Scaling estimates of vegetation structure in Amazonian tropical forests using multi-angle MODIS observations
•Multi-angle MODIS observations were used to characterize anisotropy of tropical vegetation.•MODIS anisotropy is strongly correlated to canopy entropy from LiDAR, GLAS and QuikSCAT.•Multi-angle MODIS data can be used to scale estimates of vegetation structure in tropics. Detailed knowledge of vegeta...
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| Veröffentlicht in: | ITC journal 2016-10, Vol.52, p.580-590 |
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| creator | Moura, Yhasmin Mendes de Hilker, Thomas Gonçalves, Fabio Guimarães Galvão, Lênio Soares dos Santos, João Roberto Lyapustin, Alexei Maeda, Eduardo Eiji de Jesus Silva, Camila Valéria |
| description | •Multi-angle MODIS observations were used to characterize anisotropy of tropical vegetation.•MODIS anisotropy is strongly correlated to canopy entropy from LiDAR, GLAS and QuikSCAT.•Multi-angle MODIS data can be used to scale estimates of vegetation structure in tropics.
Detailed knowledge of vegetation structure is required for accurate modelling of terrestrial ecosystems, but direct measurements of the three dimensional distribution of canopy elements, for instance from LiDAR, are not widely available. We investigate the potential for modelling vegetation roughness, a key parameter for climatological models, from directional scattering of visible and near-infrared (NIR) reflectance acquired from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS). We compare our estimates across different tropical forest types to independent measures obtained from: (1) airborne laser scanning (ALS), (2) spaceborne Geoscience Laser Altimeter System (GLAS)/ICESat, and (3) the spaceborne SeaWinds/QSCAT. Our results showed linear correlation between MODIS-derived anisotropy to ALS-derived entropy (r2=0.54, RMSE=0.11), even in high biomass regions. Significant relationships were also obtained between MODIS-derived anisotropy and GLAS-derived entropy (0.52≤r2≤0.61; p |
| doi_str_mv | 10.1016/j.jag.2016.07.017 |
| format | Article |
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Detailed knowledge of vegetation structure is required for accurate modelling of terrestrial ecosystems, but direct measurements of the three dimensional distribution of canopy elements, for instance from LiDAR, are not widely available. We investigate the potential for modelling vegetation roughness, a key parameter for climatological models, from directional scattering of visible and near-infrared (NIR) reflectance acquired from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS). We compare our estimates across different tropical forest types to independent measures obtained from: (1) airborne laser scanning (ALS), (2) spaceborne Geoscience Laser Altimeter System (GLAS)/ICESat, and (3) the spaceborne SeaWinds/QSCAT. Our results showed linear correlation between MODIS-derived anisotropy to ALS-derived entropy (r2=0.54, RMSE=0.11), even in high biomass regions. Significant relationships were also obtained between MODIS-derived anisotropy and GLAS-derived entropy (0.52≤r2≤0.61; p<0.05), with similar slopes and offsets found throughout the season, and RMSE between 0.26 and 0.30 (units of entropy). The relationships between the MODIS-derived anisotropy and backscattering measurements (σ0) from SeaWinds/QuikSCAT presented an r2 of 0.59 and a RMSE of 0.11. We conclude that multi-angular MODIS observations are suitable to extrapolate measures of canopy entropy across different forest types, providing additional estimates of vegetation structure in the Amazon.</description><identifier>ISSN: 1569-8432</identifier><identifier>ISSN: 0303-2434</identifier><identifier>EISSN: 1872-826X</identifier><identifier>DOI: 10.1016/j.jag.2016.07.017</identifier><identifier>PMID: 29618964</identifier><language>eng</language><publisher>Goddard Space Flight Center: Elsevier B.V</publisher><subject>Anisotropy ; Canopy roughness ; Earth Resources And Remote Sensing ; LiDAR ; MAIAC ; Meteorology And Climatology ; MODIS ; Multi-angle</subject><ispartof>ITC journal, 2016-10, Vol.52, p.580-590</ispartof><rights>2016 Elsevier B.V.</rights><rights>Copyright Determination: PUBLIC_USE_PERMITTED</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c472t-c81010f0362748363bcb28c63a8c7ea81c8f870a9a40b9456af1bdf7dfae625c3</citedby><cites>FETCH-LOGICAL-c472t-c81010f0362748363bcb28c63a8c7ea81c8f870a9a40b9456af1bdf7dfae625c3</cites><orcidid>0000-0001-8494-8787</orcidid></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.jag.2016.07.017$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>230,314,780,784,800,885,3550,27924,27925,45995</link.rule.ids><backlink>$$Uhttps://www.ncbi.nlm.nih.gov/pubmed/29618964$$D View this record in MEDLINE/PubMed$$Hfree_for_read</backlink></links><search><creatorcontrib>Moura, Yhasmin Mendes de</creatorcontrib><creatorcontrib>Hilker, Thomas</creatorcontrib><creatorcontrib>Gonçalves, Fabio Guimarães</creatorcontrib><creatorcontrib>Galvão, Lênio Soares</creatorcontrib><creatorcontrib>dos Santos, João Roberto</creatorcontrib><creatorcontrib>Lyapustin, Alexei</creatorcontrib><creatorcontrib>Maeda, Eduardo Eiji</creatorcontrib><creatorcontrib>de Jesus Silva, Camila Valéria</creatorcontrib><title>Scaling estimates of vegetation structure in Amazonian tropical forests using multi-angle MODIS observations</title><title>ITC journal</title><addtitle>Int J Appl Earth Obs Geoinf</addtitle><description>•Multi-angle MODIS observations were used to characterize anisotropy of tropical vegetation.•MODIS anisotropy is strongly correlated to canopy entropy from LiDAR, GLAS and QuikSCAT.•Multi-angle MODIS data can be used to scale estimates of vegetation structure in tropics.
Detailed knowledge of vegetation structure is required for accurate modelling of terrestrial ecosystems, but direct measurements of the three dimensional distribution of canopy elements, for instance from LiDAR, are not widely available. We investigate the potential for modelling vegetation roughness, a key parameter for climatological models, from directional scattering of visible and near-infrared (NIR) reflectance acquired from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS). We compare our estimates across different tropical forest types to independent measures obtained from: (1) airborne laser scanning (ALS), (2) spaceborne Geoscience Laser Altimeter System (GLAS)/ICESat, and (3) the spaceborne SeaWinds/QSCAT. Our results showed linear correlation between MODIS-derived anisotropy to ALS-derived entropy (r2=0.54, RMSE=0.11), even in high biomass regions. Significant relationships were also obtained between MODIS-derived anisotropy and GLAS-derived entropy (0.52≤r2≤0.61; p<0.05), with similar slopes and offsets found throughout the season, and RMSE between 0.26 and 0.30 (units of entropy). The relationships between the MODIS-derived anisotropy and backscattering measurements (σ0) from SeaWinds/QuikSCAT presented an r2 of 0.59 and a RMSE of 0.11. We conclude that multi-angular MODIS observations are suitable to extrapolate measures of canopy entropy across different forest types, providing additional estimates of vegetation structure in the Amazon.</description><subject>Anisotropy</subject><subject>Canopy roughness</subject><subject>Earth Resources And Remote Sensing</subject><subject>LiDAR</subject><subject>MAIAC</subject><subject>Meteorology And Climatology</subject><subject>MODIS</subject><subject>Multi-angle</subject><issn>1569-8432</issn><issn>0303-2434</issn><issn>1872-826X</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2016</creationdate><recordtype>article</recordtype><sourceid>CYI</sourceid><recordid>eNp9UU1r3DAUNKWlSZP-gEIpOuZiR5JtSaZQCOlXICGHtNCbeJafXS22tJXkhfbXV9tNQ3rpSQ_ezLwZTVG8YrRilInzTbWBqeJ5rKisKJNPimOmJC8VF9-e5rkVXamamh8VL2Lc0IyQQj0vjngnmOpEc1zMdwZm6yaCMdkFEkbiR7LDCRMk6x2JKawmrQGJdeRigV_eWXAkBb-1mUpGHzI1kjXuVZZ1TrYEN81Ibm7fX90R30cMuz9a8bR4NsIc8eX9e1J8_fjhy-Xn8vr209XlxXVpGslTaVROR0daCy4bVYu6Nz1XRtSgjERQzKhRSQodNLTvmlbAyPphlMMIKHhr6pPi3UF3u_YLDgZdCjDrbcgJw0_twep_N85-15Pf6VYpSusuC5zdCwT_Y8359GKjwXkGh36NmlPOGZdtKzOUHaAm-BgDjg9nGNX7lvRG55b0viVNpc4dZM6bx_4eGH9ryYDXB4CDCDp73J9kkmZzkom8fntYY_7EncWgo7HoDA42oEl68PY_138DUCmugQ</recordid><startdate>20161001</startdate><enddate>20161001</enddate><creator>Moura, Yhasmin Mendes de</creator><creator>Hilker, Thomas</creator><creator>Gonçalves, Fabio Guimarães</creator><creator>Galvão, Lênio Soares</creator><creator>dos Santos, João Roberto</creator><creator>Lyapustin, Alexei</creator><creator>Maeda, Eduardo Eiji</creator><creator>de Jesus Silva, Camila Valéria</creator><general>Elsevier B.V</general><general>Elsevier</general><scope>CYE</scope><scope>CYI</scope><scope>NPM</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7X8</scope><scope>5PM</scope><orcidid>https://orcid.org/0000-0001-8494-8787</orcidid></search><sort><creationdate>20161001</creationdate><title>Scaling estimates of vegetation structure in Amazonian tropical forests using multi-angle MODIS observations</title><author>Moura, Yhasmin Mendes de ; Hilker, Thomas ; Gonçalves, Fabio Guimarães ; Galvão, Lênio Soares ; dos Santos, João Roberto ; Lyapustin, Alexei ; Maeda, Eduardo Eiji ; de Jesus Silva, Camila Valéria</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c472t-c81010f0362748363bcb28c63a8c7ea81c8f870a9a40b9456af1bdf7dfae625c3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2016</creationdate><topic>Anisotropy</topic><topic>Canopy roughness</topic><topic>Earth Resources And Remote Sensing</topic><topic>LiDAR</topic><topic>MAIAC</topic><topic>Meteorology And Climatology</topic><topic>MODIS</topic><topic>Multi-angle</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Moura, Yhasmin Mendes de</creatorcontrib><creatorcontrib>Hilker, Thomas</creatorcontrib><creatorcontrib>Gonçalves, Fabio Guimarães</creatorcontrib><creatorcontrib>Galvão, Lênio Soares</creatorcontrib><creatorcontrib>dos Santos, João Roberto</creatorcontrib><creatorcontrib>Lyapustin, Alexei</creatorcontrib><creatorcontrib>Maeda, Eduardo Eiji</creatorcontrib><creatorcontrib>de Jesus Silva, Camila Valéria</creatorcontrib><collection>NASA Scientific and Technical Information</collection><collection>NASA Technical Reports Server</collection><collection>PubMed</collection><collection>CrossRef</collection><collection>MEDLINE - Academic</collection><collection>PubMed Central (Full Participant titles)</collection><jtitle>ITC journal</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Moura, Yhasmin Mendes de</au><au>Hilker, Thomas</au><au>Gonçalves, Fabio Guimarães</au><au>Galvão, Lênio Soares</au><au>dos Santos, João Roberto</au><au>Lyapustin, Alexei</au><au>Maeda, Eduardo Eiji</au><au>de Jesus Silva, Camila Valéria</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Scaling estimates of vegetation structure in Amazonian tropical forests using multi-angle MODIS observations</atitle><jtitle>ITC journal</jtitle><addtitle>Int J Appl Earth Obs Geoinf</addtitle><date>2016-10-01</date><risdate>2016</risdate><volume>52</volume><spage>580</spage><epage>590</epage><pages>580-590</pages><issn>1569-8432</issn><issn>0303-2434</issn><eissn>1872-826X</eissn><abstract>•Multi-angle MODIS observations were used to characterize anisotropy of tropical vegetation.•MODIS anisotropy is strongly correlated to canopy entropy from LiDAR, GLAS and QuikSCAT.•Multi-angle MODIS data can be used to scale estimates of vegetation structure in tropics.
Detailed knowledge of vegetation structure is required for accurate modelling of terrestrial ecosystems, but direct measurements of the three dimensional distribution of canopy elements, for instance from LiDAR, are not widely available. We investigate the potential for modelling vegetation roughness, a key parameter for climatological models, from directional scattering of visible and near-infrared (NIR) reflectance acquired from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS). We compare our estimates across different tropical forest types to independent measures obtained from: (1) airborne laser scanning (ALS), (2) spaceborne Geoscience Laser Altimeter System (GLAS)/ICESat, and (3) the spaceborne SeaWinds/QSCAT. Our results showed linear correlation between MODIS-derived anisotropy to ALS-derived entropy (r2=0.54, RMSE=0.11), even in high biomass regions. Significant relationships were also obtained between MODIS-derived anisotropy and GLAS-derived entropy (0.52≤r2≤0.61; p<0.05), with similar slopes and offsets found throughout the season, and RMSE between 0.26 and 0.30 (units of entropy). The relationships between the MODIS-derived anisotropy and backscattering measurements (σ0) from SeaWinds/QuikSCAT presented an r2 of 0.59 and a RMSE of 0.11. We conclude that multi-angular MODIS observations are suitable to extrapolate measures of canopy entropy across different forest types, providing additional estimates of vegetation structure in the Amazon.</abstract><cop>Goddard Space Flight Center</cop><pub>Elsevier B.V</pub><pmid>29618964</pmid><doi>10.1016/j.jag.2016.07.017</doi><tpages>11</tpages><orcidid>https://orcid.org/0000-0001-8494-8787</orcidid><oa>free_for_read</oa></addata></record> |
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| source | ScienceDirect Journals (5 years ago - present); NASA Technical Reports Server |
| subjects | Anisotropy Canopy roughness Earth Resources And Remote Sensing LiDAR MAIAC Meteorology And Climatology MODIS Multi-angle |
| title | Scaling estimates of vegetation structure in Amazonian tropical forests using multi-angle MODIS observations |
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