> REPLACE THIS LINE WITH YOUR PAPER IDENTIFICATION NUMBER (DOUBLE-CLICK HERE TO EDIT) < 1 Mapping high-resolution global impervious surface area: status and trends Huiqun Ren, Yu Liu, Xiaoyu Chang, Jie Yang, Xiao Xiao, Xin Huang, Senior Member, IEEE Abstract—Impervious surface area (ISA) mapping at the global scale has entered a new era. Currently, the number of high- resolution global ISA products is gradually increasing; however, a literature review that systematically investigates these ISA products is still lacking, which limits the application of these products. Thus, we provide a comprehensive analysis of the existing high-resolution global ISA products, concentrating on the aspects of the data sources, training samples, features, and methods. Moreover, we evaluate these products at multi-temporal and multi-spatial scales, using a series of independent test samples. The results demonstrate that the multi-temporal accuracy of the ISA products presents an increasing trend, due to the increase of the available sensors. Among the continuous time-series products (e.g., the updated new global impervious surface area (GISA 2.0), the global impervious surface area (GISA), global annual urban dynamics (GAUD), Global Human Settlement Layer (GHSL), and global artificial impervious areas (GAIA)), the accuracy of the GISA 2.0 outperforms the others at global, continental, and regional scales. However, the mapping performance of these products in small towns and arid and rural regions needs to be enhanced. In particular, we focus on the spatio-temporal disagreement of the ISA products. We show that the high disagreement regions are predominantly concentrated in eastern Asia, western Europe, and eastern North America. In addition, the high disagreement regions are characterized by low ISA density, high vegetation coverage, and high albedo bare ground coverage. Additionally, this paper concludes with some remarks about the future directions of global ISA mapping. Index Terms—Global, high resolution, impervious surface, Landsat, remote sensing, Sentinel, urban I. INTRODUCTION mpervious surface areas (ISAs) are usually covered by man-made materials that prevent water penetrating into soil. They usually include buildings, roads, roofs, etc. [1], [2]. In the past decades, urbanization has been growing This research was supported by the National Natural Science Foundation of China under Grant 41971295, and the Foundation for the Innovative Research Groups of the Natural Science Foundation of Hubei Province under Grant 2020CFA003. (Corresponding author: Yu Liu and Xin Huang) Huiqun Ren is with School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, PR China (e-mail: hqunren@whu.edu.cn). Yu Liu is with Key Laboratory of Aerospace Information Application of CETC, Shijiazhuang 050000, PC China, and also with School of Artificial Intelligence Xidian University, Xi'an 710071, PC China (e-mail: liuyu@stu.xidian.edu.cn). Xiaoyu Chang is with Key Laboratory of Aerospace Information Application of CETC, Shijiazhuang 050000, PC China (e-mail: lightraincxy@163.com). rapidly throughout the world, especially in developing countries such as China and India. Although urbanization has brought convenience to mankind, it has also led to climate, topographic, and ecological problems, e.g., urban heat islands, soil erosion, and air pollution[3]-[5]. The emergence of ISA products has provided new indicators for measuring human activity intensity, reflecting the urban development process and monitoring environmental quality [6], [7]. Furthermore, the mapping or estimation of ISA can help with the monitoring of population growth, urban expansion, and environmental change [8]-[10]. Global ISA mapping can provide reliable macroscopic information on global social, economic, and ecological factors, and is thus of great importance. From the 1970s to the 1980s, the main means of extracting ISA information was traditional surveying technology, such as field surveys, and aerial photo interpretation. Although the traditional surveying technology can offer accurate and reliable information on impervious surfaces, ISA mapping using the traditional surveying technology is limited in scope (i.e., limited to regional or local scales), expensive, and cannot easily be used to update datasets in a timely manner[11]. From the economic and technical point of view, traditional surveying technology is not suitable for mapping ISA datasets at a global scale. The remote sensing technology offers a new approach, with a high cost-benefit ratio, to mapping global ISA products. However, in the early years (i.e., the 1990s), the advancement of global ISA mapping was hindered by the poor availability of remote sensing images [12]. Up until the year 2000, there was only one map—The Digital Chart of the World (DCW or VMAP0)—that described the global urban areas [13]. The DCW product, as the earliest available global urban extent map with a scale of 1:1000000, represents the beginning of mapping global ISA. The period from the 2000s to the 2010s was a stage of development for global ISA mapping. During this time, satellite imagery and remote sensing techniques started to gain popularity for the mapping of global ISA datasets, and some Jie Yang is with School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, PR China (e-mail: yang9tn@163.com). Xiao Xiao is Spatial Information Technology Application Department, Changjiang River Scientific Research Institute, Wuhan, 430010, PR China (xiaoxiao@126.com). Xin Huang is with School of Remote Sensing and Information Engineering, Wuhan University, Wuhan 430079, PR China, and also with State Key Laboratory of Information Engineering in Surveying, Mapping and Remote Sensing, Wuhan University, Wuhan 430079, PR China (e-mail: xhuang@whu.edu.cn). I This article has been accepted for publication in IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing. This is the author's version which has not been fully e content may change prior to final publication. Citation information: DOI 10.1109/JSTARS.2022.3201380 This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License. For more information, see https://creativecommons.org/licenses/by-nc-nd/4.0/