The estimation of cotton-growing areas by Remote Sensing
Li Zewen, Jiang Dong, Lu Denghuai
China Institute of Land Survey & Planning
Zhang Cuizhi
Beijing Municipal Academy of Agriculture &
Forestry Science
Abstract
From 1986 to 1990, using remote sensing, the authors estimated the cotton-growing areas in Henan province, China, surveyed the farming calendar of the main crops, studied the development features, and the spectral reflectance, selected the Landsat TM digital image of cotton's heading initial and middle periods of ripening, adopted the maximum likelihood method to conduct the supervised classification of TM images. We gained data and distribution of cotton-growing areas. The research proves that it is feasible to use remote sensing technology to estimate the cotton-growing areas. The methodology has features of strong objectivity, high speed and low cost. It provides a reliable technological method to monitor cotton-growing areas.
Preface
The cotton-growing areas in china are obtained by the way of presenting the itemized report to the higher level. This way will be affected by man-made factors and limited by the presenting time and statistic method. It is impossible to obtain the accurate data of cotton-growing areas in time. But using remote sensing to estimate the cotton-growing areas before harvest, so that it can provide important basis for decision-making departments to estimate the cotton yield in advance.
General situation of test area
Huojia county lies on Northern Henan plain, with 437.15 km2 in area. It possesses abundant resources of water, soil, climate and organisms. The terrain is smooth, the traffic convenient, the condition of social economic technology better and the level of productivity higher. The dominant crops are wheat, rice, maize, cotton and soybean, etc.
The main contents of the research
The particular contents are as follow:
- To research the crop growth and development features of cotton, wheat, maize, rice and soybean, etc. to seek the development characteristics of other crops; and to seek the maximum difference of growing period between cotton and other crops;
- To determine the spectral reflectance of cotton in different growing periods so as to provide basis to select the best band in TM data to identify cotton;
- To select the types and acquired data of remote sensing data;
- To select proper classification method in order to improve the accuracy of estimation of the cotton-growing areas.
The development features of cotton and
farming calender of the test area
Cotton is perennial woody plant, originated in tropical and subtropical grassland with features of high temperature, drought and short time of sunshine. it has been changed into annual plant after having introduced a fine variety, cultivated and domesticated by human beings for a long term the life of cotton begins with the germination of seeds, the develops into the vegetative growth i.e. growing roots, increasing leaves, growing stems, branching, etc., on this basis, conduct the development of reproduction of squaring, heading, flowering, yield formation and ripening, etc. and finishes its life till the seeds are ripen. According to the order of the formation of its organs and the process of development, the development of cotton can be divided into five growing periods: germination and emerge period vegetative period (including establishment and head development periods), flowering period, yield formation period and ripening period. [2]
In order to seek the maximum difference of growing periods between cotton and other crops, we
have surveyed the farming calender of dominant crops of wheat, maize, soybean and
cotton in the test area. The development of these crops is as Table 1.
Table 1. Table of growth and development of dominant crops
From Table 1. we can see that in the periods of flowering and ripening the difference of growing situation between cotton and other crops is the largest, so the difference shown on the satellite image should be the largest. it is most suitable to choose the satellite image of cotton's flowering or ripening period to conduct classification.
