{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2024,9,9]],"date-time":"2024-09-09T13:43:08Z","timestamp":1725889388678},"reference-count":65,"publisher":"MDPI AG","issue":"17","license":[{"start":{"date-parts":[[2020,8,20]],"date-time":"2020-08-20T00:00:00Z","timestamp":1597881600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Youth Fund of Ministry of Education Laboratory for Earth Surface Processes, Peking University","award":["7100602014."]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["Remote Sensing"],"abstract":"Urbanization changes the land surface environment, which alters the regional climate system. In this study, we took the Haihe River Basin in China as a case study area, as it is highly populated and experienced rapid urbanization from 2000\u20132015. We investigated how land use and cover change (LUCC) was driven by urban land development affects land-climate dynamics. From 2000\u20132015, we collected data from the land use and cover database, the remote sensing database of the Moderate Resolution Imaging Spectroradiometer (MODIS) series, and the meteorological database to process and generate regional datasets for LUCC maps. We organized data by years aligned with the selected indicators of land surface, normalized difference vegetation index (NDVI), albedo, and land surface temperature (LST), as well as of regional climate, cloud water content (CWC), and precipitation (P). The assembled datasets were processed to perform statistical analysis and conduct structural equation modelling (SEM). Based on eco-climatology principles and the biophysical process in the land-climate dynamics, we made assumptions on how the indicators connected to each other. Moreover, we testified and quantified them in SEM. LUCC results found that from 2000\u20132015 the urban area proportion increased by 214% (2.20\u20136.91%), while the agricultural land decreased by 7.2% (53.05\u201349.25%) and the forest increased by 4.3% (10.02\u201310.45%), respectively. This demonstrated how cropland intensification and afforestation happened in the urbanizing basin. SEM results showed that the forest had both positive and negative effects on the regional hydrological cycle. The agricultural land, grassland, and shrub had indirect effects on the P via different biophysical functions of LST. The overall effects of urbanization on regional precipitation was positive (pathway correlation coefficient = 0.25). The interpretation of how urbanization drives LUCC and alters regional climate were herein discussed in different aspects of socioeconomic development, biophysical processes, and urbanization-related atmospheric effects. We provided suggestions for further possible research on monitoring and assessment, putting forth recommendations to advance sustainability via land planning and management, including agricultural land conservation, paying more attention to the quality growth of forest rather than the merely area expansion, integrating the interdisciplinary approach, and assessing climatic risk for extreme precipitation and urban flooding.<\/jats:p>","DOI":"10.3390\/rs12172701","type":"journal-article","created":{"date-parts":[[2020,8,21]],"date-time":"2020-08-21T01:13:42Z","timestamp":1597972422000},"page":"2701","source":"Crossref","is-referenced-by-count":19,"title":["Urbanization-Driven Changes in Land-Climate Dynamics: A Case Study of Haihe River Basin, China"],"prefix":"10.3390","volume":"12","author":[{"ORCID":"http:\/\/orcid.org\/0000-0003-2830-4076","authenticated-orcid":false,"given":"Zhouyuan","family":"Li","sequence":"first","affiliation":[{"name":"Institute of Ecology, College of Urban and Environmental Sciences, and Ministry of Education Laboratory for Earth Surface Processes, Peking University, Beijing 100871, China"}]},{"given":"Yanjie","family":"Xu","sequence":"additional","affiliation":[{"name":"Resource Ecology Group, Wageningen University and Research, 6708PB Wageningen, The Netherlands"}]},{"given":"Yingbao","family":"Sun","sequence":"additional","affiliation":[{"name":"NEO.B.V, 3811HN Amersfoort the Netherlands; Laboratory of Geo-Information Science and Remote Sensing, Wageningen University and Research, 6700AA Wageningen, The Netherlands"}]},{"given":"Mengfan","family":"Wu","sequence":"additional","affiliation":[{"name":"Faculty of Geographical Science, Beijing Normal University, Beijing 100875, China"}]},{"given":"Bin","family":"Zhao","sequence":"additional","affiliation":[{"name":"Vocational and Technical Education College, Fujian Normal University, No.8 Shangsan Road, Cangshan District, Fuzhou 350007, China"}]}],"member":"1968","published-online":{"date-parts":[[2020,8,20]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"251","DOI":"10.1016\/j.agee.2003.09.008","article-title":"Detecting Important Categorical Land Changes While Accounting for Persistence","volume":"101","author":"Pontius","year":"2004","journal-title":"Agric. 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