A novel design and application of spatial data management platform for natural resources

Kong, Weijiang; Wang, Tengji; Liu, Huan; Luo, Pingping; Chen, Jianjun; Wang, Ligang; Hua, Xiankang; Duan, Weili; Su, Feng

doi:10.1016/j.jclepro.2023.137183

Cited by 10 publications

(7 citation statements)

References 52 publications

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“…This differs from the conclusions of this study, which emphasize the varying roles of multiple factors in the sustainable development of rural tourism [45]. Other scholars have focused on the issue of social equity in the evaluation of rural tourism landscapes, they have found that social equity and spatial data for natural resources has a significant influence on the sustainable development of rural tourism [59]. In contrast to the findings of this study, their research considered social equity an important dimension, highlighting its importance in the sustainable development of rural tourism [31,60].…”

Section: Discussioncontrasting

confidence: 99%

Exploring the Comprehensive Evaluation of Sustainable Development in Rural Tourism: A Perspective and Method Based on the AVC Theory

Liu

Lou

et al. 2023

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The coronavirus disease (COVID-19) pandemic has led to a surge in rural tourism, catering to consumers during the pandemic. However, rural tourism faces severe issues of homogeneity and environmental degradation owing to excessive development. Sustainable development of rural tourism is an urgent problem. This study, based on the average variable cost (AVC) theory, aims to explore the sustainable development of rural tourism landscapes with a focus on the Shijing area. A landscape evaluation system was established through factor analysis and weight calculations, with ten principal components contributing to a cumulative contribution rate of 77.196%. The weighted values for attractiveness, vitality, and resilience were 0.539, 0.297, and 0.164, respectively. The findings indicate that Caijiapo Village had the highest comprehensive score of 88.79 (good level of performance), whereas Laoyukou Village had the lowest comprehensive score of 80.25 (average level of performance). Caijiapo and Liyukou exhibited the strongest overall strength, whereas Liyuanpo and Xiazhuang had moderate overall strength, and Laoyukou had the weakest overall strength. The results reveal that all five villages possess rich natural landscapes and favorable geographical conditions, demonstrating the potential and attractiveness of rural tourism development. However, the overall carrying capacity was moderate and vitality was relatively weak. This supports the AVC theory application in rural tourism research and emphasizes the importance of rural landscape quality and economic vitality. The main contributions of this study are as follows: (1) the establishment of a rural tourism landscape evaluation system based on the AVC theory, providing a scientific assessment method for sustainable development; (2) the case evaluation in the Shiying area provides decision-makers with reference for development strategies; (3) emphasis on the importance of ecological conservation in rural tourism and providing recommendations to address issues of homogenization and environmental degradation.

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Section: Discussioncontrasting

confidence: 99%

Exploring the Comprehensive Evaluation of Sustainable Development in Rural Tourism: A Perspective and Method Based on the AVC Theory

Liu

Lou

et al. 2023

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“…Furthermore, this study utilized ML for weight calculation, significantly improving the computational efficiency [66,67]. Previous studies have used neural network methods and random forest algorithms for weight calculation [51], thereby enhancing the scientific nature of weights. Therefore, this study selected the combination weighting method and combined it with local characteristics for indicator selection, indicator weighting, and subsequent subjective-objective weight adjustments.…”

Section: Discussionmentioning

confidence: 99%

“…The widely used MCR model is used due to its strong generality and operational feasibility [68]. When selecting indicators, the habitat of nationally protected animals, such as the Crested Ibis and the Giant Panda in the Qinling Mountains, was considered along with the prevention and control of natural disasters in other studies [35,51]. Factors such as ecological redlines and geological hazards were selected as the ecological security indicators.…”

Section: Discussionmentioning

confidence: 99%

“…Using RS and GISs technology, these data can be integrated, overlaid, and spatially analyzed to form a spatial representation of ESPs. Additionally, RS technology can monitor and evaluate the impact of land-use changes by analyzing the effects of human activities on the ecosystem [51,52]. Furthermore, RS and GISs can help achieve coordination among ESPs, land use, and overall urban-rural planning [53], therefore, facilitating the integration and sharing of different data sources, promoting interdepartmental and interdisciplinary collaboration and coordination, and improving the scientific accuracy of decision-making.…”

Section: Introductionmentioning

confidence: 99%

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Quantitative Model Construction for Sustainable Security Patterns in Social–Ecological Links Using Remote Sensing and Machine Learning

et al. 2023

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With the global issues of extreme climate and urbanization, the ecological security patterns (ESPs) in the Qinling Mountains are facing prominent challenges. As a crucial ecological barrier in China, understanding the characteristics of ESPs in the Qinling Mountains is vital for achieving sustainable development. This study focuses on Yangxian and employs methods such as machine learning (ML), remote sensing (RS), geographic information systems (GISs), analytic hierarchy process and principal component analysis (AHP–PCA), and the minimum cumulative resistance (MCR) model to construct an ecological security network based on multi-factor ecological sensitivity (ES) and conduct quantitative spatial analysis. The results demonstrate that the AHP–PCA method based on ML overcomes the limitations of the single-weighting method. The ESPs of Yangxian were established, consisting of 21 main and secondary ecological sources with an area of 592.81 km2 (18.55%), 41 main and secondary ecological corridors with a length of 738.85 km, and 33 ecological nodes. A coupling relationship among three dimensions was observed: comprehensive ecological sensitivity, ESPs, and administrative districts (ADs). Huangjinxia Town (1.43 in C5) and Huayang Town (7.28 in C4) likely have significant areas of ecological vulnerability, while Machang Town and Maoping Town are important in the ESPs. ADs focus on protection and management. The second corridor indicated high-quality construction, necessitating the implementation of strict protection policies in the study area. The innovation lies in the utilization of quantitative analysis methods, such as ML and RS technologies, to construct an ecological spatial pattern planning model and propose a new perspective for the quantitative analysis of ecological space. This study provides a quantitative foundation for urban and rural ecological spatial planning in Yangxian and will help facilitate the sustainable development of ecological planning in the Qinling region.

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“…Thirdly, horizontal comparisons analyzed diverse spatial contexts, examining settlement patterns across various regions formed over extended time periods at the same point in time [78]. The fourth type involves studying the evolution of three-dimensional (3D) landscape spatial patterns at different spatiotemporal scales [57,[79][80][81], which represent current research trends and hotspots. Therefore, this study has employed the fourth type and innovated a 3D modeling approach, combined with GIS and RS analysis to conduct a multi-scale dynamic evolution study of rural landscape characteristics, achieving a certain level of methodological innovation.…”

Section: Discussionmentioning

confidence: 99%

A Novel Integrated Spatiotemporal-Variable Model of Landscape Changes in Traditional Villages in the Jinshaan Gorge, Yellow River Basin

Liu,

Chen,

Luo

et al. 2023

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Spatiotemporal studies of landscape pattern evolution in traditional villages are beneficial for addressing complex urbanization and global climate change. Using the traditional villages of Jiaxian and Linxian in the Jinshaan Gorge of the Yellow River Basin, this study employed a three-dimensional (3D) analysis involving three spatial scales (macro, meso, and micro), temporal scales (past, present, and future), and variables (humanity, society, and nature) based on the methods of spatiotemporal data analysis (SDA), geographic information system, remote sensing, and landscape pattern index (LPI) by Fragstats. On the macro scale, a significant turning point in ecological conservation awareness was indicated by LPI and SDA. Urban and rural construction land continuously increased because of urbanization. Plowland, grassland, and woodland were the main influencing factors in the evolution of rural settlements, with a 0.42% cumulative transformation rate. On the meso scale, the interactions and mutual promotion of mountain and aquatic environments, aquatic facilities, agricultural production, and cultural heritage have shaped the socioeconomic dimensions of evolution. On the micro scale, with urbanization, some traditional humanistic spaces have lost their original functions. A novel spatiotemporal-variable quantitative model explored the spatiotemporal evolution characteristics of human–land coupling, which can be used for the sustainable development of river basins worldwide.

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A novel design and application of spatial data management platform for natural resources

Cited by 10 publications

References 52 publications

Exploring the Comprehensive Evaluation of Sustainable Development in Rural Tourism: A Perspective and Method Based on the AVC Theory

Exploring the Comprehensive Evaluation of Sustainable Development in Rural Tourism: A Perspective and Method Based on the AVC Theory

Quantitative Model Construction for Sustainable Security Patterns in Social–Ecological Links Using Remote Sensing and Machine Learning

A Novel Integrated Spatiotemporal-Variable Model of Landscape Changes in Traditional Villages in the Jinshaan Gorge, Yellow River Basin

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