ESDA (Exploratory Spatial Data Analysis) of Vegetation Cover in Urban Areas—Recognition of Vulnerabilities for the Management of Resources in Urban Green Infrastructure

Moura, Ana Clara Mourão; Fonseca, Bráulio Magalhães

doi:10.3390/su12051933

Cited by 16 publications

(4 citation statements)

References 26 publications

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“…In this study, we utilized ArcGIS 10.2 and GeoDa to visualize spatiotemporal evolution and local spatial autocorrelation analysis (LISA). Then, the spatiotemporal patterns of green development performance and spatial autocorrelation were explored [ 51 ]. Among them, LISA was used to explore the local spatial variation pattern of the research object or the spatial anomalies that occur, which can be divided into the following four cases: high-high cluster, high-low cluster, low-high cluster, and low-low cluster.…”

Section: Methodsmentioning

confidence: 99%

Green Development Performance Evaluation Based on Dual Perspectives of Level and Efficiency: A Case Study of the Yangtze River Economic Belt, China

Zhang

Ren

2022

IJERPH

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In the context of continuing to promote the construction of an ecological civilization, it is of great significance to explore green development performance. However, most of the literature is based on a single perspective of level or efficiency, lacking a comprehensive examination of both. It is not scientific to explore how to promote green development only from a single perspective, which may be a new advancement by breaking the conventional thinking focusing only on level or efficiency. On this basis, we first established evaluation index systems of green development performance based on a theoretical framework. Furthermore, green development performance was measured with the entropy weight technique for order preference by similarity to ideal solution (TOPSIS) and super-EBM models, and finally, we analyzed the spatial and temporal evolution patterns of green development performance using the ESDA method and examined its influencing factors with a geographic detector (GD) and econometric models. The main results were as follows: (1) The trend of the green development level in the Yangtze River Economic Belt from 2004 to 2017 had an inverted “N” shape, while the overall average green development efficiency continuously increased. (2) In terms of spatial and temporal patterns, both the green development level and green development efficiency showed “high in the east and low in the west” spatial divergence characteristics. In terms of the spatial and temporal evolution pattern of the green development level, the L-L clusters were mainly distributed in the western region. However, for green development efficiency, the L-L clusters were mostly distributed around the H-H clusters. (3) The results of the influencing factor analysis indicated that industrial structure and people’s welfare are still important factors of the green development level. The improvement of green development efficiency was mainly driven by economic development, and the inhibiting effect of energy consumption is significant. In addition, the effect of opening up has not yet changed from a “pollution paradise” to a “pollution halo”.

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Section: Methodsmentioning

confidence: 99%

Green Development Performance Evaluation Based on Dual Perspectives of Level and Efficiency: A Case Study of the Yangtze River Economic Belt, China

Zhang

Ren

2022

IJERPH

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“…The global Moran's I index analyses the overall pattern of regional rural transformation development, and it reveals the spatial correlation characteristics of rural transformation development. The local LISA index describes the local spatial heterogeneity in rural transformation development, and it identifies the correlation characteristics of local different spatial positions [37][38][39].…”

Section: Spatial Autocorrelation Modelmentioning

confidence: 99%

Spatial–Temporal Differentiation and the Driving Mechanism of Rural Transformation Development in the Yangtze River Economic Belt

Zhang

2022

Sustainability

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Rural transformation development is an important part of rural revitalization, and the study of spatial–temporal differentiation characteristics and the driving mechanism of rural transformation development can provide a decision-making reference for formulating rural revitalization programs according to local conditions. Taking the Yangtze River Economic Belt as the research case, we constructed an evaluation system of rural transformation development in the dimension of “population, land and industry”, and the entropy TOPSIS method, spatial autocorrelation model and geographic detector model were used to reveal spatial-temporal differentiation and the driving mechanism of rural transformation development in the Yangtze River Economic Belt from 1978 to 2018. The results showed that (1) rural transformation development has been significantly unbalanced in the Yangtze River Economic Belt, and rural transformation development showed a weak distribution. Moreover, in terms of dimensions, the land use transformation level > population development transformation level > industrial development transformation level. (2) On the global, rural transformation development presented a spatial distribution trend of club convergence. On the local, the H(High)–H(High) type was mainly distributed in Shanghai City and the southern part of Jiangsu Province, and it evolved to Hangzhou-Shaoxing-Ningbo and Wanjiang City Belt; the L(Low)–L(Low) type was mainly concentrated in the western part of Sichuan Province and in the southwest of Yunnan Province. (3) Natural conditions, economic social development, traffic accessibility, policies and systems were the leading factors affecting rural transformation development in the Yangtze River Economic Belt. The influences of economic social development and traffic accessibility on rural transformation development were increasing, and policy factors had an important guiding effect on rural transformation development, and the influence of natural conditions on rural transformation development has weakened. This study can provide a practical reference for rural transformation and rural revitalization in the Yangtze River Economic Belt.

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“…Thus, ESDA can aid in developing a hypothesis for spatial regimes or other types of spatial heterogeneities [18]. ESDA was initially only applied in the economic and social sciences [18,19], but in its development, ESDA has been widely used in several other fields such as geography, environmental science [20,21] and water resources [6,22].…”

Section: Introductionmentioning

confidence: 99%

Spatial-Temporal Changes in Water Supply and Demand in the Citarum Watershed, West Java, Indonesia Using a Geospatial Approach

Nahib¹,

Amhar²,

Wahyudin

et al. 2022

Sustainability

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Balancing water supply demand is vital for sustaining livelihoods. Spatial mapping and calculating water yield dynamics due to land use changes over decades are needed to manage land resources and formulate ecological protection policies. This study mapped the supply, demand, and matching status of water product service using the Integrated Valuation of Ecosystem Service and Tradeoff (InVEST) biophysical models in the Citarum Watershed (CW) in 2000, 2010, and 2020. Moreover, this study used Exploratory Spatial Data Analysis (ESDA) and Geographic Information System (GIS) techniques to study the agglomeration characteristics and evolutionary trajectories of supply–demand over two decades. The results showed that between 2000–2010 and 2010–2020, the water supply decreased by 19.01 × 108 m3 (18.28%) and 12.97 × 108 m3 (15.27%), respectively. However, the water demand in the same period increased by 6.17 × 108 m3 (23%) and 15.74 × 108 m3 (47%), respectively. Over the decades, the contribution of land use land cover (LULC) changes to variations in water supply has yielded values ranging from 2.87% to 6.37%. The analysis of the water supply–demand imbalance indicated that the entire CW experienced water shortage, and the type of spatial matching for supply and demand is dominated by a high supply and high demand class (16.09% of the total area). Based on the level of water deficit calculation, the upstream and downstream areas were identified as zones that require ecological conservation, while the middle CW area requires ecological restoration or ecological improvement.

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ESDA (Exploratory Spatial Data Analysis) of Vegetation Cover in Urban Areas—Recognition of Vulnerabilities for the Management of Resources in Urban Green Infrastructure

Cited by 16 publications

References 26 publications

Green Development Performance Evaluation Based on Dual Perspectives of Level and Efficiency: A Case Study of the Yangtze River Economic Belt, China

Green Development Performance Evaluation Based on Dual Perspectives of Level and Efficiency: A Case Study of the Yangtze River Economic Belt, China

Spatial–Temporal Differentiation and the Driving Mechanism of Rural Transformation Development in the Yangtze River Economic Belt

Spatial-Temporal Changes in Water Supply and Demand in the Citarum Watershed, West Java, Indonesia Using a Geospatial Approach

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