Spatial stratified heterogeneity is the spatial expression of natural and socio-economic process, which is an important approach for human to recognize nature since Aristotle. Geodetector is a new statistical method to detect spatial stratified heterogeneity and reveal the driving factors behind it. This method with no linear hypothesis has elegant form and definite physical meaning. Here is the basic idea behind Geodetector: assuming that the study area is divided into several subareas. The study area is characterized by spatial stratified heterogeneity if the sum of the variance of subareas is less than the regional total variance; and if the spatial distribution of the two variables tends to be consistent, there is statistical correlation between them. Q-statistic in Geodetector has already been applied in many fields of natural and social sciences which can be used to measure spatial stratified heterogeneity, detect explanatory factors and analyze the interactive relationship between variables. In this paper, the authors will illustrate the principle of Geodetector and summarize the characteristics and applications in order to facilitate the using of Geodetector and help readers to recognize, mine and utilize spatial stratified heterogeneity.

The northern border of the tropical zone of China has been the focus of studies on comprehensive physical regionalization. Based on different indexes and methods, the border was delineated by different scholars, but their results varied greatly. Based on the Geodetector model and regionalization thought of spatial stratified heterogeneity, the northern border of the tropical zone of China's mainland was investigated. Climatic elements were used as dominant demarcation partitioning indexes, combined with auxiliary indexes such as soil and multiple cropping types. The key results were as follows: (1) Using Geodetector, the northern border of the tropical zone was delineated. From west to east, the border goes through Lincang, Simao, Yuxi and Gejiu in Yunnan, Baise, Mashan, Guigang and Wuzhou in Guangxi, Zhaoqing, Guangzhou, Huizhou, Heyuan and Meizhou in Guangdong, and Zhangzhou, Quanzhou and Putian in Fujian. It generally agrees with the 12℃ isotherm of the coldest monthly mean temperature, soil border between lateritic red soil and red soil, and border of double cropping rice or its continuous thermophile dry framing and single (double) cropping rice or its continuous chimonophilous dry framing. (2) The q average value of all indexes for the border was 0.40. Using this model, regionalization principles—homogeneity of the within-strata value and heterogeneity of the between-strata value—were satisfied. The border meets the requirements of zonal heterogeneity between tropical and subtropical zones. Therefore, it is reasonable to use Geodetector in studies of comprehensive physical regionalization, and it can provide high-precision technical support.

Hu Line uncovers one of China's most important characteristics of population paper distribution: East is dense, while west is sparse. Different from most previous research, this paper examined the differentiation and changes of population distribution on both sides of Hu Line from a perspective of spatial stratified heterogeneity instead. Geodetector was employed based on the spatial database of China's census data of 1953, 1982, 1990, 2000 and 2010 to reconfirm spatial position of Hu Line and analyzed changes of spatial stratified heterogeneity of population between southeast and northwest sides of Hu Line in different periods. Changes of population distribution since the founding of New China were found and the reasons for these changes were discussed. Major findings include: (1) From the spatial stratified heterogeneity perspective, Hu Line could be improved and optimized, at least, in some periods. Although the ratio of total population on both sides of Hu Line has roughly been kept at 94:6 since 1953, spatial stratified heterogeneity of population between the two sides (the southeastern side: the northwestern side) increased when Hu Line moves to south slightly in 1953, 2000 and 2010, which means population distribution was more homogeneous within either southeastern or northwestern region and heterogeneity was more remarkable between the two regions. (2) Heterogeneity decreased gradually since the reform and opening up. We found characteristics of population distribution converged on the two sides, especially since the 1990s when convergence between the two sides became apparent. This finding is significantly different from the conclusion of "remain unchanged" from most literatures. The reasons why heterogeneity reduced were: pattern of population distribution on the southeastern side changed from relatively even distribution among cities before 1990 to agglomeration in a few huge cities after 2000, while the degree of spatial agglomeration of population decreased slightly after the reform on the northwestern side. These changes have been confirmed by the analysis from cumulative distribution function and Gini coefficient. (3) On the whole, the effect of economic factors on population distribution has become more and more important, while the effect of natural environment and institution reduced. Combined effect from economic development, natural environment and institution resulted in two opposite directions of changes of population spatial distribution on the two sides. It should be emphasized that although general effect of natural environment has decreased, some natural factors, such as Three Gradient Terrains, still have significantly influence on population distribution in China.

Rural poverty has long aroused attention from countries around the world, and eliminating poverty and achieving realize common prosperity is an important mission to build the well-off society in an all-round way. Scientifically revealing the regional differentiation mechanism of rural poverty has become an important issue of implementation of national poverty alleviation strategy. This paper, taking Fuping County of Hebei Province as a typical case, diagnoses the dominant factors of differentiation of rural poverty and reveals the dynamic mechanism of rural poverty differentiation by using the Geodetector model and multiple linear regressions, and puts forward the poverty alleviation policies and models for different poverty regions. The result shows that the dominant factors affecting rural poverty differentiation include slope, elevation, per capita arable land resources, distance to the main roads and distance to the center of county, and their power determinant value to poverty incidence differentiation are 0.14, 0.15, 0.15, and 0.17. These factors affect the occurrence of poverty from different aspects and their dynamic mechanism is also different. Among various factors, the slope and per capita arable land resources affect the structure and mode of agricultural production, while distance to the main roads and distance to the center of county have influence on the relationship between the interior and exterior of the region. There are significant differences in the four types identified of regional rural poverty, namely, environment constrained region mainly affected by slope (seven towns), resource oriented region mainly affected by per capita arable land (seven towns), area dominated by traffic location affected by distance to the main roads (three towns), and economic development leading area mainly affected by distance to the center of county (four towns). Then, Fuping County is divided into single core, dual core and multi-core area according to the number of core elements of the township. The county has shown a multi differentiation of rural poverty with a horizontal center of dual core area, and both sides have a single core and multi-core, which are affected by different dominant factors. Finally, this paper suggests that policy of targeted poverty alleviation should take science and technology as the foundation and form innovation of targeted poverty alleviation according to the core dominant factors of the differentiation mechanism of rural poverty. The county's poverty alleviation and development under different driving mechanisms need orderly promotion of poverty alleviation and integration of urban and rural development strategy with adjusting measures to local conditions, respecting for science, and stressing practical results.