Dynamic Analysis of Land Use / Cover Change in Dangshan County

Fang, Gang; Yang, Juan; Su, Hai Min

doi:10.4028/www.scientific.net/amr.356-360.2874

Cited by 4 publications

(5 citation statements)

References 6 publications

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“…Earlier studies have used spatial autocorrelation analyses [36], ordinary least squares and geographically weighted regression methods [25], the Spatial Dubin Model [35], and the three-dimensional trend surface [28], etc. The analysis indicates that the factors driving land development intensity in counties primarily comprise population, economy, and industry, which result from various factors [35,[37][38][39][40][53][54][55][56][57]. This result aligns with our findings.…”

Section: Analysis Of Causes Of Changesupporting

confidence: 90%

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Spatiotemporal Evolution and Driving Factors of Land Development: Evidence from Shandong Province, China

Zhao,

Geng,

Liu

et al. 2023

Sustainability

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As populations and economies have grown rapidly, questions of land development and use have intensified. It has become a major global concern to achieve sustainable land use practices. This study reveals evolution of the spatiotemporal pattern of land development intensity of counties in Shandong Province by introducing a land development intensity measurement model combined with three-dimensional trend surface and spatial autocorrelation analyses. Geodetector and geographically weighted regression models were employed to demonstrate the interplay and spatiotemporal heterogeneity between development intensity and drivers. The empirical results show that the value of land development intensity of counties in Shandong Province shows a general growth trend, with the number of counties with higher values gradually increasing and the number of counties with lower values gradually decreasing. We also found that the spatial heterogeneity of land development intensity across counties in Shandong Province is significant, and the spatial distribution pattern is basically consistent with the “one group, two centers and three circles” strategy proposed by the Shandong Provincial Government. There is also a positive spatial correlation and clustering effect of land development intensity of counties in Shandong Province. High (low) value clusters are concentrated in core hot (cold) counties, driving some of the surrounding counties towards radial development. The alteration in the intensity of county land development is a complex occurrence that is shaped by numerous factors. Among these, GDP per capita and population density have the primary influence on land development of counties in Shandong Province. To achieve coordinated regional social, economic, and environmental benefits, land development within the county should adhere to the principle of adapting to local conditions and implement differentiated development strategies according to different development intensities.

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Section: Analysis Of Causes Of Changesupporting

confidence: 90%

“…Furthermore, alterations in land development intensity can be supported by both topography and natural resources [25,48]. Based on the principle of data accessibility, this study combines previous research [35,[37][38][39][40][53][54][55][56][57]…”

Section: Sources Of Datamentioning

confidence: 80%

Spatiotemporal Evolution and Driving Factors of Land Development: Evidence from Shandong Province, China

Zhao,

Geng,

Liu

et al. 2023

Sustainability

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“…However, from 2005 to 2015, the area of grassland and unused land showed a decreasing trend of 43.56 km 2 and 35.97 km 2 , respectively. Water areas showed a trend of increasing and then decreasing, with an increase of 5.92 km 2 in 2005-2010 due to the increase in water conservancy facilities, and a decrease of 1.18 km 2 in 2010-2015, which was a small decrease and an insignificant change [22]. Although the decrease in grassland and unused land and the increase in construction land are in line with the current situation of regional development, the increase in forest land is the result of the effective implementation of projects such as returning farmland to forest land and afforestation in recent years.…”

Section: Overview Of the Study Areamentioning

confidence: 99%

Predicting Runoff from the Weigan River under Climate Change

Su,

Zhang,

Deng

et al. 2024

Applied Sciences

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With the warming and humidification process in the Northwest Arid Zone over the past 30 years, the runoff of a vast majority of rivers has been affected to different degrees. In this paper, the runoff from the Weigan River, a typical inland river in the arid zone of Northwest China, is taken as an example, and seven types of CMIP6 data are selected with the help of a SWAT model to predict the runoff volume of the Weigan River in the next 30 years under climate change. The results show that (1) the SWAT model can simulate the runoff from the Weigan River well and has good applicability in this study area. (2) With an increase in radiative forcing, the temperature, precipitation and runoff in the study area show an increasing trend. (3) Under the four radiative forcing scenarios in 2030 and 2050, the runoff from the Weigan River out of the mountain is predicted to be maintained at 25.68 to 30.89 × 108 m3, which is an increase of 1.35% to 21.91% compared with the current runoff, of which the contribution to the increase in future runoff caused by the changes in temperature and precipitation is 68.71% and 27.24%, respectively. It is important to explore the impact of climate change on the runoff from the Weigan River to understand the impact of climate change on the Northwest Arid Region scientifically and rationally, and to provide a scientific basis for evaluating the risk of climate change and formulating policies to deal with it.

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“…It allows transformation information to be obtained about the location and change in areas of different land types at two time phases [26], and has been widely used in LUCC analysis [25][26][27][28][29]. In addition, there are two special methods that have become popular, namely the land use dynamic degree model and intensity analysis [30][31][32][33][34][35][36]. The land use dynamic degree model can be divided into single land use dynamic degree and comprehensive land use dynamic degree.…”

Section: Introductionmentioning

confidence: 99%

“…The land use dynamic degree model can be divided into single land use dynamic degree and comprehensive land use dynamic degree. These can quantitatively describe the change rate of land use and play an important role in comparing the regional differences in LUCC and in predicting future trends [30][31][32][33][34]. The concept of intensity analysis, first proposed in 2012 [35,36], is from the perspective of system theory, and is based on the transfer matrix of land use area from different periods.…”

Section: Introductionmentioning

confidence: 99%

Comparison of the Spatiotemporal Dynamics of Land Use Changes in Four Municipalities of China Based on Intensity Analysis

et al. 2020

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Land use/cover change (LUCC) is becoming one of the most important and interesting problems in the study of global environmental change. Identifying the spatiotemporal behavior and associated driving forces behind changes in land use is crucial for the regional sustainable utilization of land resources. In this study, we consider the four municipalities of China (Beijing, Tianjin, Shanghai, and Chongqing) and compare their spatiotemporal changes in land use from 1990 to 2015 by employing intensity analysis and barycenter migration models. We then discuss their driving forces. The results show that the largest reduction and increase variations were mainly concentrated in arable and construction land, respectively. The decrement and increment were the largest in Shanghai, followed by Beijing and Tianjin, and the least in Chongqing. Furthermore, the results of the barycenter migration model indicate that in addition to Beijing, the migration distances of construction land were longer than those of arable land in three other cities. Moreover, the application of intensity analysis revealed that the rate of land use change was also the greatest in Shanghai and the slowest in Chongqing during the whole study period, with all of their arable land being mainly transformed into construction land. The driving force analysis results suggest that the spatial and temporal patterns of land use change were the results of the socio-economic development, national policies, and major events. In other words, where there was a high rate of economic and population growth, the intensity of land use change was relatively large.

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Dynamic Analysis of Land Use / Cover Change in Dangshan County

Cited by 4 publications

References 6 publications

Spatiotemporal Evolution and Driving Factors of Land Development: Evidence from Shandong Province, China

Spatiotemporal Evolution and Driving Factors of Land Development: Evidence from Shandong Province, China

Predicting Runoff from the Weigan River under Climate Change

Comparison of the Spatiotemporal Dynamics of Land Use Changes in Four Municipalities of China Based on Intensity Analysis

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