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| 1 | Topographical relief characteristics and its impact on population and economy:A case study of the mountainous area in western Henan,China显示文摘Topographical relief is a key factor that limits population distribution and economic development in mountainous areas.The limitation is especially apparent in the mountain?plain t「ansition zone.Taking the transition zone between the Qinling Mountains and the North China Plain(i.e.the mountainous area in western Henan Province)as an example and based on the 200-m resolution DEM data,we used the mean change-point analysis to determine the optimal statistical unit for topographical relief,and thereafter extracted the relief degree.Taking the 1:100,000 land use data,township population and county-level industrial data,population and economic spatial models were constructed,and 200?m resolution grid population and economic density maps were gen erated.Afterwards,statistical analysis was carried out to quantitatively reveal the impact of topographical relief on population and economy.In addition,the impacts of other topographical factors were discussed.The results showed the following.(1)The relief degree in western Henan is generally low,where 58.6%of the regional topography does not exceed half the height of a reference mountain(relative elevation W250 m).Spatially,the relief degree is high in the west while low in the east,and high in the middle while low in the north and south.There is a positive correlation between relief degree and elevation,and a much stronger correlation between relief degree and slope.(2)The linear fitting degree between the population and economic validation data and the corresponding simulation data are 0.943 and 0.909,respectively,indicating that the spatialized results can reflect the actual population and economic distribution.(3)The impact of topographical relief on population and economy was stronger than that of other topographical factors.The relief degree showed a good logarithmic fit relati on ship with population density(0.911)and economic density(0.874).Specifically,88.65%of the population lives in areas where the topographical relief is W0.5 and 88.03%of the gross regional product was from areas where the relief is W0.3.Compared with the population distribution,the economic development showed an obvious agglomeration trend towards low relief areas. | ZHANG Jingjing ZHU Wenbo ZHU Lianqi CUI Yaoping HE Shasha REN Han | 2019 | Journal of Geographical Sciences2019，29，4： | 8 |
| 2 | Study on the Formalized Development of the Street Stall Economy-based on Domestic and International Experiences and Perspectives显示文摘The ground-floor economy has a long history as a significant part of the informal economy.Due to the dependence on its own social status and relationship to the government’s political and economic objectives,it has developed precariously in recent years.In the face of post-epidemic problems,a shortcut is to learn from international experience.This paper used the structural theory and drew from the secondary data,demonstrating the background of informal economy and exploring the rational ways to maintain and develop street vending.Spatialization,legalization and network digitization are proven international approaches,which display the empirical and theoretical implications to urban practice and studies. | Yixuan Chen Lingfeng Liu Hao Liu Yukun Sun | 2021 | Journal of Economic Science Research2021，4，4： | 0 |
| 3 | Spatial Distribution of High-temperature Risk with a Return Period of Different Years in the Yangtze River Delta Urban Agglomeration显示文摘Against the background of global warming,research on the spatial distribution of high-temperature risk is of great significance to effectively prevent the adverse effects of high temperatures.By using air temperature data from 1951 to 2018 measured by meteorological stations located in the Yangtze River Delta urban agglomeration,the daily maximum air temperature distribution is interpolated at a resolution of 1 km based on the local thin disk smooth spline function;the high-temperature threshold for return periods of 5,10,20 and 30 yr are then calculated by using the generalized extreme value method.The yearly average high-temperature intensity and high-temperature days are finally calculated as high-temperature danger factors.Socioeconomic statistical data and remotely sensed image data in 2018 are used as the background data to calculate the spatial distribution of high-temperature vulnerability factors and prevention capacity factors,which are then used to compute the high-temperature risk index during different recurrence periods in the Yangtze River Delta urban agglomerations.The results show that the spatial distribution features of high-temperature risk in different return periods are similar.The high-temperature risk index gradually increases from northeast to southwest and from east coast to inland,which has obvious latitude variation characteristics and a relationship with the comprehensive influence of the underlying surface and urban scale.In terms of time variation,the high-temperature risk index and its spatial distribution difference gradually decreases with increasing return period.In different cities,the high-temperature risk in the central area of the city is generally higher than that in the surrounding suburban areas.Jinhua,Hangzhou of Zhejiang Province and Xuancheng of Anhui Province are the top three cities with high-temperature risk in the study area. | ZHANG Guixin WANG Shisheng ZHU Shanyou XU Yongming | 2022 | Chinese Geographical Science2022，32，6： | 0 |
| 4 | From statistics to grids:A two-level model to simulate crop pattern dynamics显示文摘Crop planting patterns are an important component of agricultural land systems.These patterns have been significantly changed due to the combined impacts of climatic changes and socioeconomic developments.However,the extent of these changes and their possible impacts on the environment,terrestrial landscapes and rural livelihoods are largely unknown due to the lack of spatially explicit datasets including crop planting patterns.To fill this gap,this study proposes a new method for spatializing statistical data to generate multitemporal crop planting pattern datasets.This method features a two-level model that combines a land-use simulation and a crop pattern simulation.The output of the first level is the spatial distribution of the cropland,which is then used as the input for the second level,which allocates crop censuses to individual gridded cells according to certain rules.The method was tested using data from 2000 to 2019 from Heilongjiang Province,China,and was validated using remote sensing images.The results show that this method has high accuracy for crop area spatialization.Spatial crop pattern datasets over a given time period can be important supplementary information for remote sensing and thus support a wide range of application in agricultural land systems. | XIA Tian WU Wen-bin ZHOU Qing-bo Peter HVERBURG YANG Peng HU Qiong YE Li-ming ZHU Xiao-juan | 2022 | Journal of Integrative Agriculture2022，21，6： | 0 |
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