AI Summary & Key Takeaways
AI InsightThe results showedthat: (1) PM2.5 concentration was increasing in Yangtze River Delta from 1998 to 2015; (2) PM2.5 concentrationwas negatively correlated with the forest land and grassland, while positively correlated with the urban constructionland; (3) At the level of landscape type, the urban construction land, water body and farm land PLAND,LPI, ED, MPS, AWMSI were positively correlated, the urban construction land and water body PD were positivelycorrelated with PM2.5, the farm land PD was negatively correlated with PM2.5, and the forest land and grasslandPLAND, PD, LPI, ED, MPS and AWMSI were negatively correlated with PM2.5. (4) In the integral landscape ofland use, AWMSI was negatively correlated with PM2.5 concentration.
📌 3 Key Takeaways
Özet
Land cover-landscape pattern affects the atmospheric environment directly or indirectly, and the understandingof the atmospheric environment response to land cover - landscape pattern is of great significance to themaintenance and improvement of ecological environment. In this paper, such 9 landscape metrics as PLAND, PD,LPI, ED, MPS, AWMSI, CONTAG, SHDI and SHEI were selected by remote sensing inversion of PM2.5 data andland use data in long time series. The correlation analysis and multiple stepwise regression analysis were alsoused to analyze the effect of land use and landscape pattern on PM2.5 in Yangtze River Delta. The results showedthat: (1) PM2.5 concentration was increasing in Yangtze River Delta from 1998 to 2015; (2) PM2.5 concentrationwas negatively correlated with the forest land and grassland, while positively correlated with the urban constructionland; (3) At the level of landscape type, the urban construction land, water body and farm land PLAND,LPI, ED, MPS, AWMSI were positively correlated, the urban construction land and water body PD were positivelycorrelated with PM2.5, the farm land PD was negatively correlated with PM2.5, and the forest land and grasslandPLAND, PD, LPI, ED, MPS and AWMSI were negatively correlated with PM2.5. (4) In the integral landscape ofland use, AWMSI was negatively correlated with PM2.5 concentration. It is of great significance to control PM2.5pollution from the perspective of land use planning and contributed to an estimation methods of PM2.5 concentrationsusing land use type and land use landscape metrics in the absence of missing PM2.5 monitoring data.