1. 北京农业信息技术研究中心，北京 100097 2. 安徽省农业生态大数据工程实验室，安徽大学，安徽 合肥 230601 3. 农业部农业信息技术重点实验室，北京 100097 4. 华南农业大学工学院，广东 广州 510642 5. Texas A&M AgriLife Research and Extension Center, Beaumont, TX 77712, USA
Assessment of Aerial Agrichemical Spraying Effect Using Moderate-Resolution Satellite Imagery
ZHANG Dong-yan1, 2, 3, LAN Yu-bin4, 5, WANG Xiu1, 3, ZHOU Xin-gen5, CHEN Li-ping1, 3*, LI Bin1, 3, MA Wei1, 3
1. Beijing Research Center for Information Technology in Agriculture, Beijing 100097, China 2. Anhui Engineering Laboratory of Agro-Ecological Big Data, Anhui University, Hefei 230601, China 3. Key Laboratory of Agri-informatics, Ministry of Agriculture, Beijing 100097, China 4. College of Engineering, South China Agricultural University, Guangzhou 510642, China 5. Texas A&M AgriLife Research and Extension Center, Beaumont, TX 77713, USA
Abstract：Remote sensing technique can be used to examine the effects of agrichemical application on the performance of field crops at a large scale in an effort to develop precision agricultural aerial spraying technology. In this study, an airplane M-18B at the 4-m flight height was used to spray a mix of agrichemicals (a fungicide and a plant growth regulator) to control rice leaf blast disease and improve the growth vigor of rice plants in the field. After the aerial spraying, satellite imagery of tested area was acquired and processed to calculate vegetation indices (VIs). Ground agrichemical concentration data were also collected. The relationships between droplets deposition and VIs were analyzed. The results indicated that the highest correlation coefficient between single phase spectral feature (NDVI) and droplets deposition points density (DDPD, points·cm-2) was 0.315 with P-value of 0.035 while the highest correlation coefficient between temporal change characteristic (MSAVI) and droplets deposition volume density (DDVD, μL·cm-2) was 0.312 with P-value of 0.038). Rice plants with the greatest growth vigor were all detected within the spraying swath, with a gradual decrease in the vigor of rice plants with the increase of droplets drift distance. There were similar trend patterns in the changes of the spraying effects based on the spatial interpolation maps of droplets deposition data and spectral characteristics. Therefore, vegetation indexes, NDVI and MSAVI calculated from satellite imagery can be used to determine the aerial spraying effects in the field on a large scale.
[1] Acharya K, Dutta A K, Pradhan P. Australian Journal of Crop Science, 2011, 5： 1064. [2] Mirik M, Michels G J, Jr Kassymzhanova-Mirik S, et al. Computers and Electronics in Agriculture, 2007, 57(2): 123. [3] Rakhesh Devadas. University of New England, Armidale, New South Wales, Australia, 2009. [4] Zhao Jinling, Huang Linsheng, Huang Wenjiang, et al. Europe Journal of Plant Pathology, 2014, 139: 407. [5] Lan Yubin, Thomson Steven J, Huang Yanbo, et al. Computers and Electronics in Agriculture, 2010, 74: 34. [6] Lan Yubin, Huang Yanbo, Martin Daniel E, et al. Applied Engineering in Agriculture, 2009, 25(4): 607. [7] Zhou Zhiyan, Zang Ying, Luo Xiwen, et al. Transactions of the Chinese Society of Agricultural Engineering, 2013, 29(24): 1. [8] Xue Xinyu, Lan Yubin. Transactions of the Chinese Society for Agricultural Machinery, 2013，44(5): 194. [9] Zhang Dongyan, Lan Yubin, Chen Liping, et al. Transactions of the Chinese Society of Agricultural Machinery, 2014, 45(10): 53. [10] Mirik M, Michels G J, Jr Kassymzhanova-Mirik S, et al. Computers and Electronics in Agriculture, 2006, 5： 86. [11] Huang Wenjiang, Lamb David W, Niu Zheng, et al. Precision Agriculture, 2007, 8: 187. [12] Yang Chwen-ming. Precision Agriculture, 2009, 11(1): 61. [13] Larsolle A, Muhammed H H. Precision Agriculture, 2007, 8: 37. [14] Huang Linsheng, Zhao Jinling, Zhang Dongyan, et al. International Journal of Agriculture and Biology, 2012, 14: 697. [15] Zhang Minghua, Qin Zhihao, Liu Xue. International Journal of Applied Earth Observation and Geoinformation, 2003, 4(4): 295. [16] Qin Zhihao, Zhang Minghua. International Journal of Applied Earth Observation and Geoinformation, 2005, 7: 115. [17] Huang Y, Thomson S J, Ortiz B V, et al. Biosystems Engineering, 2010, 107(3): 212. [18] Ortiz B V, Thomson S J, Huang Y, et al. Computers and Electronics in Agriculture, 2011, 77(2): 204. [19] Huang Y, Thomson S J, Hoffman W C, et al. International Journal of Agricultural and Biological Engineering, 2013, 6(3): 1. [20] Zhang H, Lan Y, Lacey R, et al. International Journal of Agricultural and Biological Engineering, 2009, 2: 1. [21] Zhang Jingcheng, Huang Wenjiang, Li Jiangyuan, et al. Precision Agriculture, 2010，12(5): 716. [22] Yuan Lin, Zhang Jingcheng, Shi Yeyin, et al. Remote Sensing, 2014, 6： 3611. [23] http://www.cresda.com/. [24] Zhang Jingcheng, Pu Ruiliang, Yuan Lin, et al. PLoS ONE, 2014, 9(4): e93107. [25] Yuan Lin, Zhang Jingcheng, Zhao Jinling, et al. Optik, 2013, 124: 4734. [26] Tyler J Nigon, David J Mulla, Carl J Rosen, et al. Computers and Electronics in Agriculture, 2015, 112: 36. [27] Maurer. International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XL-1/W1, ISPRS Hannover Workshop, 21- 24 May 2013, Hannover, Germany.
