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Urban Expansion and Its Effect on Soil Sustainability

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A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Soil Conservation and Sustainability".

Deadline for manuscript submissions: closed (31 August 2022) | Viewed by 7751

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Prof. Dr. Yongjiu Feng

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Guest Editor

College of Surveying and Geoinformatcis, Tongji University, Shanghai 200092, China
Interests: spatial modeling; remote sensing of environment; urban studies; land use change
Special Issues, Collections and Topics in MDPI journals

Dr. Chao Wang

E-Mail Website
Assistant Guest Editor

College of Surveying and Geoinformatcis, Tongji University, Shanghai 200092, China
Interests: remote sensing and spatial modeling

Special Issue Information

Dear Colleagues,

Urban expansion is a global phenomenon in which people pursue high-quality living environments and high-density economic services. Uncontrolled urban expansion has led to problems such as traffic congestion, environmental degradation, ecological land loss, ecological security, loss of habitat, decrease in water quantity, and soil pollution. Among these, urban soil change and pollution are very important problems, but the relevant research and our understanding are currently insufficient. This Special Issue encourages research to solve the soil problems caused by urban expansion, fill the gaps in our understanding, improve the regulations of urban development, and optimize urban spatial planning decisions. Multi-source heterogeneous data from field investigation, ground monitoring, and satellite observation can be used to study urban expansion and its effects on soil for sustainable development. Papers aiming to solve the soil problems caused by urban expansion which simultaneously use spatiotemporal big data, geographic information, remote sensing imagery, and new methods of spatial analysis and scenario prediction are highly welcome.

Topics include but are not limited to:

Urban encroachment on high-quality soil;
Soil pollution caused by urban expansion;
Soil pollution in urban industrial areas;
Urban soil pollution process and risk prediction;
Change of soil properties caused by urban expansion;
Soil erosion caused by urban expansion;
Effect of urban green belts on soil;
Distribution of heavy metals in the soils of major cities;
Coupling between soil pollution and economic development in urban development zones;
Distribution of soil organic carbon storage in urban green spaces;
The ecological service function of urban soil.

Prof. Dr. Yongjiu Feng
Guest Editor

Dr. Chao Wang
Assistant Guest Editor

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Keywords

urban expansion
soil erosion and pollution
carbon storage
ecological service
economic development
remote sensing
spatial analysis
scenario prediction

Published Papers (4 papers)

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Research

22 pages, 5837 KiB

Open AccessArticle

Quantitative Inversion Method of Surface Suspended Sand Concentration in Yangtze Estuary Based on Selected Hyperspectral Remote Sensing Bands

by Kuifeng Luan, Hui Li, Jie Wang, Chunmei Gao, Yujia Pan, Weidong Zhu, Hang Xu, Zhenge Qiu and Cheng Qiu

Sustainability 2022, 14(20), 13076; https://doi.org/10.3390/su142013076 - 12 Oct 2022

Cited by 2 | Viewed by 960

Abstract

The distribution of the surface suspended sand concentration (SSSC) in the Yangtze River estuary is extremely complex. Therefore, effective methods are needed to improve the efficiency and accuracy of SSSC inversion. Hyperspectral remote sensing technology provides an effective technical means of accurately monitoring and quantitatively inverting SSSC. In this study, a new framework for the accurate inversion of the SSSC in the Yangtze River estuary using hyperspectral remote sensing is proposed. First, we quantitatively simulated water bodies with different SSSCs using sediment samples from the Yangtze River estuary, and analyzed the spectral characteristics of water bodies with different SSSCs. On this basis, we compared six spectral transformation forms, and selected the first derivative (FD) transformation as the optimal spectral transformation form. Subsequently, we compared two feature band extraction methods: the successive projections algorithm (SPA) and the competitive adaptive reweighted sampling (CARS) method. Then, the partial least squares regression (PLSR) model and back propagation (BP) neural network model were constructed. The BP neural network model was determined as the best inversion model. The new FD-CARS-BP framework was applied to the airborne hyperspectral data of the Yangtze estuary, with R² of 0.9203, RPD of 4.5697, RMSE of 0.0339 kg/m³, and RMSE% of 8.55%, which are markedly higher than those of other framework combination forms, further verifying the effectiveness of the FD-CARS-BP framework in the quantitative inversion process of SSSC in the Yangtze estuary. Full article

(This article belongs to the Special Issue Urban Expansion and Its Effect on Soil Sustainability)

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17 pages, 12140 KiB

Open AccessEditor’s ChoiceArticle

RSEI-Based Modeling of Ecological Security and Its Spatial Impacts on Soil Quality: A Case Study of Dayu, China

by Xiaoxia Su, Jing Wu, Pengshuo Li, Renjie Li and Penggen Cheng

Sustainability 2022, 14(8), 4428; https://doi.org/10.3390/su14084428 - 08 Apr 2022

Cited by 2 | Viewed by 1549

Abstract

Rapid urbanization and industrialization have brought serious threats to urban ecological security, which refers to the health and integrity of urban ecosystems. By collecting multi-source data in the modeling of the ecological security pattern, we used the remote sensing ecological index (RSEI) to identify the ecological sources (ESOs), and applied five indicators to construct the resistance surface, including land-use type, normalized vegetation index (NDVI), normalized building index (NDBI), slope, and digital elevation model (DEM). Based on the ESOs and ecological resistance surface, we calculated the cost distance of each pixel to the nearest ESO using the minimum cumulative resistance model. With the natural breakpoint method, we classified the cost distance into five levels, and constructed the ecological security pattern of Dayu. In Dayu, there were areas of at least 40% with stable ecological security. We identified 39, 31, and 43 ESOs of Dayu in 2012, 2016, and 2020, respectively. During 2012 to 2016, the number of medium ESOs decreased from 16 to 5, and the number of small ESOs increased from 13 to 26. From 2016 to 2020, the number of medium-sized ESOs increased from 5 to 18, and the number of small-sized ESOs decreased from 26 to 20. The percentage of the Level-5 (the worst) ecological security was 5.84% in 2012, 6.80% in 2016, and 4.42% in 2020. The ecological security was negatively correlated with the intensity of the human activities and varied significantly in different towns. The soil quality was positively consistent with the ecological security, and the urbanization caused damage to the soil security. A few suggestions were finally provided for decision-makers to improve the ecological environments and the soil quality. Full article

(This article belongs to the Special Issue Urban Expansion and Its Effect on Soil Sustainability)

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19 pages, 5426 KiB

Open AccessArticle

Spatially Balanced Sampling for Validation of GlobeLand30 Using Landscape Pattern-Based Inclusion Probability

by Huan Xie, Fang Wang, Yali Gong, Xiaohua Tong, Yanmin Jin, Ang Zhao, Chao Wei, Xinyi Zhang and Shicheng Liao

Sustainability 2022, 14(5), 2479; https://doi.org/10.3390/su14052479 - 22 Feb 2022

Cited by 5 | Viewed by 2130

Abstract

Global and local land-cover mapping products provide important data on land surface. However, the accuracy of land-cover products is the key issue for their further scientific application. There has been neglect of the relationship between inclusion probability and spatial heterogeneity in traditional spatially balanced sampling. The aim of this paper was to propose an improved spatially balanced sampling method using landscape pattern-based inclusion probability. Compared with other global land-cover datasets, Globeland30 has the advantages of high resolution and high classification accuracy. A two-stage stratified spatially balanced sampling scheme was designed and applied to the regional validation of GlobeLand30 in China. In this paper, the whole area was divided into three parts: the Tibetan Plateau region, the Northwest China region, and the East China region. The results show that 7242 sample points were selected, and the overall accuracy of GlobeLand30-2010 in China was found to be 80.46%, which is close to the third-party assessment accuracy of GlobeLand30. This method improves the representativeness of samples, reduces the classification error of remote sensing, and provides better guidance for biodiversity and sustainable development of environment. Full article

(This article belongs to the Special Issue Urban Expansion and Its Effect on Soil Sustainability)

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19 pages, 7775 KiB

Open AccessArticle

Analysis of China’s Urban Innovation Connection Network Evolution: A Case Study of Henan Province

by Weidong Zhu, Zilin Yue, Naiying He, Kuifeng Luan, Li Ye and Chuyi Qian

Sustainability 2022, 14(3), 1089; https://doi.org/10.3390/su14031089 - 18 Jan 2022

Cited by 3 | Viewed by 1635

Abstract

The research on urban innovation links is of great significance for revealing the structural characteristics of innovation space. At the same time, it is of great significance for formulating regional innovation development strategies. Based on statistics from 2008, 2013 and 2018, the time and spatial characteristics of the urban innovation contact network evolution in Henan Province were investigated using the entropy weight and gravity-model method. The results show that the overall pattern of the regional innovation network in Henan Province is radial, with the characteristics of a “core edge”. It shows that it radiates to the surrounding cities with Zhengzhou as the core. From the perspective of time evolution, the radiation range and intensity of the innovation center city have changed to varying degrees and the overall radiation pattern has not significantly changed. From the perspective of spatial evolution, the evolution of Henan Province’s innovation network presents the following development trends. The central and southern regions developed rapidly, and the western, northern and eastern regions developed slowly. Full article

(This article belongs to the Special Issue Urban Expansion and Its Effect on Soil Sustainability)

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