Monitoring the Plant Density of Cotton with Remotely Sensed Data Junhua Bai Jing Li,and Shaokun Li 1Institute of Crop Sciences,Chinese Academy of Agriculture Sciences, Beijing 100081,P.R.China Tel:+861082108891 shaokun0004@sina.com 2 State Key Laboratory of Remote Sensing Science.Jointly Sponsored by the Institute of ese emy of Sc ences and Beijing 01.P.E niversity. China Abstract.PDC(Plant Density of Cotton)was an essential parameter for esti- mating the cotton yield and developing the zone-management measurements This paper proposed a new method to retrieve PDC from the satellite remote sensing data.The thirteen fields of Xinjiang Production and Construction Corps (XPCC)(total 630 hm2)were selected as the study area,where the sowing date emergence date,and PDC were investigated.Based on the investigation data the linear models to estimate PDC are established using EVI and DEVI respec tively.The results indicated that the difference of seedling size caused by the emergence time decreased the estim tion accuracy o To improve the e uracy were estab I in te ng the 01 Tring the n fom Jun licated tha the optim ng PD 0h 48 per of XPCC It luded that the tin nd th y of PDC and the vith the e time could i h DEV could make the mont ring time fom ard,and the optimal monitoring time was from the squa ring stage to the full-flowering s .This res arch provides ar efficient,rapid and intact way to monitor PDC.and it is significant for opera- tional application at a regional scale. Keywords:Cotton,Plant Density,Remote sensing. 1 Introduction PDC (Plant Density of Cotton)is one of key factors affecting cotton vield.and is the most important index for analyzi ing cott on growth and taking the management Corresponding author. D.Li,Y.Liu,and Y.Chen (Eds.):CCTA 2010.Part II,IFIP AICT 345.pp.90-101.2011. IFIP International Federation for Information Processing 2011 D. Li, Y. Liu, and Y. Chen (Eds.): CCTA 2010, Part II, IFIP AICT 345, pp. 90–101, 2011. © IFIP International Federation for Information Processing 2011 Monitoring the Plant Density of Cotton with Remotely Sensed Data Junhua Bai1,2,3, Jing Li2 , and Shaokun Li1,* 1 Institute of Crop Sciences, Chinese Academy of Agriculture Sciences, Beijing 100081, P. R. China Tel.: +86 10 82108891 shaokun0004@sina.com 2 State Key Laboratory of Remote Sensing Science, Jointly Sponsored by the Institute of Remote Sensing Applications of Chinese Academy of Sciences and Beijing Normal University, Beijing 100101, P. R. China 3 College of Agricultural Sciences of Shihezi University, Shihezi Xinjiang, 832003, P. R. China Abstract. PDC (Plant Density of Cotton) was an essential parameter for esti￾mating the cotton yield and developing the zone-management measurements. This paper proposed a new method to retrieve PDC from the satellite remote sensing data. The thirteen fields of Xinjiang Production and Construction Corps (XPCC) (total 630 hm2 ) were selected as the study area, where the sowing date, emergence date, and PDC were investigated. Based on the investigation data the linear models to estimate PDC are established using EVI and DEVI respec￾tively. The results indicated that the difference of seedling size caused by the emergence time decreased the estimation accuracy of PDC. To improve the es￾timation accuracy the partition functions were established in terms of sowing date. DEVI is capable of reducing the influence of soil background significantly and it can bring the monitoring time forward from June 9th to May 24th in this research. The results indicated that the optimal time monitoring PDC would be from squaring to full-flowering of cotton growing period. A demonstration to monitor PDC was taken on June 9th in the 148th farm of XPCC. It can be con￾cluded that the emergence time and the non-cotton background were the main factors affecting the monitoring accuracy of PDC, and the partition function with the emergence time could improve the estimation accuracy, and DEVI could make the monitoring time forward, and the optimal monitoring time was from the squaring stage to the full-flowering stage. This research provides an efficient, rapid and intact way to monitor PDC, and it is significant for opera￾tional application at a regional scale. Keywords: Cotton, Plant Density, Remote sensing. 1 Introduction PDC (Plant Density of Cotton) is one of key factors affecting cotton yield, and is the most important index for analyzing cotton growth and taking the management * Corresponding author