Seasonal variations for combined effects of landscape metrics on land surface temperature (LST) and aerosol optical depth (AOD).

• There were season variations of influence factors on land surface temperature (LST) and aerosol optical depth (AOD) • A part of landscape metrics only effect simultaneously to relieve LST and AOD. • Interactive effects of factor layers on LST and AOD were explored. • The direct impact of landscape metrics on LST and AOD was greater than the indirect. Urban heat island (UHI) and air pollution are common environmental problems in urban areas. However, there is no comprehensive analysis of influencing factors and their interactions on land surface temperature (LST) and aerosol optical depth (AOD). To propose strategies to comprehensively mitigate LST and AOD by optimizing the landscape pattern, we used a series of statistical analysis methods to quantify the correlation, interactive contribution, and influence mechanism that how landscape metrics influenced LST and AOD directly or indirectly. In warmer seasons and year, the percentage of landscape (PLAND), largest patch index (LPI), aggregation index (AI) in forest land (FL), and mean shape index distribution (SHAPE_MN) in wetlands (WL) were negatively correlated with LST and AOD consistently. In contrast, landscape shape index (LSI) in FL, patch density (PD) and LSI in WL, edge density (ED), PD, LPI, SHAPE_MN, and LSI in artificial surfaces were positively correlated. Landscape metrics were weakly correlated with LST and AOD in winter. The climate condition layer was dominant overall. The dominant factor layer of landscape composition, landscape configuration and green quantity on LST and AOD differed in different land types and seasons. Landscape metrics and green quantity could directly or indirectly affect LST and AOD, with the direct effects of landscape metrics and green quantity being the primary. Increasing the percentage of FL, configuring large, aggregated and simple FL, regular, simple and better connected wetlands, and increasing patterns in artificial surfaces with simple, regular, small and better connectivity characteristics are effective mitigation measures. These findings can be helpful in developing UHI and air pollution adaptation strategies. [ABSTRACT FROM AUTHOR]