Peer Review #2 of "Analyzing the interpretative ability of landscape pattern to explain thermal environmental effects in the Beijing-Tianjin-Hebei urban agglomeration (v0.2)"

Abstract

The development of the urban agglomeration has caused drastic changes in landscape pattern and increased anthropogenic heat emission and lead to the urban heat island (UHI) effect more serious. Therefore, understanding the interpretation ability of landscape pattern on the thermal environment has gradually become an important focus. In the study, the spatial heterogeneity of the surface temperature was analyzed using the hotspot analysis method which was improved by changing the calculation of space weight. Then the interpretation ability of a single landscape and a combination of landscapes to explain surface temperature was explored using the Pearson correlation coefficient and ordinary least squares (OLS) regression from different spatial levels, and the spatial heterogeneity of the interpretation ability was explored using geographical weighted regression (GWR) under the optimal granularity (5 km × 5 km). The results showed that: (1) The hot spots of surface temperature were distributed mainly in the plains and on the southeast hills, where the landscapes primarily include ArtLS and FarmLS. The cold spots were distributed mainly in the northern hills, which are dominated by ForLS. (2) On the whole, the interpretative ability of ForLS, FarmLS, ArtLS, GreenLSP and EcoLSP to explain surface temperature was stronger, whereas the interpretative ability of GraLS and WetLS to explain surface temperature was weaker. The interpretation ability of landscape pattern to explain surface temperature was obviously different in different areas. Specifically, the ability was stronger in the hills than in the plain and plateau. The results are intended to provide scientific basis for adjusting landscape structural, optimizing landscape patterns, alleviating the UHI effect and coordinating the balance among cities within the urban agglomeration.