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Editorial

Spatiotemporal Analysis of Urbanization Using GIS and Remote Sensing in Developing Countries

1
Faculty of Life and Environmental Sciences, University of Tsukuba, 1-1-1, Tennodai, Tsukuba 305-8572, Ibaraki, Japan
2
Department of Plant and Environmental Sciences, School of Natural Resources, Copperbelt University, P.O. Box 21692, Kitwe 10101, Zambia
3
Department of Environmental Management, Faculty of Social Sciences and Humanities, Rajarata University of Sri Lanka, Mihintale 50300, Sri Lanka
*
Author to whom correspondence should be addressed.
Sustainability 2021, 13(7), 3681; https://0-doi-org.brum.beds.ac.uk/10.3390/su13073681
Submission received: 15 March 2021 / Revised: 19 March 2021 / Accepted: 23 March 2021 / Published: 26 March 2021
The international statistics show that the global urban population will increase by up to 68% by 2050 [1]. The United Nations (UN) projection shows that urbanization will be faster in Asian and African countries than in other continents [1]. In the future, rapid urbanization will bring severe environmental and socio-economic problems, such as land degradation, loss of urban ecosystem services, urban heat islands, air pollution, flooding, health, urban poverty, crimes and violence, and traffic congestion [2,3]. Thus, sustainable urban development has become a widely discussed concept in various disciplines, such as geography, engineering, economics, politics, and sociology. Sustainable urban development is viewed as a way of preventing, reducing, and mitigating the environmental and socio-economic negative impacts of urbanization, notwithstanding its positive results (i.e., social and economic improvement of livelihoods). Hence, capturing the spatial-temporal variation of urbanization patterns will help introduce proper sustainable urban planning in developing countries.
During the last two decades, many researchers have focused on studying urbanization patterns. However, the scarcity of spatial data has been an obstacle to study urbanization quantitatively, especially in developing countries of Asia and Africa [4]. The use of remote sensing data and geographical information systems (GIS) techniques can overcome the limitations faced in these developing countries [4]. The data, such as land use and land cover, land surface temperature, population density, and energy consumption, can be extracted based on remote sensing in various spatial and temporal resolutions. GIS techniques can be used to analyze the urbanization patterns and predict future patterns [5]. Thus, the link between urbanization and sustainable urban development has increasingly become a principal issue in designing and developing sustainable cities at the local, regional, and global levels.
This Special Issue discusses the usefulness of the spatiotemporal analysis of urbanization using GIS and remote sensing in developing countries, with a particular focus on future urban sustainability in Asia and Africa. We contribute to this theme through 16 articles to help achieve sustainability in metropolitan cities in Asia and Africa.
The first article in the Special Issue focuses on the simulation of land use and land cover (LULC) changes to forecast strategies for urban sustainability. “A Cellular Automata Model Constrained by Spatiotemporal Heterogeneity of the Urban Development Strategy for Simulating Land-use Change: A Case Study in Nanjing City, China” [6] considered the insufficient research on the spatiotemporal heterogeneity of urban development strategies and its application to constraining cellular automata models (CA) models that have become increasingly popular in land-use and land-cover change (LULC) simulations. The authors propose a zoning transition rule and planning influence that consists of a development grade coefficient and traffic facility coefficient in the CA model to reflect the top-down and heterogeneous characteristics of spatial layout and the dynamic and heterogeneous external interference of traffic facilities on land-use development. They contend that spatial layout planning is important for urban green, humanistic, and sustainable development.
The following two articles included in the Special Issue analyze the spatial-temporal dynamics of LULC and landscape pattern changes along with their driving forces for sustainable urban development. “Remote Sensing-Based Analysis of Landscape Pattern Evolution in Industrial Rural Areas: A Case of Southern Jiangsu, China” [7] analyzed the damage on rural landscapes and the ecological environment caused by the rapid economic development of rural industrial areas using Landsat data. The authors used landscape pattern indices to capture the variation, progress, characteristics, and driving forces of landscape pattern evolution over the last 37 years. The authors suggest that their study is important in understanding the evolutionary dynamics of the urban–rural industry during urbanization that can lead to better strategies for improving the landscape pattern and promoting the development of the ecological environment. It can also be used as a reference for other developing countries for the sustainability of urban and rural development during industrialization, which helps achieve regional sustainability. “Spatial-Temporal Dynamic Analysis of Land Use and Landscape Pattern in Guangzhou, China: Exploring the Driving Forces from an Urban Sustainability Perspective” [8] focused on (i) analyzing the spatial-temporal dynamics of LULC and landscape pattern changes; (ii) figuring out the driving forces of the LULC changes; (iii) assessing the completion and value of green space systems construction; and (iv) forecasting the trend of land use and putting forward proposals about improving environmental quality. The authors use the above four areas of focus to discuss LULC changes and their causes and propose potential future trends of urban development from the perspective of sustainability.
The Special Issue also contains three articles addressing the dynamics of LULC changes and the rate of urban expansion towards achieving sustainable urban growth. “Quantitative Influence of Land-Use Changes and Urban Expansion Intensity on Landscape Pattern in Qingdao, China: Implications for Urban Sustainability” [9] used land-use change and urban expansion intensity (UEI) as inducement factors for changes in landscape patterns and stepwise regression and geographically weighted regression (GWR) were applied to quantify magnitude effects on landscape patterns, respectively. The study suggests that land-uses have different contributions to changes in the urban landscape patterns at different urban development zones (downtown, plain suburban area, and mountainous suburban areas). The authors recommend a compact city and protection policy that should be adapted to different regions in the study area to achieve strong urban sustainability. “An Analysis of Urban Land Use/Land Cover Changes in Blantyre City, Southern Malawi (1994–2018)” [10] addresses how the spatial and temporal LULC changes by rapid and unplanned urban growth could have adverse environmental and social consequences. The findings of the study reveal the pressure of human activities on the land and natural environment and provide a basis for sustainable urban planning and development in the study area. “Spatiotemporal Patterns and Driving Forces of Urban Expansion in Coastal Areas: A Study on Urban Agglomeration in the Pearl River Delta, China” [11] focused on capturing the spatiotemporal patterns of urban land expansion and further analyze the dynamic driving forces of urban agglomeration. The study applied the urban-land expansion intensity index, urban-land expansion difference index, fractal dimension, driving force analysis, and driving factors to facilitate their analysis. The authors show how understanding the mechanisms of urban agglomeration could provide useful information for coastal urban planning and also offers new knowledge regarding the interactions between different drivers of urban land expansion.
The next four articles in the Special Issue address a critical environmental impact of urbanization that threatens sustainability; the urban heat island (UHI) effect. “Spatiotemporal Patterns and Drivers of the Surface Urban Heat Island in 36 Major Cities in China: A Comparison of Two Different Methods for Delineating Rural Areas” [12] used the administrative borders (AB) method and an optimized simplified urban-extent (OSUE) algorithm to calculate and map the spatiotemporal patterns of the surface urban heat island intensity (SUHI) in 36 major cities in mainland China and explored whether administrative borders represent an appropriate standard range for the rural extent in SUHI intensity calculations. The study not only explores the standardization of the calculation of urban heat intensity but also provides insights into the relationship between urban development and the SUHI as an important issue of urban sustainability. “The Impacts of the Expansion of Urban Impervious Surfaces on Urban Heat Islands in a Coastal City in China” [13] used a combination of remote sensing data and spatial statistical methods to assess the effects of rapid urbanization on the UHI. The results of the study are presented as a useful proxy indicator for implementing sustainable planning of urban areas and for the mitigation of the effects of UHIs. “The Impacts of Landscape Changes on Annual Mean Land Surface Temperature in the Tropical Mountain City of Sri Lanka: A Case Study of Nuwara Eliya (1996–2017)” [14] addressed the UHI issue by investigating the impacts of changes in the urban landscape on Land surface temperature (LST) intensity in the tropical mountain city of Nuwara Eliya, Sri Lanka. The results of the study are presented as a useful indicator for improved future landscape and urban planning that can help minimize the negative impacts of LST on urban sustainability. “Impact of Landscape Structure on the Variation of Land Surface Temperature in Sub-Saharan Region: A Case Study of Addis Ababa using Landsat Data (1986–2016)” [15] focused on the UHI effect in the African region and assessed the impact of landscape structure on the variation in LST as a geospatial approach in Addis Ababa, Ethiopia. The authors used LULC maps and LST derived from Landsat data and employed geospatial techniques including gradient and intensity analysis, as well as multidirectional and multitemporal LST profiles to comprehend the variations of LST in the study area. The provides insights on how understanding LST variations can help introduce appropriate mitigation techniques to overcome the negative impacts of the UHI effect.
Achieving urban sustainability is also focused on improving the quality of urban environments. Therefore, the Special Issue also added three articles addressing environmental and socio-economic quality issues related to urbanization. “Analysis of Life Quality in a Tropical Mountain City Using a Multi-Criteria Geospatial Technique: A Case Study of Kandy City, Sri Lanka” [16] created a life quality index (LQI) and identified the spatial distribution pattern of the LQI in Kandy City, Sri Lanka. The authors used the analytic hierarchy process (AHP) to create the LQI using 13 environmental and socio-economic factors, and employed gradient analysis to examine the spatial distribution pattern of the LQI from the city center to the periphery. The study guides residents and the respective administrative bodies to make the study area a more livable and sustainable city. “Spatiotemporal Analysis of the Nonlinear Negative Relationship between Urbanization and Habitat Quality in Metropolitan Areas” [17] focused on examining the spatiotemporal variations and relationship between urbanization intensity (UI) and Habitat Quality (HQ) in the Yangtze River Delta Urban Agglomeration. The study further quantifies and analyses the direct and indirect impacts of urbanization on HQ. The authors demonstrate how the increasing demand for urban land has exacerbated the threat to ecological areas, thus revealing that urbanization might lead to habitat degradation. “Dynamic Monitoring and Analysis of Ecological Quality of Pingtan Comprehensive Experimental Zone, a New Type of Sea Island City, Based on RSEI” [18] emphasized the significance of monitoring and evaluating island ecology to curb the increasingly prominent environmental problems with rapid urbanization. The authors used a remote sensing-based ecological index (RSEI) to explore the ecological status and space–time changes in the Pingtan Comprehensive Experimental Zone (PZ) in the east sea of Fujian Province of China. The authors concluded that the increase in large area bare soil can lead to regional ecological degradation, while the implementation of scientific ecological planning can enhance ecological restoration and construction.
The last three articles in the Special Issue are distinct, but they still all address issues that are important for urban sustainability. “Role of Urban Public Space and the Surrounding Environment in Promoting Sustainable Development from the Lens of Social Media” [19] proposed a framework that integrates the spatial-temporal distribution for different activity categories, the urban public spaces’(UPS) check-in time and the UPSs surrounding built environment. The authors utilized a check-in database collected from Instagram in 2016 and 2017 in two central districts of Ho Chi Minh City (HCMC) to analyze the city dynamics and activities over the course of the day. By quantifying the popularity of contemporary UPSs, the authors attempt to comprehend the many attractive features spreading over the two central districts. The results contribute to enhancing the predictability of UPSs on socio-economic performance and understanding the role of urban facilities in urban sustainability.
Comparison on Multi-Scale Urban Expansion Derived from Nightlight Imagery between China and India” [20] takes a global perspective of urban sustainability. The authors conduct a multi-scale comparative analysis of urban development differences between China and India as a way of capturing global multi-polarization in the 21st century. The authors used night light data for China and India, and employ several approaches including the Gini coefficient, Getis–Ord Gi* index, and the Urban Expansion Intensity Index (UEII) to compare the two countries. The study reveals that understanding the similarities and differences of urban development between China and India can provide insight into engines of global economic growth and sustainability.
The final article, “Impact of COVID-19 Induced Lockdown on Environmental Quality in Four Indian Megacities Using Landsat 8 OLI and TIRS-Derived Data and Mamdani Fuzzy Logic Modeling Approach” [21] focused on the deadly COVID-19 virus that has caused a global pandemic health emergency and is a threat to global urban sustainability. The authors take four megacities (Mumbai, Delhi, Kolkata, and Chennai) of India for a comprehensive assessment of the dynamicity of environmental quality resulting from the COVID-19 induced lockdown situation. The authors create an environmental quality index using remotely sensed biophysical parameters like Particulate Matters (PM10) concentration, Land Surface Temperature (LST), Normalized Different Moisture Index (NDMI), Normalized Difference Vegetation Index (NDVI), and Normalized Difference Water Index (NDWI). The results indicated that lockdown is not only capable of controlling COVID-19 spread but also helpful in minimizing environmental degradation. The findings of this study can be utilized for assessing and analyzing the impacts of COVID-19 induced lockdown situation on the overall environmental quality of other megacities of the world.
The Spatiotemporal analysis of urbanization using GIS and Remote Sensing in developing countries proffers guidance for achieving urban sustainability at local, regional, and global levels. The studies presented in this special issue provide a range of useful information on various remote sensing spatial data, new geospatial methodologies, as well as other newly developed data types that can be used to capture urbanization and its related problems. Most of the remote sensing data used in the studies are freely available and can be easily accessed. We believe that readers can get a wide range of knowledge related to remote sensing data and GIS applications. The research findings can also be used as a valuable source of information that can be used to implement sustainable development goals and thus achieving urban sustainability. The publications also identify further research needs.

Funding

This research received no external funding.

Conflicts of Interest

The authors declare no conflict of interest.

References

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MDPI and ACS Style

Murayama, Y.; Simwanda, M.; Ranagalage, M. Spatiotemporal Analysis of Urbanization Using GIS and Remote Sensing in Developing Countries. Sustainability 2021, 13, 3681. https://0-doi-org.brum.beds.ac.uk/10.3390/su13073681

AMA Style

Murayama Y, Simwanda M, Ranagalage M. Spatiotemporal Analysis of Urbanization Using GIS and Remote Sensing in Developing Countries. Sustainability. 2021; 13(7):3681. https://0-doi-org.brum.beds.ac.uk/10.3390/su13073681

Chicago/Turabian Style

Murayama, Yuji, Matamyo Simwanda, and Manjula Ranagalage. 2021. "Spatiotemporal Analysis of Urbanization Using GIS and Remote Sensing in Developing Countries" Sustainability 13, no. 7: 3681. https://0-doi-org.brum.beds.ac.uk/10.3390/su13073681

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