2026-10-11T20:15:06Z https://www.scidb.cn/oai

10.57760/sciencedb.13533 2024-05-29T11:06:26Z

2024-05-29 A dataset of spatial distribution of construction land suitability with a spatial resolution of 30m on the Qinghai-Tibet Plateau doi:10.57760/sciencedb.13533 en The Qinghai-Tibet Plateau is an important ecological security barrier, and clarifying the suitability space of construction land is significant for coordinating the relationship between ecological protection and human activities and optimizing the spatial distribution of population and industry. Based on the evaluation model of human activity suitability of land resources and the bare land digital elevation model of FABDEM with forests and buildings removed, we produced a dataset of spatial distribution of construction land suitability with a spatial resolution of 30m on the Qinghai-Tibet Plateau. This dataset reveals that the suitability classes of highly suitable, suitable, moderately suitable, marginally suitable, and unsuitable cover the area of 3,593 km², 100,258 km², 166,033 km², 208,411 km², and 2,104,249 km², accounting for 0.14%, 3.88%, 6.43%, 8.07%, and 81.48% of the total area, respectively. Finally, we verified the accuracy of this dataset using the existing construction land layer from land use/ cover data of CNLUCC and GlobeLand30. We found that this dataset has high explanatory power for the spatial distribution of the existing construction land, with an overall accuracy of 76.41% and 81.65%, respectively. The dataset is stored in FGDBR raster data format with a spatial resolution of 30 m, a data type of 32-bit unsigned integer, valid data from 0 to 782200, and a scaling factor of 0.000001. This dataset can provide decision support for ecological migration, constructing rural settlements in border areas, and optimizing territorial development and conservation patterns on the Qinghai-Tibet Plateau. FABDEM; Land resources; Construction land; Land-use Suitability; Qinghai-Tibet Plateau Yang Hua Xu Yong PUBLIC https://creativecommons.org/licenses/by/4.0/ dataset http://www.doi.org/10.11922/11-6035.csd.2023.0165.zh Science Data Bank