{"status":"ok","message-type":"work","message-version":"1.0.0","message":{"indexed":{"date-parts":[[2026,3,11]],"date-time":"2026-03-11T16:08:16Z","timestamp":1773245296253,"version":"3.50.1"},"reference-count":49,"publisher":"Elsevier BV","license":[{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/tdm\/userlicense\/1.0\/"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"tdm","delay-in-days":0,"URL":"https:\/\/www.elsevier.com\/legal\/tdmrep-license"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-017"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-037"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-012"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-029"},{"start":{"date-parts":[[2024,1,1]],"date-time":"2024-01-01T00:00:00Z","timestamp":1704067200000},"content-version":"stm-asf","delay-in-days":0,"URL":"https:\/\/doi.org\/10.15223\/policy-004"}],"funder":[{"DOI":"10.13039\/501100001809","name":"National Natural Science Foundation of China","doi-asserted-by":"publisher","id":[{"id":"10.13039\/501100001809","id-type":"DOI","asserted-by":"publisher"}]}],"content-domain":{"domain":["elsevier.com","sciencedirect.com"],"crossmark-restriction":true},"short-container-title":["Computers & Geosciences"],"published-print":{"date-parts":[[2024,1]]},"DOI":"10.1016\/j.cageo.2023.105482","type":"journal-article","created":{"date-parts":[[2023,10,29]],"date-time":"2023-10-29T00:20:30Z","timestamp":1698538830000},"page":"105482","update-policy":"https:\/\/doi.org\/10.1016\/elsevier_cm_policy","source":"Crossref","is-referenced-by-count":1,"special_numbering":"C","title":["Intelligent terrain generation considering global information and terrain patterns"],"prefix":"10.1016","volume":"182","author":[{"given":"Zhanlong","family":"Chen","sequence":"first","affiliation":[]},{"given":"Xiaochuan","family":"Ma","sequence":"additional","affiliation":[]},{"given":"Houpu","family":"Li","sequence":"additional","affiliation":[]},{"given":"Xuwei","family":"Xu","sequence":"additional","affiliation":[]},{"given":"Xiaoyi","family":"Han","sequence":"additional","affiliation":[]}],"member":"78","reference":[{"issue":"9","key":"10.1016\/j.cageo.2023.105482_bib1","doi-asserted-by":"crossref","first-page":"5453","DOI":"10.1007\/s10661-011-2352-8","article-title":"Application of remote sensing data and GIS for landslide risk assessment as an environmental threat to Izmir city (west Turkey)","volume":"184","author":"Akgun","year":"2012","journal-title":"Environ. Monit. Assess."},{"issue":"1","key":"10.1016\/j.cageo.2023.105482_bib2","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1186\/s40537-021-00444-8","article-title":"Review of deep learning: concepts, CNN architectures, challenges, applications, future directions","volume":"8","author":"Alzubaidi","year":"2021","journal-title":"J. Big Data"},{"key":"10.1016\/j.cageo.2023.105482_bib3","series-title":"Geostatistics and Spatial Interpolation","first-page":"159","author":"Atkinson","year":"2009"},{"key":"10.1016\/j.cageo.2023.105482_bib4","article-title":"Survey of nearest neighbor techniques","author":"Bhatia","year":"2010","journal-title":"arXiv preprint arXiv:1007.0085"},{"issue":"1\u20132","key":"10.1016\/j.cageo.2023.105482_bib5","doi-asserted-by":"crossref","first-page":"86","DOI":"10.1016\/j.geoderma.2006.10.016","article-title":"Optimization of sample patterns for universal kriging of environmental variables","volume":"138","author":"Brus","year":"2007","journal-title":"Geoderma"},{"key":"10.1016\/j.cageo.2023.105482_bib6","doi-asserted-by":"crossref","first-page":"1038","DOI":"10.3390\/rs15041038","article-title":"An enhanced residual feature fusion network integrated with a terrain weight module for digital elevation model super-resolution","volume":"15","author":"Chen","year":"2023","journal-title":"Rem. Sens."},{"key":"10.1016\/j.cageo.2023.105482_bib7","volume":"vol. 41","author":"Chen","year":"2016"},{"issue":"3","key":"10.1016\/j.cageo.2023.105482_bib8","doi-asserted-by":"crossref","first-page":"239","DOI":"10.1007\/BF00889887","article-title":"The origins of kriging","volume":"22","author":"Cressie","year":"1990","journal-title":"Math. Geol."},{"issue":"1","key":"10.1016\/j.cageo.2023.105482_bib9","doi-asserted-by":"crossref","first-page":"53","DOI":"10.1109\/MSP.2017.2765202","article-title":"Generative adversarial networks: an overview","volume":"35","author":"Creswell","year":"2018","journal-title":"IEEE Signal Process. Mag."},{"issue":"2","key":"10.1016\/j.cageo.2023.105482_bib10","doi-asserted-by":"crossref","first-page":"295","DOI":"10.1109\/TPAMI.2015.2439281","article-title":"Image super-resolution using deep convolutional networks","volume":"38","author":"Dong","year":"2015","journal-title":"IEEE Trans. Pattern Anal. Mach. Intell."},{"issue":"3","key":"10.1016\/j.cageo.2023.105482_bib11","doi-asserted-by":"crossref","first-page":"433","DOI":"10.1016\/0166-0462(92)90038-3","article-title":"Spatial autocorrelation and neighborhood quality","volume":"22","author":"Dubin","year":"1992","journal-title":"Reg. Sci. Urban Econ."},{"issue":"11","key":"10.1016\/j.cageo.2023.105482_bib12","doi-asserted-by":"crossref","first-page":"139","DOI":"10.1145\/3422622","article-title":"Generative adversarial networks","volume":"63","author":"Goodfellow","year":"2020","journal-title":"Commun. ACM"},{"issue":"6","key":"10.1016\/j.cageo.2023.105482_bib13","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1145\/3130800.3130804","article-title":"Interactive example-based terrain authoring with conditional generative adversarial networks","volume":"36","author":"Gu\u00e9rin","year":"2017","journal-title":"ACM Trans. Graph."},{"issue":"6","key":"10.1016\/j.cageo.2023.105482_bib14","doi-asserted-by":"crossref","first-page":"1","DOI":"10.1007\/s42979-020-00373-y","article-title":"Ensemble of CheXNet and VGG-19 feature extractor with random forest classifier for pediatric pneumonia detection","volume":"1","author":"Habib","year":"2020","journal-title":"SN Comput. Sci."},{"key":"10.1016\/j.cageo.2023.105482_bib15","doi-asserted-by":"crossref","first-page":"305","DOI":"10.3390\/rs15020305","article-title":"A global-information-constrained deep learning network for digital elevation model super-resolution","volume":"15","author":"Han","year":"2023","journal-title":"Rem. Sens."},{"key":"10.1016\/j.cageo.2023.105482_bib16","series-title":"Conference of the 2nd International Conference on Computer Science and Electronics Engineering","article-title":"Comparison of commonly used image interpolation methods","author":"Han","year":"2013"},{"issue":"2","key":"10.1016\/j.cageo.2023.105482_bib17","doi-asserted-by":"crossref","first-page":"131","DOI":"10.1002\/ppp.1774","article-title":"New concepts in geophysical surveying and data interpretation for permafrost terrain","volume":"24","author":"Hauck","year":"2013","journal-title":"Permafr. Periglac. Process."},{"key":"10.1016\/j.cageo.2023.105482_bib18","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","article-title":"Deep residual learning for image recognition","author":"He","year":"2016"},{"key":"10.1016\/j.cageo.2023.105482_bib19","doi-asserted-by":"crossref","first-page":"4806","DOI":"10.1109\/ACCESS.2019.2962617","article-title":"The real-world-weight cross-entropy loss function: modeling the costs of mislabeling","volume":"8","author":"Ho","year":"2019","journal-title":"IEEE Access"},{"key":"10.1016\/j.cageo.2023.105482_bib20","series-title":"ICASSP 2020-2020 IEEE International Conference on Acoustics, Speech and Signal Processing (ICASSP)","first-page":"1055","article-title":"Unet 3+: a full-scale connected unet for medical image segmentation","author":"Huang","year":"2020"},{"key":"10.1016\/j.cageo.2023.105482_bib21","doi-asserted-by":"crossref","first-page":"24","DOI":"10.1016\/j.isprsjprs.2020.12.010","article-title":"Review on convolutional neural networks (CNN) in vegetation remote sensing","volume":"173","author":"Kattenborn","year":"2021","journal-title":"ISPRS J. Photogrammetry Remote Sens."},{"key":"10.1016\/j.cageo.2023.105482_bib22","article-title":"Adam: a method for stochastic optimization","author":"Kingma","year":"2014","journal-title":"arXiv preprint arXiv:1412.6980"},{"issue":"2","key":"10.1016\/j.cageo.2023.105482_bib23","first-page":"129","article-title":"Spatial interpolation methods: a review","volume":"10","author":"Lam","year":"1983","journal-title":"Am. Cartogr."},{"key":"10.1016\/j.cageo.2023.105482_bib24","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","article-title":"Photo-realistic single image super-resolution using a generative adversarial network","author":"Ledig","year":"2017"},{"issue":"3\u20134","key":"10.1016\/j.cageo.2023.105482_bib26","doi-asserted-by":"crossref","first-page":"228","DOI":"10.1016\/j.ecoinf.2010.12.003","article-title":"A review of comparative studies of spatial interpolation methods in environmental sciences: performance and impact factors","volume":"6","author":"Li","year":"2011","journal-title":"Ecol. Inf."},{"issue":"5","key":"10.1016\/j.cageo.2023.105482_bib27","doi-asserted-by":"crossref","first-page":"1166","DOI":"10.3390\/rs14051166","article-title":"Generating terrain data for geomorphological analysis by integrating topographical features and conditional generative adversarial networks","volume":"14","author":"Li","year":"2022","journal-title":"Rem. Sens."},{"issue":"3","key":"10.1016\/j.cageo.2023.105482_bib28","doi-asserted-by":"crossref","first-page":"300","DOI":"10.1007\/s10588-010-9066-2","article-title":"A Bayesian approach to modeling lost person behaviors based on terrain features in wilderness search and rescue","volume":"16","author":"Lin","year":"2010","journal-title":"Comput. Math. Organ. Theor."},{"key":"10.1016\/j.cageo.2023.105482_bib29","series-title":"Proceedings of the IEEE Conference on Computer Vision and Pattern Recognition","article-title":"Fully convolutional networks for semantic segmentation","author":"Long","year":"2015"},{"key":"10.1016\/j.cageo.2023.105482_bib31","first-page":"5670","article-title":"Feature-enhanced deep learning network for digital elevation model super-resolution","volume":"vol. 16","author":"Ma","year":"2023"},{"issue":"8","key":"10.1016\/j.cageo.2023.105482_bib33","doi-asserted-by":"crossref","first-page":"1246","DOI":"10.2113\/gsecongeo.58.8.1246","article-title":"Principles of geostatistics","volume":"58","author":"Matheron","year":"1963","journal-title":"Econ. Geol."},{"issue":"1","key":"10.1016\/j.cageo.2023.105482_bib34","first-page":"1049","article-title":"Cubic spline interpolation","volume":"45","author":"McKinley","year":"1998","journal-title":"Coll. Redwoods"},{"key":"10.1016\/j.cageo.2023.105482_bib35","series-title":"Convergent Outcomes in L2 Acquisition and L1 Loss","first-page":"259","author":"Montrul","year":"2004"},{"key":"10.1016\/j.cageo.2023.105482_bib36","series-title":"Proceedings of the 1968 23rd ACM National Conference","article-title":"A two-dimensional interpolation function for irregularly-spaced data","author":"Shepard","year":"1968"},{"key":"10.1016\/j.cageo.2023.105482_bib37","doi-asserted-by":"crossref","DOI":"10.1016\/j.scitotenv.2021.148497","article-title":"Effects of the interaction among climate, terrain and human activities on biodiversity on the Qinghai-Tibet Plateau","volume":"794","author":"Sun","year":"2021","journal-title":"Sci. Total Environ."},{"issue":"2","key":"10.1016\/j.cageo.2023.105482_bib38","doi-asserted-by":"crossref","first-page":"591","DOI":"10.1007\/s00521-020-04987-4","article-title":"Application of artificial neural network model based on GIS in geological hazard zoning","volume":"33","author":"Tan","year":"2021","journal-title":"Neural Comput. Appl."},{"key":"10.1016\/j.cageo.2023.105482_bib39","series-title":"2019 International Conference on Intelligent Computing and Control Systems (ICCS)","article-title":"A brief review of nearest neighbor algorithm for learning and classification","author":"Taunk","year":"2019"},{"issue":"Suppl. 1","key":"10.1016\/j.cageo.2023.105482_bib40","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":"10.1016\/j.cageo.2023.105482_bib41","series-title":"Ordinary Kriging (Multivariate Geostatistics","first-page":"79","author":"Wackernagel","year":"2003"},{"issue":"1","key":"10.1016\/j.cageo.2023.105482_bib42","doi-asserted-by":"crossref","first-page":"5","DOI":"10.1137\/0902002","article-title":"Spline interpolation and smoothing on the sphere","volume":"2","author":"Wahba","year":"1981","journal-title":"SIAM J. Sci. Stat. Comput."},{"issue":"4","key":"10.1016\/j.cageo.2023.105482_bib43","doi-asserted-by":"crossref","first-page":"588","DOI":"10.1109\/JAS.2017.7510583","article-title":"Generative adversarial networks: introduction and outlook","volume":"4","author":"Wang","year":"2017","journal-title":"IEEE\/CAA J. Autom. Sin."},{"key":"10.1016\/j.cageo.2023.105482_bib44","doi-asserted-by":"crossref","DOI":"10.1016\/j.earscirev.2022.104191","article-title":"Geomorphometry and terrain analysis: data, methods, platforms and applications","author":"Xiong","year":"2022","journal-title":"Earth Sci. Rev."},{"key":"10.1016\/j.cageo.2023.105482_bib45","article-title":"Empirical evaluation of rectified activations in convolutional network","author":"Xu","year":"2015","journal-title":"arXiv preprint arXiv:1505.00853"},{"key":"10.1016\/j.cageo.2023.105482_bib46","series-title":"BigGIS: How Big Data Can Shape Next-Generation GIS. 2014 the Third International Conference on Agro-Geoinformatics","author":"Yue","year":"2014"},{"key":"10.1016\/j.cageo.2023.105482_bib47","doi-asserted-by":"crossref","DOI":"10.1016\/j.gmod.2021.101122","article-title":"Authoring multi-style terrain with global-to-local control","volume":"119","author":"Zhang","year":"2022","journal-title":"Graph. Model."},{"key":"10.1016\/j.cageo.2023.105482_bib48","article-title":"Progress of surveying and mapping science and technology in the information age","author":"Zhang","year":"2021","journal-title":"J. Phys. Conf."},{"issue":"3","key":"10.1016\/j.cageo.2023.105482_bib49","doi-asserted-by":"crossref","DOI":"10.3390\/s22030745","article-title":"Comparison of DEM super-resolution methods based on interpolation and neural networks","volume":"22","author":"Zhang","year":"2022","journal-title":"Sensors"},{"key":"10.1016\/j.cageo.2023.105482_bib50","doi-asserted-by":"crossref","first-page":"143","DOI":"10.1016\/j.isprsjprs.2022.04.028","article-title":"Terrain feature-aware deep learning network for digital elevation model superresolution","volume":"189","author":"Zhang","year":"2022","journal-title":"ISPRS J. Photogrammetry Remote Sens."},{"issue":"16","key":"10.1016\/j.cageo.2023.105482_bib51","doi-asserted-by":"crossref","first-page":"3089","DOI":"10.3390\/rs13163089","article-title":"An enhanced double-filter deep residual neural network for generating super resolution DEMs","volume":"13","author":"Zhou","year":"2021","journal-title":"Rem. Sens."},{"issue":"4","key":"10.1016\/j.cageo.2023.105482_bib52","doi-asserted-by":"crossref","first-page":"735","DOI":"10.1080\/13658816.2019.1599122","article-title":"Spatial interpolation using conditional generative adversarial neural networks","volume":"34","author":"Zhu","year":"2020","journal-title":"Int. J. Geogr. Inf. Sci."}],"container-title":["Computers & Geosciences"],"original-title":[],"language":"en","link":[{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0098300423001863?httpAccept=text\/xml","content-type":"text\/xml","content-version":"vor","intended-application":"text-mining"},{"URL":"https:\/\/api.elsevier.com\/content\/article\/PII:S0098300423001863?httpAccept=text\/plain","content-type":"text\/plain","content-version":"vor","intended-application":"text-mining"}],"deposited":{"date-parts":[[2025,9,25]],"date-time":"2025-09-25T18:36:37Z","timestamp":1758825397000},"score":1,"resource":{"primary":{"URL":"https:\/\/linkinghub.elsevier.com\/retrieve\/pii\/S0098300423001863"}},"subtitle":[],"short-title":[],"issued":{"date-parts":[[2024,1]]},"references-count":49,"alternative-id":["S0098300423001863"],"URL":"https:\/\/doi.org\/10.1016\/j.cageo.2023.105482","relation":{},"ISSN":["0098-3004"],"issn-type":[{"value":"0098-3004","type":"print"}],"subject":[],"published":{"date-parts":[[2024,1]]},"assertion":[{"value":"Elsevier","name":"publisher","label":"This article is maintained by"},{"value":"Intelligent terrain generation considering global information and terrain patterns","name":"articletitle","label":"Article Title"},{"value":"Computers & Geosciences","name":"journaltitle","label":"Journal Title"},{"value":"https:\/\/doi.org\/10.1016\/j.cageo.2023.105482","name":"articlelink","label":"CrossRef DOI link to publisher maintained version"},{"value":"article","name":"content_type","label":"Content Type"},{"value":"\u00a9 2023 Elsevier Ltd. All rights reserved.","name":"copyright","label":"Copyright"}],"article-number":"105482"}}