{"id":"https://openalex.org/W4307943431","doi":"https://doi.org/10.3390/rs14215425","title":"Machine Learning and Hyperparameters Algorithms for Identifying Groundwater Aflaj Potential Mapping in Semi-Arid Ecosystems Using LiDAR, Sentinel-2, GIS Data, and Analysis","display_name":"Machine Learning and Hyperparameters Algorithms for Identifying Groundwater Aflaj Potential Mapping in Semi-Arid Ecosystems Using LiDAR, Sentinel-2, GIS Data, and Analysis","publication_year":2022,"publication_date":"2022-10-28","ids":{"openalex":"https://openalex.org/W4307943431","doi":"https://doi.org/10.3390/rs14215425"},"language":"en","primary_location":{"id":"doi:10.3390/rs14215425","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14215425","pdf_url":"https://www.mdpi.com/2072-4292/14/21/5425/pdf?version=1667999178","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/2072-4292/14/21/5425/pdf?version=1667999178","any_repository_has_fulltext":true},"authorships":[{"author_position":"first","author":{"id":"https://openalex.org/A5060151464","display_name":"Khalifa M. Al\u2010Kindi","orcid":"https://orcid.org/0000-0001-9107-5566"},"institutions":[{"id":"https://openalex.org/I209803261","display_name":"University of Nizwa","ror":"https://ror.org/01pxe3r04","country_code":"OM","type":"education","lineage":["https://openalex.org/I209803261"]}],"countries":["OM"],"is_corresponding":true,"raw_author_name":"Khalifa M. Al-Kindi","raw_affiliation_strings":["UNESCO Chair of Aflaj Studies, Archaeohydrology, University of Nizwa, Nizwa P.O. Box 33, Oman"],"affiliations":[{"raw_affiliation_string":"UNESCO Chair of Aflaj Studies, Archaeohydrology, University of Nizwa, Nizwa P.O. Box 33, Oman","institution_ids":["https://openalex.org/I209803261"]}]},{"author_position":"last","author":{"id":"https://openalex.org/A5005775373","display_name":"Saeid Janizadeh","orcid":"https://orcid.org/0000-0002-6314-6838"},"institutions":[{"id":"https://openalex.org/I1516879","display_name":"Tarbiat Modares University","ror":"https://ror.org/03mwgfy56","country_code":"IR","type":"education","lineage":["https://openalex.org/I1516879"]}],"countries":["IR"],"is_corresponding":false,"raw_author_name":"Saeid Janizadeh","raw_affiliation_strings":["Department of Watershed Management Engineering and Sciences, Faculty of Natural Resources and Marine Science, Tarbiat Modares University, Tehran 14115-111, Iran"],"affiliations":[{"raw_affiliation_string":"Department of Watershed Management Engineering and Sciences, Faculty of Natural Resources and Marine Science, Tarbiat Modares University, Tehran 14115-111, Iran","institution_ids":["https://openalex.org/I1516879"]}]}],"institutions":[],"countries_distinct_count":2,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5060151464"],"corresponding_institution_ids":["https://openalex.org/I209803261"],"apc_list":{"value":2500,"currency":"CHF","value_usd":2707},"apc_paid":{"value":2500,"currency":"CHF","value_usd":2707},"fwci":2.0773,"has_fulltext":false,"cited_by_count":28,"citation_normalized_percentile":{"value":0.85912176,"is_in_top_1_percent":false,"is_in_top_10_percent":false},"cited_by_percentile_year":{"min":97,"max":100},"biblio":{"volume":"14","issue":"21","first_page":"5425","last_page":"5425"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T12543","display_name":"Groundwater and Watershed Analysis","score":0.9994000196456909,"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"}},"topics":[{"id":"https://openalex.org/T12543","display_name":"Groundwater and Watershed Analysis","score":0.9994000196456909,"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"}},{"id":"https://openalex.org/T10930","display_name":"Flood Risk Assessment and Management","score":0.9933000206947327,"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/T10889","display_name":"Soil erosion and sediment transport","score":0.9767000079154968,"subfield":{"id":"https://openalex.org/subfields/1111","display_name":"Soil Science"},"field":{"id":"https://openalex.org/fields/11","display_name":"Agricultural and Biological Sciences"},"domain":{"id":"https://openalex.org/domains/1","display_name":"Life Sciences"}}],"keywords":[{"id":"https://openalex.org/keywords/support-vector-machine","display_name":"Support vector machine","score":0.620489776134491},{"id":"https://openalex.org/keywords/groundwater","display_name":"Groundwater","score":0.5587841272354126},{"id":"https://openalex.org/keywords/hyperparameter","display_name":"Hyperparameter","score":0.5384791493415833},{"id":"https://openalex.org/keywords/machine-learning","display_name":"Machine learning","score":0.4769146144390106},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.4626738727092743},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.45615142583847046},{"id":"https://openalex.org/keywords/random-forest","display_name":"Random forest","score":0.4128604531288147},{"id":"https://openalex.org/keywords/algorithm","display_name":"Algorithm","score":0.3940686583518982},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.3663683235645294},{"id":"https://openalex.org/keywords/geology","display_name":"Geology","score":0.21357446908950806}],"concepts":[{"id":"https://openalex.org/C12267149","wikidata":"https://www.wikidata.org/wiki/Q282453","display_name":"Support vector machine","level":2,"score":0.620489776134491},{"id":"https://openalex.org/C76177295","wikidata":"https://www.wikidata.org/wiki/Q161598","display_name":"Groundwater","level":2,"score":0.5587841272354126},{"id":"https://openalex.org/C8642999","wikidata":"https://www.wikidata.org/wiki/Q4171168","display_name":"Hyperparameter","level":2,"score":0.5384791493415833},{"id":"https://openalex.org/C119857082","wikidata":"https://www.wikidata.org/wiki/Q2539","display_name":"Machine learning","level":1,"score":0.4769146144390106},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.4626738727092743},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.45615142583847046},{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.4128604531288147},{"id":"https://openalex.org/C11413529","wikidata":"https://www.wikidata.org/wiki/Q8366","display_name":"Algorithm","level":1,"score":0.3940686583518982},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.3663683235645294},{"id":"https://openalex.org/C127313418","wikidata":"https://www.wikidata.org/wiki/Q1069","display_name":"Geology","level":0,"score":0.21357446908950806},{"id":"https://openalex.org/C187320778","wikidata":"https://www.wikidata.org/wiki/Q1349130","display_name":"Geotechnical engineering","level":1,"score":0.0}],"mesh":[],"locations_count":3,"locations":[{"id":"doi:10.3390/rs14215425","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14215425","pdf_url":"https://www.mdpi.com/2072-4292/14/21/5425/pdf?version=1667999178","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:00626a793d814aa9b2b90c5bffcdb736","is_oa":true,"landing_page_url":"https://doaj.org/article/00626a793d814aa9b2b90c5bffcdb736","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","license_id":"https://openalex.org/licenses/cc-by","version":"submittedVersion","is_accepted":false,"is_published":false,"raw_source_name":"Remote Sensing, Vol 14, Iss 21, p 5425 (2022)","raw_type":"article"},{"id":"pmh:oai:mdpi.com:/2072-4292/14/21/5425/","is_oa":true,"landing_page_url":"https://dx.doi.org/10.3390/rs14215425","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; Volume 14; Issue 21; Pages: 5425","raw_type":"Text"}],"best_oa_location":{"id":"doi:10.3390/rs14215425","is_oa":true,"landing_page_url":"https://doi.org/10.3390/rs14215425","pdf_url":"https://www.mdpi.com/2072-4292/14/21/5425/pdf?version=1667999178","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":[{"id":"https://metadata.un.org/sdg/6","score":0.6600000262260437,"display_name":"Clean water and sanitation"}],"awards":[],"funders":[],"has_content":{"pdf":true,"grobid_xml":true},"content_urls":{"pdf":"https://content.openalex.org/works/W4307943431.pdf","grobid_xml":"https://content.openalex.org/works/W4307943431.grobid-xml"},"referenced_works_count":62,"referenced_works":["https://openalex.org/W980991078","https://openalex.org/W1597161500","https://openalex.org/W1950417250","https://openalex.org/W1985288162","https://openalex.org/W1991313106","https://openalex.org/W1994197834","https://openalex.org/W1997191710","https://openalex.org/W2020010421","https://openalex.org/W2046827489","https://openalex.org/W2050545266","https://openalex.org/W2091350393","https://openalex.org/W2097998348","https://openalex.org/W2143853783","https://openalex.org/W2148300238","https://openalex.org/W2245970762","https://openalex.org/W2396951543","https://openalex.org/W2474890513","https://openalex.org/W2592063591","https://openalex.org/W2765259263","https://openalex.org/W2767759878","https://openalex.org/W2788287173","https://openalex.org/W2794916302","https://openalex.org/W2797310831","https://openalex.org/W2885700865","https://openalex.org/W2905470463","https://openalex.org/W2914012905","https://openalex.org/W2915893383","https://openalex.org/W2951213714","https://openalex.org/W2957884258","https://openalex.org/W2967663220","https://openalex.org/W2970023375","https://openalex.org/W2972746663","https://openalex.org/W2980376317","https://openalex.org/W2997037219","https://openalex.org/W3003595390","https://openalex.org/W3008964196","https://openalex.org/W3011694704","https://openalex.org/W3015779580","https://openalex.org/W3023830374","https://openalex.org/W3037492766","https://openalex.org/W3045004532","https://openalex.org/W3099802519","https://openalex.org/W3111588349","https://openalex.org/W3118418198","https://openalex.org/W3122925777","https://openalex.org/W3124590480","https://openalex.org/W3128091358","https://openalex.org/W3130089959","https://openalex.org/W3138381537","https://openalex.org/W3163557518","https://openalex.org/W3166698666","https://openalex.org/W3183160603","https://openalex.org/W3193549939","https://openalex.org/W3198917754","https://openalex.org/W4206624569","https://openalex.org/W4399647672","https://openalex.org/W6673543561","https://openalex.org/W6674385629","https://openalex.org/W6766576792","https://openalex.org/W6772330579","https://openalex.org/W6785668412","https://openalex.org/W6869608176"],"related_works":["https://openalex.org/W4396689146","https://openalex.org/W4386295066","https://openalex.org/W4200112873","https://openalex.org/W4396679425","https://openalex.org/W2955796858","https://openalex.org/W2602382373","https://openalex.org/W3003615511","https://openalex.org/W2004826645","https://openalex.org/W4285827128","https://openalex.org/W3198113463"],"abstract_inverted_index":{"Aflaj":[0],"(plural":[1],"of":[2,18,46,55,89,111,142,155,197,220,231,258],"falaj)":[3],"are":[4],"tunnels":[5],"or":[6],"trenches":[7],"built":[8],"to":[9,15,34,85,108,254,284],"deliver":[10],"groundwater":[11,36,122,191,198,242,260,270],"from":[12,290],"its":[13],"source":[14,277],"the":[16,40,44,59,87,90,140,145,148,159,162,180,201,206,226,232,286],"point":[17,54],"consumption.":[19],"Support":[20],"vector":[21],"machine":[22,29],"(SVM)":[23],"and":[24,68,80,94,97,115,118,135,172,215,228,246,265,274],"extreme":[25],"gradient":[26],"boosting":[27],"(XGB)":[28],"learning":[30],"models":[31,150],"were":[32,83,106,126,205,223],"used":[33,84],"predict":[35],"aflaj":[37,56,123,192,261,287],"potential":[38,124,199],"in":[39,43,144,189,200,225,252],"Nizwa":[41,49],"watershed":[42],"Sultanate":[45],"Oman":[47],"(Oman).":[48],"city":[50],"is":[51,250],"a":[52,152],"focal":[53],"that":[57,179,239],"underlies":[58],"historical":[60],"relationship":[61],"between":[62],"ecology,":[63],"economic":[64],"dynamics,":[65],"agricultural":[66],"systems,":[67],"human":[69],"settlements.":[70],"Three":[71],"hyperparameter":[72,182],"algorithms,":[73],"grid":[74],"search":[75,78],"(GS),":[76],"random":[77],"(RS),":[79],"Bayesian":[81,181],"optimisation,":[82],"optimise":[86],"parameters":[88],"XGB":[91,173,186,207],"model.":[92],"Sentinel-2":[93],"light":[95],"detection":[96],"ranging":[98],"(LiDAR)":[99],"data":[100],"via":[101],"geographical":[102],"information":[103],"systems":[104,256],"(GIS)":[105],"employed":[107],"derive":[109],"variables":[110],"land":[112],"use/land":[113],"cover,":[114],"hydrological,":[116],"topographical,":[117],"geological":[119],"factors.":[120],"The":[121,175,194,236],"maps":[125],"categorised":[127],"into":[128],"five":[129],"classes:":[130],"deficient,":[131],"low,":[132],"moderate,":[133],"high,":[134],"very":[136,202],"high.":[137],"Based":[138],"on":[139,158,263],"evaluation":[141],"accuracy":[143,156],"training":[146],"stage,":[147],"following":[149],"showed":[151,178],"high":[153,203],"level":[154],"based":[157,262],"area":[160],"under":[161],"curve:":[163],"Bayesian-XGB":[164,216],"(0.99),":[165],"GS-XGB":[166,211],"(0.97),":[167],"RS-XGB":[168,213],"(0.96),":[169,171],"SVM":[170,209],"(0.93).":[174],"validation":[176],"results":[177],"algorithm":[183],"significantly":[184],"increased":[185],"model":[187],"efficiency":[188],"modelling":[190],"potential.":[193],"highest":[195],"percentages":[196],"class":[204],"(10%),":[208],"(8%),":[210],"(6%),":[212,214],"(6%)":[217],"models.":[218],"Most":[219],"these":[221],"areas":[222],"located":[224],"central":[227],"northeast":[229],"parts":[230],"case":[233],"study":[234,237],"area.":[235],"concluded":[238],"evaluating":[240],"existing":[241],"datasets,":[243],"facilities,":[244],"current,":[245],"future":[247],"spatial":[248],"datasets":[249],"critical":[251],"order":[253],"design":[255],"capable":[257],"mapping":[259],"geospatial":[264],"ML":[266],"techniques.":[267],"In":[268],"turn,":[269],"protection":[271],"service":[272],"projects":[273],"integrated":[275],"water":[276],"management":[278],"(IWSM)":[279],"programs":[280],"will":[281],"be":[282],"able":[283],"protect":[285],"irrigation":[288],"system":[289],"threats":[291],"by":[292],"implementing":[293],"timely":[294],"preventative":[295],"measures.":[296]},"counts_by_year":[{"year":2026,"cited_by_count":4},{"year":2025,"cited_by_count":11},{"year":2024,"cited_by_count":9},{"year":2023,"cited_by_count":4}],"updated_date":"2026-04-16T08:26:57.006410","created_date":"2025-10-10T00:00:00"}