An evaluation of MODIS 8- and 16-day composite products for monitoring maize green leaf area index
► Green leaf area index in maize can be estimated accurately using MODIS data. ► High spatial (250m) and temporal (8-day composite) resolutions are required for retrieval of crop LAI. ► WDRVI and EVI are the best predictors of maize green LAI. The seasonal patterns of green leaf area index (GLAI) ca...
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| Veröffentlicht in: | Agricultural and forest meteorology 2012-08, Vol.161, p.15-25 |
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| creator | Guindin-Garcia, Noemi Gitelson, Anatoly A. Arkebauer, Timothy J. Shanahan, John Weiss, Albert |
| description | ► Green leaf area index in maize can be estimated accurately using MODIS data. ► High spatial (250m) and temporal (8-day composite) resolutions are required for retrieval of crop LAI. ► WDRVI and EVI are the best predictors of maize green LAI.
The seasonal patterns of green leaf area index (GLAI) can be used to assess crop physiological and phenological status, to assess yield potential, and to incorporate in crop simulation models. This study focused on examining the potential capabilities and limitations of satellite data retrieved from the moderate resolution imaging spectroradiometer (MODIS) 8- and 16-day composite products to quantitatively estimate GLAI over maize (Zea mays L.) fields. Results, based on the nine years of data used in this study, indicated a wide variability of temporal resolution obtained from MODIS 8- and 16-day composite periods and highlighted the importance of information about day of MODIS products pixel composite for monitoring agricultural crops. Due to high maize GLAI temporal variability, the inclusion of day of pixel composite is necessary to decrease substantial uncertainties in estimating GLAI. Results also indicated that maize GLAI can be accurately retrieved from the 250-m resolution MODIS products (MOD13Q1 and MOD09Q1) by a wide dynamic range vegetation index with root mean square error (RMSE) below 0.60m2m−2 or by the enhanced vegetation index with RMSE below 0.70m2m−2. |
| doi_str_mv | 10.1016/j.agrformet.2012.03.012 |
| format | Article |
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The seasonal patterns of green leaf area index (GLAI) can be used to assess crop physiological and phenological status, to assess yield potential, and to incorporate in crop simulation models. This study focused on examining the potential capabilities and limitations of satellite data retrieved from the moderate resolution imaging spectroradiometer (MODIS) 8- and 16-day composite products to quantitatively estimate GLAI over maize (Zea mays L.) fields. Results, based on the nine years of data used in this study, indicated a wide variability of temporal resolution obtained from MODIS 8- and 16-day composite periods and highlighted the importance of information about day of MODIS products pixel composite for monitoring agricultural crops. Due to high maize GLAI temporal variability, the inclusion of day of pixel composite is necessary to decrease substantial uncertainties in estimating GLAI. Results also indicated that maize GLAI can be accurately retrieved from the 250-m resolution MODIS products (MOD13Q1 and MOD09Q1) by a wide dynamic range vegetation index with root mean square error (RMSE) below 0.60m2m−2 or by the enhanced vegetation index with RMSE below 0.70m2m−2.</description><identifier>ISSN: 0168-1923</identifier><identifier>EISSN: 1873-2240</identifier><identifier>DOI: 10.1016/j.agrformet.2012.03.012</identifier><identifier>CODEN: AFMEEB</identifier><language>eng</language><publisher>Amsterdam: Elsevier B.V</publisher><subject>Agricultural and forest climatology and meteorology. Irrigation. Drainage ; Agronomy. Soil science and plant productions ; Biological and medical sciences ; corn ; crop models ; Crops ; Estimating ; Fundamental and applied biological sciences. Psychology ; General agronomy. Plant production ; Green leaf area index ; Leaf area index ; Maize ; moderate resolution imaging spectroradiometer ; MODIS ; Monitoring ; physiological state ; Pixels ; satellites ; seasonal variation ; Temporal resolution ; uncertainty ; Vegetation ; Vegetation indices ; Zea mays</subject><ispartof>Agricultural and forest meteorology, 2012-08, Vol.161, p.15-25</ispartof><rights>2012 Elsevier B.V.</rights><rights>2015 INIST-CNRS</rights><lds50>peer_reviewed</lds50><oa>free_for_read</oa><woscitedreferencessubscribed>false</woscitedreferencessubscribed><citedby>FETCH-LOGICAL-c501t-4903700e49ceee5898334882cb70460bf930a3f60c7c9bc03649a6b811d42f7d3</citedby><cites>FETCH-LOGICAL-c501t-4903700e49ceee5898334882cb70460bf930a3f60c7c9bc03649a6b811d42f7d3</cites></display><links><openurl>$$Topenurl_article</openurl><openurlfulltext>$$Topenurlfull_article</openurlfulltext><thumbnail>$$Tsyndetics_thumb_exl</thumbnail><linktohtml>$$Uhttps://dx.doi.org/10.1016/j.agrformet.2012.03.012$$EHTML$$P50$$Gelsevier$$H</linktohtml><link.rule.ids>314,777,781,3537,27905,27906,45976</link.rule.ids><backlink>$$Uhttp://pascal-francis.inist.fr/vibad/index.php?action=getRecordDetail&idt=25906437$$DView record in Pascal Francis$$Hfree_for_read</backlink></links><search><creatorcontrib>Guindin-Garcia, Noemi</creatorcontrib><creatorcontrib>Gitelson, Anatoly A.</creatorcontrib><creatorcontrib>Arkebauer, Timothy J.</creatorcontrib><creatorcontrib>Shanahan, John</creatorcontrib><creatorcontrib>Weiss, Albert</creatorcontrib><title>An evaluation of MODIS 8- and 16-day composite products for monitoring maize green leaf area index</title><title>Agricultural and forest meteorology</title><description>► Green leaf area index in maize can be estimated accurately using MODIS data. ► High spatial (250m) and temporal (8-day composite) resolutions are required for retrieval of crop LAI. ► WDRVI and EVI are the best predictors of maize green LAI.
The seasonal patterns of green leaf area index (GLAI) can be used to assess crop physiological and phenological status, to assess yield potential, and to incorporate in crop simulation models. This study focused on examining the potential capabilities and limitations of satellite data retrieved from the moderate resolution imaging spectroradiometer (MODIS) 8- and 16-day composite products to quantitatively estimate GLAI over maize (Zea mays L.) fields. Results, based on the nine years of data used in this study, indicated a wide variability of temporal resolution obtained from MODIS 8- and 16-day composite periods and highlighted the importance of information about day of MODIS products pixel composite for monitoring agricultural crops. Due to high maize GLAI temporal variability, the inclusion of day of pixel composite is necessary to decrease substantial uncertainties in estimating GLAI. Results also indicated that maize GLAI can be accurately retrieved from the 250-m resolution MODIS products (MOD13Q1 and MOD09Q1) by a wide dynamic range vegetation index with root mean square error (RMSE) below 0.60m2m−2 or by the enhanced vegetation index with RMSE below 0.70m2m−2.</description><subject>Agricultural and forest climatology and meteorology. Irrigation. Drainage</subject><subject>Agronomy. Soil science and plant productions</subject><subject>Biological and medical sciences</subject><subject>corn</subject><subject>crop models</subject><subject>Crops</subject><subject>Estimating</subject><subject>Fundamental and applied biological sciences. Psychology</subject><subject>General agronomy. Plant production</subject><subject>Green leaf area index</subject><subject>Leaf area index</subject><subject>Maize</subject><subject>moderate resolution imaging spectroradiometer</subject><subject>MODIS</subject><subject>Monitoring</subject><subject>physiological state</subject><subject>Pixels</subject><subject>satellites</subject><subject>seasonal variation</subject><subject>Temporal resolution</subject><subject>uncertainty</subject><subject>Vegetation</subject><subject>Vegetation indices</subject><subject>Zea mays</subject><issn>0168-1923</issn><issn>1873-2240</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>2012</creationdate><recordtype>article</recordtype><recordid>eNqFkU9v1DAUxCMEEkvhM9QXJC4Jz39iO8dVoVCpqIfSs-U4zyuvEnuxsxXl0-PVVr32NJffmzeaaZpLCh0FKr_uO7vLPuUF144BZR3wrsqbZkO14i1jAt42m0rqlg6Mv28-lLKHSig1bJpxGwk-2vlo15AiSZ78uvt2c090S2ycCJXtZJ-IS8shlbAiOeQ0Hd1aSP1IlhTDmnKIO7LY8A_JLiNGMqP1xGa0JMQJ_35s3nk7F_z0rBfNw_X331c_29u7HzdX29vW9UDXVgzAFQCKwSFirwfNudCauVGBkDD6gYPlXoJTbhgdcCkGK0dN6SSYVxO_aL6cfWvGP0csq1lCcTjPNmI6FlMb6DWVjKnXUWCgRW2OVlSdUZdTKRm9OeSw2PxUIXMawOzNywDmNIABbqrUy8_PT2xxdvbZRhfKyznrB5CCn8Jcnjlv08mqMg_31UjUkZTsNVRieyaw1vcYMJviAkaHU8joVjOl8Gqa_xMFpwU</recordid><startdate>20120815</startdate><enddate>20120815</enddate><creator>Guindin-Garcia, Noemi</creator><creator>Gitelson, Anatoly A.</creator><creator>Arkebauer, Timothy J.</creator><creator>Shanahan, John</creator><creator>Weiss, Albert</creator><general>Elsevier B.V</general><general>Elsevier</general><scope>FBQ</scope><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7TG</scope><scope>7UA</scope><scope>C1K</scope><scope>KL.</scope><scope>8FD</scope><scope>FR3</scope><scope>H8D</scope><scope>KR7</scope><scope>L7M</scope></search><sort><creationdate>20120815</creationdate><title>An evaluation of MODIS 8- and 16-day composite products for monitoring maize green leaf area index</title><author>Guindin-Garcia, Noemi ; Gitelson, Anatoly A. ; Arkebauer, Timothy J. ; Shanahan, John ; Weiss, Albert</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c501t-4903700e49ceee5898334882cb70460bf930a3f60c7c9bc03649a6b811d42f7d3</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>2012</creationdate><topic>Agricultural and forest climatology and meteorology. 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Plant production</topic><topic>Green leaf area index</topic><topic>Leaf area index</topic><topic>Maize</topic><topic>moderate resolution imaging spectroradiometer</topic><topic>MODIS</topic><topic>Monitoring</topic><topic>physiological state</topic><topic>Pixels</topic><topic>satellites</topic><topic>seasonal variation</topic><topic>Temporal resolution</topic><topic>uncertainty</topic><topic>Vegetation</topic><topic>Vegetation indices</topic><topic>Zea mays</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Guindin-Garcia, Noemi</creatorcontrib><creatorcontrib>Gitelson, Anatoly A.</creatorcontrib><creatorcontrib>Arkebauer, Timothy J.</creatorcontrib><creatorcontrib>Shanahan, John</creatorcontrib><creatorcontrib>Weiss, Albert</creatorcontrib><collection>AGRIS</collection><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Meteorological & Geoastrophysical Abstracts</collection><collection>Water Resources Abstracts</collection><collection>Environmental Sciences and Pollution Management</collection><collection>Meteorological & Geoastrophysical Abstracts - Academic</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>Aerospace Database</collection><collection>Civil Engineering Abstracts</collection><collection>Advanced Technologies Database with Aerospace</collection><jtitle>Agricultural and forest meteorology</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext</fulltext></delivery><addata><au>Guindin-Garcia, Noemi</au><au>Gitelson, Anatoly A.</au><au>Arkebauer, Timothy J.</au><au>Shanahan, John</au><au>Weiss, Albert</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>An evaluation of MODIS 8- and 16-day composite products for monitoring maize green leaf area index</atitle><jtitle>Agricultural and forest meteorology</jtitle><date>2012-08-15</date><risdate>2012</risdate><volume>161</volume><spage>15</spage><epage>25</epage><pages>15-25</pages><issn>0168-1923</issn><eissn>1873-2240</eissn><coden>AFMEEB</coden><abstract>► Green leaf area index in maize can be estimated accurately using MODIS data. ► High spatial (250m) and temporal (8-day composite) resolutions are required for retrieval of crop LAI. ► WDRVI and EVI are the best predictors of maize green LAI.
The seasonal patterns of green leaf area index (GLAI) can be used to assess crop physiological and phenological status, to assess yield potential, and to incorporate in crop simulation models. This study focused on examining the potential capabilities and limitations of satellite data retrieved from the moderate resolution imaging spectroradiometer (MODIS) 8- and 16-day composite products to quantitatively estimate GLAI over maize (Zea mays L.) fields. Results, based on the nine years of data used in this study, indicated a wide variability of temporal resolution obtained from MODIS 8- and 16-day composite periods and highlighted the importance of information about day of MODIS products pixel composite for monitoring agricultural crops. Due to high maize GLAI temporal variability, the inclusion of day of pixel composite is necessary to decrease substantial uncertainties in estimating GLAI. Results also indicated that maize GLAI can be accurately retrieved from the 250-m resolution MODIS products (MOD13Q1 and MOD09Q1) by a wide dynamic range vegetation index with root mean square error (RMSE) below 0.60m2m−2 or by the enhanced vegetation index with RMSE below 0.70m2m−2.</abstract><cop>Amsterdam</cop><pub>Elsevier B.V</pub><doi>10.1016/j.agrformet.2012.03.012</doi><tpages>11</tpages><oa>free_for_read</oa></addata></record> |
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| subjects | Agricultural and forest climatology and meteorology. Irrigation. Drainage Agronomy. Soil science and plant productions Biological and medical sciences corn crop models Crops Estimating Fundamental and applied biological sciences. Psychology General agronomy. Plant production Green leaf area index Leaf area index Maize moderate resolution imaging spectroradiometer MODIS Monitoring physiological state Pixels satellites seasonal variation Temporal resolution uncertainty Vegetation Vegetation indices Zea mays |
| title | An evaluation of MODIS 8- and 16-day composite products for monitoring maize green leaf area index |
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