Long Chen , Heng Li , Chunxiao Zhang , Wenhao Chu , Jonathan Corcoran , Tianbao Wang
{"title":"关中平原城市群热环境景观动因动态分析","authors":"Long Chen , Heng Li , Chunxiao Zhang , Wenhao Chu , Jonathan Corcoran , Tianbao Wang","doi":"10.1016/j.jag.2024.104239","DOIUrl":null,"url":null,"abstract":"<div><div>Climate change caused by rapid urbanization in the Guanzhong region of China is becoming an increasingly significant problem. Previous empirical studies have confirmed that landscape patterns inextricably linked with the thermal environment, but static results based on a single temporal cross section of image data provide only a partial understanding. In this paper, we constructed a dynamic framework using Weather Research and Forecasting Model (WRF) for temperature simulation and Geodetector to study the landscape factors and their interactions that influence near-surface temperature (NST) changes in the Guanzhong Plain Urban Agglomeration (GPUA) between 2000 and 2020. Results showed that the GPUA average NST increased by 0.012 °C and 0.053 °C in January and July from 2000 to 2020, respectively. In terms of the dynamic correlation between landscape patterns and NST, cropland (CPL) was negative, urban land (UBL) was positive, and the remainder of the landscapes differed in winter and summer. Furthermore, results from the Geodetector showed that UBL embodied a stronger influence in summer than during winter months. This finding helps to explain why the average NST increase is higher in summer than during winter. The Dynamic Q values (DQ) of the area-based landscape metrics were generally larger than those of other spatial configuration metrics, and the interaction results showed that the landscape metrics of various land-cover classifications were enhanced, indicating that the superposition effect among landscape metrics needs to be taken into account in landscape planning in addition to area factors. The study of the relationship between landscape patterns and thermal environment considering dynamic perspective using WRF offers an important theoretical reference allied with practical guidance for understanding and adapting to forthcoming change in our climate through which we can help drive sustainable development decisions of the GPUA.</div></div>","PeriodicalId":73423,"journal":{"name":"International journal of applied earth observation and geoinformation : ITC journal","volume":"134 ","pages":"Article 104239"},"PeriodicalIF":7.6000,"publicationDate":"2024-10-22","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Dynamic analysis of landscape drivers in the thermal environment of Guanzhong plain urban agglomeration\",\"authors\":\"Long Chen , Heng Li , Chunxiao Zhang , Wenhao Chu , Jonathan Corcoran , Tianbao Wang\",\"doi\":\"10.1016/j.jag.2024.104239\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"<div><div>Climate change caused by rapid urbanization in the Guanzhong region of China is becoming an increasingly significant problem. Previous empirical studies have confirmed that landscape patterns inextricably linked with the thermal environment, but static results based on a single temporal cross section of image data provide only a partial understanding. In this paper, we constructed a dynamic framework using Weather Research and Forecasting Model (WRF) for temperature simulation and Geodetector to study the landscape factors and their interactions that influence near-surface temperature (NST) changes in the Guanzhong Plain Urban Agglomeration (GPUA) between 2000 and 2020. Results showed that the GPUA average NST increased by 0.012 °C and 0.053 °C in January and July from 2000 to 2020, respectively. In terms of the dynamic correlation between landscape patterns and NST, cropland (CPL) was negative, urban land (UBL) was positive, and the remainder of the landscapes differed in winter and summer. Furthermore, results from the Geodetector showed that UBL embodied a stronger influence in summer than during winter months. This finding helps to explain why the average NST increase is higher in summer than during winter. The Dynamic Q values (DQ) of the area-based landscape metrics were generally larger than those of other spatial configuration metrics, and the interaction results showed that the landscape metrics of various land-cover classifications were enhanced, indicating that the superposition effect among landscape metrics needs to be taken into account in landscape planning in addition to area factors. The study of the relationship between landscape patterns and thermal environment considering dynamic perspective using WRF offers an important theoretical reference allied with practical guidance for understanding and adapting to forthcoming change in our climate through which we can help drive sustainable development decisions of the GPUA.</div></div>\",\"PeriodicalId\":73423,\"journal\":{\"name\":\"International journal of applied earth observation and geoinformation : ITC journal\",\"volume\":\"134 \",\"pages\":\"Article 104239\"},\"PeriodicalIF\":7.6000,\"publicationDate\":\"2024-10-22\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"International journal of applied earth observation and geoinformation : ITC journal\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://www.sciencedirect.com/science/article/pii/S1569843224005958\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q1\",\"JCRName\":\"REMOTE SENSING\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"International journal of applied earth observation and geoinformation : ITC journal","FirstCategoryId":"1085","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1569843224005958","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"REMOTE SENSING","Score":null,"Total":0}
Dynamic analysis of landscape drivers in the thermal environment of Guanzhong plain urban agglomeration
Climate change caused by rapid urbanization in the Guanzhong region of China is becoming an increasingly significant problem. Previous empirical studies have confirmed that landscape patterns inextricably linked with the thermal environment, but static results based on a single temporal cross section of image data provide only a partial understanding. In this paper, we constructed a dynamic framework using Weather Research and Forecasting Model (WRF) for temperature simulation and Geodetector to study the landscape factors and their interactions that influence near-surface temperature (NST) changes in the Guanzhong Plain Urban Agglomeration (GPUA) between 2000 and 2020. Results showed that the GPUA average NST increased by 0.012 °C and 0.053 °C in January and July from 2000 to 2020, respectively. In terms of the dynamic correlation between landscape patterns and NST, cropland (CPL) was negative, urban land (UBL) was positive, and the remainder of the landscapes differed in winter and summer. Furthermore, results from the Geodetector showed that UBL embodied a stronger influence in summer than during winter months. This finding helps to explain why the average NST increase is higher in summer than during winter. The Dynamic Q values (DQ) of the area-based landscape metrics were generally larger than those of other spatial configuration metrics, and the interaction results showed that the landscape metrics of various land-cover classifications were enhanced, indicating that the superposition effect among landscape metrics needs to be taken into account in landscape planning in addition to area factors. The study of the relationship between landscape patterns and thermal environment considering dynamic perspective using WRF offers an important theoretical reference allied with practical guidance for understanding and adapting to forthcoming change in our climate through which we can help drive sustainable development decisions of the GPUA.
期刊介绍:
The International Journal of Applied Earth Observation and Geoinformation publishes original papers that utilize earth observation data for natural resource and environmental inventory and management. These data primarily originate from remote sensing platforms, including satellites and aircraft, supplemented by surface and subsurface measurements. Addressing natural resources such as forests, agricultural land, soils, and water, as well as environmental concerns like biodiversity, land degradation, and hazards, the journal explores conceptual and data-driven approaches. It covers geoinformation themes like capturing, databasing, visualization, interpretation, data quality, and spatial uncertainty.