An evaluation of MODIS 8- and 16-day composite products for monitoring maize green leaf area index

• Published in: Agricultural and forest meteorology Vol. 161; pp. 15 - 25
• Main Authors: Guindin-Garcia, Noemi, Gitelson, Anatoly A., Arkebauer, Timothy J., Shanahan, John, Weiss, Albert
• Format: Journal Article
• Language: English
• Published: Amsterdam Elsevier B.V 15.08.2012; Elsevier
• 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; Temporal resolution; Maize; Green leaf area index; Vegetation indices; MODIS; Biometeorology; Evaluation; Monocotyledones; Vegetals; Zea mays; Vegetation index; C4-Type; Leaf area; Cereal crop; Time resolution; Plant part; Surveillance; Gramineae; Angiospermae; Vegetative apparatus; Above ground plant part; Spermatophyta; Day; Leaf area index
• ISSN: 0168-1923; 1873-2240
• DOI: 10.1016/j.agrformet.2012.03.012

► 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.