caa a22 4500 467903573 CHVBK 20180406152826.0 cr unu---uuuuu 170328e20060801xx s 000 0 eng 10.1007/s10661-005-9006-7 doi (NATIONALLICENCE)springer-10.1007/s10661-005-9006-7 Assessment of MODIS-EVI, MODIS-NDVI and VEGETATION-NDVI Composite Data Using Agricultural Measurements: An Example at Corn Fields in Western Mexico [Elektronische Daten] [Pei-Yu Chen, Gunar Fedosejevs, Mario Tiscareño-LóPez, Jeffrey Arnold] Although several types of satellite data provide temporal information of the land use at no cost, digital satellite data applications for agricultural studies are limited compared to applications for forest management. This study assessed the suitability of vegetation indices derived from the TERRA-Moderate Resolution Imaging Spectroradiometer (MODIS) sensor and SPOT-VEGETATION (VGT) sensor for identifying corn growth in western Mexico. Overall, the Normalized Difference Vegetation Index (NDVI) composites from the VGT sensor based on bi-directional compositing method produced vegetation information most closely resembling actual crop conditions. The NDVI composites from the MODIS sensor exhibited saturated signals starting 30 days after planting, but corresponded to green leaf senescence in April. The temporal NDVI composites from the VGT sensor based on the maximum value method had a maximum plateau for 80 days, which masked the important crop transformation from vegetative stage to reproductive stage. The Enhanced Vegetation Index (EVI) composites from the MODIS sensor reached a maximum plateau 40 days earlier than the occurrence of maximum leaf area index (LAI) and maximum intercepted fraction of photosynthetic active radiation (fPAR) derived from in-situ measurements. The results of this study showed that the 250-m resolution MODIS data did not provide more accurate vegetation information for corn growth description than the 500-m and 1000-m resolution MODIS data. Springer Science + Business Media, Inc., 2005 MODIS nationallicence SPOT/VEGETATION nationallicence NDVI nationallicence EVI nationallicence Chen Pei-Yu Blackland Research & Extension Center, Texas Agricultural Experiment Station, 720 East Blackland Road, 76502, Temple, Texas, U.S.A. aut Fedosejevs Gunar Canada Center for Remote Sensing, 588 Booth Street, K1A 0Y7, Ottawa, Ontario, Canada aut Tiscareño-LóPez Mario Laboratorio Nacional de Modelaje y Sensores Remotos, INIFAP, Km 32 Carr. Aguascalientes-Zacatecas, Pabellon de Arteaga, Ags., 20660, Aguacalienties, Mexico aut Arnold Jeffrey USDA-Agricultural Research Service, Grassland, Soil and Water Research Lab., 808 East Blackland Road, 76502, Temple, Texas, U.S.A. aut Environmental Monitoring and Assessment Kluwer Academic Publishers 119/1-3(2006-08-01), 69-82 0167-6369 119:1-3<69 2006 119 10661 https://doi.org/10.1007/s10661-005-9006-7 text/html Onlinezugriff via DOI 1 research-article jats NATIONALLICENCE 856 40 https://doi.org/10.1007/s10661-005-9006-7 text/html Onlinezugriff via DOI NATIONALLICENCE 700 1- Chen Pei-Yu Blackland Research & Extension Center, Texas Agricultural Experiment Station, 720 East Blackland Road, 76502, Temple, Texas, U.S.A aut NATIONALLICENCE 700 1- Fedosejevs Gunar Canada Center for Remote Sensing, 588 Booth Street, K1A 0Y7, Ottawa, Ontario, Canada aut NATIONALLICENCE 700 1- Tiscareño-LóPez Mario Laboratorio Nacional de Modelaje y Sensores Remotos, INIFAP, Km 32 Carr. Aguascalientes-Zacatecas, Pabellon de Arteaga, Ags., 20660, Aguacalienties, Mexico aut NATIONALLICENCE 700 1- Arnold Jeffrey USDA-Agricultural Research Service, Grassland, Soil and Water Research Lab., 808 East Blackland Road, 76502, Temple, Texas, U.S.A aut NATIONALLICENCE 773 0- Environmental Monitoring and Assessment Kluwer Academic Publishers 119/1-3(2006-08-01), 69-82 0167-6369 119:1-3<69 2006 119 10661 Metadata rights reserved Springer special CC-BY-NC licence nationallicence BK010053 XK010053 XK010000 NATIONALLICENCE NATIONALLICENCE NL-springer