{"id":"https://openalex.org/W2985357608","doi":"https://doi.org/10.1109/igarss.2019.8899234","title":"Predicting Impervious Land Expansion Using Deep Deconvolutional Neural Networks","display_name":"Predicting Impervious Land Expansion Using Deep Deconvolutional Neural Networks","publication_year":2019,"publication_date":"2019-07-01","ids":{"openalex":"https://openalex.org/W2985357608","doi":"https://doi.org/10.1109/igarss.2019.8899234","mag":"2985357608"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2019.8899234","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8899234","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"article","indexed_in":["crossref"],"open_access":{"is_oa":false,"oa_status":"closed","oa_url":null,"any_repository_has_fulltext":false},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5012692667","display_name":"Pariya Pourmohammadi","orcid":"https://orcid.org/0000-0002-0330-2122"},"institutions":[{"id":"https://openalex.org/I12097938","display_name":"West Virginia University","ror":"https://ror.org/011vxgd24","country_code":"US","type":"education","lineage":["https://openalex.org/I12097938"]}],"countries":["US"],"is_corresponding":true,"raw_author_name":"Pariya Pourmohammadi","raw_affiliation_strings":["Davis College of Agriculture, Natural Resources & Design, West Virginia University"],"affiliations":[{"raw_affiliation_string":"Davis College of Agriculture, Natural Resources & Design, West Virginia University","institution_ids":["https://openalex.org/I12097938"]}]},{"author_position":"middle","author":{"id":"https://openalex.org/A5085141731","display_name":"Donald Adjeroh","orcid":"https://orcid.org/0000-0002-7982-4744"},"institutions":[{"id":"https://openalex.org/I12097938","display_name":"West Virginia University","ror":"https://ror.org/011vxgd24","country_code":"US","type":"education","lineage":["https://openalex.org/I12097938"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Donald Adjeroh","raw_affiliation_strings":["West Virginia University, West Virginia University"],"affiliations":[{"raw_affiliation_string":"West Virginia University, West Virginia University","institution_ids":["https://openalex.org/I12097938"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5061787970","display_name":"Michael P. Strager","orcid":"https://orcid.org/0000-0002-3231-3197"},"institutions":[{"id":"https://openalex.org/I12097938","display_name":"West Virginia University","ror":"https://ror.org/011vxgd24","country_code":"US","type":"education","lineage":["https://openalex.org/I12097938"]}],"countries":["US"],"is_corresponding":false,"raw_author_name":"Michael P. Strager","raw_affiliation_strings":["Davis College of Agriculture, Natural Resources & Design, West Virginia University"],"affiliations":[{"raw_affiliation_string":"Davis College of Agriculture, Natural Resources & Design, West Virginia University","institution_ids":["https://openalex.org/I12097938"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":3,"corresponding_author_ids":["https://openalex.org/A5012692667"],"corresponding_institution_ids":["https://openalex.org/I12097938"],"apc_list":null,"apc_paid":null,"fwci":0.3832,"has_fulltext":false,"cited_by_count":3,"citation_normalized_percentile":{"value":0.64274039,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":89,"max":95},"biblio":{"volume":"9351","issue":null,"first_page":"9855","last_page":"9858"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10226","display_name":"Land Use and Ecosystem Services","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"field":{"id":"https://openalex.org/fields/23","display_name":"Environmental Science"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10226","display_name":"Land Use and Ecosystem Services","score":0.9995999932289124,"subfield":{"id":"https://openalex.org/subfields/2306","display_name":"Global and Planetary Change"},"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/T10111","display_name":"Remote Sensing in Agriculture","score":0.9907000064849854,"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/T11164","display_name":"Remote Sensing and LiDAR Applications","score":0.9866999983787537,"subfield":{"id":"https://openalex.org/subfields/2305","display_name":"Environmental Engineering"},"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/computer-science","display_name":"Computer science","score":0.7193200588226318},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.576174259185791},{"id":"https://openalex.org/keywords/transformation","display_name":"Transformation (genetics)","score":0.5530324578285217},{"id":"https://openalex.org/keywords/focus","display_name":"Focus (optics)","score":0.5522390604019165},{"id":"https://openalex.org/keywords/artificial-neural-network","display_name":"Artificial neural network","score":0.5309849381446838},{"id":"https://openalex.org/keywords/watershed","display_name":"Watershed","score":0.5259552001953125},{"id":"https://openalex.org/keywords/impervious-surface","display_name":"Impervious surface","score":0.4758286774158478},{"id":"https://openalex.org/keywords/scale","display_name":"Scale (ratio)","score":0.4685688316822052},{"id":"https://openalex.org/keywords/deep-learning","display_name":"Deep learning","score":0.46565940976142883},{"id":"https://openalex.org/keywords/population","display_name":"Population","score":0.4548923373222351},{"id":"https://openalex.org/keywords/data-mining","display_name":"Data mining","score":0.453273206949234},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.3720574975013733},{"id":"https://openalex.org/keywords/cartography","display_name":"Cartography","score":0.28582942485809326},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.1634720265865326}],"concepts":[{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.7193200588226318},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.576174259185791},{"id":"https://openalex.org/C204241405","wikidata":"https://www.wikidata.org/wiki/Q461499","display_name":"Transformation (genetics)","level":3,"score":0.5530324578285217},{"id":"https://openalex.org/C192209626","wikidata":"https://www.wikidata.org/wiki/Q190909","display_name":"Focus (optics)","level":2,"score":0.5522390604019165},{"id":"https://openalex.org/C50644808","wikidata":"https://www.wikidata.org/wiki/Q192776","display_name":"Artificial neural network","level":2,"score":0.5309849381446838},{"id":"https://openalex.org/C150547873","wikidata":"https://www.wikidata.org/wiki/Q947851","display_name":"Watershed","level":2,"score":0.5259552001953125},{"id":"https://openalex.org/C2668921","wikidata":"https://www.wikidata.org/wiki/Q1434713","display_name":"Impervious surface","level":2,"score":0.4758286774158478},{"id":"https://openalex.org/C2778755073","wikidata":"https://www.wikidata.org/wiki/Q10858537","display_name":"Scale (ratio)","level":2,"score":0.4685688316822052},{"id":"https://openalex.org/C108583219","wikidata":"https://www.wikidata.org/wiki/Q197536","display_name":"Deep learning","level":2,"score":0.46565940976142883},{"id":"https://openalex.org/C2908647359","wikidata":"https://www.wikidata.org/wiki/Q2625603","display_name":"Population","level":2,"score":0.4548923373222351},{"id":"https://openalex.org/C124101348","wikidata":"https://www.wikidata.org/wiki/Q172491","display_name":"Data mining","level":1,"score":0.453273206949234},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.3720574975013733},{"id":"https://openalex.org/C58640448","wikidata":"https://www.wikidata.org/wiki/Q42515","display_name":"Cartography","level":1,"score":0.28582942485809326},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.1634720265865326},{"id":"https://openalex.org/C86803240","wikidata":"https://www.wikidata.org/wiki/Q420","display_name":"Biology","level":0,"score":0.0},{"id":"https://openalex.org/C18903297","wikidata":"https://www.wikidata.org/wiki/Q7150","display_name":"Ecology","level":1,"score":0.0},{"id":"https://openalex.org/C104317684","wikidata":"https://www.wikidata.org/wiki/Q7187","display_name":"Gene","level":2,"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/C185592680","wikidata":"https://www.wikidata.org/wiki/Q2329","display_name":"Chemistry","level":0,"score":0.0},{"id":"https://openalex.org/C55493867","wikidata":"https://www.wikidata.org/wiki/Q7094","display_name":"Biochemistry","level":1,"score":0.0},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.0},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.0},{"id":"https://openalex.org/C149923435","wikidata":"https://www.wikidata.org/wiki/Q37732","display_name":"Demography","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2019.8899234","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2019.8899234","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2019 - 2019 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"id":"https://metadata.un.org/sdg/15","score":0.4099999964237213,"display_name":"Life in Land"}],"awards":[],"funders":[],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1901129140","https://openalex.org/W1976526581","https://openalex.org/W1996641843","https://openalex.org/W2041588414","https://openalex.org/W2043701535","https://openalex.org/W2047752910","https://openalex.org/W2057204588","https://openalex.org/W2072461811","https://openalex.org/W2135822449","https://openalex.org/W2168765914","https://openalex.org/W2480078828","https://openalex.org/W2488187315","https://openalex.org/W2963881378","https://openalex.org/W6639824700","https://openalex.org/W6680169923","https://openalex.org/W6684770863","https://openalex.org/W6722710385"],"related_works":["https://openalex.org/W2364341326","https://openalex.org/W2757433404","https://openalex.org/W4254235682","https://openalex.org/W2054563345","https://openalex.org/W2520989432","https://openalex.org/W2159637219","https://openalex.org/W3132993209","https://openalex.org/W2089568015","https://openalex.org/W4386353287","https://openalex.org/W4386359901"],"abstract_inverted_index":{"In":[0],"this":[1,142],"research,":[2],"we":[3,61],"propose":[4],"a":[5,28,32,72,104],"method":[6,73],"for":[7],"modeling":[8,99,136],"land":[9,58,78,157],"change":[10],"using":[11,106],"the":[12,49,55,85,100,110,113,118,121,139,149],"idea":[13],"of":[14,44,51,57,77,87,112,123,133,141],"pixel-wise":[15],"semantic":[16],"segmentation":[17],"through":[18,117],"deep":[19,52],"deconvolutional":[20],"neural":[21],"networks.":[22],"This":[23],"analysis":[24],"is":[25,47,115],"done":[26],"on":[27,34],"watershed":[29,105],"scale":[30],"with":[31],"focus":[33],"where":[35,60],"developed":[36],"lands":[37],"are":[38],"predicted":[39],"to":[40,74,84,90,144],"expand.":[41],"The":[42],"novelty":[43],"our":[45],"approach":[46],"in":[48,54,103,156],"application":[50],"learning":[53],"prediction":[56],"transformation,":[59],"integrate":[62],"high":[63],"dimensional":[64],"feature":[65],"classes":[66],"encompassing":[67],"multiple":[68],"variables.":[69],"We":[70],"introduce":[71],"construct":[75],"cubes":[76],"patches":[79],"which":[80],"include":[81],"information":[82],"related":[83],"characteristics":[86],"terrain,":[88],"proximity":[89],"other":[91],"features,":[92],"population,":[93],"geo-political-boundaries,":[94],"and":[95,147,154],"public":[96],"policy.":[97],"After":[98],"development":[101],"expansion":[102],"an":[107,131],"encoder-decoder":[108],"network,":[109],"accuracy":[111,132],"model":[114],"computed":[116],"Area":[119],"Under":[120],"Curve":[122],"Receiver":[124],"Operating":[125],"Characteristics":[126],"(AUC-ROC).":[127],"Model":[128],"performance":[129],"indicates":[130],"80%.":[134],"Future":[135],"should":[137],"consider":[138],"use":[140,158],"technique":[143],"better":[145],"understand":[146],"map":[148],"spatially":[150],"explicit":[151],"landscape":[152],"changes":[153],"aid":[155],"decision":[159],"making.":[160]},"counts_by_year":[{"year":2021,"cited_by_count":2},{"year":2020,"cited_by_count":1}],"updated_date":"2025-11-06T03:46:38.306776","created_date":"2025-10-10T00:00:00"}