?ngstr?m-Prescott equation is the recommended algorithm for calculating the radiation coefficients for the Penman-Monteith formula, which is the standard method for reference crop evapotranspiration recommended by the Food and Agriculture Organization (FAO) of the United Nations. The calibration and optimization of a_s and b_s coefficients in the equation is the key to accurately calculate the surface solar radiation. This study aims at obtaining the ?ngstr?m-Prescott equation coefficients a_s and b_s, which are optimized for China's comprehensive agricultural areas. The monthly average solar radiation (R_s) (from Dataset of Monthly Values of Radiation Data from Chinese Surface Stations) and srelative sunshine duration data (from Dataset of Monthly Values of Climate Data from Chinese Surface Stations) at 121 stations during 1957-2016 were collected. Using the data from 1957 to 2010, we calculated the monthly a_s and b_s coefficients for each area through the least squares regression. Then, taking the observation values of R_s from 2011 to 2016 as the true values, we estimated and compared the relative accuracy of R_s calculated by regression values of coefficients a_s and b_s and that calculated by FAO suggested coefficients a_s and b_s. The results showed that the monthly average coefficients a_s and b_s of each area are significantly different from the FAO recommended coefficients both temporally and spatially. There are some differences between regions and within regions, and the relative value of a_s and b_s shows the opposite state. The relative error range (0-54%) of solar radiation calculated by the regression a_s and b_s coefficients is small, while the relative error range (0-77%) of solar radiation calculated by the FAO recommended value is large. So, overall, the relative accuracy of R_s calculated by regression values of a_s and b_s coefficients is better than that calculated by the FAO suggested coefficients. The relative error was reduced by 1% to 6%, and the relative error decreases more in winter and spring than in summer and autumn. However, regression values of a_s and b_s coefficients perform worse in some months and some agricultural areas for verification in application. It is said that the regression values of a_s and b_s are not entirely reliable. For each month and each agricultural area, the best scheme is to combine the regression values of a_s and b_s coefficients with the FAO recommended values. Therefore, we chose the a_s and b_s coefficients with the minimum R_s estimation error as the final coefficients and made a coefficient recommendation table for 38 agricultural production and management areas in the Chinese mainland. This study further illustrates the necessity of localization modification of ?ngstr?m-Prescott equation coefficients in application, and enriches the case study of coefficient calibration of ?ngstr?m-Prescott equation in China, which is helpful for improving the accuracy of calculation of surface solar radiation and reference crop evapotranspiration based on existing data.

Poverty eradication is a worldwide concern. Regional impoverishment has been considered to be closely related to the geographical environment. Therefore, the relationship between poverty and geographical environment has become the core content of poverty geography. Based on the theoretical basis of regional multidimensional poverty and impoverished areal system, this study constructed a "poverty-environment-economy-society" analytical framework to examine the nexus between poverty and geo-environment. On this basis, taking 124000 poverty-stricken villages as the research object, this study used the methods of spatial autocorrelation, kernel density analysis and geographical detector to depict the spatial geographical pattern of China's poverty-stricken villages in the new era, quantitatively detect the leading factors of the regional differentiation of poverty-stricken villages, and reveal the interaction mechanism between the village impoverishment and the geographical environment. The main conclusions can be drawn in the following three aspects. First of all, poverty and the geo-environment interact with each other, and the paths and manifestations of the interaction between the two are complex and diverse. In general, factors leading to village poverty can be detected from the two categories of nature and humanities and the three dimensions of environment, economy, and society. Environmental factors play a fundamental role in the evolution of poverty, economic factors are the most direct and important contributor to impoverishment, and social factors have a magnifying effect on poverty. Secondly, the distribution of poor villages in China has obvious spatial agglomeration characteristics. The spatial distribution pattern of poverty-stricken villages across the country is consistent with the basic geographic pattern depicted by the Hu Huanyong Line and the three-level topography, with obvious vertical and slope differentiation characteristics. The poor villages in China are spatially distributed with one first-level core area, five second-level core areas and seven third-level core areas. Last but not least, the spatial distribution pattern of poor villages in China is the result of the interaction of multiple factors. Topography, natural resources endowment, labors, transportation and public services were identified as the main contributors to spatial differentiation of poor villages in China. Interaction detection results indicated that the driving force between two-factor interaction is stronger than that of a single factor, and the interaction types are non-linear enhancement except for topographic factors and location. Facing the 2030 UN Sustainable Development Goals, China needs to establish the long-term mechanism to effectively link up poverty reduction, rural revitalization, ecological civilization construction, territorial space optimization and urban-rural integrated development, so as to stimulate the endogenous development momentum of poverty-stricken areas and promote regional sustainable development.

As important carriers of Chinese civilization, traditional villages are endowed with rich and diversified values. Although the government and academia have implemented lots of programmes on protections and researches, the sustainable development still has a long way to go. Therefore, it is of profound significance to establish an evaluation system for the sustainable development of Chinese traditional villages and to evaluate the sustainable development level of Chinese traditional villages. Through long-term field survey of traditional villages, this study proposes that understanding the two basic attributes of community and heritage is the key to cognizing the sustainable development of traditional villages. Then it uses the analytic hierarchy process and Delphi method to construct the index system of community development subsystem and heritage protection subsystem, and applies an expert judgment matrix and the Delphi method to determine the index weights of the subsystems at all levels, and constructs the systems of data collection, assignment, and standardization for each secondary index. The comprehensive evaluation index is used to evaluate the development level of traditional villages, and determine the criteria for ranking. In order to better evaluate the sustainable development level of traditional Chinese villages, a coupling coordination model is further introduced to construct an evaluation system. Finally, through the evaluation of 10 traditional Lingnan villages in Guangzhou, Foshan and Zhongshan cities of Guangdong province, the validity of the index system is verified and further revised. This index system can not only promote the research paradigm of traditional villages, coupling degree and sustainable development assessment, but also widely guide and apply to the protection practices of traditional villages in China.

The scientific understanding of the transformation process and rules of agricultural settlement since the reform and opening-up after 1978 is very important to revitalizing and improving the agricultural economy and living condition. In this paper, we take a small village, Licheng, Ningjin County of Hebei Province as an example to explore the transformation process and development mechanism of agricultural settlement from settlement space, economic situation and social life since the reform and opening-up. In this case, some conclusions can be drawn as follows. (1) The total space of construction area increased significantly, with the gradual enlargement of residential space and the expansion of industrial land along the edge of the old village. Three stages have been identified, namely, slow development, rapid expansion, and high speed reconstruction. (2) With the continuous improvement of agricultural mechanization and farm products commercialization, the proportion of non-agricultural income increased gradually, indicating more and more commercial production and consumption in farmers' daily life. The transformation of village economic situation also has gone through three stages: agricultural livelihood stage, part-time agricultural and part-time non-agricultural livelihood stage, non-agricultural and part-time agricultural livelihood stage. (3) Due to the enlargement and reconstruction of social relation between villagers, the transformation of villagers' social life went through three stages: traditional rural life stage, separation of occupation and residence stage, and partly empty-nest elderly and partly empty-nest stage. (4) Natural endowment, behavior representatives (village committees, peasant households, and enterprises), urban-rural interaction, and policy environment respectively play roles of basic binding force, internal pushing force, external pulling force, and space-economy-society regulating force in the transformation of agricultural villages, which interact and jointly promote the transformation and development of agricultural settlements. A new concept of town and village co-community was proposed. It will provide a theoretical reference for implementing the strategy of rural revitalization and solving the dilemma of agricultural settlement transformation in China.