Land use/cover change and ITS eco-environment effect in Shiyang River Basin

Hu, Xiaonong; Jin, Yuhao; Ji, Lei; Zeng, Jianbin; Cui, Yubo; Song, Zhihua; Sun, D Y; Cheng, Yu Fei(程雨菲)

doi:10.1088/1755-1315/191/1/012016

Cited by 8 publications

(7 citation statements)

References 20 publications

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“…In addition, Optimizing water resources in densely populated zones is challenging for scientists, communities, and policymakers, especially in arid and semiarid regions [130]. For example, several studies conducted in the Shiyang River basin raised concerns about the correlation between population pressure and water resources shortage as the center of desert expansion in the Shiyang River basin [47,71,131,132]. However, by analyzing road networks and waterway buffers as a proxy for population and water use in the Shiyang River basin, the closer the distance to the waterway, the lower the land degradation risk, Fig 8.…”

Section: Environmental Risk Detection Of Desertification In the Shiya...mentioning

confidence: 99%

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Quantitative analysis of desertification driving mechanisms in the Shiyang River Basin: Examining interactive effects of key factors through the Geographic Detector Model

Ngabire¹,

Wang²,

Lü³

et al. 2023

Preprint

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Desertification is a global environmental and socio-economical issue threatening humanity's survival and development. The Shiyang River Basin ecosystem is vulnerable and prone to desertification. In addition, establishing the quantitative analysis of desertification driving factors and understanding their relative contribution, separately or combined, is still an unresolved problem. The present study applied geographic information system (GIS) techniques and a geographic detector model to quantify desertification spatial extent and driving mechanisms. This research utilized Fractional Vegetation Cover (FVC) to elucidate desertification spatial heterogeneity. The 30 years Coefficient of Variation (CV) of the Normalized Difference Vegetation Index (NDVI) was a dependent variable and indicator of ecosystem terrestrial conditions; Elevation, near-surface air temperature, precipitation, wind velocity, land cover change, soil salinity, road buffers, waterway buffers, and soil types were independent variables. The results showed that 89.41% of the total area is under desertification risk, where 20.99% is extremely desertified, 34.45% is severely desertified, 12.05% is moderately, and 21.92% is slightly desertified. The results from the Geodetector model showed that Power Determinant (PD) values ranged between 0.004 and 0.270. Elevation and soil types had the highest contributing factors with PD values of 0.270 and 0.227, whereas precipitation, soil salinity, the buffer of the waterway, and wind velocity played a moderate role with PD values of 0.146, 0.117, 0.107, and 0.071. Near-surface air temperature, road buffer, and land cover dynamics exhibited lower impact with PD values of 0.028, 0.013, and 0.004. In most cases, investigating the interaction between driving factors resulted in a mutual or non-linear enhancement. There was an apparent linear and mutual enhancement between elevation and soil salinity, precipitation, and soil types with values of 0.3513, 0.3232, and 0.3204, respectively. In addition, there was a mutual enhancement between soil salinity and soil types with a value of 0.2962. On the other hand, a non-linear enhancement was observed between Elevation and near-surface air temperature (0.3116), Elevation and Land cover dynamics (0.2759), soil types and near-surface air temperature (0.2687), land cover dynamics and soil types (0.234), precipitation and near-surface air temperature (0.2248), precipitation and wind velocity (0.2248), and between land cover dynamics and precipitation (0.223). This research revealed irrefutable evidence that environmental factors might be the primary drivers of ecosystem disturbance, provided the basis for the environmental footprint of desertification mechanism, and might be a cornerstone for future policy on ecological restoration sustainability in the Shiyang River Basin.

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Section: Environmental Risk Detection Of Desertification In the Shiya...mentioning

confidence: 99%

“…These measures include biological indicators such as vegetation greening trend patterns and physical indicators such as top-layer soil properties, landscape change, etc. [44][45][46][47][48][49][50].…”

Section: Introductionmentioning

confidence: 99%

Quantitative analysis of desertification driving mechanisms in the Shiyang River Basin: Examining interactive effects of key factors through the Geographic Detector Model

Ngabire¹,

Wang²,

Lü³

et al. 2023

Preprint

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“…The land use transformation matrix represents the transfer area of each land use type from the beginning to the end of the research period in a matrix form [40]. The calculation formula is…”

Section: Land Use Transformation Matrixmentioning

confidence: 99%

Land Use Transformation Based on Production−Living−Ecological Space and Associated Eco-Environment Effects: A Case Study in the Yangtze River Delta Urban Agglomeration

Zhang

Xiao

et al. 2022

Land

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We investigate the eco-environmental effects and the driving factors of transforming the production–living–ecological space (PLES) land use function and offer a scientific foundation for developing regional territorial area and environmental preservation. Eco-environment quality index and ecological contribution ratio are used to analyze the spatial–temporal evolution characteristics and eco-environment effects of land use transformation in the Yangtze River Delta Urban Agglomeration (YRDUA) over the three time periods of 2000, 2010, and 2020, and the geographic detectors are used to analyze the factors that influence the spatial difference of eco-environment quality (EEQ). The findings indicate the following: (1) The land use transformation of YRDUA is primarily shown in the shrinkage of the production land area, the stability of ecological land, and the rapid increase of living land. The area of ecological land, such as water, forest, and pasture, has remained relatively steady from the perspective of secondary land types. In contrast, the area of urban and rural living land has significantly increased. (2) Most land use environment comprises the lower-value zone, accounting for about 50%. The area of the low-value zone has continued to rise owing to the rapid urban and rural living land development, tending to continuous growth. (3) Both the ecological improvement and degradation trends are present simultaneously, although the ecological improvement trend is less prominent than the environmental degradation trend. The primary factor is improving the eco-environment by transforming agricultural production land into forest, water, and ecological pasture land. The degradation of the regional EEQ is mostly due to the occupation of agricultural production land by urban and rural living land. (4) Considering natural elements such as altitude, precipitation, and slope, the extent of land use impacts the EEQ. The combination of several factors has changed the EEQ of the YRDUA. The effect of any two elements is stronger than that of a single factor.

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“…Land is an important link between humans and nature [1][2][3], and it is the basis for human survival and development. In recent years, with the acceleration of global climate change, the increase in the frequency and expansion of the scope of human activities, such as the growing population and rapid urbanization, have led to great changes in land-use types [4][5][6]. Land use/cover change (LUCC) is an important component in the study of global climate and environmental changes [7][8][9] and has an important role in the Earth's system [10].…”

Section: Introductionmentioning

confidence: 99%

Analysis of the Evolution of Land-Use Types in the Qilian Mountains from 1980 to 2020

Wang

Yang

2023

Land

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The Qilian Mountains (QMs), located in the northeast part of the Qinghai–Tibetan Plateau in China, have a fragile ecological environment, complex and sensitive climate, and diverse land-cover types. It plays an important role in the “Qinghai–Tibetan Plateau Ecological Barrier” and “Northern Sand Control Belt” in China’s “two screens and three belts” ecological security strategy. Based on land use data of 1980, 1990, 1995, 2000, 2005, 2010, 2015, and 2020, we utilized GIS technology, land use dynamic degree, and land use transition matrixes to analyze the spatial and temporal evolution of land use in the QMs from 1980 to 2020. The results showed the following: (1) From 1980 to 2020, grassland, forest land, and unused land were the main land-use types in the QMs, and the proportion of construction land accounted for only 0.31% of all land-use types. (2) The single land use dynamic degree showed that the dynamic degree of construction land was the highest and the fastest change rate from 2010 to 2015. The comprehensive land use dynamic degree showed that the intensity of land-use change was relatively drastic in the three time periods of 1990–1995, 1995–2000, and 2015–2020. (3) The land-use types in the study area switched infrequently during 2000–2005, 2005–2010, and 2010–2015. (4) The main transition directions of land-use types were grassland and unused land to other land-use types. These changes altered the spatial distributions of different land-use types. The study is critical for understanding the spatial and temporal change patterns of land-use change in the QMs and providing guidance for the optimization of land use in the study area and the improvement of regional eco-environmental protection.

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Land use/cover change and ITS eco-environment effect in Shiyang River Basin

Cited by 8 publications

References 20 publications

Quantitative analysis of desertification driving mechanisms in the Shiyang River Basin: Examining interactive effects of key factors through the Geographic Detector Model

Quantitative analysis of desertification driving mechanisms in the Shiyang River Basin: Examining interactive effects of key factors through the Geographic Detector Model

Land Use Transformation Based on Production−Living−Ecological Space and Associated Eco-Environment Effects: A Case Study in the Yangtze River Delta Urban Agglomeration

Analysis of the Evolution of Land-Use Types in the Qilian Mountains from 1980 to 2020

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