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Historic distribution and driving factors of human-caused fires in the Chinese boreal forest between 1972 and 2005

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Journal of Plant Ecology 2015年第5期8卷 480-490页

作者： Futao Guo John L.Innes Guangyu Wang Xiangqing Ma Long Sun Haiqing Hu Zhangwen Su Faculty of Forestry Fujian Agriculture and Forestry UniversityNo.15 Shangxiadian RoadFuzhou 350002China Sustainable Forest Management Laboratory Faculty of ForestryUniversity of British Columbia2424 Main MallVancouverBritish Columbia V6T 1Z4Canada Faculty of Forestry Northeast Forestry UniversityNo.26 Hexing RoadHarbinHeilongjiang Province 150040China

Aims The pattern and driving factors of forest fires are of interest for fire occurrence prediction and forest fire *** aims of the study were:(i)to describe the history of human-caused fires by season and size of burned area over time;(ii)to identify the spatial patterns of human-caused fires and test for the existence of‘hotspots’to determine their exact locations in the Daxing’an mountains;(iii)to determine the driving factors that determine the spatial distribution and the possibility of human-caused fire *** In this study,k-function and kernel density estimation were used to analyze the spatial pattern of human-caused *** analysis was conducted in s-plus and arcgIs environments,*** analysis of driving factors was performed in SPSS 19.0 based on a logistic regression *** variables used to identify factors that influence fire occurrence included vegetation types,meteorological conditions,socioeconomic factors,topography and infrastructure factors,which were extracted and collected through the spatial analysis mode of arcgIs and from official statistics,*** Findings The annual number of human-caused fires and the area burnt have declined since 1987 due to the implementation of a forest fire protection *** were significant spatial heterogeneity and seasonal variations in the distribution of human-caused fires in the Daxing’an *** heterogeneity was caused by elevation,distance to the nearest railway,forest type and temperature.a logistic regression model was developed to predict the likelihood of human-caused fire occurrence in the Daxing’an mountains;its global accuracy attained 64.8%.The model was thus comparable to other relevant studies.

关键词： anthropogenic fire spatial distribution k-function kernel intensity estimation boreal forest logistic regression

Spatio-temporal point pattern analysis on Wenchuan strong earthquake

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Earthquake Science 2009年第3期22卷 231-237页

作者： Peijian Shi Jie Liu Zhen Yang Agricultural College JiangxiAgricultural University Nanehang 330045 China China Earthquake Networks Center Beij'ing 100036 China Department of Precision Instrument andMechanology Tsingkua University Beijing 100084 China

For exploring the aftershock occurrence process of the 2008 Wenchuan strong earthquake, the spatio-temporal point pattern analysis method is employed to study the sequences of aflershocks with magnitude M≥4.0, M≥4.5, and M≥5.0. It is found that these data exhibit the spatio-temporal clustering on a certain distance scale and on a certain time scale. In particular, the space-time interaction obviously strengthens when the distance is less than 60 km and the time is less than 260 h for the first two aftershock sequences; however, it becomes strong when the distance scale is less than 80 km and the time scale is less than 150 h for the last aftershock sequence. The completely spatial randomness analysis on the data regardless of time component shows that the spatial clustering of the aftershocks gradually strengthens on the condition that the distance is less than 60 km. The results are valuable for exploring the occurrence rules of the Wenchuan strong earthquake and for predicting the aftershocks.

关键词： Wenchuan earthquake completely spatial randomness spatio-temporal point pattern k-function

GIS-based spatial analysis of urban traffic accidents： Case study in Mashhad, Iran

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Journal of Traffic and Transportation Engineering(English Edition) 2017年第3期4卷 290-299页

作者： Gholam Ali Shafabakhsh Afshin Famili Mohammad Sadegh Bahadori Department of Civil Engineering Semnan University Semnan Iran Glenn Department of Civil Engineering Clemson Unioersity Clemson SC 29634 USA Instituto Superior Tecnico University of Lisbon Lisbon 1600-276 Portugal

There is a growing concern in traffic accident rate in recent years. Using Mashhad city （Iran second populous city） traffic accident records as case study, this paper applied the combi- nation of geo-information technology and spatial-statistical analysis to bring out the influence of spatial factors in their formation. The aim of the study is to examine 4 clustering analyses to have a better understanding of traffic accidents patterns in complex urban network. In order to deploy the clustering technique in urban roads, 9331 point features for inner city traffic accidents during 12 months have been registered according to their x and y location in geographic information system （GIS）. The mentioned areas were analyzed by kernel density estimation （kDE） using ARCMAP and two other analyses using SANET 4th edition software so that the results of network analysis can be compared with traditional kDE method. In addi- tion, this research introduces five classifications for determining the eventfulness of the under study area based on standard deviation and to make priority in creating security in the area. The nearest neighbor and k-function output analysis consist of four curves and regarding the fact that for all fatal, injury and property damage only crashes, the observed value curve is above the 5% confidence interval. Accidents in the study region are more clustered than ex- pected by random chance. The importance of this study is to use GIS as a management system for accident analysis by combination of spatial-statistical methods.

关键词： Traffic accidents Hotspots kernel density analysis Nearest neighbor k-function

Location patterns of urban industry in Shanghai and implications for sustainability

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Journal of Geographical Sciences 2017年第7期27卷 857-878页

作者： CAO Weidong LI Yingying CHENG Jianquan Steven MILLINGTON College of Territorial Resources and Tourism Anhui Normal University Wuhu 241003 Anhui China key Laboratory of Beibu Gulf Environmental Change and Resources Utilization under Ministry of Education Guangxi Teachers Education University Nanning 530001 China School of Science and the Environment Manchester Metropolitan University (MMU) Chester Street Manchester M1 5GD UK

China＇s economy has undergone rapid transition and industrial restructuring. The term ＂urban industry＂ describes a particular type of industry within Chinese cities experiencing restructuring. Given the high percentage of industrial firms that have either closed or relo- cated from city centres to the urban fringe and beyond, emergent global cities such as Shanghai, are implementing strategies for local economic and urban development, which involve urban industrial upgrading numerous firms in the city centre and urban fringe. This study aims to analyze the location patterns of seven urban industrial sectors within the Shanghai urban region using 2008 micro-geography data. To avoid Modifiable Areal Unit Problem （MAUP） issue, four distance-based measures including nearest neighbourhood analysis, kernel density estimation, k-function and co-location quotient have been exten- sively applied to analyze and compare the concentration and co-location between the seven sectors. The results reveal disparate patterns varying with distance and interesting co-location as well. The results are as follows： the city centre and the urban fringe have the highest intensity of urban industrial firms, but the zones with 20-30 km from the city centre is a watershed for most categories; the degree of concentration varies with distance, weaker at shorter distance, increasing up to the maximum distance of 30 km and then decreasing until 50 km; for all urban industries, there are three types of patterns, mixture of clustered, random and dispersed distribution at a varied range of distances. Consequently, this paper argues that the location pattern of urban industry reflects the stage-specific industrial restructuring and spatial transformation, conditioned by sustainability objectives.

关键词： urban industry industrial location pattern co-location quotient k-function Shanghai

Spatio-Temporal Patterns of Wildlife Road Mortality in Golestan National Park-North East of Iran

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Open Journal of Ecology 2016年第6期6卷 312-324页

作者： Vahed Dehghani kazemi Hamidreza Jafari Ahmadreza Yavari Department of Environmental Planning Graduate Faculty of Environment University of Tehran Tehran Iran

Nowadays, wildlife road mortality is acknowledged as a main source of threatening long-term survival of wildlife. This paper as the first to analysis wild life vehicle collisions in Iran, aims to reconstruct and interpret the spatio-temporal patterns of WVCs on Asiaei highway in Golestan National Park (GNP). With the collaboration of environmental protection department of GNP, we identified about 1900 WVC Records involving 34 different species of mammals, birds, reptiles and amphibians between 2004 and 2013. Mammals were involved in more than 50% of overall WVCs, among which wild boar (Sus scrofa), Golden Jackal (Canis aureus), Red Fox (Vulpes vulpes), hedgehog (Erinaceus concolor), stone marten (Martes foina) and porcupine (Hystrix indica) were involved in more than 90% of mammals’ mortalities;So, we focused on analyzing spatio-temporal pattern of vehicle collisions of these six mammal species. During the study period, these species have undergone 95% increase in road mortalities, averagely. Detailed temporal analyses exhibited an increasing trend of road mortalities from spring to summer and then a reducing one to late winter. It was shown that a large number of collisions occurred in holiday periods when recreational trips considerably increased the traffic volume of Asiaei highway. Preliminary inspection of spatial patterns using kernel density analysis revealed six collision hotspots, mostly located in the road bends with densely forested land cover on both sides;the promenades along the road seemed to play a significant role too. Scale dependency analyses of collision patterns, demonstrated clustering pattern at micro scales less than 10 km, randomness at meso scales 10 - 20 km and both regularity and clustering at macro scales more than 20 km. This paper suggests that road mortality of common species in GNP is a momentous issue, which needs to be considered by relevant governmental and public organizations. We also emphasize that the analyses of spatial and t

关键词： Golestan National Park Wildlife Vehicle Collision (WVC) Spatio-Temporal Pattern k-function

Small-Scale Spatial Patterns of <i>Copernicia alba</i>Morong near Bahia Negra, Paraguay

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Natural Resources 2013年第5期4卷 369-377页

作者： Michelle E. Cisz Michael J. Falkowski Blair Orr School of Forest Resources and Environmental Science Michigan Technological University Houghton USA

We assessed the spatial distribution of Copernicia alba Morong. In the study area, a lowland palm savanna floodplain, C. alba is the only overstory species. We hypothesized C. alba would be randomly distributed within natural stands. Palms were tallied in six randomly located 0.25 haplots and analyzed using a first-order, Ripley’s k function to assess the distribution of juvenile, adult, and total palm populations. While the total population had either aggregated or random distributions, when analyzing juvenile and adult population separately, we found juveniles were consistently more aggregated than the adults.

关键词： Ripley’s k-function First Order Analysis Floodplain Fire Chaco Monotypic Stands Disturbance Ecol-ogy Population Dynamics

ArcGIS<sup>TM</sup>Proximity and Cluster Analysis of Electron Probe Micro-Maps of Round Top Critical Mineral Deposit

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Advances in Materials Physics and Chemistry 2020年第3期10卷 63-76页

作者： Lorraine M. Negrón Margaret Piranian Maria A. Amaya Daniel Gorski Nicholas E. Pingitore Department of Geological Sciences The University of Texas at El Paso El Paso Texas USA School of Nursing The University of Texas at El Paso El Paso Texas USA Texas Mineral Resources Corporation Sierra Blanca Texas USA

Critical and rare earth elements are in high demand for their increasing incorporation in modern technological devices for applications in the military, industrial, commercial, and consumer sectors. Round Top Mountain, a rhyolite laccolith in Sierra Blanca, west Texas, U.S.A. is a unique mineral deposit that offers opportunity for development of rare earth elements, especially the heavy rare earths, as well as associated critical elements. The main objective here is to evaluate the distances between accessory minerals of potential economic value (yttrofluorite, cryolite, uraninite, thorite, cassiterite, and columbite), and to major (potassium feldspar, albite, and quartz) and minor minerals (annite mi-ca, magnetite, and zircon). In this study we explore the proximity and clustering of these minor and accessory minerals, at the mi-cron-to-millimeter scale, from mineral maps constructed in a previous application of ArcGISTM tools to electron probe microanal-ysis (EPMA) element maps. Our goal is to determine whether specific minerals cluster spatially and, if so, at what distances. We noted that the high-value target yttrofluorite grains often neighbor potassium feldspar and quartz grains, but less commonly magnetite and mica grains. With regard to cluster analysis, most minor and accessory minerals were found to group together at small scales (low micrometer) and were dis-persed or random at larger (up to 1 mm) distances.

关键词： ArcGISTM EPMA Proximity Ripley’s k-function Critical Minerals Yttro-fluorite Round Top Deposit