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Afr. J. Agric. Res.


Vol. 6 No. 1
7



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Scientific Research and Essays
 

African Journal of Agricultural Research Vol. 6(17), pp.4025-4033, 5 September, 2011

Available online at http://www.academicjournals.org/AJAR

DOI: 10.5897/AJAR11.770

ISSN 1991-637X ©2011 Academic Journals

 

 

Full Length Research Paper

 

MODIS data based NDVI Seasonal dynamics in agro-ecosystems of south bank Hangzhouwan bay

 

Zhao Hanbing1, Yang Xiaoping2* and Li Jialin2

 

1College of Information, South China Agricultural University, Guangzhou 510642, Guangdong, China.

2Coastal Resources and Environment Research Center, Ningbo University, Ningbo 315211, China.

 

*Corresponding author. E-mail: yxpnb@126.com .

 

Accepted 9 August, 2011

 

 Abstract

 

Normalized difference vegetation index (NDVI) is an important index characterizing the growth dynamics of plants. During the growth process of plants, NDVI value gradually increases, reaching its maximum at a certain stage of its growth period and then gradually dwindle. The variation curve of NDVI varies for different plants. Due to its high time resolution, Moderate Resolution Imaging Spectrometer–Normalized difference vegetation index (MODIS-NDVI) data can be applied to the study on the NDVI’s variation of agro-ecosystem. The analysis on the NDVI’s variation characteristics in different cropping systems of the agro-ecosystem of south bank Hangzhouwan Bay (Southeast Shanghai, China with north latitude of 30°02′ to 30°24′ and east longitude of 121°02′ to 121°42′) was conducted by employing the field investigation data and remote sensing data of 23 time sequences synthesized by MODIS-NDVI 16d in 2002. The results indicate that NDVI curves of different cropping systems are characterized by specific variation law. NDVI feature model extracted from different cropping systems based on MODIS-NDVI data can be used for the analysis of the cropping system of the agro-ecosystem, providing basic data for remote sensing yield estimation.

 

Key words: MODIS – NDVI, agro-ecosystem, cropping system, seasonal dynamics.

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