Land underpins nearly all human activities, with different economic sectors exhibiting varying degrees of dependence on land resources. Sector-specific land use analysis is essential for optimizing resource allocation, improving land-use efficiency, and promoting sustainable urban development. However, existing land-use classification data are often coarse-grained and lack the detail needed to capture land use at the level of national economic sectors. To address this limitation, this study constructs a sector-specific land use dataset covering 97 and 42 national economic sectors across 11 cities in the Guangdong–Hong Kong–Macao Greater Bay Area for the period 2015–2022. This dataset enables systematic examination of sectoral land use patterns, identification of high land-consuming and low-efficiency sectors, and provides empirical evidence to guide industrial restructuring, spatial planning, and resource–environment policy design. Moreover, the dataset can be integrated with complementary indicators (e.g., carbon emissions, water footprints) to support ecological management and low-carbon development strategies.
Li et al. (Thu,) studied this question.