Assessing Land Cover and Ecological Quality Changes under the New-Type Urbanization from Multi-Source Remote Sensing

Shi, Fang; Li, Mingshi

doi:10.3390/su132111979

Cited by 16 publications

(11 citation statements)

References 60 publications

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“…It can be employed as a thermal indicator to respond to the land surface ecological environment. In this study, based on inversion using the atmospheric correction method, LST is calculated [ 52 ]:

where

is the grayscale value of each pixel;

is the radiation value in thermal infrared bands;

and

are band bias and gain, respectively, which can be obtained from image header files;

and

are calibration parameters and can be obtained from user manuals;

is the temperature at the sensor;

is the central wavelength of thermal infrared bands, i.e., 11.5 μm for the sixth band of TM data, 11.457 μm for the sixth band of ETM+ data, and 10.9 μm for the tenth band of OLI data;

is the surface specific emissivity; and

= 1.438 × 10 −2 m∙K.…”

Section: Methodsmentioning

confidence: 99%

Urban Ecological Environment Quality Evaluation and Territorial Spatial Planning Response: Application to Changsha, Central China

Shi

et al. 2023

IJERPH

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Scientific territorial spatial planning is of great significance in the realization of the sustainable development goals in China, especially in the context of China’s ecological civilization construction and territorial spatial planning. However, limited research has been carried out to understand the spatio-temporal change in EEQ and territorial spatial planning. In this study, Changsha County and six districts of Changsha City were selected as the research objects. Based on the remote sensing ecological index (RSEI) model, the spatio-temporal changes in the EEQ and spatial planning response in the study area during 2003–2018 were analyzed. The results reveal that (1) the EEQ of Changsha declined and then rose between 2003 and 2018, showing an overall decreasing trend. The average RSEI declined from 0.532 in 2003 to 0.500 in 2014 and then increased to 0.523 in 2018, with an overall decrease of 1.7%. (2) In terms of spatial pattern changes, the Xingma Group, the Airport Group and the Huangli Group in the east of the Xiangjiang River had the most serious EEQ degradation. The EEQ degradation of Changsha showed an expanding and polycentric decentralized grouping pattern. (3) Massive construction land expansion during rapid urbanization caused significant EEQ degradation in Changsha. Particularly, the areas with low EEQ were concentrated in the areas with concentrated industrial land. Scientific territorial spatial planning and strict control were conducive to regional EEQ improvement. (4) The prediction using the urban ecological model demonstrates that every 0.549 unit increase in NDVI or 0.2 unit decrease in NDBSI can improve the RSEI of the study area by 0.1 unit, thus improving EEQ. In the future territorial spatial planning and construction of Changsha, it is necessary to promote the transformation and upgrading of low-end industries into high-end manufacturing industries and control the scale of inefficient industrial land. The EEQ degradation caused by industrial land expansion needs to be noted. All of these findings can provide valuable information for relevant decision-makers to formulate ecological environment protection strategies and conduct future territorial spatial planning.

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where

is the grayscale value of each pixel;

is the radiation value in thermal infrared bands;

and

are band bias and gain, respectively, which can be obtained from image header files;

and

are calibration parameters and can be obtained from user manuals;

is the temperature at the sensor;

is the central wavelength of thermal infrared bands, i.e., 11.5 μm for the sixth band of TM data, 11.457 μm for the sixth band of ETM+ data, and 10.9 μm for the tenth band of OLI data;

is the surface specific emissivity; and

= 1.438 × 10 −2 m∙K.…”

Section: Methodsmentioning

confidence: 99%

Urban Ecological Environment Quality Evaluation and Territorial Spatial Planning Response: Application to Changsha, Central China

Shi

et al. 2023

IJERPH

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“…Where i z is the I features attribute deviation from its mean value ( -) i x X , i,j w is the spatial weight of i and j feature, n is the total number of features and 0 S is the aggregate of all spatial weights. elements clustered based on the high (hot spots) or low (cold spots) values of adjacent elements [22]. The Getis-Ord Gi* statistic is calculated by the following equation [23].…”

Section: Global Spatial Auto-correlationmentioning

confidence: 99%

Urban ecological quality and statistical correlation analysis based on satellite remote sensing

et al. 2023

IOP Conf. Ser.: Earth Environ. Sci.

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Jiangsu Province is an area with active economic and social development. With the advancement of urbanization, ecological issues have become a hot spot in the region. Objectively and quantitatively assessing spatial-temporal environmental quality changes is crucial for environmental protection and policymaking. Remote sensing is a very effective ground-based information acquisition tool for long-term ecological analysis. Thus, this study uses remote sensing to evaluate the quality of the ecological environment in Jiangsu Province. The Remote Sensing Ecological Index (RSEI) from 1990 to 2020 is calculated on the Google Earth Engine platform. The spatial-temporal changes and spatial auto-correlation of the ecological environment quality are evaluated. The results show that from 1990 to 2020, the ecological status shows a downward-rising-flat trend. The RSEI has decreased from 0.4677(1990) to 0.4524(2005) and then increased from 0.4524(2005) to 0.4562(2020). The spatial auto-correlation analysis show that the spatial distribution of ecological quality is positively correlated. The clustering map of RSEI spatially correlated local indicators show that the hot points are mainly located in the north and middle parts of the study area. The cold points are mainly distributed in the southern Yangtze River coastal urban cluster. Such a technique is not limited by time and space, so it can be widely used in monitoring and protecting the ecological environment.

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“…(5) Urban built-up area data were obtained from the dataset of urban built-up area in China (1992-2020) v1.0, providing support for understanding the urban expansion process and its impact in China [56,57]. (6) Land cover data used were sourced from the China Land Cover Dataset (CLCD) of Wuhan University [58], containing annual land cover information for China in 1985 and 1990-2022.…”

Section: Remote Sensing Productsmentioning

confidence: 99%

“…The expansion of urban areas has encroached upon arable land and other ecologically sensitive areas, giving rise to numerous ecological challenges and environmental problems, including environmental pollution, biodiversity crises, and degradation of ecological quality [5]. These issues have significantly impacted human livelihoods and disrupted normal production processes [6]. As awareness grows regarding the importance of balancing human socioeconomic development and ecological restoration, the establishment of high-quality urban ecosystems, where humans and nature coexist harmoniously, has become a key goal for governments and urban planning [7,8].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the Spatiotemporal Change of Ecological Quality under the Context of Urban Expansion—A Case Study of Typical Urban Agglomerations in China

Guo,

Zhao,

Zhao

et al. 2023

Remote Sensing

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As a significant manifestation of human activities influencing natural environment, rapid urbanization has enhanced economic prosperity while simultaneously posing threats to ecological quality. Beijing–Tianjin–Hebei (BTH), the core region of the Yangtze River Delta (CYRD), and the Pearl River Delta (PRD) stand as three major economic centers characterized by the highest level of urbanization in China, encompassing areas of heightened ecological sensitivity. Nevertheless, the ecological quality at the scale of urban agglomerations remains ambiguous, with many studies failing to develop a comprehensive and effective method for comparing diverse urban agglomerations. Consequently, this study integrates multi-source remote sensing data, including information on land cover and other socio-economic parameters, to construct the Ecological Quality Index (EQI) based on the “Function–Interaction–Pressure–Stability” (FIPS) framework. Through a stratified determination of indicator weights grounded in both objective importance and empirical knowledge, we mapped the spatiotemporal changes of EQI and analyzed the impact of urbanization on ecological quality in three urban agglomerations from 2001 to 2020. We determined the following: (1) The calculated EQI can further capture the nuanced details with better performance at both underlining the discrepancy of highs and lows of EQI and describing the spatial detail of urban agglomerations’ characteristics. (2) Substantial disparities in EQI and its changes are evident across different urban agglomerations. Notably, only the average EQI improves in PRD, while ecological degradation is prominent in specific regions, such as the southeastern plains of BTH area, along the Yangtze River, and around Shanghai in CYRD and central PRD. The CYRD exhibits the largest affected area. (3) Urbanization predominantly influences ecological quality through land cover transitions. In expansion areas, ecological deterioration is significantly more pronounced, constituting approximately 90% of the total area. (4) Despite significant urbanization, city-level analysis in CYRD reveals a better coordination between urban expansion and ecological protection, with a lower intensity of ecological degradation compared to urban expansion rates. Conversely, some cities in the BTH, despite modest urban expansion, exhibit substantial declines in ecological quality, highlighting the need for targeted policy interventions. In conclusion, this study elucidates the intricate relationship between urbanization and ecological quality, offering valuable insights for the development of targeted protection strategies and sustainable urban planning.

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Assessing Land Cover and Ecological Quality Changes under the New-Type Urbanization from Multi-Source Remote Sensing

Cited by 16 publications

References 60 publications

Urban Ecological Environment Quality Evaluation and Territorial Spatial Planning Response: Application to Changsha, Central China

Urban Ecological Environment Quality Evaluation and Territorial Spatial Planning Response: Application to Changsha, Central China

Urban ecological quality and statistical correlation analysis based on satellite remote sensing

Evaluation of the Spatiotemporal Change of Ecological Quality under the Context of Urban Expansion—A Case Study of Typical Urban Agglomerations in China

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