{"id":"https://openalex.org/W3203412372","doi":"https://doi.org/10.3390/rs13193893","title":"Improving Estimates of Natural Resources Using Model-Based Estimators: Impacts of Sample Design, Estimation Technique, and Strengths of Association","display_name":"Improving Estimates of Natural Resources Using Model-Based Estimators: Impacts of Sample Design, Estimation Technique, and Strengths of Association","publication_year":2021,"publication_date":"2021-09-29","ids":{"openalex":"https://openalex.org/W3203412372","doi":"https://doi.org/10.3390/rs13193893","mag":"3203412372"},"language":"en","primary_location":{"id":"doi:10.3390/rs13193893","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs13193893","pdf_url":"https://www.mdpi.com/2072-4292/13/19/3893/pdf?version=1632901130","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"type":"article","indexed_in":["crossref","doaj"],"open_access":{"is_oa":true,"oa_status":"gold","oa_url":"https://www.mdpi.com/2072-4292/13/19/3893/pdf?version=1632901130","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5036241282","display_name":"John Hogland","orcid":"https://orcid.org/0000-0003-2676-6277"},"institutions":[{"id":"https://openalex.org/I1313416372","display_name":"US Forest Service","ror":"https://ror.org/03zmjc935","country_code":"US","type":"government","lineage":["https://openalex.org/I1313416372","https://openalex.org/I1336096307"]},{"id":"https://openalex.org/I4210140135","display_name":"Rocky Mountain Research Station","ror":"https://ror.org/04347cr60","country_code":"US","type":"government","lineage":["https://openalex.org/I1313416372","https://openalex.org/I1336096307","https://openalex.org/I4210140135"]},{"id":"https://openalex.org/I4210156316","display_name":"Rocky Mountain Research (United States)","ror":"https://ror.org/05f1fs902","country_code":"US","type":"company","lineage":["https://openalex.org/I4210156316"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"John Hogland","raw_affiliation_strings":["Rocky Mountain Research Station, U.S. Forest Service, Missoula, MT 59801, USA"],"affiliations":[{"raw_affiliation_string":"Rocky Mountain Research Station, U.S. Forest Service, Missoula, MT 59801, USA","institution_ids":["https://openalex.org/I4210156316","https://openalex.org/I1313416372","https://openalex.org/I4210140135"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5052077430","display_name":"David L.R. Affleck","orcid":"https://orcid.org/0000-0001-8370-7631"},"institutions":[{"id":"https://openalex.org/I6750721","display_name":"University of Montana","ror":"https://ror.org/0078xmk34","country_code":"US","type":"education","lineage":["https://openalex.org/I6750721"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"David L. R. Affleck","raw_affiliation_strings":["W.A. Franke College of Forestry and Conservation, University of Montana, Missoula, MT 59812, USA"],"affiliations":[{"raw_affiliation_string":"W.A. Franke College of Forestry and Conservation, University of Montana, Missoula, MT 59812, USA","institution_ids":["https://openalex.org/I6750721"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5036241282"],"corresponding_institution_ids":["https://openalex.org/I1313416372","https://openalex.org/I4210140135","https://openalex.org/I4210156316"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":0.0,"has_fulltext":true,"cited_by_count":0,"citation_normalized_percentile":{"value":0.16647069,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":null,"biblio":{"volume":"13","issue":"19","first_page":"3893","last_page":"3893"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10841","display_name":"Economic and Environmental Valuation","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},"topics":[{"id":"https://openalex.org/T10841","display_name":"Economic and Environmental Valuation","score":0.9945999979972839,"subfield":{"id":"https://openalex.org/subfields/2002","display_name":"Economics and Econometrics"},"field":{"id":"https://openalex.org/fields/20","display_name":"Economics, Econometrics and Finance"},"domain":{"id":"https://openalex.org/domains/2","display_name":"Social Sciences"}},{"id":"https://openalex.org/T13388","display_name":"Rangeland and Wildlife Management","score":0.9886999726295471,"subfield":{"id":"https://openalex.org/subfields/2303","display_name":"Ecology"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},{"id":"https://openalex.org/T10895","display_name":"Species Distribution and Climate Change","score":0.9842000007629395,"subfield":{"id":"https://openalex.org/subfields/2302","display_name":"Ecological Modeling"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/estimator","display_name":"Estimator","score":0.7534452676773071},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.6112271547317505},{"id":"https://openalex.org/keywords/inference","display_name":"Inference","score":0.5834833383560181},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.5283071994781494},{"id":"https://openalex.org/keywords/probabilistic-logic","display_name":"Probabilistic logic","score":0.5252109169960022},{"id":"https://openalex.org/keywords/sample","display_name":"Sample (material)","score":0.5076769590377808},{"id":"https://openalex.org/keywords/sampling-design","display_name":"Sampling design","score":0.46596482396125793},{"id":"https://openalex.org/keywords/statistics","display_name":"Statistics","score":0.4546109437942505},{"id":"https://openalex.org/keywords/sampling","display_name":"Sampling (signal processing)","score":0.4465835690498352},{"id":"https://openalex.org/keywords/statistical-inference","display_name":"Statistical inference","score":0.444854199886322},{"id":"https://openalex.org/keywords/econometrics","display_name":"Econometrics","score":0.4336034059524536},{"id":"https://openalex.org/keywords/statistical-model","display_name":"Statistical model","score":0.42792707681655884},{"id":"https://openalex.org/keywords/estimation","display_name":"Estimation","score":0.4274739921092987},{"id":"https://openalex.org/keywords/sample-size-determination","display_name":"Sample size determination","score":0.4161217510700226},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.347744345664978},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.27957719564437866},{"id":"https://openalex.org/keywords/mathematics","display_name":"Mathematics","score":0.24939456582069397},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.2129000723361969},{"id":"https://openalex.org/keywords/engineering","display_name":"Engineering","score":0.10120770335197449}],"concepts":[{"id":"https://openalex.org/C185429906","wikidata":"https://www.wikidata.org/wiki/Q1130160","display_name":"Estimator","level":2,"score":0.7534452676773071},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.6112271547317505},{"id":"https://openalex.org/C2776214188","wikidata":"https://www.wikidata.org/wiki/Q408386","display_name":"Inference","level":2,"score":0.5834833383560181},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.5283071994781494},{"id":"https://openalex.org/C49937458","wikidata":"https://www.wikidata.org/wiki/Q2599292","display_name":"Probabilistic logic","level":2,"score":0.5252109169960022},{"id":"https://openalex.org/C198531522","wikidata":"https://www.wikidata.org/wiki/Q485146","display_name":"Sample (material)","level":2,"score":0.5076769590377808},{"id":"https://openalex.org/C75373757","wikidata":"https://www.wikidata.org/wiki/Q7410160","display_name":"Sampling design","level":3,"score":0.46596482396125793},{"id":"https://openalex.org/C105795698","wikidata":"https://www.wikidata.org/wiki/Q12483","display_name":"Statistics","level":1,"score":0.4546109437942505},{"id":"https://openalex.org/C140779682","wikidata":"https://www.wikidata.org/wiki/Q210868","display_name":"Sampling (signal processing)","level":3,"score":0.4465835690498352},{"id":"https://openalex.org/C134261354","wikidata":"https://www.wikidata.org/wiki/Q938438","display_name":"Statistical inference","level":2,"score":0.444854199886322},{"id":"https://openalex.org/C149782125","wikidata":"https://www.wikidata.org/wiki/Q160039","display_name":"Econometrics","level":1,"score":0.4336034059524536},{"id":"https://openalex.org/C114289077","wikidata":"https://www.wikidata.org/wiki/Q3284399","display_name":"Statistical model","level":2,"score":0.42792707681655884},{"id":"https://openalex.org/C96250715","wikidata":"https://www.wikidata.org/wiki/Q965330","display_name":"Estimation","level":2,"score":0.4274739921092987},{"id":"https://openalex.org/C129848803","wikidata":"https://www.wikidata.org/wiki/Q2564360","display_name":"Sample size determination","level":2,"score":0.4161217510700226},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.347744345664978},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.27957719564437866},{"id":"https://openalex.org/C33923547","wikidata":"https://www.wikidata.org/wiki/Q395","display_name":"Mathematics","level":0,"score":0.24939456582069397},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.2129000723361969},{"id":"https://openalex.org/C127413603","wikidata":"https://www.wikidata.org/wiki/Q11023","display_name":"Engineering","level":0,"score":0.10120770335197449},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0},{"id":"https://openalex.org/C43617362","wikidata":"https://www.wikidata.org/wiki/Q170050","display_name":"Chromatography","level":1,"score":0.0},{"id":"https://openalex.org/C144024400","wikidata":"https://www.wikidata.org/wiki/Q21201","display_name":"Sociology","level":0,"score":0.0},{"id":"https://openalex.org/C106131492","wikidata":"https://www.wikidata.org/wiki/Q3072260","display_name":"Filter (signal processing)","level":2,"score":0.0},{"id":"https://openalex.org/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C201995342","wikidata":"https://www.wikidata.org/wiki/Q682496","display_name":"Systems engineering","level":1,"score":0.0},{"id":"https://openalex.org/C31972630","wikidata":"https://www.wikidata.org/wiki/Q844240","display_name":"Computer vision","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs13193893","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs13193893","pdf_url":"https://www.mdpi.com/2072-4292/13/19/3893/pdf?version=1632901130","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},{"id":"pmh:oai:doaj.org/article:2acd91ca21ac4be98c45df8fa54d051b","is_oa":true,"landing_page_url":"https://doaj.org/article/2acd91ca21ac4be98c45df8fa54d051b","pdf_url":null,"source":{"id":"https://openalex.org/S112646816","display_name":"SHILAP Revista de lepidopterolog\u00eda","issn_l":"0300-5267","issn":["0300-5267","2340-4078"],"is_oa":true,"is_in_doaj":true,"is_core":false,"host_organization":null,"host_organization_name":null,"host_organization_lineage":[],"host_organization_lineage_names":[],"type":"journal"},"license":"cc-by-sa","license_id":"https://openalex.org/licenses/cc-by-sa","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 13, Iss 19, p 3893 (2021)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/13/19/3893/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs13193893","pdf_url":null,"source":{"id":"https://openalex.org/S4306400947","display_name":"MDPI (MDPI AG)","issn_l":null,"issn":null,"is_oa":true,"is_in_doaj":false,"is_core":false,"host_organization":"https://openalex.org/I4210097602","host_organization_name":"Multidisciplinary Digital Publishing Institute (Switzerland)","host_organization_lineage":["https://openalex.org/I4210097602"],"host_organization_lineage_names":[],"type":"repository"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs13193893","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs13193893","pdf_url":"https://www.mdpi.com/2072-4292/13/19/3893/pdf?version=1632901130","source":{"id":"https://openalex.org/S43295729","display_name":"Remote Sensing","issn_l":"2072-4292","issn":["2072-4292"],"is_oa":true,"is_in_doaj":true,"is_core":true,"host_organization":"https://openalex.org/P4310310987","host_organization_name":"Multidisciplinary Digital Publishing Institute","host_organization_lineage":["https://openalex.org/P4310310987"],"host_organization_lineage_names":["Multidisciplinary Digital Publishing Institute"],"type":"journal"},"license":"cc-by","license_id":"https://openalex.org/licenses/cc-by","version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"Remote Sensing","raw_type":"journal-article"},"sustainable_development_goals":[],"awards":[{"id":"https://openalex.org/G7163481259","display_name":null,"funder_award_id":"17-IA-11083150-001","funder_id":"https://openalex.org/F4320314089","funder_display_name":"Gulf Coast Ecosystem Restoration Council"},{"id":"https://openalex.org/G7674315537","display_name":null,"funder_award_id":"17-IA-11083150-001","funder_id":"https://openalex.org/F4320306114","funder_display_name":"U.S. Department of Agriculture"},{"id":"https://openalex.org/G7718812893","display_name":null,"funder_award_id":"State","funder_id":"https://openalex.org/F4320332478","funder_display_name":"U.S. Forest Service"}],"funders":[{"id":"https://openalex.org/F4320306114","display_name":"U.S. Department of Agriculture","ror":"https://ror.org/01na82s61"},{"id":"https://openalex.org/F4320314089","display_name":"Gulf Coast Ecosystem Restoration Council","ror":null},{"id":"https://openalex.org/F4320332478","display_name":"U.S. Forest Service","ror":"https://ror.org/03zmjc935"},{"id":"https://openalex.org/F4320337818","display_name":"Rocky Mountain Research Station","ror":"https://ror.org/04347cr60"}],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W3203412372.pdf","grobid_xml":"https://content.openalex.org/works/W3203412372.grobid-xml"},"referenced_works_count":44,"referenced_works":["https://openalex.org/W273955616","https://openalex.org/W1513618424","https://openalex.org/W1989314352","https://openalex.org/W1998724987","https://openalex.org/W2003034323","https://openalex.org/W2010430502","https://openalex.org/W2024968541","https://openalex.org/W2030225528","https://openalex.org/W2033003748","https://openalex.org/W2037825289","https://openalex.org/W2052611179","https://openalex.org/W2065040528","https://openalex.org/W2080439372","https://openalex.org/W2089564362","https://openalex.org/W2100805904","https://openalex.org/W2103043899","https://openalex.org/W2103884260","https://openalex.org/W2109758583","https://openalex.org/W2119160928","https://openalex.org/W2137155271","https://openalex.org/W2141120444","https://openalex.org/W2167827350","https://openalex.org/W2489398676","https://openalex.org/W2536753532","https://openalex.org/W2612036486","https://openalex.org/W2613889334","https://openalex.org/W2616917210","https://openalex.org/W2736100037","https://openalex.org/W2771841295","https://openalex.org/W2796172891","https://openalex.org/W2885372267","https://openalex.org/W2889784734","https://openalex.org/W2911964244","https://openalex.org/W2916265849","https://openalex.org/W2964258221","https://openalex.org/W2964635321","https://openalex.org/W2965151408","https://openalex.org/W2990090364","https://openalex.org/W3015798368","https://openalex.org/W3195147183","https://openalex.org/W4240294902","https://openalex.org/W6610017368","https://openalex.org/W6728688930","https://openalex.org/W6759220978"],"related_works":["https://openalex.org/W137830373","https://openalex.org/W3000984192","https://openalex.org/W2103073163","https://openalex.org/W4286952477","https://openalex.org/W4321348134","https://openalex.org/W2795206833","https://openalex.org/W3183730129","https://openalex.org/W2125401957","https://openalex.org/W2970045733","https://openalex.org/W3035045542"],"abstract_inverted_index":{"Natural":[0],"resource":[1],"managers":[2],"need":[3],"accurate":[4],"depictions":[5],"of":[6,60,127,168,185,192],"existing":[7],"resources":[8,18],"to":[9,16,33,70,102,109],"make":[10],"informed":[11],"decisions.":[12],"The":[13,149],"classical":[14],"approach":[15],"describing":[17],"for":[19,45,139],"a":[20,24,80,110,218],"given":[21,81,111],"area":[22],"in":[23,195,200],"quantitative":[25],"manner":[26],"uses":[27],"probabilistic":[28,38,219],"sampling":[29],"and":[30,65,89,120,130,135,145,159,170,224],"design-based":[31,46,115,208],"inference":[32,76],"estimate":[34],"population":[35,112,128,169,186],"parameters.":[36],"While":[37,73],"designs":[39,54,142],"are":[40,222],"accepted":[41],"as":[42,118],"being":[43],"necessary":[44],"inference,":[47],"many":[48],"recent":[49],"studies":[50],"have":[51,66],"adopted":[52],"non-probabilistic":[53],"that":[55,79,143,152,214,221],"do":[56],"not":[57],"include":[58],"elements":[59],"random":[61],"selection":[62],"or":[63],"balance":[64,119,144,178],"relied":[67],"on":[68],"models":[69,105],"justify":[71],"inferences.":[72],"common,":[74],"model-based":[75,137,153,183,205],"alone":[77],"assumes":[78],"model":[82],"accurately":[83],"depicts":[84],"the":[85,166],"relationship":[86],"between":[87],"response":[88],"predictors":[90],"across":[91,161,226],"all":[92,196],"populations.":[93],"Within":[94],"complex":[95],"systems,":[96],"this":[97],"assumption":[98],"can":[99,106],"be":[100,107],"difficult":[101],"justify.":[103],"Alternatively,":[104],"trained":[108],"by":[113],"adopting":[114],"principles":[116],"such":[117],"spread.":[121],"Through":[122],"simulation,":[123],"we":[124],"compare":[125],"estimates":[126,184,191],"totals":[129,187],"pixel-level":[131],"values":[132],"using":[133,204],"linear":[134],"nonlinear":[136],"estimators":[138,154],"multiple":[140],"sample":[141,147],"spread":[146,158,223],"units.":[148],"findings":[150],"indicate":[151],"derived":[155],"from":[156,217],"samples":[157,175,215],"balanced":[160,225],"predictor":[162,227],"variable":[163,228],"space":[164],"reduce":[165],"variability":[167],"unit-level":[171],"estimators.":[172],"Moreover,":[173],"if":[174],"achieve":[176],"approximate":[177],"over":[179,207],"feature":[180],"space,":[181,229],"then":[182],"approached":[188],"simple":[189],"expansion-based":[190],"totals.":[193],"Finally,":[194],"comparisons":[197],"made,":[198],"improvements":[199],"estimation":[201,206,209,231],"were":[202],"achieved":[203],"alone.":[210],"Our":[211],"simulations":[212],"suggest":[213],"drawn":[216],"design,":[220],"improve":[230],"accuracy.":[232]},"counts_by_year":[],"updated_date":"2026-04-10T15:06:20.359241","created_date":"2025-10-10T00:00:00"}
