{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2025,10,12]],"date-time":"2025-10-12T03:55:33Z","timestamp":1760241333594,"version":"build-2065373602"},"reference-count":35,"publisher":"MDPI AG","issue":"1","license":[{"start":{"date-parts":[[2018,1,4]],"date-time":"2018-01-04T00:00:00Z","timestamp":1515024000000},"content-version":"vor","delay-in-days":0,"URL":"https:\/\/creativecommons.org\/licenses\/by\/4.0\/"}],"content-domain":{"domain":[],"crossmark-restriction":false},"short-container-title":["IJGI"],"abstract":"<jats:p>Semivariograms have been widely used in research to obtain optimal resolutions for ground features. To obtain the semivariogram curve and its attributes (range and sill), parameters including sample size (SS), maximum distance (MD), and group number (GN) have to be defined, as well as a mathematic model for fitting the curve. However, a clear guide on parameter setting and model selection is currently not available. In this study, a Monte Carlo simulation-based approach (MCS) is proposed to enhance the performance of semivariograms by optimizing the parameters, and case studies in three regions are conducted to determine the optimal resolution for natural resource surveys. Those parameters are optimized one by one through several rounds of MCS. The result shows that exponential model is better than sphere model; sample size has a positive relationship with R2, while the group number has a negative one; increasing the simulation number could improve the accuracy of estimation; and eventually the optimized parameters improved the performance of semivariogram. In case study, the average sizes for three general ground features (grassland, farmland, and forest) of three counties (Ansai, Changdu, and Taihe) in different geophysical locations of China were acquired and compared, and imagery with an appropriate resolution is recommended. The results show that the ground feature sizes acquired by means of MCS and optimized parameters in this study match well with real land cover patterns.<\/jats:p>","DOI":"10.3390\/ijgi7010013","type":"journal-article","created":{"date-parts":[[2018,1,4]],"date-time":"2018-01-04T11:52:47Z","timestamp":1515066767000},"page":"13","update-policy":"https:\/\/doi.org\/10.3390\/mdpi_crossmark_policy","source":"Crossref","is-referenced-by-count":1,"title":["Using Monte Carlo Simulation to Improve the Performance of Semivariograms for Choosing the Remote Sensing Imagery Resolution for Natural Resource Surveys: Case Study on Three Counties in East, Central, and West China"],"prefix":"10.3390","volume":"7","author":[{"given":"Juanle","family":"Wang","sequence":"first","affiliation":[{"name":"State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"Jiangsu Center for Collaborative Innovation in Geographical Information Resource Development and Application, Nanjing 210023, China"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"ORCID":"https:\/\/orcid.org\/0000-0002-9828-5168","authenticated-orcid":false,"given":"Junxiang","family":"Zhu","sequence":"additional","affiliation":[{"name":"Australasian Joint Research Centre for Building Information Modelling, School of Built Environment, Curtin University, Bentley, WA 6102, Australia"}],"role":[{"role":"author","vocabulary":"crossref"}]},{"given":"Xuehua","family":"Han","sequence":"additional","affiliation":[{"name":"State Key Laboratory of Resources and Environmental Information System, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China"},{"name":"University of Chinese Academy of Sciences, Beijing 100049, China"}],"role":[{"role":"author","vocabulary":"crossref"}]}],"member":"1968","published-online":{"date-parts":[[2018,1,4]]},"reference":[{"key":"ref_1","doi-asserted-by":"crossref","unstructured":"Saturno, W., Sever, T.L., Irwin, D.E., Howell, B.F., and Garrison, T.G. (2007). Putting us on the map: Remote sensing investigation of the ancient maya landscape. Remote Sensing in Archaeology, Springer.","DOI":"10.1007\/0-387-44455-6_6"},{"key":"ref_2","first-page":"289","article-title":"Remote sensing investigation and survey of qinghai lake in the past 25 years","volume":"15","author":"Shen","year":"2002","journal-title":"J. Lake Sci."},{"key":"ref_3","doi-asserted-by":"crossref","first-page":"68","DOI":"10.1016\/j.geomorph.2014.05.028","article-title":"Gully annealing by aeolian sediment: Field and remote-sensing investigation of aeolian-hillslope-fluvial interactions, colorado river corridor, arizona, USA","volume":"220","author":"Sankey","year":"2014","journal-title":"Geomorphology"},{"key":"ref_4","unstructured":"Kim, J., Grunwald, S., Osborne, T., Robbins, R., Yamataki, H., and Rivero, R. (2016). Spatial resolution effects of remote sensing images on digital soil models in aquatic ecosystems. Computing Ethics: A Multicultural Approach, CRC Press."},{"key":"ref_5","doi-asserted-by":"crossref","first-page":"564","DOI":"10.1016\/j.jenvman.2016.07.073","article-title":"Using remote sensing in support of environmental management: A framework for selecting products, algorithms and methods","volume":"182","author":"Gilbertson","year":"2016","journal-title":"J. Environ. Manag."},{"key":"ref_6","unstructured":"Qiu, B., Sui, Y., Chen, C., and Tu, X. (2010, January 20\u201323). Identification of optimal spatial resolution with local variance, semivariogram and wavelet method. Proceedings of the Accuracy 2010 Symposium, Leicester, UK."},{"key":"ref_7","doi-asserted-by":"crossref","first-page":"323","DOI":"10.1016\/0034-4257(88)90108-3","article-title":"The use of variograms in remote sensing: I. Scene models and simulated images","volume":"25","author":"Woodcock","year":"1988","journal-title":"Remote Sens. Environ."},{"key":"ref_8","doi-asserted-by":"crossref","first-page":"813","DOI":"10.1109\/LGRS.2011.2182604","article-title":"Semivariogram-based spatial bandwidth selection for remote sensing image segmentation with mean-shift algorithm","volume":"9","author":"Ming","year":"2012","journal-title":"IEEE Geosci. Remote Sens. Lett."},{"key":"ref_9","doi-asserted-by":"crossref","first-page":"268","DOI":"10.1016\/S0034-4257(99)00098-X","article-title":"High spatial resolution remote sensing data for forest ecosystem classification: An examination of spatial scale","volume":"72","author":"Treitz","year":"2000","journal-title":"Remote Sens. Environ."},{"key":"ref_10","doi-asserted-by":"crossref","first-page":"349","DOI":"10.1016\/0034-4257(88)90109-5","article-title":"The use of variograms in remote sensing: II. Real digital images","volume":"25","author":"Woodcock","year":"1988","journal-title":"Remote Sens. Environ."},{"key":"ref_11","doi-asserted-by":"crossref","first-page":"390","DOI":"10.1016\/j.rse.2006.02.022","article-title":"Retrieving forest structure variables based on image texture analysis and ikonos-2 imagery","volume":"102","author":"Kayitakire","year":"2006","journal-title":"Remote Sens. Environ."},{"key":"ref_12","doi-asserted-by":"crossref","first-page":"112","DOI":"10.1016\/S0034-4257(98)00104-7","article-title":"Airborne digital camera image semivariance for evaluation of forest structural damage at an acid mine site","volume":"68","author":"Levesque","year":"1999","journal-title":"Remote Sens. Environ."},{"key":"ref_13","doi-asserted-by":"crossref","first-page":"2019","DOI":"10.1016\/j.rse.2009.05.009","article-title":"Estimation of forest structural parameters using 5 and 10 meter spot-5 satellite data","volume":"113","author":"Wolter","year":"2009","journal-title":"Remote Sens. Environ."},{"key":"ref_14","doi-asserted-by":"crossref","first-page":"3305","DOI":"10.1080\/01431160600993413","article-title":"Estimating tree crown size with spatial information of high resolution optical remotely sensed imagery","volume":"28","author":"Song","year":"2007","journal-title":"Int. J. Remote Sens."},{"key":"ref_15","first-page":"153","article-title":"Estimation on forest stand crown of the picea schrenkiana based on high spatial resolution imagery","volume":"36","author":"Liu","year":"2013","journal-title":"J. Xinjiang Agric. Univ."},{"key":"ref_16","doi-asserted-by":"crossref","first-page":"25","DOI":"10.3959\/1536-1098-71.1.25","article-title":"How to improve dendrogeomorphic sampling: Variogram analyses of wood density using X-ray computed tomography","volume":"71","author":"Stoffel","year":"2015","journal-title":"Tree Ring Res."},{"key":"ref_17","first-page":"33","article-title":"An appropriate scale extraction method for complicated scene model based on semivariogram analysis","volume":"31","author":"Zhu","year":"2015","journal-title":"Geogr. Geo-Inf. Sci."},{"key":"ref_18","doi-asserted-by":"crossref","unstructured":"Webster, R., and Oliver, M.A. (1993). How large a sample is needed to estimate the regional variogram adequately?. Geostatistics Tr\u00f3ia\u201992, Springer.","DOI":"10.1007\/978-94-011-1739-5_14"},{"key":"ref_19","first-page":"593","article-title":"Vegetation changes of loess plateau and ansai county and the responding characteristics of climate","volume":"29","author":"Han","year":"2009","journal-title":"Acta Bot. Boreali-Occident. Sin."},{"key":"ref_20","first-page":"1866","article-title":"Impacts of the sloping land conversion program on the land use\/cover change in the loess plateau: A case study in Ansai county of Shaanxi province, China","volume":"26","author":"Zhou","year":"2011","journal-title":"J. Nat. Resour."},{"key":"ref_21","doi-asserted-by":"crossref","first-page":"301","DOI":"10.1080\/15481603.2014.912874","article-title":"Comparison of naip orthophotography and rapideye satellite imagery for mapping of mining and mine reclamation","volume":"51","author":"Maxwell","year":"2014","journal-title":"GISci. Remote Sens."},{"key":"ref_22","first-page":"1345","article-title":"Choosing an appropriate spatial resolution for remote sensing investigations","volume":"63","author":"Atkinson","year":"1997","journal-title":"Photogramm. Eng. Remote Sens."},{"key":"ref_23","doi-asserted-by":"crossref","first-page":"463","DOI":"10.1109\/36.3050","article-title":"Autocorrelation and regularization in digital images. I. Basic theory","volume":"26","author":"Jupp","year":"1988","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_24","doi-asserted-by":"crossref","first-page":"549","DOI":"10.1080\/014311698216170","article-title":"Semivariogram textural classification of jers-1 (fuyo-1) sar data obtained over a flooded area of the amazon rainforest","volume":"19","author":"Miranda","year":"1998","journal-title":"Int. J. Remote Sens."},{"key":"ref_25","doi-asserted-by":"crossref","first-page":"768","DOI":"10.1109\/36.387592","article-title":"Defining an optimal size of support for remote sensing investigations","volume":"33","author":"Atkinson","year":"1995","journal-title":"IEEE Trans. Geosci. Remote Sens."},{"key":"ref_26","first-page":"12","article-title":"Multiresolution segmentation: An optimization approach for high quality multi-scale image segmentation","volume":"12","author":"Baatz","year":"2000","journal-title":"Angew. Geogr. Informationsverarbeitung"},{"key":"ref_27","unstructured":"Robert, C., and Casella, G. (2013). Monte Carlo Statistical Methods, Springer Science & Business Media."},{"key":"ref_28","doi-asserted-by":"crossref","first-page":"331","DOI":"10.1109\/JPROC.2004.840490","article-title":"Parallel matlab: Doing it right","volume":"93","author":"Choy","year":"2005","journal-title":"Proc. IEEE"},{"key":"ref_29","doi-asserted-by":"crossref","first-page":"3","DOI":"10.1007\/s10766-008-0082-5","article-title":"Matlab\u00ae: A language for parallel computing","volume":"37","author":"Sharma","year":"2009","journal-title":"Int. J. Parallel Program."},{"key":"ref_30","doi-asserted-by":"crossref","first-page":"205","DOI":"10.1007\/s11442-017-1372-x","article-title":"Modelling the integrated effects of land use and climate change scenarios on forest ecosystem aboveground biomass, a case study in taihe county of china","volume":"27","author":"Wu","year":"2017","journal-title":"J. Geogr. Sci."},{"key":"ref_31","unstructured":"Wang, P. (2013). Volving Law of Land Use and Driving Force in Jiangxi Province. [Master\u2019s Thesis, Jiangxi Agriculture University]."},{"key":"ref_32","first-page":"192","article-title":"Analysis on information entropy of land use structure in changdu area of Tibet","volume":"16","author":"He","year":"2007","journal-title":"Resour. Environ. Yangtze Basin"},{"key":"ref_33","first-page":"346","article-title":"Agricultural landscape spatial heterogeneity analysis and optimal scale selection: An example applied to sanjiang plain","volume":"67","author":"Wen","year":"2012","journal-title":"Acta Geogr. Sin."},{"key":"ref_34","first-page":"607","article-title":"Appropriate scale in typical objects feature extraction","volume":"30","author":"Yang","year":"2012","journal-title":"J. Mt. Sci."},{"key":"ref_35","unstructured":"Satellite Imaging Corporation (2017, December 28). Satellite Sensors. Available online: https:\/\/www.satimagingcorp.com\/satellite-sensors\/."}],"container-title":["ISPRS International Journal of Geo-Information"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/www.mdpi.com\/2220-9964\/7\/1\/13\/pdf","content-type":"unspecified","content-version":"vor","intended-application":"similarity-checking"}],"deposited":{"date-parts":[[2025,10,11]],"date-time":"2025-10-11T14:50:03Z","timestamp":1760194203000},"score":1,"resource":{"primary":{"URL":"https:\/\/www.mdpi.com\/2220-9964\/7\/1\/13"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2018,1,4]]},"references-count":35,"journal-issue":{"issue":"1","published-online":{"date-parts":[[2018,1]]}},"alternative-id":["ijgi7010013"],"URL":"https:\/\/doi.org\/10.3390\/ijgi7010013","relation":{},"ISSN":["2220-9964"],"issn-type":[{"type":"electronic","value":"2220-9964"}],"subject":[],"published":{"date-parts":[[2018,1,4]]}}}