自20世纪90年代以来，随着我国经济的快速发展、人口数量的增加从而导致区域生态环境受到人为因素的干扰日趋严重，土地资源的不合理利用也严重影响着区域生态稳定性。景观生态风险评价是以土地利用类型作为景观生态风险评价的综合体，通过选取合适的景观指数构建景观生态风险评价模型，进而对区域内景观生态风险进行评价，并探究自然因素和人为因素对区域内生态环境造成的影响。基于土地利用类型数据进行景观生态风险评价，对区域内土地资源的合理配置、生态环境保护和促进资源可持续性利用具有重要的现实意义。
本文以渭河流域为研究对象，首先对研究区域内土地利用类型进行时空变化分析；其次选取景观指数来构建景观生态风险评价模型，对渭河流域1990-2018年七个时期的景观生态风险进行时空变化特征分析；再结合地理加权回归模型和地理探测器研究渭河流域景观生态风险发生的驱动因子、驱动因子对景观生态风险空间分布的作用强度及驱动因子之间的交互作用对景观生态风险发生的影响。主要结论如下：
（1）基于中国科学院资源环境科学数据中心下载的1990-2018年土地利用数据，从土地利用类型的数量、结构、动态度和转移方向等方面定量地分析渭河流域土地利用时空变化规律。结果表明：在整个研究期间内，渭河流域以耕地和草地为主要土地利用类型，耕地和草地的面积占流域总面积的75%以上；从渭河流域土地利用变化的时空动态度的角度看，渭河流域的综合动态度呈现“N型”的发展趋势，其中2015-2018年的综合动态度最大为4.80%，说明这一时期渭河流域综合土地利用类型的变化最为显著；从土地利用类型转移的数量和方向看，渭河流域内的土地利用类型的转化方式以耕地和草地之间进行相互转化、耕地的转出和建设用地的转入为主。
（2）基于景观生态学的角度选取了景观破碎度、景观分离度、景观优势度和景观脆弱度等指数构建景观生态风险评价模型，对1990-2018年渭河流域景观生态风险进行评价，并对其时空变化规律进行分析，利用空间自相关方法探究其空间的自相关性和空间异质性。结果表明：1990-2018年，渭河流域内较低风险、中风险和较高风险区域的面积在增加，高风险区域的面积在减少，其中较低风险区、中风险区和较高风险区的面积分别增加了2.94%、4.97%和3.54%，但高风险区的面积减少了11.24%，说明在研究时期内渭河流域的景观生态风险整体上呈现降低的趋势，表明渭河流域内景观生态风险正在向好的方向发展；在空间自相关分析中，1990-2018年间渭河流域景观生态风险在空间上具有显著的正相关性，在空间分布呈现“高-高”聚集和“低-低”聚集的形式。
（3）从自然因素和人为因素两个方面选取渭河流域景观生态风险发生的驱动因子, 用地理加权回归模型和地理探测器方法研究驱动因子对景观生态风险空间分布的作用强度及驱动因子之间的交互作用。结果表明：对渭河流域景观生态风险影响较为显著的驱动因子为：DEM、坡度、降水量、年均气温、相对湿度、人口密度和人为干扰度，其中各驱动因子对渭河流域景观生态风险的作用强度和空间分布均不相同，其中人为干扰度的对渭河流域内景观生态风险的发生作用强度最大；从驱动因子之间的交互作用来看，坡度和人为干扰度交互后对渭河流域内景观生态风险发生的解释力达到了60%以上，而且两两驱动因子交互作用后的强度均大于单驱动因子，说明渭河流域景观生态风险的发生并不是单个驱动因子直接作用的结果，而是各驱动因子之间两两交互作用后增强的结果。

Since the 1990s, with the rapid development lor='red'>of China's economy and the rapid increase lor='red'>of the population, the region ecological environment has been strongly disturbed by human factors, and the irrational use lor='red'>of land resources also seriously affected the stability lor='red'>of region ecology. Landscape ecological risk assessment (LERA) is based on land use landscape, and the assessment model was constructed by selecting and calculating the appropriate landscape index in land use time series. The landscape ecological risk change can reveal the pattern lor='red'>of landscape ecological risk and the influence lor='red'>of natural factors and human activities in the region. Therefore, the research on LERA is very important for the rational allocation lor='red'>of land resources, ecological environmental protection and the promotion lor='red'>of sustainable utilization lor='red'>of resources in the region.

The paper analyzed the spatial-temporal changes lor='red'>of land use types in Weihe River Basin from 1990 to 2018, and using landscape indexes to construct LERA model. The spatial-temporal changes lor='red'>of landscape ecological risks have been analyzed. Combined with the geographical weighted regression model and geographical detectors, the lor='red'>driving factors lor='red'>of landscape ecological risk occurrence in the Weihe River Basin, the intensity lor='red'>of the lor='red'>driving factors on the spatial distribution lor='red'>of landscape ecological risks, and the interaction between lor='red'>driving factors on the occurrence lor='red'>of landscape ecological risks were studied. The main conclusions are as follows:

(1) Based on land use data form Data Center for Resources and Environmental Sciences, Chinese Academy lor='red'>of Sciences, the spatial and temporal changes lor='red'>of land use in the Weihe River Basin were quantitatively analyzed from the aspects lor='red'>of quantity, structure, dynamic degree and transfer direction lor='red'>of land use types. The results showed that during the whole study period, cultivated land and grassland were the main land use types in the Weihe River Basin, and the area lor='red'>of cultivated land and grassland accounted for more than 75% lor='red'>of the total area. From the perspective lor='red'>of the spatial-temporal dynamics lor='red'>of land use change in the Weihe River Basin, the comprehensive dynamics lor='red'>of the Weihe River Basin showed an ‘N-type’ development trend, in which the maximum comprehensive dynamic degree from 2015 to 2018 was 4.80%. The change lor='red'>of comprehensive land use types in the Weihe River Basin during this period was the most significant. From the perspective lor='red'>of the number and direction lor='red'>of land use type transfer, the transformation mode lor='red'>of land use class in the Weihe River Basin are mainly the mutual transformation between cultivated land and grassland, the transfer lor='red'>of cultivated land and the transfer lor='red'>of construction land.

(2) Landscape fragmentation, landscape separation, landscape advantage and landscape vulnerability in landscape ecology were selected to construct landscape ecological risk evaluation model from 1990 to 2018 for Weihe River Basin. The spatial-temporal autocorrelation and spatial heterogeneity were explored by spatial autocorrelation methods. The results showed that from 1990 to 2018, the area lor='red'>of lower-risk, medium-risk and higher-risk areas in the Weihe River Basin were increased, and the area lor='red'>of high-risk areas was decreased. The areas lor='red'>of lower-risk areas, medium-risk areas and higher-risk areas increased by 2.94%, 4.97% and 3.54% respectively, and the area lor='red'>of high-risk areas decreased by 11.24%. These indicated that the landscape ecological risk lor='red'>of the Weihe River Basin showed a decreasing trend during the whole period. It also showed that the landscape ecological risk in the Weihe River Basin is developing in a good direction. The spatial autocorrelation analysis showed that the landscape ecological risks lor='red'>of the Weihe River Basin had a significant positive correlation in space from 1990 to 2018, and the spatial distribution showed the forms lor='red'>of "high-high" aggregation and "low-low" aggregation.

(3) The factors for the occurrence lor='red'>of ecological risks in the Weihe River Basin were selected from the aspects lor='red'>of natural factors and human factors, and then interactive detectors were used to interactively detect the dominant factors. The intensity lor='red'>of the lor='red'>driving factors and the interaction between lor='red'>driving factors were studied by geographical weighted regression model and geographical detectors. The results showed that the significant lor='red'>driving factors were DEM, slope, precipitation, annual average temperature, relative humidity, population density and human interference. The intensity and spatial differences lor='red'>of the lor='red'>driving factors on the landscape ecological risk lor='red'>of the Weihe River Basin are different, and the intensity lor='red'>of human interference was most important. From the perspective lor='red'>of the interaction between the lor='red'>driving factors, the explanatory power lor='red'>of the occurrence lor='red'>of landscape ecological risk in the Weihe River Basin after the interaction lor='red'>of slope and human interference has reached more than 60%, and the intensity lor='red'>of the interaction lor='red'>of the two lor='red'>driving factors were greater than single lor='red'>driving factor, which indicated that the occurrence lor='red'>of landscape ecological risk in the Weihe River Basin was not only the result lor='red'>of a single lor='red'>driving factor, but also the result lor='red'>of the interaction between the lor='red'>driving factors.

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