保存先:
| 主要な著者: | , |
|---|---|
| フォーマット: | Recurso digital |
| 言語: | 英語 |
| 出版事項: |
Zenodo
2026
|
| オンライン･アクセス: | https://doi.org/10.5281/zenodo.19846944 |
| タグ: |
タグ追加
タグなし, このレコードへの初めてのタグを付けませんか!
|
目次:
- <p> </p> <h1>High-Resolution Land-Use Change Dataset for China (1950–2100)</h1> <p>This dataset provides spatially explicit land-use maps for 31 provinces of China from 1950 to 2100 at a 5-year interval and 100 m spatial resolution. It integrates historical reconstructions (1950–2015) and future simulations (2020–2100) under eight SSP-RCP scenarios. The dataset accompanies the manuscript:</p> <div><em>Integrating historical reconstruction and future simulation for mapping high-resolution land-use change in China from 1950 to 2100</em></div> <div> </div> <div><strong>Note: </strong>Hong Kong, Macau, and Taiwan are excluded due to data limitations.</div> <div> </div> <h2>Coordinate System</h2> <p> </p> <div> <div>All GeoTIFF files are projected in the <em>Asia North Albers Equal Area Conic</em> projection (EPSG:102025). Pixel size is <em>100 m × 100 m</em>.</div> <br> <h2>Land-Use Classification</h2> <br> <div>Each pixel stores an integer value representing one of six land-use types:</div> <div> </div> <div> <table> <tbody> <tr> <td>Value</td> <td>Land-Use Type</td> </tr> <tr> <td>0</td> <td>NoData</td> </tr> <tr> <td>1</td> <td>Cropland</td> </tr> <tr> <td>2</td> <td>Forest</td> </tr> <tr> <td>3</td> <td>Grassland</td> </tr> <tr> <td>4</td> <td>Water bodies</td> </tr> <tr> <td>5</td> <td>Urban</td> </tr> <tr> <td>6</td> <td>Barren land</td> </tr> </tbody> </table> </div> <br><br> <h2>Directory Structure</h2> <br> <div> </div> <div>├── reconstruct_result/ # Historical reconstruction (1950–2015)</div> <div>│ ├── Anhui/</div> <div>│ │ ├── 1950.tif</div> <div>│ │ ├── 1955.tif</div> <div>│ │ ├── ...</div> <div>│ │ └── 2015.tif (14 time steps: 1950–2015 at 5-year intervals)</div> <div>│ ├── Beijing/</div> <div>│ ├── ...</div> <div>│ └── Zhejiang/ (31 provinces in total)</div> <div>│</div> <div>└── simulation_result/ # Future simulation (2020–2100)</div> <div> ├── Anhui/</div> <div> │ ├── ssp119/</div> <div> │ │ ├── 2020.tif</div> <div> │ │ ├── ...</div> <div> │ │ └── 2100.tif (17 time steps: 2020–2100 at 5-year intervals)</div> <div> │ ├── ssp126/</div> <div> │ ├── ssp245/</div> <div> │ ├── ssp370/</div> <div> │ ├── ssp434/</div> <div> │ ├── ssp460/</div> <div> │ ├── ssp534/</div> <div> │ └── ssp585/ (8 SSP-RCP scenarios in total)</div> <div> ├── Beijing/</div> <div> ├── ...</div> <div> └── Zhejiang/ (31 provinces in total)</div> <div> </div> <br> <h3>Provinces</h3> <br> <div>Anhui, Beijing, Chongqing, Fujian, Gansu, Guangdong, Guangxi, Guizhou, Hainan, Hebei, Heilongjiang, Henan, Hubei, Hunan, Inner Mongolia, Jiangsu, Jiangxi, Jilin, Liaoning, Ningxia, Qinghai, Shaanxi, Shandong, Shanghai, Shanxi, Sichuan, Tianjin, Xinjiang, Xizang, Yunnan, Zhejiang.</div> <br> <h3>SSP-RCP Scenarios</h3> <p>SSP1-1.9, SSP1-2.6, SSP2-4.5, SSP3-7.0, SSP4-3.4, SSP4-6.0, SSP5-3.4, SSP5-8.5</p> <br><br> <h3>File Format</h3> <br> <div>All data files are in <strong>GeoTIFF</strong> format with unsigned integer pixel values. NoData value is <strong>0</strong>.</div> <br> <h2>Data Summary</h2> <table> <tbody> <tr> <td> </td> <td>Period </td> <td>Spatial Resolution</td> <td>Provinces</td> <td>Scenarios</td> </tr> <tr> <td>Historical reconstruction</td> <td>1950–2015</td> <td>100 m</td> <td>31</td> <td>-</td> </tr> <tr> <td>Future simulation</td> <td>2020–2100</td> <td>100 m</td> <td>31</td> <td>8</td> </tr> </tbody> </table> <br><br> <h3>Usage</h3> <br> <div>The files can be opened with any GIS software (e.g., QGIS, ArcGIS) or programmatically with libraries such as GDAL or rasterio in Python.</div> </div>