Cotton Area and Yield Estimation at Zhanhua County of China Using HJ-1 EVI Time Series

Xin-Yang Li,T Yang,T Gong,Gao-Huan Liu,Chong Huang,J Xu,Yu-Shan Guo,Qing-Sheng Liu

doi:10.1051/itmconf/20160709001

Abstract

Cotton is a significant cash crop of China. Timely and accurate cotton area and yield estimation is useful for management decisions related to the cotton procurement and sales. This study is a first research on cotton area and yield estimation based on remote sensing at Zhanhua County which is one of the high-quality cotton production demonstration bases of China. After normalization of Enhanced Vegetation Index (EVI) time series derived from Huanjin 1 A/B satellite (HJ-1 A/B), decision tree classifier was used to identify the cotton, and then K-Means classifier was applied to estimate cotton yield. The results indicated an overall accuracy of 95% for the cotton area estimation and 91% for the cotton yield classification. With further validation, it suggests that this method can be used to timely achieve the cotton area and growth information of this region.

Highlights

Cotton is a significant cash crop of China which is mainly planted in Xinjiang, Henan, Shandong, Hebei Province and so on [1]
And accurate cotton area and yield estimation is useful for management decisions related to the cotton procurement, sales, import and export program of a country [2, 3]
It is easy to acquire the images of crop growing season and improve the cotton acreage and yield estimation accuracy

Summary

Introduction

Cotton is a significant cash crop of China which is mainly planted in Xinjiang, Henan, Shandong, Hebei Province and so on [1]. Remote sensing imagery can offer a repeated unbiased view of large areas, and has been widely used to estimate crop yields. Lots of studies have shown that cotton area and yield can be efficiently estimated by remote sensing [2,3,4,5,6,7,8,9,10,11,12,13]. Landsat Thematic Mapper (Landsat TM), Indian Remote Sensing (IRS), China-Brazil Earth Resource Satellite (CBERS) and Huanjin (HJ-1 A/B) satellite with the higher spatial resolution are often used to estimate cotton yields at regional and field levels [2, 3, 8, 11,12,13]. Site-specific lint yields were estimated using field soil and multispectral images data [4, 5, 9, 10]

Objectives

Methods

Results

Conclusion