[1]王晶晶,兰仕浩,邱琳,等.基于哨兵二号的大豆、玉米遥感识别——以江苏徐淮地区为例[J].江苏农业学报,2023,(08):1698-1706.[doi:doi:10.3969/j.issn.1000-4440.2023.08.009]
　WANG Jing-jing,LAN Shi-hao,QIU Lin,et al.Recognition of corn and soybean based on Sentinel-2 imagery: a case study in Xuhuai area, Jiangsu province[J].,2023,(08):1698-1706.[doi:doi:10.3969/j.issn.1000-4440.2023.08.009]
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基于哨兵二号的大豆、玉米遥感识别——以江苏徐淮地区为例()
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江苏农业学报[ISSN:1006-6977/CN:61-1281/TN]

卷:
期数:
2023年08期
页码:
1698-1706
栏目:
农业信息工程
出版日期:
2023-12-31

文章信息/Info

Title:
Recognition of corn and soybean based on Sentinel-2 imagery: a case study in Xuhuai area, Jiangsu province
作者:
王晶晶1;  兰仕浩2;  邱琳1;  汪曙1;  单捷1;  黄晓军1;  李牧1
(1.江苏省农业科学院农业信息研究所,江苏南京210014;2.南京信息工程大学遥感与测绘工程学院,江苏南京210044)
Author(s):
WANG Jing-jing1; LAN Shi-hao2; QIU Lin1; WANG Shu1; SHAN Jie1; HUANG Xiao-jun1; LI Mu1
(1.Institute of Agricultural Information, Jiangsu Academy of Agricultural Sciences, Nanjing 210014, China;2.School of Remote Sensing and Geomatics Engineering, Nanjing University of Information Science and Technology, Nanjing 210044, China)
关键词:
玉米; 大豆; 哨兵二号影像; 特征选择; 遥感识别
Keywords:
corn; soybean; Sentinel-2 imagery; feature selection; remote sensing identification
分类号:
TP79
DOI:
doi:10.3969/j.issn.1000-4440.2023.08.009
文献标志码:
A
摘要:
本研究以哨兵二号影像为数据源,以江苏徐淮地区邳州市西南部作为研究区,开展大豆、玉米遥感识别研究。采用覆盖玉米和大豆主要生长期的多时相哨兵二号影像构建遥感特征参数数据集,包括12个光谱波段的反射率和47个植被指数,采用递归特征消除与随机森林、支持向量机相结合的算法开展特征参数优选,明确最优识别时相-特征参数组合,在此基础上,采用随机森林和支持向量机分类器进行分类,并比较分类精度。研究结果表明,利用特征参数优选方法提取最优特征参数组合,在保证总体精度的前提下能够减少特征参数数量；陆地水指数和倒数差值等植被指数是2种优选算法所提取出的共性特征参数；9月8日是研究区玉米和大豆遥感识别的最佳时相,总体精度和Kappa系数均为0.99。
Abstract:
In this study, the southwest of Pizhou City of Xuhuai area, Jiangsu province, China, was taken as the study area, and multi-temporal Sentinel-2 images covering the main growing period of the corn and soybean were adopted to build the multi-temporal candidate features data set including the reflectance of 12 spectral bands and 47 vegetation indices. Two machine-learning algorithms, i.e., random forest and support vector machine combined with the recursive feature elimination process were employed and their respective performance in crop identification was evaluated to determine the optimal characteristic parameters of remote sensing identification with the best recognition time phases of corn and soybean. Results indicated that feature parameter selection method could be used to extract the optimal feature parameter combination and reduce the number of feature parameters under the premise of ensuring the overall accuracy. The combination of features of multiple time phases obtained by the two algorithms had some of the same preferred feature parameters including land surface water index and derivative difference vegetation index. The classification accuracy analysis showed that September 8 was the best phase for corn and soybean recognition in this study with the overall accuracy and kappa coefficient of 0.99.

参考文献/References:

[1]郭伟,赵春江,顾晓鹤,等. 乡镇尺度的玉米种植面积遥感监测 [J]. 农业工程学报,2011,27(9):69-74.
[2]MATHUR A, FOODY G. Crop classification by support vector machine with intelligently selected training data for an operational application [J]. International Journal of Remote Sensing,2008,29:2227-2240.
[3]陈仲新,任建强,唐华俊,等. 农业遥感研究应用进展与展望 [J]. 遥感学报,2016,20(5):748-767.
[4]杨邦杰. 农情遥感监测[M]. 1版.北京:中国农业出版社,2005.
[5]许青云,杨贵军,龙慧灵,等. 基于MODIS-NDVI多年时序数据的农作物种植识别 [J]. 农业工程学报,2014,30(11):134-144.
[6]唐华俊. 农业遥感研究进展与展望 [J]. 农学学报,2018,8(1):167-171.
[7]董金玮,吴文斌,黄健熙,等. 农业土地利用遥感信息提取的研究进展与展望 [J]. 地球信息科学学报,2020,22(4):772-783.
[8]DE SOUZA C H W, MERCANTE E, JOHANN J A, et al. Mapping and discrimination of soya bean and corn crops using spectro-temporal profiles of vegetation indices [J]. International Journal of Remote Sensing,2015,36:1809-1824.
[9]DA SILVA JUNIOR C A, NANNI M R, TEODORO P E, et al. Vegetation indices for discrimination of soybean areas: a new approach [J]. Agronomy Journal,2017,109:1331-1343.
[10]ZHONG L H, HU L N, YU L, et al. Automated mapping of soybean and corn using phenology [J]. ISPRS Journal of Photogrammetry and Remote Sensing,2016,119:151-164.
[11]刘佳,王利民,滕飞,等. RapidEye卫星红边波段对农作物面积提取精度的影响 [J]. 农业工程学报,2016,32(13):140-148.
[12]YIN L K, YOU N S, ZHANG G L, et al. Optimizing feature selection of individual crop types for improved crop mapping[J]. Remote Sensing,2020,12(1):1-20.
[13]FOERSTER S, KADEN K, OERSTER M, et al. Crop type mapping using spectral-temporal profiles and phenological information [J]. Computers and Electronics in Agriculture,2012,89:30-40.
[14]HU Q, SULLA D, XU B D, et al. A phenology-based spectral and temporal feature selection method for crop mapping from satellite time series [J]. International Journal of Applied Earth Observation and Geoinformation,2019,80:218-229.
[15]黄健熙,侯矞焯,苏伟,等. 基于GF-1 WFV数据的玉米与大豆种植面积提取方法 [J]. 农业工程学报,2017,33(7):164-170.
[16]DEFRIES R, TOWNSHEND J. NDVI-derived land classifications at a global scale [J]. Journal of Remote Sensing,1994,17:3567-3586.
[17]GITELSON A A, KAUFMAN Y J, MERZLYAK M N. Use of a green channel in remote sensing of global vegetation from EOS-MODIS [J]. Remote Sensing of Environment,1996,58:289-298.
[18]JORDAN C F. Derivation of leaf-area index from quality of light on the forest floor [J]. Ecology,1969,50:663-666.
[19]GITELSON A A, MERALYAK M N. Spectral reflectance changes associated with autumn senescence of Aesculus hippocastanum L. and Acer platanoides L. leaves. Spectral features and relation to chlorophyll estimation [J]. Journal of Plant Physiology,1994,143:286-292.
[20]CHAPPELLE E W, KIM M S, MC MURTREY J E. Ratio analysis of reflectance spectra (RARS): an algorithm for the remote estimation of the concentrations of chlorophyll A, chlorophyll B, and carotenoids in soybean leaves [J]. Remote Sensing of Environment,1992,39:239-247.
[21]SIMS D A, GAMON J A. Relationships between leaf pigment content and spectral reflectance across a wide range of species, leaf structures and developmental stages [J]. Remote Sensing of Environment,2002,81:337-354.
[22]HUETE A R. A soil-adjusted vegetation index(SAVI) [J]. Remote Sensing of Environment,1988,25:295-309.
[23]RICHARDSON A J, EVERITT J H. Using spectral vegetation indices to estimate rangeland productivity [J]. Geocarto International,1992,7:63-69.
[24]GITELSON A, SOLOVCHENKO A. Non-invasive quantification of foliar pigments: Possibilities and limitations of reflectance- and absorbance-based approaches [J]. Journal of Photochemistry and Photobiology B-Biology,2018,178:537-544.
[25]HUETE A, JUSTICE C, LIU H. Development of vegetation and soil indices for MODIS-EOS [J]. Remote Sensing of Environment,1994,49:224-234.
[26]XIAO X, BOLES S, LIU J, et al. Characterization of forest types in Northeastern China, using multi-temporal SPOT-4 VEGETATION sensor data [J]. Remote Sensing of Environment,2002,82:335-348.
[27]BANNARI A, ASALHI H, TEILLET P M. Transformed difference vegetation index(TDVI) for vegetation cover mapping [C]. Toronto, Canada: IGARSS,2002:3053-3055.
[28]RONDEAUX G, STEVEN M, BARET F. Optimization of soil-adjusted vegetation indices [J]. Remote Sensing of Environment,1996,55:95-107.
[29]GITELSON A A. Wide dynamic range vegetation index for remote quantification of biophysical characteristics of vegetation [J]. Journal of Plant Physiology,2004,161:165-173.
[30]GITELSON A A, KAUFMAN Y J, STARK R, et al. Novel algorithms for remote estimation of vegetation fraction [J]. Remote Sensing,2002,80:76-87.
[31]GOEL N S, QIN W. Influences of canopy architecture on relationships between various vegetation indices and LAI and FPAR: a computer simulation [J]. Remote Sensing Reviews,1994,10:309-347.
[32]GONG P, PU R, BIGING G S, et al. Estimation of forest leaf area index using vegetation indices derived from Hyperion hyperspectral data [J]. IEEE Transactions on Geoscience and Remote Sensing,2003,41:1355-1362.

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备注/Memo

备注/Memo:
收稿日期:2022-11-07基金项目:江苏省农业科技自主创新基金项目[CX(22)2001]作者简介:王晶晶(1981-) , 女 , 江苏扬州人, 博士, 副研究员 , 主要从事农业遥感应用研究。 (E-mail)immi103@163.com
更新日期/Last Update: 2024-01-15