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Special Issue "Urban Remote Sensing: Sustainability of Earth’s Environment, Resources and Ecology"

A special issue of Sustainability (ISSN 2071-1050). This special issue belongs to the section "Sustainable Urban and Rural Development".

Deadline for manuscript submissions: closed (30 April 2019)

Special Issue Editor

Guest Editor
Prof. Ramesh P. Singh

School of Life and Environmental Sciences, Schmid College of Science and Technology, Chapman University, Orange, California 92866, USA
Website | E-Mail
Interests: Remote sensing; Land–Ocean–Atmospheric coupling; Natural Hazards; Atmospheric Pollution; Urban Climate; Snow/Glaciers; Air quality

Special Issue Information

Dear Colleagues,

The Earth systems consist of land, ocean, biosphere, cryosphere and atmosphere. These Earth systems interact each other. With the growing population and human activities, different Earth systems behave differently and the coupling among these systems are becoming more complex with human activities and sun interactions. With the growing interactions, different elements of the Earth systems are being polluted and associated natural hazards are frequently observed in different parts of the world. The environment is being degraded, resources are depleting and the ecological balance is being disturbed and raise questions of sustainability. This Special Issue in “Urban Remote Sensing” invites contributions related to land­–water–air–biosphere–cryosphere interactions, land use/land cover, degrading resources, ecological balance, impact of growing pollution on natural resources, increasing population, resources and environment, food securities, water resources, depletion of snow/glaciers, increasing frequency of natural hazards and impacts on environment and ecological balance, modelling studies, and how to make our planet sustainable.

Prof. Ramesh Singh
Guest Editor

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Keywords

  • Natural Resources
  • Earth Systems
  • Natural Hazards
  • Ecological and Environments
  • Sustainable planet

Published Papers (14 papers)

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Research

Open AccessArticle
Spatio-Temporal Pattern of Land Degradation along the China-Mongolia Railway (Mongolia)
Sustainability 2019, 11(9), 2705; https://doi.org/10.3390/su11092705
Received: 18 March 2019 / Revised: 4 May 2019 / Accepted: 7 May 2019 / Published: 13 May 2019
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Abstract
The increasingly serious problem of land degradation has a direct impact on the ecosystem and sustainable development in Mongolia. The influence of land degradation on the main China–Mongolia–Russia traffic arteries is currently unclear and poses a risk to the construction of transportation infrastructure. [...] Read more.
The increasingly serious problem of land degradation has a direct impact on the ecosystem and sustainable development in Mongolia. The influence of land degradation on the main China–Mongolia–Russia traffic arteries is currently unclear and poses a risk to the construction of transportation infrastructure. In this study, for the first time, we obtained land cover data from 1990, 2010, and 2015, at a 30 m, resolution based on the Landsat Thematic Mapper (TM) and Landsat Operational Land Imager (OLI) images along the China–Mongolia railway (Mongolia section). We then analyzed the change in the obtained land cover data using the geographic information system (GIS) spatial analysis technology to obtain the land pattern and development trend of this region. Results showed that the newly-increased degraded land was distributed mainly in the center of the region and tended to expand northward. The joint effect of natural and socioeconomic factors resulted in land degradation. We speculated that the significant temperature fluctuation and the decrease in rainfall were the inducing factors. Population migration, overgrazing, infrastructure construction, unreasonable mineral exploitation, and rapid urbanization aggravate the degree of land degradation. It is thus necessary to use a broader view to observe patterns of desertification and variations in regions along the Railway facing its sustainable development. Full article
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Open AccessArticle
Relationships between Ecosystem Services and Urbanization in Jiangsu Province, Eastern China
Sustainability 2019, 11(7), 2073; https://doi.org/10.3390/su11072073
Received: 27 January 2019 / Revised: 30 March 2019 / Accepted: 1 April 2019 / Published: 8 April 2019
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Abstract
Ecosystem services are comprehensive and quantitative indicators for describing ecosystem–human interactions. China has experienced rapid urbanization in the past 30 years, which has created a significant impact on regional ecosystem services. However, whether the impact is linear is not clear as yet. In [...] Read more.
Ecosystem services are comprehensive and quantitative indicators for describing ecosystem–human interactions. China has experienced rapid urbanization in the past 30 years, which has created a significant impact on regional ecosystem services. However, whether the impact is linear is not clear as yet. In this study, the Jiangsu province, a main body of the Chinese Yangtze River Delta city cluster, was chosen as a case study. Multi-source remotely-sensed geospatial data, including meteorological, land use, vegetation, and socio-economic data, were collected to estimate the total amount of ecosystem services (TESV) and urbanization levels. Subsequently, the relationships between TESV and urbanization indices (i.e., gross domestic product (GDP) per unit area, GPUA; population per unit area, PPUA; and built-up land proportion, BULP) were determined using the Pearson correlation analysis and piecewise linear regression. The primary findings of this study were as follows: (1) There was a distinct spatial pattern in TESV, which gradually increased from west to east with high-value areas located in eastern coastal areas of Jiangsu. Among different land use types, cropland and woodland contributed the most to TESV; (2) The three urbanization indices had spatial patterns, indicating higher urbanization in southern Jiangsu than in central or northern Jiangsu; and (3) Once GPUA and PPUA exceeded threshold values of 3719.55 × 104 yuan/km2 and 744.37 person/km2, respectively, TESV sharply decreased with an increase in these indices. However, the BULP showed a linear and significantly negative relationship with TESV at all values, which indicated that the impacts of economic and population growth on TESV lagged behind that of built-up land expansion. These findings provide a potentially significant reference for decision-makers to rationally enhance regional ecosystem services during rapid urbanization processes. Full article
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Open AccessArticle
Long-Term Regional Environmental Risk Assessment and Future Scenario Projection at Ningbo, China Coupling the Impact of Sea Level Rise
Sustainability 2019, 11(6), 1560; https://doi.org/10.3390/su11061560
Received: 18 February 2019 / Revised: 5 March 2019 / Accepted: 8 March 2019 / Published: 14 March 2019
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Abstract
Regional environmental risk (RER) denotes potential threats to the natural environment, human health and socioeconomic development caused by specific risks. It is valuable to assess long-term RER in coastal areas with the increasing effects of global change. We proposed a new approach to [...] Read more.
Regional environmental risk (RER) denotes potential threats to the natural environment, human health and socioeconomic development caused by specific risks. It is valuable to assess long-term RER in coastal areas with the increasing effects of global change. We proposed a new approach to assess coastal RER considering spatial factors using principal component analysis (PCA) and used a future land use simulation (FLUS) model to project future RER scenarios considering the impact of sea level rise (SLR). In our study, the RER status was classified in five levels as highest, high, medium, low and lowest. We evaluated the 30 m × 30 m gridded spatial pattern of the long-term RER at Ningbo of China by assessing its 1975–2015 history and projecting this to 2020–2050. Our results show that RER at Ningbo has increased substantially over the past 40 years and will slowly increase over the next 35 years. Ningbo’s city center and district centers are exposed to medium-to-highest RER, while the suburban areas are exposed to lowest-to-medium lower RER. Storm surges will lead to strong RER increases along the Ningbo coast, with the low-lying northern coast being more affected than the mountainous southern coast. RER at Ningbo is affected principally by the combined effects of increased human activity, rapid population growth, rapid industrialization, and unprecedented urbanization. This study provides early warnings to support practical regulation for disaster mitigation and environmental protection. Full article
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Open AccessArticle
Study on Urban Expansion Using the Spatial and Temporal Dynamic Changes in the Impervious Surface in Nanjing
Sustainability 2019, 11(3), 933; https://doi.org/10.3390/su11030933
Received: 15 January 2019 / Revised: 6 February 2019 / Accepted: 8 February 2019 / Published: 12 February 2019
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Abstract
Impervious surface area is a key factor affecting urbanization and urban environmental quality. It is of great significance to analysis timely and accurately the dynamic changes of impervious surface for urban development planning. In this study, we use a comprehensive method to extract [...] Read more.
Impervious surface area is a key factor affecting urbanization and urban environmental quality. It is of great significance to analysis timely and accurately the dynamic changes of impervious surface for urban development planning. In this study, we use a comprehensive method to extract the time series data on the impervious surface area (ISA) from the multi-temporal Landsat remote sensing images with a high overall accuracy of 90%. The processes and mechanisms of urban expansion at different political administration and direction level in the Nanjing metropolitan area are investigated by using the comprehensive classification method consisting of minimum noise fraction, linear spectral mixture analysis, spectral index, and decision tree classifiers. The expansion of Nanjing is examined by using various ISA indexes and concentric regression analyses. Results indicate that the overall classification accuracy of ISA is higher than 90%. The ISA in Nanjing has dramatically increased in the past three decades from 427.36 km2 to 1780.21 km2 and with a high expansion rate of 0.48 from 2000 to 2005. The city sprawls from monocentric to urban core with multiple subcenters in a concentric structure, and the geometric gravity center of construction land moves southward annually. The stages of urbanization in different district levels and the dynamic changes in different direction levels are influenced by the topographic and economic factors. Full article
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Open AccessArticle
Water Bodies’ Cooling Effects on Urban Land Daytime Surface Temperature: Ecosystem Service Reducing Heat Island Effect
Sustainability 2019, 11(3), 787; https://doi.org/10.3390/su11030787
Received: 20 December 2018 / Revised: 26 January 2019 / Accepted: 31 January 2019 / Published: 2 February 2019
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Abstract
The urban heat island (UHI) effect caused by urbanization is a major environmental concern. Utilizing cooling effects of water bodies as one type of ecosystem service is an important way to mitigate UHI in urban areas during the daytime. This study aims to [...] Read more.
The urban heat island (UHI) effect caused by urbanization is a major environmental concern. Utilizing cooling effects of water bodies as one type of ecosystem service is an important way to mitigate UHI in urban areas during the daytime. This study aims to examine the influence of water bodies’ cooling effects on the urban land surface temperature (LST). The potential influence on the relationship between urban land cover and the LST are also discussed. The daytime LST in April was retrieved from Landsat-8 thermal infrared band and the grid-based method was adopted to analyze the potential influence. The results indicated that Suzhou Bay is broadly capable of lowering daytime temperatures. The cooling distance can reach 800 m in horizontal space, and the maximum cooling effect was 3.02 °C. Furthermore, the distance to the Suzhou Bay is a great factor for the relationship between land cover and the LST. We found that the cooling effects have weakened the correct quantitative correlation between land cover (e.g., green space and impervious surface) and the LST, particularly green space in the range of 200 m. In addition, the cooling effects have strengthened the “cool edge” phenomenon when analyzing the relationship between the normal difference vegetation index (NDVI) and the LST. We suggest that the distance to the water bodies should be effectively utilized in the microclimate regulation provided by ecosystem services of water bodies. When investigating the thermal effects of urban land, urban planners and designers should consider water bodies’ effects on surrounding areas. These findings have implications for understanding the role of water bodies with ecosystem services of temperature mitigation, which must be fully appreciated for sustainable urban and landscape planning. Full article
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Open AccessArticle
Urban Land Intensive Use Evaluation Study Based on Nighttime Light—A Case Study of the Yangtze River Economic Belt
Sustainability 2019, 11(3), 675; https://doi.org/10.3390/su11030675
Received: 10 December 2018 / Revised: 18 January 2019 / Accepted: 21 January 2019 / Published: 28 January 2019
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Abstract
Urban land intensive use meets the requirements for the sustainable development of urban land and is an important part of urban sustainable development. The Yangtze River Economic Belt (YREB) spans the three major regions of China, which are the most active areas of [...] Read more.
Urban land intensive use meets the requirements for the sustainable development of urban land and is an important part of urban sustainable development. The Yangtze River Economic Belt (YREB) spans the three major regions of China, which are the most active areas of China’s economy. The contradiction between humans and land is becoming more acute. There are also regional differences in land use patterns affecting the coordinated development of the YREB and the construction of an ecological civilization. Therefore, the scientific evaluation of urban land intensive use is a key area in the current research field of urban sustainable development. In this study, the YREB is chosen as the research object, and urban land intensive use is studied using nighttime light data and statistical data on the urban built-up area. An evaluation model based on urban nighttime light intensity and land urbanization is constructed with an allometric growth model. Considering that the impact of land urbanization on urban nighttime light has a possible lag effect, an evaluation model of land intensive use that considers the lag effect between urban nighttime light and the land urbanization level is proposed. Using urban agglomerations and some typical cities in the study area as research samples, the characteristics of urban nighttime light and land urbanization are analyzed to reveal the spatial and temporal characteristics of land development in the YREB. The results show that nighttime light remote-sensing data can better reflect the level of urban land use, the allometric growth model can better fit the intensity of urban light and the land urbanization level, and the allometric growth characteristics can reflect the land use characteristics of different cities and urban agglomerations. In regional experiments with typical cities and with urban agglomerations, compared to the original allometric growth model, the goodness of fit of the allometric growth model with the lag effect improves, on average, by 3.2% and 2%, respectively, with the highest increases being by 9.9% and 4.9%, respectively. The level of intensive land use in the YREB gradually decreases from east to west, and there are great differences among different cities in the provinces and urban agglomerations. The lower reaches of the Yangtze River have high land intensive use on the whole. In the middle reaches, multicenter cities have a greater efficiency of land use than the surrounding cities. In the upper reaches, only Chengdu and Chongqing have clear advantages in urban land intensive use. The results of this study can be helpful in providing an important reference for the sustainable development of land in the YREB and can provide a basis for future urban land optimization and sustainable development. Realizing the coordination and linkage between key cities and major cities is the key to enhancing the overall sustainable development ability of the core cities in the YREB. Full article
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Open AccessArticle
Linking Social Perception and Provision of Ecosystem Services in a Sprawling Urban Landscape: A Case Study of Multan, Pakistan
Sustainability 2019, 11(3), 654; https://doi.org/10.3390/su11030654
Received: 28 November 2018 / Revised: 23 January 2019 / Accepted: 23 January 2019 / Published: 27 January 2019
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Abstract
Urban sprawl causes changes in land use and a decline in many ecosystem services. Understanding the spatial patterns of sprawl and exploration of citizens’ perception towards the sporadic urban expansion and its impacts on an ecosystem to deliver services can help to guide [...] Read more.
Urban sprawl causes changes in land use and a decline in many ecosystem services. Understanding the spatial patterns of sprawl and exploration of citizens’ perception towards the sporadic urban expansion and its impacts on an ecosystem to deliver services can help to guide land use planning and the conservation of the urban ecosystem. Here, we spatially examined land use changes in Multan, Pakistan, and investigated public perception about urban sprawl and its impacts on the quality and provision of ecosystem services, using a survey instrument. The spatial analysis of the historical land cover of Multan indicated an exponential expansion of the city in the last decade. Large areas of natural vegetation and agricultural land were converted to urban settlements in the past two decades. The citizens of Multan believe that the quality and provision of ecosystem services have declined in the recent past and strongly correlate the deteriorating ecosystem services with urban sprawl. Education and income levels of the respondents are the strongest predictors of urban ecosystem health literacy. Citizens associated with laborious outdoor jobs are more sensitive to the changes in ecosystem services. We concluded that the rapidly expanding cities, especially in the tropical arid zones, need to be prioritized for an increase in vegetation cover, and economically vulnerable settlements in these cities should be emphasized in climate change mitigation campaigns. Full article
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Open AccessArticle
Land Use and Land Cover Changes, and Environment and Risk Evaluation of Dujiangyan City (SW China) Using Remote Sensing and GIS Techniques
Sustainability 2018, 10(12), 4631; https://doi.org/10.3390/su10124631
Received: 1 November 2018 / Revised: 3 December 2018 / Accepted: 4 December 2018 / Published: 6 December 2018
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Abstract
Understanding of the Land Use and Land Cover (LULC) change, its transitions and Landscape risk (LR) evaluation in earthquake-affected areas is important for planning and urban sustainability. In the present study, we have considered Dujiangyan City and its Environs (DCEN), a seismic-prone area [...] Read more.
Understanding of the Land Use and Land Cover (LULC) change, its transitions and Landscape risk (LR) evaluation in earthquake-affected areas is important for planning and urban sustainability. In the present study, we have considered Dujiangyan City and its Environs (DCEN), a seismic-prone area close to the 2008 Wenchuan earthquake (8.0 Mw) during 2007–2018. Five different multi-temporal data sets for the years 2007, 2008, 2010, 2015, and 2018 were considered for LULC mapping, followed by the maximum likelihood supervised classification technique. The individual LULC maps were further used in four time periods, i.e., 2007–2018, 2008–2018, 2010–2018, and 2015–2018, to evaluate the Land Use and Land Cover Transitions (LULCT) using combined remote sensing and GIS (Geographical Information System). Furthermore, multi-criteria evaluation (MCE) techniques were applied for LR mapping. The results of the LULC change data indicate that built-up, agricultural area, and forest cover are the prime categories that had been changed by the natural and anthropogenic activities. LULCT, along with multi-parameters, are suggested to avoid development in fault-existing areas that are seismically vulnerable for future landscape planning in a sustainable manner. Full article
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Open AccessArticle
Postseismic Restoration of the Ecological Environment in the Wenchuan Region Using Satellite Data
Sustainability 2018, 10(11), 3990; https://doi.org/10.3390/su10113990
Received: 9 October 2018 / Revised: 25 October 2018 / Accepted: 25 October 2018 / Published: 1 November 2018
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Abstract
Using Landsat remote-sensing data combined with geological information extracted from ALOS and Sentinel-1A radar data, the ecological environment was evaluated in the years 2007, 2008, 2013, and 2017 through gray correlation analysis on the basis of the construction of the pressure-state-response model. The [...] Read more.
Using Landsat remote-sensing data combined with geological information extracted from ALOS and Sentinel-1A radar data, the ecological environment was evaluated in the years 2007, 2008, 2013, and 2017 through gray correlation analysis on the basis of the construction of the pressure-state-response model. The main objective of this research was to assess the ecological environment changes in Wenchuan County before and after the earthquake, and to provide reference for future social development and policy implementation. The grading map of the ecological environment was obtained for every year, and the ecological restoration status of Wenchuan County after the earthquake was evaluated. The results showed that the maximum area cover at a “safe” ecological level was over 46.4% in 2007. After the 2008 earthquake, the proportion of “unsafe” and “very unsafe” ecological levels was 40.0%, especially around the Lancang River and the western mountain area in Wenchuan County. After five years of restoration, ecological conditions were improved, up to 48.0% in the region. The areas at “critically safe” and above recovered to 85.5% in 2017 within nine years after the deadly Wenchuan earthquake of May 12, 2008. In this paper, we discuss the results of detailed analysis of ecological improvements and correlation with the degrees of pressure, state, and response layers of the Pressure-State-Response (PSR) model. Full article
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Open AccessArticle
Land-Use/Land-Cover Changes and Their Influence on the Ecosystem in Chengdu City, China during the Period of 1992–2018
Sustainability 2018, 10(10), 3580; https://doi.org/10.3390/su10103580
Received: 12 September 2018 / Revised: 30 September 2018 / Accepted: 2 October 2018 / Published: 8 October 2018
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Abstract
Due to urban expansion, economic development, and rapid population growth, land use/land cover (LULC) is changing in major cities around the globe. Quantitative analysis of LULC change is important for studying the corresponding impact on the ecosystem service value (ESV) that helps in [...] Read more.
Due to urban expansion, economic development, and rapid population growth, land use/land cover (LULC) is changing in major cities around the globe. Quantitative analysis of LULC change is important for studying the corresponding impact on the ecosystem service value (ESV) that helps in decision-making and ecosystem conservation. Based on LULC data retrieved from remote-sensing interpretation, we computed the changes of ESV associated with the LULC dynamics using the benefits transfer method and geographic information system (GIS) technologies during the period of 1992–2018 following self-modified coefficients which were corrected by net primary productivity (NPP). This improved approach aimed to establish a regional value coefficients table for facilitating the reliable evaluation of ESV. The main objective of this research was to clarify the trend and spatial patterns of LULC changes and their influence on ecosystem service values and functions. Our results show a continuous reduction in total ESV from United States (US) $1476.25 million in 1992, to US $1410.17, $1335.10, and $1190.56 million in 2001, 2009, and 2018, respectively; such changes are attributed to a notable loss of farmland and forest land from 1992–2018. The elasticity of ESV in response to changes in LULC shows that 1% of land transition may have caused average changes of 0.28%, 0.34%, and 0.50% during the periods of 1992–2001, 2001–2009, and 2009–2018, respectively. This study provides important information useful for land resource management and for developing strategies to address the reduction of ESV. Full article
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Open AccessArticle
Does the Exhaustion of Resources Drive Land Use Changes? Evidence from the Influence of Coal Resources-Exhaustion on Coal Resources–Based Industry Land Use Changes
Sustainability 2018, 10(8), 2698; https://doi.org/10.3390/su10082698
Received: 3 July 2018 / Revised: 30 July 2018 / Accepted: 31 July 2018 / Published: 1 August 2018
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Abstract
Analyzing the spatial-temporal changes of resources–based industrial land is essential to the transformation and development of resources–exhausted cities. In this paper, we studied coal resources–based industrial land use changes and their driving factors in a typical coal resources–exhausted city, Anyuan District, Pingxiang city. [...] Read more.
Analyzing the spatial-temporal changes of resources–based industrial land is essential to the transformation and development of resources–exhausted cities. In this paper, we studied coal resources–based industrial land use changes and their driving factors in a typical coal resources–exhausted city, Anyuan District, Pingxiang city. The changes between coal resources–based industrial land and other land-use types were analyzed. The logistic regression models were applied to identify the main driving factors and quantify their contributions to coal resources–based industrial land-use changes during the two periods of 2003–2008 and 2008–2013. The results show that coal resources–based industrial land declined by 34.37% during the period 2008–2013 as coal resources were being exhausted. Altitude, distance to roads, distance to town, population density change, fixed-asset investment per area change, and GDP per capita change drove coal resources–based industrial land-use changes. However, the patterns of the driving effects differed, and even the same factors had different influences on coal resources–based industrial land-use changes during the two periods. The changes in the driving factors can be seen as responses to socioeconomic transformation and development in the city, which is experiencing the exhaustion of coal resources. As a result of the comprehensive effects of these driving factors, coal resources–based industrial land use has changed in complex ways. Full article
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Open AccessArticle
Spatial Variation of Urban Thermal Environment and Its Relation to Green Space Patterns: Implication to Sustainable Landscape Planning
Sustainability 2018, 10(7), 2249; https://doi.org/10.3390/su10072249
Received: 28 May 2018 / Revised: 15 June 2018 / Accepted: 26 June 2018 / Published: 29 June 2018
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Abstract
The rapid changes of land covers in urban areas are one of major environmental concerns because of their environmental impacts. Such land cover changes include the transformation of green space to impervious surface, and the increase of land surface temperature (LST). The objective [...] Read more.
The rapid changes of land covers in urban areas are one of major environmental concerns because of their environmental impacts. Such land cover changes include the transformation of green space to impervious surface, and the increase of land surface temperature (LST). The objective of this study was to examine the spatial variation of urban landscape composition and configuration, as well as their influences on LST in Suzhou City, China. Landsat-8 image was processed to extract land covers and retrieve LSTs that were used to study relationship between spatial variation of LST and land covers. The results indicated that there was a significantly negative correlation between mean LST and green space coverage along the urban–rural gradients. With every 10% increased green space coverage, the mean LST drop was about 1.41 °C. A grid-base analysis performed at various grid sizes indicated that an increase in the percentage of surface water body area has a greater cooling effect of the mean LST than a vegetation increase. The mean LST had a significantly negative correlation with both the shape and aggregation indexes of the green space patches. Our results suggest that the sustainable landscape planning of green space in a typical city with a large water area should include both the vegetation and the surface water covers. The increased percentage of vegetation and surface water covers had the greatest cooling effect on an urban thermal environment, which is one of the ecosystem services that green space provides. A dense distribution of green space patches with complex shapes should be considered in urban sustainable landscape planning for increasing ecosystem services. Full article
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Open AccessArticle
The Spatial Patterns of Land Surface Temperature and Its Impact Factors: Spatial Non-Stationarity and Scale Effects Based on a Geographically-Weighted Regression Model
Sustainability 2018, 10(7), 2242; https://doi.org/10.3390/su10072242
Received: 7 June 2018 / Revised: 25 June 2018 / Accepted: 26 June 2018 / Published: 29 June 2018
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Abstract
Understanding the spatial distribution of land surface temperature (LST) and its impact factors is crucial for mitigating urban heat island effect. However, few studies have quantitatively investigated the spatial non-stationarity and spatial scale effects of the relationships between LST and its impact factors [...] Read more.
Understanding the spatial distribution of land surface temperature (LST) and its impact factors is crucial for mitigating urban heat island effect. However, few studies have quantitatively investigated the spatial non-stationarity and spatial scale effects of the relationships between LST and its impact factors at multi-scales. The main purposes of this study are as follows: (1) to estimate the spatial distributions of urban heat island (UHI) intensity by using hot spots analysis and (2) to explore the spatial non-stationarity and scale effects of the relationships between LST and related impact factors at multiple resolutions (30–1200 m) and to find appropriate scales for illuminating the relationships in a plain city. Based on the LST retrieved from Landsat 8 OLI/TIRS images, the Geographically-Weighted Regression (GWR) model is used to explore the scale effects of the relationships in Zhengzhou City between LST and six driving indicators: The Fractional Vegetation Cover (FVC), the Impervious Surface (IS), the Population Density (PD), the Fossil-fuel CO2 Emission data (FFCOE), the Shannon Diversity Index (SHDI) and the Perimeter-area Fractal Dimension (PAFRAC),which indicate the vegetation abundance, built-up, social-ecological variables and the diversity and shape complexity of land cover types. Our findings showed that the spatial patterns of LST show statistically significant hot spot zones in the center of the study area, partly extending to the western and southern industrial areas, indicating that the intensity of the urban heat island is significantly spatial clustering in Zhengzhou City. In addition, compared with the Ordinary Least Squares (OLS) model, the GWR model has a better ability to characterize spatial non-stationarity and analyze the relationships between the LST and its impact factors by considering the space-varying relationships of different variables, especially at the fine spatial scales (30–480 m). However, the strength of GWR model has become relatively weak with the increase of spatial scales (720–1200 m). This reveals that the GWR model is recommended to be applied in the analysis of UHI problems and related impact factors at scales finer than 480 m in the plain city. If the spatial scale is coarser than 720 m, both OLS and GWR models are suitable for illustrating the correct relationships between UHI effect and its influence factors in the plain city due to their undifferentiated performance. These findings can provide valuable information for urban planners and researchers to select appropriate models and spatial scales seeking to mitigate urban thermal environment effect. Full article
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Open AccessArticle
A Multi-Temporal Analyses of Land Surface Temperature Using Landsat-8 Data and Open Source Software: The Case Study of Modena, Italy
Sustainability 2018, 10(5), 1678; https://doi.org/10.3390/su10051678
Received: 26 April 2018 / Revised: 17 May 2018 / Accepted: 18 May 2018 / Published: 22 May 2018
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Abstract
The Urban Heat Island (UHI) phenomenon, namely urban areas where the atmospheric temperature is significantly higher than in the surrounding rural areas, is currently a very well-known topic both in the scientific community and in public debates. Growing urbanization is one of the [...] Read more.
The Urban Heat Island (UHI) phenomenon, namely urban areas where the atmospheric temperature is significantly higher than in the surrounding rural areas, is currently a very well-known topic both in the scientific community and in public debates. Growing urbanization is one of the anthropic causes of UHI. The UHI phenomenon has a negative impact on the life quality of the local population (thermal discomfort, summer thermal shock, etc.), thus investigations and analyses on this topic are really useful and important for correct and sustainable urban planning; this study is included in this context. A multi-temporal analysis was performed in the municipality of Modena (Italy) to identify and estimate the Surface Urban Heat Island (SUHI, strictly correlated to the UHI phenomenon) from 2014 to 2017. For this purpose, Landsat-8 satellite images were processed with Quantum Geographic Information System (QGIS) to obtain the Land Surface Temperature (LST) and the Normalized Difference Vegetation Index (NDVI). For every pixel, LST and NDVI values of three regions of interest (ROI, i.e., Countryside, Suburbs, and City Center) were extracted and their correlations were investigated. A maximum variation of 6.4 °C in the LST values between City Center and Countryside was highlighted, confirming the presence of the SUHI phenomenon even in a medium-sized municipality like Modena. The implemented procedure demonstrates that satellite data are suitable for SUHI identification and estimation, therefore it could be a useful tool for public administration for urban planning policies. Full article
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