temporal drift |
+| **Sensor heterogeneity** | LiDAR, photogrammetry, SfM, satellite stereo — different noise characteristics | Explicitly treated as cross-domain challenge |
+| **Resolution heterogeneity** | Native resolutions range from 0.5 m to 2.0 m | |
+| **Missing data** | Water bodies, ocean excluded; NoData=-9999 | Documented in per-tile metadata |
+| **ATA_MV uncertainty** | Antarctica data from REMA satellite stereophotogrammetry | Marked for verification |
+| **CHN_WS CRS discrepancy** | BibTeX says EPSG:32649; user previously mentioned EPSG:32648 | To be verified from actual file |
+| **Vertical CRS** | No explicit vertical GeoKey in GeoTIFFs; elevations are source-dependent (orthometric or ellipsoidal) | Documented in per-region `metadata.json` |
+---
+## 8. Citation
+If you use this dataset in your research, please cite:
+```bibtex
+@dataset{correa_2026_matchgeo,
+  author       = {Correa, S. P. L. P. and Pazini Pedro, D. F. and Oliveira, H. N. and Belton, D. and Ivánová, I. and Santos, A. de Paula},
+  title        = {{MatchGeo: Digital Elevation Model Dataset for Local Feature Matching}},
+  year         = 2026,
+  publisher    = {Zenodo},
+  version      = {1.1},
+  doi          = {10.5281/zenodo.21229785},
+  url          = {https://doi.org/10.5281/zenodo.21229785},
+  note         = {Contains data derived from REMA, GeoSampa, OpenTopography, CNIG, Maanmittauslaitos, Geobasis NRW, LINZ, LiPAD, and USGS 3DEP}
+}
+```
+**Plain text citation:**
+Correa, S. P. L. P., Pazini Pedro, D. F., Oliveira, H. N., Belton, D., Ivánová, I., & Santos, A. de Paula. (2026). *MatchGeo: Digital Elevation Model Dataset for Local Feature Matching* (Version 1.1) [Data set]. Zenodo. https://doi.org/10.5281/zenodo.21229785
+### Source Dataset Citations
+When using specific cities, also cite the original sources:
+```bibtex
+% BRA_SP
+@misc{datasetgeosampa,
+  author = {{Prefeitura do Munic{'i}pio de S{\~a}o Paulo (PMSP)}},
+  title = {{Nuvem de Pontos {MDS} 2020}},
+  year = {2020},
+  publisher = {GeoSampa},
+  url = {https://geosampa.prefeitura.sp.gov.br/}
+}
+% CHN_WS
+@misc{datasetchinayingwang2021,
+  author = {Zhou, C.},
+  title = {High Resolution Topography of {Wutai Shan} and {Yingwang Shan}, China, 2021},
+  year = {2023},
+  publisher = {OpenTopography},
+  doi = {10.5069/G98C9TGT}
+}
+% ESP_EH
+@misc{datasetspain,
+  author = {{Centro Nacional de Informaci{'o}n Geogr{'a}fica (CNIG)}},
+  title = {{PNOA-LiDAR --- 3{\textordfeminine} Cobertura (2022--2025)}},
+  year = {2022--2025},
+  url = {https://centrodedescargas.cnig.es/CentroDescargas/lidar-tercera-cobertura}
+}
+% FIN_LM
+@misc{datasetfinland,
+  author = {{Maanmittauslaitos --- National Land Survey of Finland}},
+  title = {{Korkeusmalli 2 m / Elevation Model 2 m}},
+  year = {2026},
+  url = {https://www.maanmittauslaitos.fi/en/maps-and-spatial-data/datasets-and-interfaces/product-descriptions/elevation-model-2-m}
+}
+% GER_BN
+@misc{datasetgermany,
+  author = {{Geobasis NRW --- Bezirksregierung K{\"o}ln}},
+  title = {{Digitales Oberfl{\"a}chenmodell ({DOM})}},
+  year = {2024},
+  url = {https://www.bezreg-koeln.nrw.de/geobasis-nrw/produkte-und-dienste/hoehenmodelle/digitale-oberflaechenmodelle/digitales}
+}
+% IDN_SV
+@misc{datasetindonesiasinabung2018,
+  author = {Carr, B.},
+  title = {{Sinabung Volcano} (Indonesia), {June 20, 2018}},
+  year = {2021},
+  publisher = {OpenTopography},
+  doi = {10.5069/G8988568}
+}
+% KAZ_AC
+@misc{datasetkazakhstanalmaty2017,
+  author = {Amey, R. and Watson, C. S. and Elliott, J. and Walker, R.},
+  title = {{Almaty City, Kazakhstan, 2017, Derived from {Pleiades} Tristereo Imagery}},
+  year = {2021},
+  publisher = {OpenTopography},
+  doi = {10.5069/G9H41PMP}
+}
+% KSA_WA
+@misc{dataset_saudiarabia_wadi_al_akhdar_2016,
+  author = {Matthieu, R. and Moulin, A. and J{'o}nsson, S.},
+  title = {{Digital Surface Model of {Wadi-al-Akhdar} Graben, Saudi Arabia, 2016}},
+  year = {2024},
+  publisher = {OpenTopography},
+  doi = {10.5069/G9V40SDZ}
+}
+% NAM_HF
+@misc{datasetnamibiahebron_2017,
+  author = {Salomon, G. and Smit, J. and Muir, R. and Stevens, V. and Sloan, R. A.},
+  title = {{Hebron Fault, Namibia 2017 {WorldView-3} Stereophotogrammetric {DEM}}},
+  year = {2021},
+  publisher = {OpenTopography},
+  doi = {10.5069/G9W957BC}
+}
+% NZL_KP
+@misc{datasetnewzealand,
+  author = {{Toit{\=u} Te Whenua Land Information New Zealand ({LINZ})}},
+  title = {New Zealand {LiDAR} 1m {DEM}},
+  year = {2025},
+  url = {https://data.linz.govt.nz/layer/121859-new-zealand-lidar-1m-dem/services/csw/}
+}
+% PHL_TA
+@misc{datasetphilippines,
+  author = {{Disaster Risk and Exposure Assessment for Mitigation (DREAM) Program}},
+  title = {{LiPAD --- {LiDAR} Portal for Archiving and Distribution}},
+  year = {2016},
+  url = {https://lipad.dream.upd.edu.ph/}
+}
+% USA_GC
+@misc{datasetusa,
+  author = {{U.S. Geological Survey}},
+  title = {{3D Elevation Program (3DEP) Digital Elevation Models}},
+  year = {2026},
+  url = {https://apps.nationalmap.gov/downloader/}
+}
+```
+---
+## 9. Version History
+| Version | Date | Changes | Author |
+|---|---|---|---|
+| 1.0 | 2026-03-30 | Initial release; GER_BN 20,000+ handcrafted annotations | Correa et al. |
+| 1.1 | 2026-05-11 | Expanded to 13 cities; reorganized into labelled/unlabelled; added per-region metadata; synchronized with FAIR + OGC 23-008r3 | Correa et al. |
+---
+## 10. Acknowledgments & Funding
+- **Data providers**: European Commission / ESA (Copernicus), Prefeitura de São Paulo (GeoSampa), OpenTopography, CNIG (Spain), Maanmittauslaitos (Finland), Geobasis NRW (Germany), LINZ (New Zealand), UP Diliman TCAGP / DREAM (Philippines), USGS (United States)
+- **Imagery providers**: CNES / Airbus DS (Pleiades), Maxar (WorldView-3), SPOT Image (SPOT 6)
+- **Institutional support**: Universidade Federal de Viçosa (UFV)
+---
+## 11. Contact & Support
+- **General inquiries**: sabrina.correa@ufv.br
+- **Dataset maintainer**: Sabrina Correa, Universidade Federal de Viçosa
+- **Issues / bug reports**: [GitHub Issues](https://github.com/paeslemesa/matchgeo/issues)
+- **Discussions**: [GitHub Discussions](https://github.com/paeslemesa/matchgeo/discussions)
+---
+**Last Updated**: 2026-07-09

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	@@ -0,0 +1,140 @@

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	@@ -0,0 +1,272 @@

+{
+  "@context": {
+    "@vocab": "https://schema.org/",
+    "dcat": "http://www.w3.org/ns/dcat#",
+    "geo": "http://www.w3.org/2003/01/geo/wgs84_pos#",
+    "fair": "https://www.go-fair.org/fair-principles/"
+  },
+  "@type": "Dataset",
+  "name": "MatchGeo",
+  "version": "1.1",
+  "datePublished": "2026-05-11",
+  "dateModified": "2026-07-07",
+  "identifier": {
+    "@type": "PropertyValue",
+    "propertyID": "DOI",
+    "value": "10.5281/zenodo.21229785"
+  },
+  "url": "https://doi.org/10.5281/zenodo.21229785",
+  "license": "https://creativecommons.org/licenses/by/4.0/",
+  "creator": [
+    {
+      "@type": "Person",
+      "name": "Correa, S. P. L. P.",
+      "email": "sabrina.correa@ufv.br",
+      "affiliation": "Universidade Federal de Viçosa"
+    },
+    {
+      "@type": "Person",
+      "name": "Pazini Pedro, Daniele Fernanda",
+      "affiliation": "Universidade Federal do Rio Grande do Norte"
+    },
+    {
+      "@type": "Person",
+      "name": "Oliveira, H. N.",
+      "affiliation": "Universidade Federal de Viçosa"
+    },
+    {
+      "@type": "Person",
+      "name": "Belton, D.",
+      "affiliation": "Curtin University of Technology"
+    },
+    {
+      "@type": "Person",
+      "name": "Ivánová, I.",
+      "affiliation": "Curtin University of Technology"
+    },
+    {
+      "@type": "Person",
+      "name": "Santos, A. de Paula",
+      "affiliation": "Universidade Federal de Viçosa"
+    }
+  ],
+  "regions": [
+    {
+      "tile_id": "ATA_MV",
+      "name": "Antarctic Peninsula, Antarctica",
+      "epsg": 3031,
+      "resolution": 1.0,
+      "method": "satellite_stereophotogrammetry",
+      "n_tiles": 2760,
+      "labelled": false,
+      "n_annotations": 0,
+      "source": "REMA",
+      "doi": null,
+      "area_km2": 711.37,
+      "elevation_min_m": -55.0,
+      "elevation_max_m": 375.32,
+      "elevation_range_m": 430.49
+    },
+    {
+      "tile_id": "BRA_SP",
+      "name": "São Paulo, Brazil",
+      "epsg": 31983,
+      "resolution": 0.5,
+      "method": "airborne_lidar",
+      "n_tiles": 895,
+      "labelled": true,
+      "n_annotations": 19515,
+      "source": "GeoSampa",
+      "doi": null,
+      "area_km2": 15.49,
+      "elevation_min_m": 708.46,
+      "elevation_max_m": 995.03,
+      "elevation_range_m": 286.57
+    },
+    {
+      "tile_id": "CHN_WS",
+      "name": "Wutai Shan / Yingwang Shan, China",
+      "epsg": 32649,
+      "resolution": 1.0,
+      "method": "uav_sfm",
+      "n_tiles": 1784,
+      "labelled": false,
+      "n_annotations": 0,
+      "source": "OpenTopography",
+      "doi": "10.5069/G98C9TGT",
+      "area_km2": 105.0,
+      "elevation_min_m": 1338.9,
+      "elevation_max_m": 2181.95,
+      "elevation_range_m": 843.05
+    },
+    {
+      "tile_id": "ESP_EH",
+      "name": "El Hierro, Canary Islands (Spain)",
+      "epsg": 4074,
+      "resolution": 0.5,
+      "method": "airborne_lidar",
+      "n_tiles": 2046,
+      "labelled": false,
+      "n_annotations": 0,
+      "source": "PNOA-LiDAR 3ª Cobertura",
+      "doi": null,
+      "area_km2": 156.0,
+      "elevation_min_m": 2.0,
+      "elevation_max_m": 1191.39,
+      "elevation_range_m": 1189.39
+    },
+    {
+      "tile_id": "FIN_LM",
+      "name": "Lahti Lake, Finland",
+      "epsg": 400,
+      "resolution": 2.0,
+      "method": "airborne_lidar_photogrammetry",
+      "n_tiles": 2000,
+      "labelled": false,
+      "n_annotations": 0,
+      "source": "National Land Survey of Finland",
+      "doi": null,
+      "area_km2": 98.0,
+      "elevation_min_m": 64.38,
+      "elevation_max_m": 403.79,
+      "elevation_range_m": 342.42
+    },
+    {
+      "tile_id": "GER_BN",
+      "name": "Bonn, Germany",
+      "epsg": 25832,
+      "resolution": 1.0,
+      "method": "airborne_lidar",
+      "n_tiles": 1857,
+      "labelled": true,
+      "n_annotations": 20772,
+      "source": "Geobasis NRW",
+      "doi": null,
+      "area_km2": 135.58,
+      "elevation_min_m": 31.73,
+      "elevation_max_m": 390.35,
+      "elevation_range_m": 358.62
+    },
+    {
+      "tile_id": "IDN_SV",
+      "name": "Sinabung Volcano, Indonesia",
+      "epsg": 32647,
+      "resolution": 0.87,
+      "method": "uas_sfm",
+      "n_tiles": 301,
+      "labelled": false,
+      "n_annotations": 0,
+      "source": "OpenTopography",
+      "doi": "10.5069/G8988568",
+      "area_km2": 17.67,
+      "elevation_min_m": 1100.06,
+      "elevation_max_m": 2385.18,
+      "elevation_range_m": 1185.11
+    },
+    {
+      "tile_id": "KAZ_AC",
+      "name": "Almaty City, Kazakhstan",
+      "epsg": 32643,
+      "resolution": 1.0,
+      "method": "satellite_stereophotogrammetry",
+      "n_tiles": 1698,
+      "labelled": false,
+      "n_annotations": 0,
+      "source": "OpenTopography",
+      "doi": "10.5069/G9H41PMP",
+      "area_km2": 247.47,
+      "elevation_min_m": 594.71,
+      "elevation_max_m": 1660.38,
+      "elevation_range_m": 1065.57
+    },
+    {
+      "tile_id": "KSA_WA",
+      "name": "Wadi Al-Akhdar, Saudi Arabia",
+      "epsg": 32637,
+      "resolution": 1.6,
+      "method": "satellite_stereophotogrammetry",
+      "n_tiles": 6521,
+      "labelled": false,
+      "n_annotations": 0,
+      "source": "OpenTopography",
+      "doi": "10.5069/G9V40SDZ",
+      "area_km2": 1260.57,
+      "elevation_min_m": 856.2,
+      "elevation_max_m": 1457.76,
+      "elevation_range_m": 601.56
+    },
+    {
+      "tile_id": "NAM_HF",
+      "name": "Hebron Fault, Namibia",
+      "epsg": 32733,
+      "resolution": 0.53,
+      "method": "satellite_stereophotogrammetry",
+      "n_tiles": 2405,
+      "labelled": false,
+      "n_annotations": 0,
+      "source": "OpenTopography",
+      "doi": "10.5069/G9W957BC",
+      "area_km2": 77.48,
+      "elevation_min_m": 861.89,
+      "elevation_max_m": 1251.9,
+      "elevation_range_m": 390.01
+    },
+    {
+      "tile_id": "NZL_KP",
+      "name": "Kapiti Coast, New Zealand",
+      "epsg": 2193,
+      "resolution": 1.0,
+      "method": "airborne_lidar",
+      "n_tiles": 3087,
+      "labelled": false,
+      "n_annotations": 0,
+      "source": "LINZ LiDAR 1m DEM",
+      "doi": null,
+      "area_km2": 195.52,
+      "elevation_min_m": 95.16,
+      "elevation_max_m": 1609.97,
+      "elevation_range_m": 1514.81
+    },
+    {
+      "tile_id": "PHL_TA",
+      "name": "Tarlac, Philippines",
+      "epsg": 32651,
+      "resolution": 1.0,
+      "method": "airborne_lidar",
+      "n_tiles": 462,
+      "labelled": false,
+      "n_annotations": 0,
+      "source": "LiPAD",
+      "doi": null,
+      "area_km2": 30.04,
+      "elevation_min_m": 22.09,
+      "elevation_max_m": 401.14,
+      "elevation_range_m": 379.05
+    },
+    {
+      "tile_id": "USA_GC",
+      "name": "Grand Canyon, United States",
+      "epsg": 6341,
+      "resolution": 0.5,
+      "method": "lidar",
+      "n_tiles": 1024,
+      "labelled": false,
+      "n_annotations": 0,
+      "source": "USGS 3DEP",
+      "doi": null,
+      "area_km2": 16.2,
+      "elevation_min_m": 461.76,
+      "elevation_max_m": 1384.25,
+      "elevation_range_m": 922.49
+    }
+  ],
+  "total_size_gb": 12.5,
+  "total_tiles": 26255,
+  "labelled_tiles": 473,
+  "total_annotations": 30000,
+  "splits": {
+    "train": "splits/train.csv",
+    "validation": "splits/validation.csv",
+    "test": "splits/test.csv"
+  }
+}