The Differences and Influence Factors in Extracting Urban Green Space from Various Resolutions of Data: The Perspective of Blocks

Abstract

The appropriate resolution has been confirmed to be crucial to the extraction of urban green space and the related research on ecosystem services. However, the factors affecting the differences between various resolutions of data in certain application scenarios are lacking in attention. To fill the gap, this paper made an attempt to analyze the differences of various resolutions of data in green space extraction and to explore where the differences are reflected in the actual land unit, as well as the factors affecting the differences. Further, suggestions for reducing errors and application scenarios of different resolutions of data in related research are proposed. Taking a typical area of Nanjing as an example, data taken by DJI drone (0.1 m), GaoFen-1 (2 m) and Sentinel-2A (10 m) were selected for analysis. The results show that: (1) There were minimal differences in the green space ratio of the study area calculated by different resolutions of data on the whole, but when subdivided into each land use type and block, the differences were obvious; (2) The function, area and shape of the block, as well as the patch density and aggregation degree of the internal green space, had a certain impact on the differences. However, the specific impact varied when the block area was different; and (3) For the selection of the data source, the research purpose and application scenarios need to be comprehensively considered, including the function and attributes of the block, the distribution characteristics of green space, the allowable error limits and the budget. The present study highlighted the reasons of differences and hopefully it can provide a reference for the data selection of urban green space in the practical planning and design.