<b>Spatially Explicit Land-Use Transitions Reveal the Landscape Drivers of Urban Warming i

Spatially explicit land-use transition rasters and land surface temperature data for the Guangdong-Hong Kong-Macao Greater Bay Area across three time periods. The dataset integrates multi-source geospatial data, including 30m annual land cover maps and 1km MODIS temperature composites, processed into a 1000m analytical grid. Shengyu Guan published this 107.9 MB dataset under a CC-BY-4.0 license in May 2026.

Use Cases

• Modeling urban warming drivers based on land-use transition types like appearing, merging, and contracting.
• Analyzing phased warming or cooling processes based on ΔLST rasters for 2005-2015, 2015-2024, and 2005-2024.
• Calculating landscape metrics for land-use classes (agricultural, forest, impervious, water) within a 1000m fishnet grid.
• Training machine learning models (e.g., LightGBM-SHAP) to explain temperature changes based on spatial transition patterns.

Strengths

• Includes data for three distinct years (2005, 2015, 2024) enabling longitudinal analysis.
• Integrates two key data types: 30m resolution land-use maps and 1km resolution land surface temperature data.
• Provides spatially explicit transition rasters detailing eight patch-level dynamics for four main land-use classes.
• Data is clipped to a defined regional boundary (Guangdong-Hong Kong-Macao Greater Bay Area) and integrated into a consistent 1000m analytical grid.

Limitations

• Column-level documentation is absent; field semantics must be inferred after download.
• Row count is unknown, which may limit suitability assessment for some analytical tasks.
• The 1km resolution of the temperature data may be too coarse for micro-scale urban analysis.

Provenance

Source

Land-use data derived from the 30m annual land cover dataset of China; LST data from MODIS Terra and Aqua products.

Collection Method

Data extracted and harmonized using Google Earth Engine, then integrated into a fishnet grid for analysis.

Time Range

2005, 2015, and 2024.

Freshness

Last updated 2026-05-26 09:58:45; freshness should be verified.

Geography

Guangdong-Hong Kong-Macao Greater Bay Area (GBA).