基于地理探测器和最大熵模型的人类出行活动强度空间格局模拟：以云南省域为例

doi:10.13249/j.cnki.sgs.2023.08.005

Abstract

Abstract:

Quantitative evaluation of the human travel activity intensity (hereinafter referred to as "human travel intensity") is a fundamental element of human disturbance research, which is of utmost importance for the preservation of biodiversity. Taking the difference between urban areas and non-urban areas into account, in order to improve the response of human travel intensity to each type of environmental variable, this paper focuses on the non-urban areas of Yunnan Province, based on the Tencent location big data, using the geodetector and maximum entropy model to investigate the impact of environmental variables on human travel intensity. The results of the paper reveal that the environmental variables affecting the human travel intensity in the non-urban areas of Yunnan Province present a nonlinear enhancement or bivariate enhancement type under the interaction, and the combination of the distance to residences and the land cover type has the largest explanatory power for the human travel intensity. The prediction accuracy of the maximum entropy model meets the "good" criterion according to the standard (Area Under Curve, AUC= 0.855), and the human travel intensity in the non-urban areas of Yunnan Province shows a general pattern of "high in the east and low in the west". Among all the environmental variables, distance to residences, land cover type, distance to roads, and slope are the main influencing variables, and the cumulative contribution of these four environmental variables exceeds 90%. As a whole, human travel intensity in the non-urban areas of Yunnan Province is concentrated near residences that have gentle topography, a mild climate, moderate precipitation, and easily accessible transportation. The findings of the paper can be utilized to gain an understanding of the factors that are influencing the heterogeneity of human travel and can be a source of guidance for species protection and development in Yunnan Province.

Key words: Yunnan Province, human travel activity intensity, geodetector, maximum entropy model

CLC Number:

P942

Qin Shujie, Qian Tianlu, Wu Zhaoning, Li Yunhao, Wang Jiechen. Simulation of the spatial pattern of human travel activity intensity based on geodetector and maximum entropy model: A case study of Yunnan Province[J].SCIENTIA GEOGRAPHICA SINICA, 2023, 43(8): 1360-1370.

Figures/Tables 7

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	X1	X2	X3	X4	X5	X6	X7	X8	X9
注：X1~X9分别表示海拔、湿润指数、地表覆盖类型、年降水量、距居民点距离、距河流距离、距道路距离、坡度、年均温。
X1	0.0238
X2	0.0364	0.0040
X3	0.3207	0.2995	0.2901
X4	0.0518	0.0356	0.3105	0.0228
X5	0.3523	0.3320	0.5994	0.3596	0.3201
X6	0.0484	0.0326	0.3090	0.0494	0.3312	0.0203
X7	0.1280	0.1120	0.4020	0.1320	0.3816	0.1240	0.1060
X8	0.1199	0.1068	0.3308	0.1215	0.4221	0.1178	0.1987	0.0961
X9	0.0356	0.0410	0.3161	0.0537	0.3462	0.0513	0.1298	0.1198	0.0278

Simulation of the spatial pattern of human travel activity intensity based on geodetector and maximum entropy model: A case study of Yunnan Province

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