Water Management in Agriculture

Water Management in Agriculture

Estimation of Rice LAI in a Large Scale Using Landsat Imageries

Authors
Mojtaba Rezaei 1
Majid Vazifedoust 2
Naser Davatgar 1
Nader Pirmoradian 2
Shiva Mokhtari 3
Ali shahnazari 3
Mahmood Raeini Sarjaz 4
Abrahim Amiri 5
1 Rice ResearchIn stitute of lran, Agricultural Research Education and Exiension Organization (AREEO), Rash, Iran
2 Assistant professor, Faculty of Agricultural Sciences, University of Guilan, Rasht
3 MSc. Student, Irrigation and drainage, University of Guilan
4 Assistant Professor, Faculty of Agricultural Sciences, University of Sari, Sari, Iran
5 Professor, Department Of Water Engineering, Lahidjan Branch, Islamic Azad University, Lahidjan, Iran.
Abstract
Leaf area index (LAI) is an important index in crop evapotranspiration estimation and in monitoring abiotic stresses like water stress. The LAI determination using direct methods is costly as well as time consuming, making it nearly impossible especially over large scales. For these reasons, attempts have been made to forecast LAI using remotely sensed vegetation indices (i.e., the Normalized Difference Vegetation Index, NDVI). The present study aimed to estimate rice LAI in a large scale using remote sensing imageries from Landsat 5 and 7. Actual LAI were measured during 2010  in four different growing phases in 10 paddy fields of Fouman, Guilan, the northern part of Iran. The samples were taken from the fields and the LAI were measured by a LAI meter in laboratory. The results showed that the accuracy of estimation of LAI by Landsat imageries changed during the season, but the best results gained in rice full coverage in flowering phase (R2=0.85). In the early stage of rice growing season using NDVI and in full coverage using SAVI gave the best correlation of LAI estimation.
Keywords
LAI، NDVI، SAVI
paddy field
Rs
رضایی، م.، 1394. برآورد تأثیر تغییرات میزان کاربرد آب آبیاری بر بهره­وری آب در سطح وسیع با استفاده از ترکیب داده­های ماهواره­ای و مدل DSSAT. رساله دکتری. گروه مهندسی آب دانشکده علوم کشاورزی و منابع طبیعی ساری. 148 ص.
مختاری، ش.، 1390. توسعه و کاربرد یک مدل ساده (VSM) جهت تخمین منطقه­ای عملکرد برنج با بهره­گیری از داده­های ماهواره­ای. پایان‌نامه کارشناسی ارشد. گروه مهندسی آب دانشکده علوم کشاورزی دانشگاه گیلان.80 ص.
Rao, N.R., Garg, P.K., and Ghosh, S.K. 2006. Estimation and comparison of leaf area index of agricultural crops using IRS LISS-III and EO-1 Hyperion images. Journal of the Indian Society of Remote Sensing, 34(1):69-78.
Sharma, N., Piscioneri, I., Baviello, G., and Orlandini, S. 2000. Promising industrial energy crop, Cynara cardunculus: a potential source for biomass production and alternative energy. Energy Conversion and Management, 41(10):1091-1105.
 
Water Management in Agriculture
Volume 3, Issue 2
December 2016
Pages 53-60