Global land use and land cover pattern has greatly changed in the past 50 years, which exerts direct or indirect influence on the climate change remarkably at both regional and global scales. Therefore, observing and estimating the land use impacts on surface climate is essential and has been continuously promoted by researchers. This paper explores the advancement in the models, data, and application for observing and estimating the land use impacts on surface climate and points out further research needs and priorities, which hopefully will provide some references for related studies. 1. Introduction The study of land use and land cover change (LUCC) and its impact on climate is of great significance [1]. There have been tremendous changes in the global land use pattern in the past 50 years, which have enormous influence on the global climate change. Quantitative analysis for the impacts of LUCC on surface climate is one of the core scientific issues to understand the influence of human activities on global climate. For instance, the diverse role of LUCC on precipitation has been documented and land conversion continues at a rapid pace, making this type of human induced disturbances of the climate system continue and become even more significant [2]. The review paper of Deng et al. [1] comprehensively analyzed the primary scientific issues about the impacts of LUCC on the regional climate and reviewed the progress in relevant researches. Earlier as there was no systematic review paper, Deng et al. reviewed the systematic modeling of impacts of LUCC on regional climate for the first time. This paper further develops a systematic review to cover the advances in this research field, in which the improved data, upgraded models, and case studies in observation and estimation of land use impacts on climate changes have been introduced. 2. Advancement in LUCC Dataset 2.1. Previous Dataset LUCC has been recognized as a key component in global environmental change. It was not until the last twenty years that land cover products were applied to most of the climate models. These products were initially compiled from maps, ground surveys, and various national statistical sources, which have inherent limitations [3–5]. In the mid-1990s, global-scale land cover products generated from remote sensing images became available. Various land cover datasets were usually classified from remote sensing images, including MSS/TM/ETM+, SPOT, and MODIS, which have been used in numerous climate modeling studies at regional to global scales. Since the 1990s, a series of land
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