ArticleHigh-resolution urban land-cover mapping and landscape analysis of the 42 major cities in China using ZY-3 satellite images
Graphical abstract
Introduction
Urbanization, which is characterized by a population shift from rural to urban and a transformation in the surface physical and geometric properties, has dramatically changed human habitats [1]. The evolution of the urban landscape has had a pronounced influence on the energy balance, carbon cycle, hydrological process, and climate of the urban systems [2], [3]. Meanwhile, the accompanying problems include air and water pollution, the urban heat island (UHI) effect, environmental noise, and biodiversity reduction, which are threatening our health and future development [4], [5], [6]. Measuring and analyzing the urban landscape is thus essential for many applications in climatology, hydrology, environmental planning, and resource management, where detailed and precise urban land-cover maps are indispensable [7], [8], [9].
It is widely recognized that the satellite remote sensing technique can provide an effective tool for land-cover mapping at local, regional, and global scales [10]. Several global land-use/cover datasets have been developed based on satellite images, with spatial resolutions of 300 m to about 1 km [11], [12], [13], [14]. However, the drawbacks of these datasets are the coarse spatial resolutions, low accuracies, and poor agreement concerning time, space, and theme [15], [16]. With the free availability of medium-resolution satellite images such as the Landsat and Sentinel series, more precise land-cover datasets with 10–30 m resolutions have become feasible. At the global level, the state-of-the-art products include the Finer Resolution Observation and Monitoring of Global Land Cover (FROM-GLC) maps [17], the Global Land Cover Dataset (GlobeLand30) [18], FROM-GLC-agg [19], and FROM-GLC10 [20]. At the regional level, the products include the European CORINE dataset [21], the United States National Land Cover Dataset (NLCD) [22], and the National Land Cover/Use Database of China (NLUD-C) [23]. Nevertheless, restricted by their spatial resolutions, none of these datasets can offer the necessary level of details within urban areas, such as individual buildings, sidewalks, and urban green spaces (e.g., roadside trees), which are crucial for the in-depth interpretation of the urban landscape. In this context, although the existing products are effective for the large-scale measurement and analysis of urban areas, they are still far from satisfactory for some urban planning and environmental analysis applications, due to the dearth of spatial details [8].
High-resolution satellite images can minimize the mixed-pixel phenomenon, and can thus provide abundant information in the spatial domain. Given their potential in delineating the structure and shape of individual objects (e.g., buildings, trees), high-resolution satellite images have been successfully applied in many urban-related studies, e.g., monitoring subtle urban dynamics [24], interpreting urban scenes [25], and investigating the effects of the landscape on the environment, such as the UHI effect [26]. Nevertheless, these studies were usually carried out in several small-size urban areas, for the purpose of classification algorithm analysis. To the best of our knowledge, to date, there has been very little practical research on techniques for high-resolution urban land-cover mapping over a large number of cities, and the related urban map products are also lacking.
The Ziyuan-3 (ZY-3) satellites are the first high-resolution civilian stereo mapping satellites in China, and the ZY-3 01 and ZY-3 02 satellites were successfully launched in 2012 and 2016, respectively. With a large swath width (50 km), the ZY-3 satellites can cover a large spatial extent with a spatial resolution of 2.1 m. The satellites are equipped with three high-resolution panchromatic cameras positioned 22° from each other to provide forward, nadir, and backward imaging modes, which enables them to provide abundant three-dimensional (3D) information to support accurate classification in complex urban scenes. Compared with other multi-angle high-resolution satellites (e.g., the WorldView series and the Cartosat series), the unique imaging mode of the ZY-3 satellites (along-track stereo mode with stable nadir-view cameras) enables them to provide nearly orthographic images, which can effectively minimize the angular effects, and therefore delineate urban surface cover more precisely. The angular effects can trigger distortion and occlusion of the land-cover maps, especially in urban scenes with complex high-rise structures, where the occlusion of buildings seriously hampers the accurate interpretation of the land-cover footprint [27]. With the available ZY-3 satellite imagery, we now have an unprecedented opportunity for mapping urban land cover.
In recent years, from the perspective of high-resolution image classification, auxiliary geospatial data has been increasingly utilized in land-use/cover classification, e.g., OpenStreetMap (OSM), open social data, and socioeconomic data [28], [29]. However, the related studies have been carried out only at the local scale or in a small area, and we do not yet have an effective and feasible mapping scheme for large-scale use. In this context, we propose an operational mapping approach by integrating ZY-3 high-resolution satellite imagery and auxiliary geospatial data (A-map, Map World, and OSM). Under this framework, we developed a high-resolution (2 m) urban land-cover map (Hi-ULCM) covering the 42 major cities of China. China is currently undergoing urbanization at an unprecedented rate, and by the end of 2017, the urban population in China accounted for 58.52% [30], which is higher than the world average level (55%) [31]. During the past few years, significant land-cover changes have occurred in China [32], and a unified high-resolution land-cover map is urgently required. The Hi-ULCM dataset has the potential to fill this gap by providing detailed land-cover information of the urban areas. In this paper, based on this new land-cover dataset, the landscape patterns of the 42 major cities of China are analyzed and compared. Moreover, the potential of the Hi-ULCM dataset is fully discussed.
Section snippets
Materials and methods
In this study, we focused on the 42 major cities in China, including four municipalities, 26 provincial capitals, and 12 large cities (Fig. 1). These cities are spread over a wide range of climatic zones [33], and represent a variety of urban sizes, landscape characteristics, and urbanization intensities. The 42 cities were stratified into three levels according to the urban population in 2016 [34]: level Ⅰ (greater than 5 million, 8 cities), level II (2 million to 5 million, 20 cities), and
Results and validation
The Hi-ULCM product for two representative cities is presented in Fig. 3. We also provide the results for an additional four representative cities in Fig. S1 (online). These maps demonstrate that the footprint of the land cover, e.g., buildings, can be well depicted by the Hi-ULCM dataset. In particular, the product can delineate compact and small buildings, such as those found in urban villages and residential areas. Some buildings with low reflectance that are difficult to distinguish from
Discussion
Based on the Hi-ULCM dataset, the land-cover composition of the 42 cities was analyzed with respect to the climatic zones (Fig. 5a) and city levels (Fig. 5b). The area percentage of OISAs is the largest among the 42 cities, with an average percentage of 27.49%, followed by buildings (16.23%), grass/shrubs (15.22%), trees (14.18%), roads (11.13%), soil (10.08%), and water (5.67%). The area percentages of artificial surfaces (i.e., buildings, roads, and OISAs) do not exhibit significant
Conclusion
In this paper, we have proposed an operational mapping framework for high-resolution urban land-cover mapping, and we have described the development of the first high-resolution (2 m) urban land-cover product—Hi-ULCM—covering the 42 major cities of China, courtesy of the high-resolution images acquired by the ZY-3 satellites. The proposed framework achieved a satisfactory performance, with an OA of 88.55%. Meanwhile, the PA and UA of each land-cover type exceeded 85%, for most of the
Conflict of interest
The authors declare that they have no conflict of interest.
Acknowledgments
This work was supported by the National Natural Science Foundation of China (41771360 and 41971295), the National Program for Support of Top-notch Young Professionals, the Hubei Provincial Natural Science Foundation of China (2017CFA029), and the National Key Resarch & Development Program of China (2016YFB0501403). Maps in this article were reviewed by Ministry of Natural Resources of the People’s Republic of China (GS(2020)819).
Author contributions
Xin Huang and Jianya Gong conceived and supervised the work; Ying Wang, Jiayi Li, Xiaoyu Chang, and Yinxia Cao designed the method; Jiayi Li, Xiaoyu Chang and Yinxia Cao helped with the data processing; the remaining authors contributed collection of data and samples; all authors helped in writing the paper.
Xin Huang is currently a Luojia Distinguished Professor of Wuhan University, China. He is the Founder of the Institute of Remote Sensing Information Processing, School of Remote Sensing and Information Engineering, Wuhan University. His research interests include remote sensing image processing methods and applications.
References (59)
- et al.
The relationship between urbanization, energy use and carbon emissions: evidence from a panel of association of Southeast Asian Nations (ASEAN) countries
J Clean Prod
(2016) - et al.
Urbanisation and health in China
Lancet
(2012) - et al.
Epidemic transition of environmental health risk during China’s urbanization
Sci Bull
(2017) - et al.
Urban biodiversity in China: who are winners? Who are losers?
Sci Bull
(2016) - et al.
Urban growth models: progress and perspective
Sci Bull
(2016) - et al.
Implementation of China’s new urbanization strategy requires new thinking
Sci Bull
(2017) - et al.
High-resolution multi-temporal mapping of global urban land using Landsat images based on the google earth engine platform
Remote Sens Environ
(2018) - et al.
Modis collection 5 global land cover: algorithm refinements and characterization of new datasets
Remote Sens Environ
(2010) - et al.
Some challenges in global land cover mapping: an assessment of agreement and accuracy in existing 1 km datasets
Remote Sens Environ
(2008) - et al.
Global land cover mapping at 30 m resolution: a POK-based operational approach
ISPRS J Photogr Remote Sens
(2015)
Stable classification with limited sample: transferring a 30-m resolution sample set collected in 2015 to mapping 10-m resolution global land cover in 2017
Sci Bull
Completion of the 2011 national land cover database for the conterminous united states – representing a decade of land cover change information
Photogr Eng Remote Sens
A 2010 update of national land use/cover database of China at 1:100000 scale using medium spatial resolution satellite images
Remote Sens Environ
Multi-level monitoring of subtle urban changes for the megacities of China using high-resolution multi-view satellite imagery
Remote Sens Environ
Angular difference feature extraction for urban scene classification using ZY-3 multi-angle high-resolution satellite imagery
ISPRS J Photogr Remote Sens
Investigating the effects of 3d urban morphology on the surface urban heat island effect in urban functional zones by using high-resolution remote sensing data: a case study of Wuhan, central China
ISPRS J Photogr Remote Sens
Understanding angular effects in VHR imagery and their significance for urban land-cover model portability: a study of two multi-angle in-track image sequences
ISPRS J Photogr Remote Sens
Exploring semantic elements for urban scene recognition: deep integration of high-resolution imagery and OpenStreetMap (OSM)
ISPRS J Photogr Remote Sens
Integrating earth observation and GIScience for high resolution spatial and functional modeling of urban land use
Comput Environ Urban Syst
40-Year (1978–2017) human settlement changes in China reflected by impervious surfaces from satellite remote sensing
Sci Bull
Surface urban heat island in China’s 32 major cities: spatial patterns and drivers
Remote Sens Environ
Random forest in remote sensing: a review of applications and future directions
ISPRS J Photogr Remote Sens
Analysis of the relationships between environmental noise and urban morphology
Environ Pollut
A global comparative analysis of urban form: applying spatial metrics and remote sensing
Landsc Urban Plann
Urban form revisited-selecting indicators for characterising European cities
Landsc Urban Plann
Landscape pattern indices for evaluating urban spatial morphology – a case study of Chinese cities
Ecol Indic
Attribution of PM2.5 exposure in Beijing-Tianjin-Hebei region to emissions: implication to control strategies
Sci Bull
Semantic classification of urban buildings combining VHR image and GIS data: an improved random forest approach
ISPRS J Photogramm Remote Sens
Object-based land cover mapping and comprehensive feature calculation for an automated derivation of urban structure types at block level
Remote Sens Environ
Cited by (0)
Xin Huang is currently a Luojia Distinguished Professor of Wuhan University, China. He is the Founder of the Institute of Remote Sensing Information Processing, School of Remote Sensing and Information Engineering, Wuhan University. His research interests include remote sensing image processing methods and applications.
Ying Wang is currently pursuing the master’s degree in the School of Remote Sensing and Information Engineering, Wuhan University. Her research interests include urban environment and urban land cover mapping.
- 1
These authors contributed equally to this work.