{"id":"https://openalex.org/W2113901002","doi":"https://doi.org/10.14358/pers.73.12.1367","title":"A Theoretical Approach to Modeling the Accuracy Assessment of Digital Elevation Models","display_name":"A Theoretical Approach to Modeling the Accuracy Assessment of Digital Elevation Models","publication_year":2007,"publication_date":"2007-12-01","ids":{"openalex":"https://openalex.org/W2113901002","doi":"https://doi.org/10.14358/pers.73.12.1367","mag":"2113901002"},"language":"en","primary_location":{"id":"doi:10.14358/pers.73.12.1367","doi":"https://doi.org/10.14358/pers.73.12.1367","is_oa":true,"landing_page_url":"https://doi.org/10.14358/pers.73.12.1367","pdf_url":null,"source":{"id":"https://openalex.org/S99003644","display_name":"Photogrammetric Engineering & Remote Sensing","issn_l":"0099-1112","issn":["0099-1112","2374-8079"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","jufo-1","norway-1","poland-140","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4320800734","host_organization_name":"American Society for Photogrammetry and Remote Sensing","host_organization_lineage":["https://openalex.org/P4320800734"],"host_organization_lineage_names":["American Society for Photogrammetry and Remote Sensing"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Photogrammetric Engineering & Remote Sensing","raw_type":"journal-article"},"volume":null,"type":"article","is_traditional":true,"indexed_in":["crossref"],"open_access":{"is_oa":true,"oa_status":"hybrid","oa_url":"https://doi.org/10.14358/pers.73.12.1367","any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5073721457","display_name":"Fernando Jos\u00e9 Aguilar","orcid":"https://orcid.org/0000-0002-5144-6411","observed_orcids":["https://orcid.org/0000-0002-5144-6411"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Fernando J. Aguilar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"middle","author":{"id":"https://openalex.org/A5052861689","display_name":"Francisco Ag\u00fcera-Vega","orcid":"https://orcid.org/0000-0003-0709-3388","observed_orcids":["https://orcid.org/0000-0003-0709-3388"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Francisco Ag\u00fcera","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]},{"author_position":"last","author":{"id":"https://openalex.org/A5037562936","display_name":"Manuel Angel Aguilar","orcid":"https://orcid.org/0000-0003-0404-9875","observed_orcids":["https://orcid.org/0000-0003-0404-9875"]},"institutions":[],"countries":[],"is_corresponding":false,"raw_author_name":"Manuel A. Aguilar","raw_affiliation_strings":[],"raw_orcid":null,"affiliations":[]}],"institutions":[],"countries_distinct_count":0,"institutions_distinct_count":0,"corresponding_author_ids":[],"corresponding_institution_ids":[],"apc_list":null,"apc_paid":null,"fwci":2.2711,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.89543529,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":87,"max":97},"biblio":{"volume":"73","issue":"12","first_page":"1367","last_page":"1379"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12983","display_name":"Satellite Image Processing and Photogrammetry","score":0.9721999764442444,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T12983","display_name":"Satellite Image Processing and Photogrammetry","score":0.9721999764442444,"subfield":{"id":"https://openalex.org/subfields/1707","display_name":"Computer Vision and Pattern Recognition"},"field":{"id":"https://openalex.org/fields/17","display_name":"Computer Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T13511","display_name":"Geodetic Measurements and Engineering Structures","score":0.020099999383091927,"subfield":{"id":"https://openalex.org/subfields/2205","display_name":"Civil and Structural Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T11211","display_name":"3D Surveying and Cultural Heritage","score":0.0031999999191612005,"subfield":{"id":"https://openalex.org/subfields/1907","display_name":"Geology"},"field":{"id":"https://openalex.org/fields/19","display_name":"Earth and Planetary Sciences"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/root-mean-square-error","display_name":"root mean square error","score":0.7450000047683716},{"id":"https://openalex.org/keywords/residual-distribution","display_name":"residual distribution","score":0.5709999799728394},{"id":"https://openalex.org/keywords/non-normal-residuals","display_name":"non-normal residuals","score":0.6320000290870667},{"id":"https://openalex.org/keywords/spatial-autocorrelation","display_name":"spatial autocorrelation","score":0.8569999933242798},{"id":"https://openalex.org/keywords/skewness-and-kurtosis","display_name":"skewness and kurtosis","score":0.7279999852180481},{"id":"https://openalex.org/keywords/multiquadric-radial-basis-functions","display_name":"multiquadric radial basis functions","score":0.8169999718666077},{"id":"https://openalex.org/keywords/inverse-distance-weighting","display_name":"inverse distance weighting","score":0.9850000143051147},{"id":"https://openalex.org/keywords/monte-carlo-simulation","display_name":"Monte Carlo simulation","score":0.6959999799728394},{"id":"https://openalex.org/keywords/terrain-morphology","display_name":"terrain morphology","score":0.5479999780654907},{"id":"https://openalex.org/keywords/stereophotogrammetry","display_name":"stereophotogrammetry","score":0.6880000233650208}],"concepts":[{"id":"https://openalex.org/C181843262","wikidata":"https://www.wikidata.org/wiki/Q640492","display_name":"Digital elevation model","level":2,"score":0.7076886892318726},{"id":"https://openalex.org/C37054046","wikidata":"https://www.wikidata.org/wiki/Q641888","display_name":"Elevation (ballistics)","level":2,"score":0.5853814482688904},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.5198191404342651},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.47772714495658875},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.4745888411998749},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.3640367388725281},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.1763717532157898},{"id":"https://openalex.org/C2524010","wikidata":"https://www.wikidata.org/wiki/Q8087","display_name":"Geometry","level":1,"score":0.06988239288330078}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.14358/pers.73.12.1367","doi":"https://doi.org/10.14358/pers.73.12.1367","is_oa":true,"landing_page_url":"https://doi.org/10.14358/pers.73.12.1367","pdf_url":null,"source":{"id":"https://openalex.org/S99003644","display_name":"Photogrammetric Engineering & Remote Sensing","issn_l":"0099-1112","issn":["0099-1112","2374-8079"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","jufo-1","norway-1","poland-140","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4320800734","host_organization_name":"American Society for Photogrammetry and Remote Sensing","host_organization_lineage":["https://openalex.org/P4320800734"],"host_organization_lineage_names":["American Society for Photogrammetry and Remote Sensing"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Photogrammetric Engineering & Remote Sensing","raw_type":"journal-article"}],"best_oa_location":{"id":"doi:10.14358/pers.73.12.1367","doi":"https://doi.org/10.14358/pers.73.12.1367","is_oa":true,"landing_page_url":"https://doi.org/10.14358/pers.73.12.1367","pdf_url":null,"source":{"id":"https://openalex.org/S99003644","display_name":"Photogrammetric Engineering & Remote Sensing","issn_l":"0099-1112","issn":["0099-1112","2374-8079"],"is_oa":false,"is_in_doaj":false,"is_core":true,"listed_in":["cwts-core","dongbi-c","jufo-1","norway-1","poland-140","russia-white-list-2","vabb-shw"],"host_organization":"https://openalex.org/P4320800734","host_organization_name":"American Society for Photogrammetry and Remote Sensing","host_organization_lineage":["https://openalex.org/P4320800734"],"host_organization_lineage_names":["American Society for Photogrammetry and Remote Sensing"],"type":"journal"},"license":"cc-by-nc-nd","license_id":"https://openalex.org/licenses/cc-by-nc-nd","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Photogrammetric Engineering & Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"study_designs":[],"awards":[],"funders":[],"has_content":{"grobid_xml":false,"pdf":false},"content_urls":null,"referenced_works_count":19,"referenced_works":["https://openalex.org/W29771957","https://openalex.org/W142046526","https://openalex.org/W143850130","https://openalex.org/W1571356903","https://openalex.org/W1580513099","https://openalex.org/W1600552940","https://openalex.org/W1972754657","https://openalex.org/W1978955804","https://openalex.org/W1988848536","https://openalex.org/W2021211360","https://openalex.org/W2041617254","https://openalex.org/W2087018060","https://openalex.org/W2120612314","https://openalex.org/W2152554462","https://openalex.org/W2154167027","https://openalex.org/W2225770107","https://openalex.org/W2305802177","https://openalex.org/W2494630704","https://openalex.org/W2610661438"],"related_works":["https://openalex.org/W2146378450","https://openalex.org/W2390473960","https://openalex.org/W1978955804","https://openalex.org/W6979710480","https://openalex.org/W2358259289","https://openalex.org/W7100124259","https://openalex.org/W2386132658","https://openalex.org/W2153759474","https://openalex.org/W2063943115","https://openalex.org/W1988848536"],"abstract_inverted_index":{"In":[0,163],"this":[1,164],"paper,":[2],"a":[3,19,171,243,287],"theoretical":[4,63,227,271],"analysis":[5],"is":[6,50,290],"presented":[7],"of":[8,11,18,39,57,72,80,89,124,130,138,142,191,201,259,281],"the":[9,15,37,43,55,58,70,73,78,86,121,131,136,139,187,234,247,252,256,278,282,285],"degree":[10],"correctness":[12],"to":[13,53,85,156,186,218],"which":[14,103,289],"accuracy":[16,44,60,75,144],"figures":[17,76],"grid":[20,224],"Digital":[21],"Elevation":[22],"Model":[23],"(DEM)":[24],"have":[25,65,203],"been":[26,66,204],"estimated,":[27],"measured":[28],"as":[29,54,266],"Root":[30],"Mean":[31],"Square":[32],"Error":[33],"(RMSE)":[34],"depending":[35],"on":[36],"number":[38,79],"checkpoints":[40,81],"used":[41],"in":[42,102,128,135,293],"assessment":[45],"process.":[46],"The":[47,226,239,269],"latter":[48],"concept":[49],"sometimes":[51],"referred":[52],"Reliability":[56],"DEM":[59,74],"tests.":[61],"Two":[62,198],"models":[64,241,272],"developed":[67],"for":[68,246,251,276],"estimating":[69],"reliability":[71],"using":[77,151,206,233],"and":[82,94,115,134,212,255],"parameters":[83],"related":[84],"statistical":[87],"distribution":[88,125,280],"residuals":[90,104],"(mean,":[91],"variance,":[92],"skewness,":[93],"standardized":[95],"kurtosis).":[96],"A":[97],"general":[98],"case":[99],"was":[100],"considered":[101],"might":[105],"be":[106],"weakly":[107],"correlated":[108],"(local":[109],"spatial":[110],"autocorrelation)":[111],"with":[112,170],"non-zero":[113],"mean":[114,267],"non-normal":[116],"distribution.":[117],"Thus,":[118],"we":[119],"avoided":[120],"\u201cstrong":[122],"assumption\u201d":[123],"normality":[126],"accepted":[127],"some":[129],"previous":[132],"works":[133],"majority":[137],"current":[140],"standards":[141],"positional":[143],"control":[145],"methods.":[146],"Sampled":[147],"data":[148,250],"were":[149,168,230],"collected":[150],"digital":[152],"photogrammetric":[153],"methods":[154],"applied":[155],"large":[157],"scale":[158],"stereo":[159],"imagery":[160],"(1:5":[161],"000).":[162],"way,":[165],"seven":[166,253],"morphologies":[167,254],"sampled":[169],"2":[172,175,263],"m":[173,176],"by":[174],"sampling":[177],"interval,":[178],"ranging":[179],"from":[180,222],"flat":[181],"(3":[182],"percent":[183,195],"average":[184,196],"slope)":[185],"highly":[188],"rugged":[189],"terrain":[190],"marble":[192],"quarries":[193],"(82":[194],"slope).":[197],"local":[199],"schemes":[200,258],"interpolation":[202,260],"employed,":[205],"Multiquadric":[207],"Radial":[208],"Basis":[209],"Functions":[210],"(MRBF)":[211],"Inverse":[213],"Distance":[214],"Weighted":[215],"(IDW)":[216],"interpolators,":[217],"generate":[219],"interpolated":[220],"surfaces":[221],"high-resolution":[223],"DEMs.":[225],"results":[228],"obtained":[229],"experimentally":[231],"validated":[232],"Monte":[235],"Carlo":[236],"simulation":[237],"method.":[238],"proposed":[240,270],"provided":[242],"good":[244],"fit":[245],"raw":[248],"simulated":[249],"two":[257],"tested":[261],"(r":[262],".":[264],"0.96":[265],"value).":[268],"performed":[273],"very":[274,291],"well":[275],"modeling":[277],"non-gaussian":[279],"errors":[283],"at":[284],"checkpoints,":[286],"property":[288],"common":[292],"geographically":[294],"distributed":[295],"data.":[296]},"counts_by_year":[{"year":2025,"cited_by_count":3},{"year":2023,"cited_by_count":1},{"year":2022,"cited_by_count":1},{"year":2021,"cited_by_count":1},{"year":2020,"cited_by_count":2},{"year":2019,"cited_by_count":2},{"year":2018,"cited_by_count":1},{"year":2017,"cited_by_count":1},{"year":2016,"cited_by_count":1},{"year":2015,"cited_by_count":3},{"year":2014,"cited_by_count":2},{"year":2013,"cited_by_count":1},{"year":2012,"cited_by_count":1}],"updated_date":"2026-10-16T09:59:22.235173","created_date":"2016-06-24T00:00:00"}