{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,4]],"date-time":"2026-03-04T08:13:47Z","timestamp":1772612027123,"version":"3.50.1"},"reference-count":68,"publisher":"MDPI AG","issue":"5","license":[{"start":{"date-parts":[[2017,5,3]],"date-time":"2017-05-03T00:00:00Z","timestamp":1493769600000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"funder":[{"name":"Key Program of National Natural Science Foundation of China","award":["41531178"],"award-info":[{"award-number":["41531178"]}]},{"name":"National Science Foundation of Guangdong Province","award":["2014A030312010"],"award-info":[{"award-number":["2014A030312010"]}]},{"name":"National Natural Science Foundation for Outstanding Youth","award":["41522104"],"award-info":[{"award-number":["41522104"]}]}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>The relationship between burglary and socio-demographic factors has long been a hot topic in crime research. Spatial dependence and spatial heterogeneity are two issues to be addressed in modeling geographic data. When these two issues arise at the same time, it is difficult to model them simultaneously. A cross-comparison of three models is presented in this study to identify which spatial effect should be addressed first in crime analysis. The negative binominal model (NB), Bayesian hierarchical model (BHM) and the geographically weighted Poisson regression model (GWPR) were implemented based on a three-year residential burglary data set from ZG, China. The modeling result shows that both BHM and GWPR outperform NB as they capture either of the spatial effects. Compared to the NB model, the mean absolute deviation (MAD) of BHM and GWPR was decreased by 83.71% and 49.39%, the mean squared error (MSE) of BHM and GWPR was decreased by 97.88% and 77.15%, and the      R d 2      of BHM and GWPR was improved by 26.7% and 19.1%, respectively. In comparison with BHM and GWPR, BHM fits the data better with lower MAD, MSE and higher      R d 2     . The empirical analysis indicates that the percentage of renter population, percentage of people from other provinces, bus line density, and bus stop density have a significantly positive impact on the number of residential burglaries. The percentage of residents with a bachelor degree or higher, on the other hand, is negatively associated with the number of residential burglaries.<\/jats:p>","DOI":"10.3390\/ijgi6050138","type":"journal-article","created":{"date-parts":[[2017,5,3]],"date-time":"2017-05-03T12:24:47Z","timestamp":1493814287000},"page":"138","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":28,"title":["Modeling Spatial Effect in Residential Burglary: A Case Study from ZG City, China"],"prefix":"10.3390","volume":"6","author":[{"ORCID":"https:\/\/orcid.org\/0000-0002-7084-0158","authenticated-orcid":false,"given":"Jianguo","family":"Chen","sequence":"first","affiliation":[{"name":"Center of Integrated Geographic Information Analysis, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China"}]},{"given":"Lin","family":"Liu","sequence":"additional","affiliation":[{"name":"Center of Integrated Geographic Information Analysis, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China"},{"name":"Department of Geography, University of Cincinnati, Cincinnati, OH 45221-0131, USA"}]},{"given":"Suhong","family":"Zhou","sequence":"additional","affiliation":[{"name":"Center of Integrated Geographic Information Analysis, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-6318-8958","authenticated-orcid":false,"given":"Luzi","family":"Xiao","sequence":"additional","affiliation":[{"name":"Center of Integrated Geographic Information Analysis, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China"}]},{"given":"Guangwen","family":"Song","sequence":"additional","affiliation":[{"name":"Center of Integrated Geographic Information Analysis, School of Geography and Planning, Sun Yat-sen University, Guangzhou 510275, China"}]},{"given":"Fang","family":"Ren","sequence":"additional","affiliation":[{"name":"MS GIS Program, University of Redlands, Redlands, CA 30074, USA"}]}],"member":"1968","published-online":{"date-parts":[[2017,5,3]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","first-page":"261","DOI":"10.1016\/j.apgeog.2014.12.001","article-title":"Permeability, space syntax, and the patterning of residential burglaries in urban China","volume":"60","author":"Wu","year":"2015","journal-title":"Appl. Geogr."},{"key":"ref_2","doi-asserted-by":"crossref","first-page":"481","DOI":"10.1007\/s10940-014-9235-4","article-title":"Examining the relationship between road structure and burglary risk via quantitative network analysis","volume":"31","author":"Davies","year":"2015","journal-title":"J. Quant. Criminol."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"711","DOI":"10.1177\/0022427816647991","article-title":"The impact of neighborhood context on spatiotemporal patterns of burglary","volume":"53","author":"Nobles","year":"2016","journal-title":"J. Res. Crime Delinquency"},{"key":"ref_4","doi-asserted-by":"crossref","first-page":"515","DOI":"10.1177\/0013916514551047","article-title":"The relation between residential property and its surroundings and day- and night-time residential burglary","volume":"48","author":"Montoya","year":"2016","journal-title":"Environ. Behav."},{"key":"ref_5","doi-asserted-by":"crossref","unstructured":"Liu, H., and Zhu, X. (2016). Exploring the influence of neighborhood characteristics on burglary risks: A Bayesian random effects modeling approach. ISPRS Int. J. Geo-Inf., 5.","DOI":"10.3390\/ijgi5070102"},{"key":"ref_6","doi-asserted-by":"crossref","first-page":"44","DOI":"10.1016\/j.ijlcj.2015.10.004","article-title":"Victimization immunity and lifestyle: A comparative study of over-dispersed burglary victimizations in South Korea and U.S.","volume":"45","author":"Parka","year":"2016","journal-title":"Int. J. Law Crime Justice"},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1093\/bjc\/azr010","article-title":"Income disparities of burglary risk: Security availability during the crime drop","volume":"51","author":"Tilley","year":"2011","journal-title":"Br. J. Criminol."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"919","DOI":"10.1080\/07418825.2011.605073","article-title":"Unemployment, guardianship, and weekday residential burglary","volume":"29","author":"Eitle","year":"2012","journal-title":"Justice Q."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"148","DOI":"10.1016\/j.habitatint.2016.03.007","article-title":"Do all commercial land uses deteriorate neighborhood safety?: Examining the relationship between commercial land-use mix and residential burglary","volume":"55","author":"Sohn","year":"2016","journal-title":"Habitat Int."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"265","DOI":"10.1057\/sj.2011.22","article-title":"Repeat burglary victimization in Malawi and the influence of housing type and area-level affluence","volume":"25","author":"Sidebottom","year":"2012","journal-title":"Secur. J."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"27","DOI":"10.1016\/j.apgeog.2014.07.007","article-title":"A spatial analysis of the impact of housing foreclosures on residential burglary","volume":"54","author":"Zhang","year":"2014","journal-title":"Appl. Geogr."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.apgeog.2015.08.004","article-title":"A discrete spatial choice model of burglary target selection at the house-level","volume":"64","author":"Vandevivera","year":"2015","journal-title":"Appl. Geogr."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"157","DOI":"10.1057\/sj.2009.23","article-title":"The effects of target characteristics on the sighting and arrest of offenders at burglary emergencies","volume":"24","author":"Coupe","year":"2011","journal-title":"Secur. J."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"168","DOI":"10.1080\/07418825.2012.760644","article-title":"Keeping the barbarians outside the gate? Comparing burglary victimization in gated and non-gated communities","volume":"32","author":"Addington","year":"2015","journal-title":"Justice Q."},{"key":"ref_15","doi-asserted-by":"crossref","first-page":"56","DOI":"10.1177\/1057567713476887","article-title":"Burglary in gated communities: An empirical analysis using routine activities theory","volume":"23","author":"Breetzke","year":"2013","journal-title":"Int. Crim. Justice Rev."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"739","DOI":"10.1177\/0011128710364804","article-title":"Placing the neighborhood accessibility\u2013burglary link in social-structural context","volume":"56","author":"Ward","year":"2014","journal-title":"Crime Delinquency"},{"key":"ref_17","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1016\/j.apgeog.2011.10.017","article-title":"The effect of altitude and slope on the spatial patterning of burglary","volume":"34","author":"Breetzke","year":"2012","journal-title":"Appl. Geogr."},{"key":"ref_18","doi-asserted-by":"crossref","first-page":"210","DOI":"10.1016\/j.apgeog.2014.11.022","article-title":"Space-time interaction of residential burglaries in Wuhan, China","volume":"60","author":"Ye","year":"2015","journal-title":"Appl. Geogr."},{"key":"ref_19","doi-asserted-by":"crossref","first-page":"49","DOI":"10.1016\/j.jcrimjus.2015.12.003","article-title":"The decline and locational shift of automotive theft: A local level analysis","volume":"44","author":"Hodgkinson","year":"2016","journal-title":"J. Crim. Justice"},{"key":"ref_20","doi-asserted-by":"crossref","first-page":"25","DOI":"10.1007\/s10940-014-9223-8","article-title":"Early warning system for temporary crime hot spots","volume":"31","author":"Gorr","year":"2015","journal-title":"J. Quant. Criminol."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"215","DOI":"10.3138\/cjccj.2012.E13","article-title":"Exploring hotspots of drug offences in Toronto: A comparison of four local spatial cluster detection methods","volume":"55","author":"Quick","year":"2013","journal-title":"Can. J. Criminol. Crim. Justice"},{"key":"ref_22","doi-asserted-by":"crossref","first-page":"365","DOI":"10.1111\/j.1467-9671.2011.01255.x","article-title":"Street-level spatial scan statistic and STAC for analysing street crime concentrations","volume":"15","author":"Shiode","year":"2011","journal-title":"Trans. GIS"},{"key":"ref_23","unstructured":"Lesage, J.P. (1999). The Theory and Practice of Spatial Econometrics, University of Toledo."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"65","DOI":"10.4018\/IJAEIS.2016010105","article-title":"Sensitivity analysis of spatial autocorrelation using distinct geometrical settings: Guidelines for the quantitative geographer","volume":"7","year":"2016","journal-title":"Int. J. Agric. Environ. Inf. Syst. (IJAEIS)"},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"234","DOI":"10.2307\/143141","article-title":"A computer movie simulating urban growth in the detroit region","volume":"46","author":"Tobler","year":"1970","journal-title":"Econ. Geogr."},{"key":"ref_26","doi-asserted-by":"crossref","first-page":"546","DOI":"10.1016\/j.jcrimjus.2008.09.008","article-title":"Fear of crime in two post-socialist capital cities\u2014Ljubljana, Slovenia and Sarajevo, Bosnia and Herzegovina","volume":"36","author":"Fallshore","year":"2008","journal-title":"J. Crim. Justice"},{"key":"ref_27","doi-asserted-by":"crossref","first-page":"582","DOI":"10.2747\/0272-3638.24.7.582","article-title":"The determinants of crime in tucson, arizona","volume":"24","author":"Cahill","year":"2003","journal-title":"Urban Geogr."},{"key":"ref_28","doi-asserted-by":"crossref","unstructured":"Dewan, A.M., Haider, M.R., and Amin, M.R. (2014). Exploring crime statistics. Dhaka Megacity: Geospatial Perspectives on Urbanisation, Environment and Health, Springer.","DOI":"10.1007\/978-94-007-6735-5"},{"key":"ref_29","first-page":"197","article-title":"A Bayesian approach to modeling binary data: The case of high-intensity crime areas","volume":"36","author":"Law","year":"2004","journal-title":"Geogr. Anal."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"1057","DOI":"10.1177\/0042098013492232","article-title":"How places influence crime: The impact of surrounding areas on neighborhood burglary rates in a british city","volume":"51","author":"Hirschfield","year":"2014","journal-title":"Urban Stud."},{"key":"ref_31","doi-asserted-by":"crossref","first-page":"193","DOI":"10.1080\/00330124.2010.547151","article-title":"The ambient population and crime analysis","volume":"63","author":"Andresen","year":"2011","journal-title":"Prof. Geogr."},{"key":"ref_32","doi-asserted-by":"crossref","first-page":"446","DOI":"10.1016\/j.jcrimjus.2010.04.013","article-title":"Modeling violent crime rates: A test of social disorganization in the city of Tshwane, South Africa","volume":"38","author":"Breetzke","year":"2010","journal-title":"J. Crim. Justice"},{"key":"ref_33","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1016\/j.apgeog.2015.02.011","article-title":"Spatial variation of the urban taxi ridership using GPS data","volume":"59","author":"Qian","year":"2015","journal-title":"Appl. Geogr."},{"key":"ref_34","doi-asserted-by":"crossref","first-page":"118","DOI":"10.1111\/j.2041-210X.2010.00021.x","article-title":"Do not log-transform count data","volume":"1","author":"Robert","year":"2010","journal-title":"Methods Ecol. Evol."},{"key":"ref_35","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s40163-016-0051-z","article-title":"Equity, justice and the crime drop: The case of burglary in England and Wales","volume":"5","author":"Hunter","year":"2016","journal-title":"Crime Sci."},{"key":"ref_36","unstructured":"Fotheringham, A.S., Brunsdon, C., and Charlton, M. (2002). Geographically Weighted Regression: The Analysis of Spatially Varying Relationships, John Wiley & Sons Ltd."},{"key":"ref_37","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1007\/s12061-009-9021-0","article-title":"Using geographically weighted regression to validate approaches for modelling accessibility to primary health care","volume":"2","author":"Bagheri","year":"2009","journal-title":"Appl. Spat. Anal. Policy"},{"key":"ref_38","doi-asserted-by":"crossref","first-page":"737","DOI":"10.1016\/j.apgeog.2011.07.018","article-title":"Using multilevel modeling and geographically weighted regression to identify spatial variations in the relationship between place-level disadvantages and obesity in Taiwan","volume":"32","author":"Chen","year":"2012","journal-title":"Appl. Geogr."},{"key":"ref_39","doi-asserted-by":"crossref","first-page":"13","DOI":"10.1186\/1476-072X-12-13","article-title":"Modelling typhoid risk in Dhaka Metropolitan Area of Bangladesh: The role of socio-economic and environmental factors","volume":"12","author":"Corner","year":"2013","journal-title":"Int. J. Health Geogr."},{"key":"ref_40","doi-asserted-by":"crossref","unstructured":"Dewan, A.M., Corner, R., Hashizume, M., and Ongee, E.T. (2013). Typhoid fever and its association with environmental factors in the dhaka metropolitan area of bangladesh: A spatial and Time-Series approach. PLoS Negl. Trop. Dis., 7.","DOI":"10.1371\/journal.pntd.0001998"},{"key":"ref_41","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1016\/j.ssci.2013.04.005","article-title":"Using geographically weighted poisson regression for county-level crash modeling in California","volume":"58","author":"Li","year":"2013","journal-title":"Saf. Sci."},{"key":"ref_42","doi-asserted-by":"crossref","first-page":"192","DOI":"10.1111\/j.2517-6161.1974.tb00999.x","article-title":"Spatial interaction and the statistical analysis of lattice systems","volume":"36","author":"Besag","year":"1974","journal-title":"J. R. Stat. Soc."},{"key":"ref_43","doi-asserted-by":"crossref","first-page":"147","DOI":"10.1016\/j.aap.2016.05.001","article-title":"Macroscopic modeling of pedestrian and bicycle crashes: A cross-comparison of estimation methods","volume":"93","author":"Saberi","year":"2016","journal-title":"Accid. Anal. Prev."},{"key":"ref_44","doi-asserted-by":"crossref","first-page":"12","DOI":"10.1016\/j.aap.2016.07.028","article-title":"Macro-level safety analysis of pedestrian crashes in Shanghai, China","volume":"96","author":"Wang","year":"2016","journal-title":"Accid. Anal. Prev."},{"key":"ref_45","doi-asserted-by":"crossref","first-page":"73","DOI":"10.1007\/s12061-011-9060-1","article-title":"Bayesian spatial random effect modelling for analysing burglary risks controlling for offender, socioeconomic, and unknown risk factors","volume":"5","author":"Law","year":"2012","journal-title":"Appl. Spat. Anal. Policy"},{"key":"ref_46","doi-asserted-by":"crossref","first-page":"866","DOI":"10.3390\/ijerph110100866","article-title":"Exploring neighborhood influences on small-area variations in intimate partner violence risk: A bayesian random-effects modeling approach","volume":"11","author":"Gracia","year":"2014","journal-title":"Int. J. Environ. Res. Public Health."},{"key":"ref_47","first-page":"1","article-title":"Monitoring schistosomiasis risk in East China over space and time using a Bayesian hierarchical modeling approach","volume":"6","author":"Hu","year":"2016","journal-title":"Sci. Rep."},{"key":"ref_48","first-page":"1","article-title":"An application of Bayesian approach in modeling risk of death in an intensive care unit","volume":"11","author":"Wong","year":"2016","journal-title":"PLoS ONE"},{"key":"ref_49","doi-asserted-by":"crossref","first-page":"1486","DOI":"10.1016\/j.aap.2008.03.009","article-title":"Modelling area-wide count outcomes with spatial correlation and heterogeneity: An analysis of London crash data","volume":"40","author":"Quddus","year":"2008","journal-title":"Accid. Anal. Prev."},{"key":"ref_50","doi-asserted-by":"crossref","first-page":"146","DOI":"10.1016\/j.aap.2015.03.003","article-title":"Multivariate crash modeling for motor vehicle and non-motorized modes at the macroscopic level","volume":"78","author":"Lee","year":"2015","journal-title":"Accid. Anal. Prev."},{"key":"ref_51","doi-asserted-by":"crossref","first-page":"2695","DOI":"10.1002\/sim.2129","article-title":"Geographically weighted Poisson regression for disease association mapping","volume":"24","author":"Nakaya","year":"2005","journal-title":"Stat. Med."},{"key":"ref_52","doi-asserted-by":"crossref","first-page":"321","DOI":"10.1111\/tgis.12107","article-title":"Exploring spatial non-stationarity and varying relationships between crash data and related factors using geographically weighted poisson regression","volume":"19","author":"Shahri","year":"2015","journal-title":"Trans. GIS"},{"key":"ref_53","first-page":"209","article-title":"R-squared measures for count data regression models with applications to health-care utilization","volume":"14","author":"Cameron","year":"1996","journal-title":"J. Bus. Econ. Stat."},{"key":"ref_54","doi-asserted-by":"crossref","first-page":"918","DOI":"10.1093\/bjc\/azm026","article-title":"A multilevel analysis of the risk of household burglary in the city of Tianjin, China","volume":"47","author":"Zhang","year":"2007","journal-title":"Br. J. Criminol."},{"key":"ref_55","unstructured":"Bureau, C.S. (2015). China Statistical Yearbook, Statistical Publishing House."},{"key":"ref_56","doi-asserted-by":"crossref","first-page":"588","DOI":"10.2307\/2094589","article-title":"Social change and crime rate trends: A routine activity approach","volume":"44","author":"Cohen","year":"1979","journal-title":"Am. Sociol. Rev."},{"key":"ref_57","doi-asserted-by":"crossref","unstructured":"Shaw, R.C., and McKay, D.H. (1942). Juvenile Delinquency and Urban Areas, University of Chicago Press.","DOI":"10.2307\/1334446"},{"key":"ref_58","doi-asserted-by":"crossref","first-page":"418","DOI":"10.1080\/19361610.2014.942823","article-title":"Nature of residential burglary and prevention by design approaches in a nigerian traditional urban center","volume":"9","author":"Badiora","year":"2014","journal-title":"J. Appl. Secur. Res."},{"key":"ref_59","doi-asserted-by":"crossref","first-page":"66","DOI":"10.1093\/bjc\/44.1.66","article-title":"Burglary victimization in england and wales, the united states and the netherlands: A cross-national comparative test of routine activities and lifestyle theories","volume":"44","author":"Tseloni","year":"2004","journal-title":"Br. J. Criminol."},{"key":"ref_60","doi-asserted-by":"crossref","first-page":"516","DOI":"10.1111\/j.1467-9272.2005.00496.x","article-title":"Residential burglaries and neighborhood socioeconomic context in London, Ontario: Global and local regression analysis","volume":"57","author":"Malczewski","year":"2005","journal-title":"Prof. Geogr."},{"key":"ref_61","doi-asserted-by":"crossref","first-page":"31","DOI":"10.1057\/palgrave.udi.9000079","article-title":"Can streets be made safe?","volume":"9","author":"Hillier","year":"2004","journal-title":"Urban Des. Int."},{"key":"ref_62","doi-asserted-by":"crossref","first-page":"177","DOI":"10.1057\/palgrave.udi.9000016","article-title":"Housing layout and crime vulnerability","volume":"5","author":"Shu","year":"2000","journal-title":"Urban Des. Int."},{"key":"ref_63","first-page":"26","article-title":"Social crime or spatial crime? Exploring the effects of social, economical, and spatial factors on burglary rates","volume":"43","author":"Chang","year":"2011","journal-title":"Environ. Psychol. Nonverbal Behav."},{"key":"ref_64","doi-asserted-by":"crossref","first-page":"296","DOI":"10.1093\/bjc\/azh070","article-title":"How do residential burglars select target areas?: A new approach to the analysis of criminal location choice","volume":"45","author":"Bernasco","year":"2005","journal-title":"Br. J. Criminol."},{"key":"ref_65","doi-asserted-by":"crossref","first-page":"115","DOI":"10.1007\/s10464-013-9582-6","article-title":"Collective efficacy as a task specific process: Examining the relationship between social ties, neighborhood cohesion and the capacity to respond to violence, delinquency and civic problems","volume":"52","author":"Wickes","year":"2013","journal-title":"Am. J. Community Psychol."},{"key":"ref_66","doi-asserted-by":"crossref","first-page":"123","DOI":"10.1007\/s10464-012-9507-9","article-title":"Sense of community and informal social control among lower income households: The role of homeownership and collective efficacy in reducing subjective neighborhood crime and disorder","volume":"51","author":"Lindblad","year":"2013","journal-title":"Am. J. Community Psychol."},{"key":"ref_67","doi-asserted-by":"crossref","first-page":"2325","DOI":"10.1016\/j.worlddev.2008.04.009","article-title":"Life satisfaction in urban china: Components and determinants","volume":"36","author":"Appleton","year":"2008","journal-title":"World Dev."},{"key":"ref_68","doi-asserted-by":"crossref","first-page":"89","DOI":"10.1007\/s10109-012-0164-1","article-title":"Exploring links between juvenile offenders and social disorganization at a large map scale: A Bayesian spatial modeling approach","volume":"15","author":"Law","year":"2013","journal-title":"J. Geogr. Syst."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/6\/5\/138\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T18:34:27Z","timestamp":1760207667000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/6\/5\/138"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2017,5,3]]},"references-count":68,"journal-issue":{"issue":"5","published-online":{"date-parts":[[2017,5]]}},"alternative-id":["ijgi6050138"],"URL":"https:\/\/doi.org\/10.3390\/ijgi6050138","relation":{},"ISSN":["2220-9964"],"issn-type":[{"value":"2220-9964","type":"electronic"}],"subject":[],"published":{"date-parts":[[2017,5,3]]}}}