{"id":"https://openalex.org/W2158549858","doi":"https://doi.org/10.1109/igarss.2008.4779073","title":"Forest Spatial Structure Enhancing Non-Gaussian Texture in Airborne L-Band Polsar Images","display_name":"Forest Spatial Structure Enhancing Non-Gaussian Texture in Airborne L-Band Polsar Images","publication_year":2008,"publication_date":"2008-01-01","ids":{"openalex":"https://openalex.org/W2158549858","doi":"https://doi.org/10.1109/igarss.2008.4779073","mag":"2158549858"},"language":"en","primary_location":{"id":"doi:10.1109/igarss.2008.4779073","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2008.4779073","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"},"type":"conference-paper","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/A5103911317","display_name":"Seisuke Fukuda","orcid":null},"institutions":[{"id":"https://openalex.org/I2800865746","display_name":"Japan Aerospace Exploration Agency","ror":"https://ror.org/059yhyy33","country_code":"JP","type":"facility","lineage":["https://openalex.org/I2800865746"]},{"id":"https://openalex.org/I4210136277","display_name":"Institute of Space and Astronautical Science","ror":"https://ror.org/034gcgw60","country_code":"JP","type":"facility","lineage":["https://openalex.org/I2800865746","https://openalex.org/I4210136277"]}],"countries":["JP"],"is_corresponding":true,"raw_author_name":"Seisuke Fukuda","raw_affiliation_strings":["Institute of Space and Astronautical Science (ISAS), Japan Aerospace Exploration Agency, Sagamihara, Kanagawa, Japan"],"raw_orcid":null,"affiliations":[{"raw_affiliation_string":"Institute of Space and Astronautical Science (ISAS), Japan Aerospace Exploration Agency, Sagamihara, Kanagawa, Japan","institution_ids":["https://openalex.org/I2800865746","https://openalex.org/I4210136277"]}]}],"institutions":[],"countries_distinct_count":1,"institutions_distinct_count":2,"corresponding_author_ids":["https://openalex.org/A5103911317"],"corresponding_institution_ids":["https://openalex.org/I2800865746","https://openalex.org/I4210136277"],"apc_list":null,"apc_paid":null,"fwci":null,"has_fulltext":false,"cited_by_count":1,"citation_normalized_percentile":null,"cited_by_percentile_year":null,"biblio":{"volume":"e83 b","issue":null,"first_page":"II","last_page":"637"},"is_retracted":false,"is_paratext":false,"is_xpac":false,"primary_topic":{"id":"https://openalex.org/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace Engineering"},"field":{"id":"https://openalex.org/fields/22","display_name":"Engineering"},"domain":{"id":"https://openalex.org/domains/3","display_name":"Physical Sciences"}},"topics":[{"id":"https://openalex.org/T10801","display_name":"Synthetic Aperture Radar (SAR) Applications and Techniques","score":1.0,"subfield":{"id":"https://openalex.org/subfields/2202","display_name":"Aerospace 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/T11312","display_name":"Soil Moisture and Remote Sensing","score":0.9983000159263611,"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/T10535","display_name":"Landslides and related hazards","score":0.9966999888420105,"subfield":{"id":"https://openalex.org/subfields/2308","display_name":"Management, Monitoring, Policy and Law"},"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/random-forest","display_name":"Random forest","score":0.6485143899917603},{"id":"https://openalex.org/keywords/gaussian","display_name":"Gaussian","score":0.6209031343460083},{"id":"https://openalex.org/keywords/texture","display_name":"Texture (cosmology)","score":0.6134554743766785},{"id":"https://openalex.org/keywords/remote-sensing","display_name":"Remote sensing","score":0.587644100189209},{"id":"https://openalex.org/keywords/polarimetry","display_name":"Polarimetry","score":0.5506883263587952},{"id":"https://openalex.org/keywords/polarization","display_name":"Polarization (electrochemistry)","score":0.4653658866882324},{"id":"https://openalex.org/keywords/scattering","display_name":"Scattering","score":0.44848501682281494},{"id":"https://openalex.org/keywords/spatial-distribution","display_name":"Spatial distribution","score":0.4458167552947998},{"id":"https://openalex.org/keywords/artificial-intelligence","display_name":"Artificial intelligence","score":0.40461885929107666},{"id":"https://openalex.org/keywords/computer-science","display_name":"Computer science","score":0.39793020486831665},{"id":"https://openalex.org/keywords/environmental-science","display_name":"Environmental science","score":0.3782247006893158},{"id":"https://openalex.org/keywords/pattern-recognition","display_name":"Pattern recognition (psychology)","score":0.35757410526275635},{"id":"https://openalex.org/keywords/geography","display_name":"Geography","score":0.3171880841255188},{"id":"https://openalex.org/keywords/physics","display_name":"Physics","score":0.1921149492263794},{"id":"https://openalex.org/keywords/optics","display_name":"Optics","score":0.16061115264892578},{"id":"https://openalex.org/keywords/image","display_name":"Image (mathematics)","score":0.10845360159873962}],"concepts":[{"id":"https://openalex.org/C169258074","wikidata":"https://www.wikidata.org/wiki/Q245748","display_name":"Random forest","level":2,"score":0.6485143899917603},{"id":"https://openalex.org/C163716315","wikidata":"https://www.wikidata.org/wiki/Q901177","display_name":"Gaussian","level":2,"score":0.6209031343460083},{"id":"https://openalex.org/C2781195486","wikidata":"https://www.wikidata.org/wiki/Q289436","display_name":"Texture (cosmology)","level":3,"score":0.6134554743766785},{"id":"https://openalex.org/C62649853","wikidata":"https://www.wikidata.org/wiki/Q199687","display_name":"Remote sensing","level":1,"score":0.587644100189209},{"id":"https://openalex.org/C28493345","wikidata":"https://www.wikidata.org/wiki/Q899381","display_name":"Polarimetry","level":3,"score":0.5506883263587952},{"id":"https://openalex.org/C205049153","wikidata":"https://www.wikidata.org/wiki/Q2698605","display_name":"Polarization (electrochemistry)","level":2,"score":0.4653658866882324},{"id":"https://openalex.org/C191486275","wikidata":"https://www.wikidata.org/wiki/Q210028","display_name":"Scattering","level":2,"score":0.44848501682281494},{"id":"https://openalex.org/C2777016058","wikidata":"https://www.wikidata.org/wiki/Q7574061","display_name":"Spatial distribution","level":2,"score":0.4458167552947998},{"id":"https://openalex.org/C154945302","wikidata":"https://www.wikidata.org/wiki/Q11660","display_name":"Artificial intelligence","level":1,"score":0.40461885929107666},{"id":"https://openalex.org/C41008148","wikidata":"https://www.wikidata.org/wiki/Q21198","display_name":"Computer science","level":0,"score":0.39793020486831665},{"id":"https://openalex.org/C39432304","wikidata":"https://www.wikidata.org/wiki/Q188847","display_name":"Environmental science","level":0,"score":0.3782247006893158},{"id":"https://openalex.org/C153180895","wikidata":"https://www.wikidata.org/wiki/Q7148389","display_name":"Pattern recognition (psychology)","level":2,"score":0.35757410526275635},{"id":"https://openalex.org/C205649164","wikidata":"https://www.wikidata.org/wiki/Q1071","display_name":"Geography","level":0,"score":0.3171880841255188},{"id":"https://openalex.org/C121332964","wikidata":"https://www.wikidata.org/wiki/Q413","display_name":"Physics","level":0,"score":0.1921149492263794},{"id":"https://openalex.org/C120665830","wikidata":"https://www.wikidata.org/wiki/Q14620","display_name":"Optics","level":1,"score":0.16061115264892578},{"id":"https://openalex.org/C115961682","wikidata":"https://www.wikidata.org/wiki/Q860623","display_name":"Image (mathematics)","level":2,"score":0.10845360159873962},{"id":"https://openalex.org/C62520636","wikidata":"https://www.wikidata.org/wiki/Q944","display_name":"Quantum mechanics","level":1,"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/C147789679","wikidata":"https://www.wikidata.org/wiki/Q11372","display_name":"Physical chemistry","level":1,"score":0.0}],"mesh":[],"locations_count":1,"locations":[{"id":"doi:10.1109/igarss.2008.4779073","is_oa":false,"landing_page_url":"https://doi.org/10.1109/igarss.2008.4779073","pdf_url":null,"source":null,"license":null,"license_id":null,"version":"publishedVersion","is_accepted":true,"is_published":true,"raw_source_name":"IGARSS 2008 - 2008 IEEE International Geoscience and Remote Sensing Symposium","raw_type":"proceedings-article"}],"best_oa_location":null,"sustainable_development_goals":[{"display_name":"Life in Land","score":0.7599999904632568,"id":"https://metadata.un.org/sdg/15"}],"awards":[],"funders":[{"id":"https://openalex.org/F4320334900","display_name":"Japan Aerospace Exploration Agency","ror":"https://ror.org/059yhyy33"},{"id":"https://openalex.org/F4320335839","display_name":"National Institute of Information and Communications Technology","ror":"https://ror.org/016bgq349"}],"has_content":{"pdf":false,"grobid_xml":false},"content_urls":null,"referenced_works_count":17,"referenced_works":["https://openalex.org/W1566880740","https://openalex.org/W1602107991","https://openalex.org/W1696853265","https://openalex.org/W1966194886","https://openalex.org/W1996176293","https://openalex.org/W2061220758","https://openalex.org/W2077717067","https://openalex.org/W2094842984","https://openalex.org/W2096045557","https://openalex.org/W2097272115","https://openalex.org/W2100566779","https://openalex.org/W2112570958","https://openalex.org/W2116319373","https://openalex.org/W2135324386","https://openalex.org/W2150666871","https://openalex.org/W2152214791","https://openalex.org/W3036543524"],"related_works":["https://openalex.org/W2026860918","https://openalex.org/W2035593284","https://openalex.org/W3193043704","https://openalex.org/W4386259002","https://openalex.org/W2225281849","https://openalex.org/W1546989560","https://openalex.org/W2612145225","https://openalex.org/W2059660610","https://openalex.org/W3171520305","https://openalex.org/W2161058488"],"abstract_inverted_index":{"In":[0,44],"this":[1],"paper,":[2],"results":[3],"of":[4,23,35,57,78,92,103,106],"texture":[5,42,52],"analyses":[6],"over":[7],"coniferous":[8],"forests":[9],"using":[10],"airborne":[11],"L-band":[12],"POLSAR":[13],"data":[14],"are":[15,38],"shown.":[16],"Interestingly,":[17],"field":[18],"experiments":[19],"have":[20],"disclosed":[21],"existence":[22,56],"patch-like":[24,59],"sparse":[25,60],"areas":[26],"in":[27,40,84],"a":[28],"forest":[29,88,108],"division":[30],"where":[31],"low":[32],"order":[33,45],"parameters":[34],"the":[36,41,49,58,62,85,93,107],"K-distribution":[37],"calculated":[39],"analyses.":[43],"to":[46,55],"validate":[47],"that":[48,72],"observed":[50],"non-Gaussian":[51],"is":[53,66,69,74],"related":[54],"forests,":[61],"two-component":[63],"decomposition":[64],"method":[65],"applied.":[67],"It":[68],"successfully":[70],"revealed":[71],"there":[73],"spotted":[75],"high":[76],"contribution":[77,95],"ground":[79,94],"(double-bounce":[80],"or":[81],"direct)":[82],"scattering":[83],"highly":[86],"textured":[87],"division.":[89],"Furthermore,":[90],"difference":[91],"between":[96],"polarization":[97],"channels":[98],"could":[99],"encourage":[100],"our":[101],"understanding":[102],"polarimetric":[104],"variation":[105],"texture.":[109]},"counts_by_year":[{"year":2014,"cited_by_count":1}],"updated_date":"2026-07-14T23:27:15.235271","created_date":"2025-10-10T00:00:00"}