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Exploring spatial non-stationarity of near-miss ship collisions from AIS data under the influence of sea fog using geographically weighted regression:A case study in the Bohai Sea,China

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Acta Oceanologica Sinica 2023年第12期42卷 77-89页

作者： Yongtian Shen Zhe Zeng Dan Liu Pei Du China University of Petroleum Qingdao 266580China Anhui Provincial Geomatic Center Hefei 230031China Nanjing Normal University School of Geography Nanjing 210023China

Sea fog is a disastrous weather phenomenon,posing a risk to the safety of maritime transportation.Dense sea fogs reduce visibility at sea and have frequently caused ship collisions.This study used a geographically weighted regression(GWR)model to explore the spatial non-stationarity of near-miss collision risk,as detected by a vessel conflict ranking operator(VCRO)model from automatic identification system(AIS)data under the influence of sea fog in the Bohai Sea.Sea fog was identified by a machine learning method that was derived from Himawari-8 satellite data.The spatial distributions of near-miss collision risk,sea fog,and the parameters of GWR were mapped.The results showed that sea fog and near-miss collision risk have specific spatial distribution patterns in the Bohai Sea,in which near-miss collision risk in the fog season is significantly higher than that outside the fog season,especially in the northeast(the sea area near Yingkou Port and Bayuquan Port)and the southeast(the sea area near Yantai Port).GWR outputs further indicated a significant correlation between near-miss collision risk and sea fog in fog season,with higher R-squared(0.890 in fog season,2018),than outside the fog season(0.723 in non-fog season,2018).GWR results revealed spatial non-stationarity in the relationships between-near miss collision risk and sea fog and that the significance of these relationships varied locally.Dividing the specific navigation area made it possible to verify that sea fog has a positive impact on near-miss collision risk.

关键词： near-miss sea fog geographically weighted regression automatic identification system(AIS)

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Determination of the effective utilization coefficient of irrigation water based on geographically weighted regression

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Frontiers of Earth Science 2022年第2期16卷 401-410页

作者： Rui SHI Gaoxu WANG Xuan ZHANG Yi XU Yongxiang WU Wei WU College of Hydrology and Water Resource Hohai UniversityNanjing 210098China State Key Laboratory of Hydrology-Water Resources and Hydraulic Engineering Nanjing 210029China Hydrology and Water Resources Department Nanjing Hydraulic Research InstituteNanjing 210029China

This study uses geographically weighted regression to determine the spatial distribution of the effective utilization coefficient of irrigation water in Zhejiang Province,China,owing to the influences of spatial attributes on the irrigation efficiency.The sample set of this study comprised 165 agricultural test sites.A multivariate linear regression model and a geographically weighted regression model were established using the effective utilization coefficient of agricultural irrigation water as the dependent variable in addition to a suite of independent variables,including the actual irrigation area,the percentage of farmland using water-saving irrigation,the type of irrigation area,the net water consumption per mu,the water intake method,the terrain slope,and the soil field capacity.Results revealed a positive spatial correlation and noticeable agglomeration features in the effective utilization coefficient of irrigation water in Zhejiang Province.The geographically weighted regression model performed better in terms of fit and prediction accuracy than the multivariate linear regression model.The obtained findings confirm the suitability of the geographically weighted regression model for determining the spatial distribution of the effective utilization coefficient of irrigation water in Zhejiang,and offer a new approach on a regional scale.

关键词： effective utilization coefficient of irrigation water spatial autocorrelation multivariate linear regression geographically weighted regression

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Uphill or downhill?Cropland use change and its drivers from the perspective of slope spectrum

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Journal of Mountain Science 2024年第2期21卷 484-499页

作者： PAN Sipei LIANG Jiale CHEN Wanxu PENG Yelin College of Land Management Nanjing Agricultural UniversityNanjing 210095China National&Local Joint Engineering Research Center for Rural Land Resources Use and Consolidation Nanjing 210095China Jiangsu Provincial Key Laboratory of Geographic Information Technology School of Geography and Ocean ScienceNanjing UniversityNanjing 210023China Key Laboratory of Natural Resources Monitoring and Supervision in Southern Hilly Region Ministry of Natural ResourcesChangsha 410118China Yunnan Key Laboratory of Plateau Geographic Processes and Environmental Changes Faculty of GeographyYunnan Normal UniversityKunming 650500China Hubei Key Laboratory of Regional Ecology and Environmental Change School of Geography and Information EngineeringChina University of GeosciencesWuhan 430074China

The continuous decrease of low-slope cropland resources caused by construction land crowding poses huge threat to regional sustainable development and food security.Slope spectrum analysis of topographic and geomorphic features is considered as a digital terrain analysis method which reflects the macro-topographic features by using micro-topographic factors.However,pieces of studies have extended the concept of slope spectrum in the field of geoscience to construction land to explore its expansion law,while research on the slope trend of cropland from that perspective remains rare.To address the gap,in virtue of spatial analysis and geographically weighted regression(GWR)model,the cropland use change in the Yangtze River Basin(YRB)from 2000 to 2020 was analyzed and the driving factors were explored from the perspective of slope spectrum.Results showed that the slope spectrum curves of cropland area-frequency in the YRB showed a first upward then a downward trend.The change curve of the slope spectrum of cropland in each province(municipality)exhibited various distribution patterns.Quantitative analysis of morphological parameters of cropland slope spectrum revealed that the further down the YRB,the stronger the flattening characteristics,the more obvious the concentration.The province experienced the greatest downhill cropland climbing(CLC)was Shannxi,while province experienced the highest uphill CLC was Zhejiang.The most common cropland use change type in the YRB was horizontal expansion type.The factors affecting average cropland climbing index(ACCI)were quite stable in different periods,while population density(POP)changed from negative to positive during the study period.This research is of practical significance for the rational utilization of cropland at the watershed scale.

关键词： Cropland climbing Land use change Slope spectrum Driving factors geographically weighted regression Yangtze River Basin

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基于地理加权回归模型探索小学生通勤方式选择的区域异质性

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Journal of Geographical Sciences 2024年第4期34卷 804-833页

作者：吴大伟马路闫学东 School of Traffic and Transportation Beijing Jiaotong UniversityBeijing 100044China Ministry of Transport Key Laboratory of Transport Industry of Big Data Application Technologies for Comprehensive Transport Beijing 100044China

Commuting is an important part of primary school students' travel behavior, which has been concerned for a long time. We found that the commute-mode choice behavior of primary school students in the context of regional segmentation shows strong characteristics in space, but has not yet been considered in traditional research. To fill this gap, this study summarizes the commute-mode choices of primary school students with different characteristics based on the Beijing School Commute Survey. And the geographically weighted regression(GWR) model is built to analyze the zonal heterogeneity of the impact of personal characteristics, family factors and school factors on the primary school students' commutemode choices from a low-carbon perspective. The results demonstrate that the possibility of primary school students choosing low-carbon commuting modes is positively correlated with the grade, commuting time, commuting escort type and housing category, but is inversely related with the commuting distance and the distance from the school to the city center. The coefficient estimates of explanatory variables vary across regions. Finally, we put forward policy suggestions regarding promoting the low-carbon commuting structure, such as developing the urban slow traffic system, which serve as a reference for policymakers.

关键词： primary school students school commute mode choice zonal heterogeneity geographically weighted regression

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Spatiotemporal Differentiation of Urban Spatial Form and Carbon Emissions in Poyang Lake City Group

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Journal of Landscape Research 2024年第2期16卷 87-92页

作者： LUO Xiaolin LI Zhi CHU Xi College of City Construction Jiangxi Normal UniversityNanchangJiangxi 330022China

In response to the inherent requirements of low-carbon land spatial planning in Jiangxi Province and the lack of existing research,this paper explored the mechanism of spatial form elements of Poyang Lake urban agglomeration on urban carbon emissions.Based on generalized linear regression and geographically weighted regression models,this paper analyzed the spatiotemporal distribution characteristics of carbon emissions,the spatiotemporal relationship between urban form index and carbon emissions,and the spatial differentiation of the intensity of dominant factors from 63 county-level administrative units in the Poyang Lake city group from 2005 to 2020.The results showed that:①The carbon emissions of urban agglomerations around Poyang Lake are generally increasing,and the spatial distribution of carbon emissions is characterized by high-value concentration in the middle and low-value agglomeration in pieces;②The main driving factor for the spatial heterogeneity of carbon emissions was the expansion of built-up area;③Improving urban compactness and optimizing urban form could effectively reduce urban carbon emissions.The results showcased the correlation between urban spatial landscape pattern and the spatiotemporal distribution of carbon emissions,which could make the low-carbon land spatial planning in the Poyang Lake city group more reasonable and practical.

关键词： Carbon emissions Urban spatial form the Poyang Lake city group Landscape pattern index geographically weighted regression

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Comparison of geographically weighted regression of Benthic Substrate Modeling Accuracy on Large and Small Wadeable Streams

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Journal of Geographic Information System 2021年第2期13卷 194-209页

作者： Ken R. Sheehan Stuart A. Welsh KnoWhere LLC 969 Ocean Blvd #3 Hampton NH USA U.S. Geological Survey West Virginia Cooperative Fish and Wildlife Research Unit West Virginia University Morgantown West Virginia USA

Aquatic habitat assessments encompass large and small wadeable streams which vary from many meters wide to ephemeral. Differences in stream sizes within or across watersheds, however, may lead to incompatibility of data at varying spatial scales. Specifically, issues caused by moving between scales on large and small streams are not typically addressed by many forms of statistical analysis, making the comparison of large (>30 m wetted width) and small stream (geographically weighted regression (GWR) may provide avenues for efficiency and needed insight into stream habitat data by addressing issues caused by moving between scales. This study examined the ability of GWR to consistently model stream substrate on both large and small wadeable streams at an equivalent resolution. We performed GWR on two groups of 60 randomly selected substrate patches from large and small streams and used depth measurements to model substrate. Our large and small stream substrate models responded equally well to GWR. Results showed no statistically significant difference between GWR R2 values of large and small stream streams. Results also provided a much needed method for comparison of large and small wadeable streams. Our results have merit for aquatic resource managers, because they demonstrate ability to spatially model and compare substrate on large and small streams. Using depth to guide substrate modeling by geographically weighted regression has a variety of applications which may help manage, monitor stream health, and interpret substrate change over time.

关键词： Stream Habitat Modeling geographically weighted regression Spatial Scale Habitat Interpolation Geographic Information System

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Spatiotemporal dynamics of population density in China using nighttime light and geographic weighted regression method

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International Journal of Digital Earth 2023年第1期16卷 2704-2723页

作者： Wei Guo Jinke Liu Xuesheng Zhao Wei Hou Yunxuan Zhao Yongxing Li Wenbin Sun Deqin Fan College of Geoscience and Surveying Engineering China University of Mining and TechnologyBeijingPeople’s Republic of China Chinese Academy of Surveying&Mapping BeijingPeople’s Republic of China

The distribution and dynamic changes of regional or national population data with long time series are very important for regional planning,resource allocation,government decision-making,disaster assessment,ecological protection,and other sustainability research.However,the existing population datasets such as LandScan and WorldPop all provide data from 2000 with limited time series,while GHS-POP only utilizes land use data with limited accuracy.In view of the limited remote sensing images of long time series,it is necessary to combine existing multi-source remote sensing data for population spatialization research.In this research,we developed a nighttime light desaturation index(NTLDI).Through the cross-sensor calibration model based on an autoencoder convolutional neural network,the NTLDl was calibrated with the same period Visible Infrared Imaging Radiometer Suite Day/Night Band(VIRS-DNB)data.Then,the geographically weighted regression method is used to determine the population density of China from 1990 to 2020 based on the long time series NTL.Furthermore,the change characteristics and the driving factors of China's population spatial distribution are analyzed.The large-scale,long-term population spatialization results obtained in this study are of great significance in government planning and decision-making,disaster assessment,resource allocation,and other aspects.

关键词： Nighttime light Population density geographically weighted regression Population spatialization Driving force analysis

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Spatio-temporal characteristics of population and economy in transitional geographic space at the southern end of"Hu Huan-yong Line"

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Journal of Mountain Science 2022年第2期19卷 350-364页

作者： DENG Wei CHENG Yu-fang YU Huan PENG Li KONG Bo HOU Yu-ting School of Geography and Resource Science Sichuan Normal UniversityChengdu 610066China School of Earth Sciences Chengdu University of TechnologyChengdu 610059China Institute of Mountain Hazards and Environment Chinese Academy of SciencesChengdu 610041China Institute of Aerospace Information Innovation Chinese Academy of SciencesBeijing 100094China

"Hu Huan-yong Line(Hu Line)"depicts a geographical pattern of China’s population distribution.Its essence is the regionality of humanland relationship and reflects basic characteristics and laws of human beings’adaptation to the natural environment.With the development of the times and the progress of modern science and technology,especially the rapid urbanization and construction of transportation network system in China,the connection between economic and geographical space has been continuously strengthened.The geographical transition zones from mountain areas to plains,i.e.,transitional geographical space,have promoted the changes in human-land relationships through population migration and agglomeration.Taking Sichuan-Yunnan provinces at the southern end of Hu Line as study area,this study analyzed the spatial correlation between population distribution and economy in this region,explored the pattern of geographical agglomeration and deagglomeration,and explained the changing characteristics of humanland relationship in transitional geographic space using global Moran’s I index,global regression model(GRM)and geographically weighted regression(GWR).The results show that population and Gross Domestic Product(GDP)have significant spatial dependence to this region,with obvious aggregation in geographical distribution and positive autocorrelation;comparing with the general least square model,the GWR model incorporating spatial effect was more suitable for revealing the distribution characteristics of geographical elements,with fine results and better fitting;the spatial model of population and GDP as well as the spatio-temporal evolution model of their changes,all of them strongly indicated that Normalized Difference Vegetation Index(NDVI)and road density were important factors governing the spatial differentiation of population and economy;under the rapid development of regional economy and continuous evolution of urban-rural relations,rural transformation and spatial reconstruction promoted the change of popul

关键词： Hu Huan-yong Line Spatial correlation geographically weighted regression Population distribution Transitional geographic space

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Spatial heterogeneity of the economic growth pattern and influencing factors in formerly destitute areas of China

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Journal of Geographical Sciences 2022年第5期32卷 829-852页

作者： YIN Jiangbin LI Shangqian ZHOU Liang JIANG Lei MA Wei Northwest Land and Resource Research Center Global Regional and Urban Research InstituteShaanxi Normal UniversityXi’an710119China School of Geography and Planning Sun Yat-sen UniversityGuangzhou510275China Faculty of Geomatics Lanzhou Jiaotong UniversityLanzhou730070China School of Economics Zhejiang University of Finance and EconomicsHangzhou310018China Business School Yangzhou UniversityYangzhouJiangsu225127China

Accelerating economic growth in formerly destitute areas and narrowing the economic gap with other regions are essential tasks for poverty alleviation in China after 2020.In this study,the spatio-temporal characteristics of economic growth in 14 formerly destitute areas of China were identified.Moreover,the spatial heterogeneity of various influencing factors was analyzed using a geographically weighted regression model.The results were as follows:(1)The economic level of the formerly destitute areas was low,but their economies grew rapidly after 2011,with annual per capita GDP growth of 10.54%until 2018,higher than the national average of 9.14%.Western and southern counties grew faster economically than central and northern counties.(2)The impact of various factors on the economic growth of counties exhibited clear spatial heterogeneity.The influences of secondary industry growth and level of financial development on economic growth were mainly positive,whereas the effects of initial economic level and market location were mainly negative.(3)Six economic growth driving modes were identified for the 14 contiguous destitute areas,among which the secondary industry-driven mode was the most common.The study can serve as a scientific reference for differentiating regional policies.

关键词： formerly destitute areas economic growth spatial variation geographically weighted regression China

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Untangling the increasing elevation of cropland in China from 1980 to 2020

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Geography and Sustainability 2023年第4期4卷 281-293页

作者： Wanxu Chen Liyan Yang Jie Zeng Jintao Yuan Tianci Gu Zhiling Liu Department of Geography School of Geography and Information EngineeringChina University of GeosciencesWuhan 430078China School of Public Administration China University of GeosciencesWuhan 430074China

The redistribution of cropland to areas of higher elevation in China has long affected agricultural development and could seriously threaten national food security.However,there is currently little research reported on this phenomenon,which may limit the improvement of cropland protection policies.To fill this gap,we analyzed the spatiotemporal characteristics and driving mechanisms of increased cropland elevation in China during the period 1980-2020.The average cropland elevation in China increased by 17.38 m from 1980 to 2020.The gravity center of the cropland area and average cropland elevation in China moved to the northwest by 81.00 km and 51.47 km,respectively.The amount of newly added cropland in eastern China was less than that in occupied regions;however,the average elevation of newly added cropland was greater than that of occupied cropland,though the opposite phenomenon was observed in western China.Slope,temperature,land-use intensity,population,economic density,and distance to main roads were the main factors affecting the redistribution of cropland to areas of higher elevation.The effects of these major driving factors exhibited significant spatial and temporal variations in China.This study has important implications for improving existing cropland protection policies and developing more effective cropland management systems in China.

关键词： Cropland Elevation Geodetector geographically weighted regression Spatial analysis China

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