遥感光谱技术在农作物估产中的应用研究进展
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摘要
农作物产量是一个国家或地区的重要经济信息,关系着国家和区域粮食安全,对农业规划布局、政策调整及可持续发展等方面具有重要意义。农作物遥感估产主要包括作物识别和产量评估2项主要环节,文章通过总结农作物遥感识别与产量估算的研究现状,以其依据的特征不同、针对的目标不同对现有的作物识别分为2类进行总结;根据数据源与评估模型原理的区别将现有作物遥感估产方法总结为4类,对其方法、原理和应用要点进行总结,讨论分析了各类方法的优势和仍需完善的问题,并对今后的发展趋势进行了展望。
Crop yield is the important economic information for a country or region, it is related to national and regional food security, which is of great significance to the layout of agricultural planning, policy adjustment and sustainable development. The remote sensing estimation of crop mainly includes crop identification and evaluation. This paper summarizes the research status of crop remote sensing identification and yield estimation, and according to their different characteristics and targets, divides existing crop identification into two categories. Based on the difference between data source and evaluation model principle, this paper classifies existing crop yield estimation methods into four categories, summarizes methods, principles and application points, and discusses the advantages of various methods and presents the problems need to be improved. Finally, this paper forecasts the research trend in this field.
Crop yield is the important economic information for a country or region, it is related to national and regional food security, which is of great significance to the layout of agricultural planning, policy adjustment and sustainable development. The remote sensing estimation of crop mainly includes crop identification and evaluation. This paper summarizes the research status of crop remote sensing identification and yield estimation, and according to their different characteristics and targets, divides existing crop identification into two categories. Based on the difference between data source and evaluation model principle, this paper classifies existing crop yield estimation methods into four categories, summarizes methods, principles and application points, and discusses the advantages of various methods and presents the problems need to be improved. Finally, this paper forecasts the research trend in this field.
引文
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[8]张喜旺,刘剑锋,秦奋,等.作物类型遥感识别研究进展[J].中国农学通报,2014,30(33):278-285.
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[10]梅安新,彭望琭,秦其明,等.遥感导论[M].北京:高等教育出版社,2001.
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[12] Patil A, Ishwarappa R K. Classification of crops using FCM segmentation and texture, color feature[J].World Journal of Science and Technology,2013,2(10):371-376.
[13]唐华俊,吴文斌,杨鹏,等.农作物空间格局遥感监测研究进展[J].中国农业科学,2010,43(14):2879-2888.
[14]胡琼,吴文斌,宋茜,等.农作物种植结构遥感提取研究进展[J].中国农业科学,2015,48(10):1900-1914.
[15]杨鹏,唐华俊,刘佳.作物遥感估产中自动分类方法研究进展与展望[J].中国农业资源与区划,2000,21(3):57-60.
[16]范燕敏,钟骏平,武红旗,等.用ETM+数据及ArcviewGIS编制1:25000农业土地利用及作物分布图[J].新疆农业大学学报,2001,24(1):31-34.
[17]杨武德,宋艳暾,宋晓彦,等.基于3S和实测相结合的冬小麦估产研究[J].农业工程学报,2009,25(02):131-135,315.
[18]王召海.棉花种植面积遥感调查研究[J].遥感信息,1999(01):29-32.
[19]林文鹏,王长耀,储德平,等.基于光谱特征分析的主要秋季作物类型提取研究[J].农业工程学报,2006,22(09):128-132.
[20]熊勤学,黄敬峰.利用NDVI指数时序特征监测秋收作物种植面积[J].农业工程学报,2009,25(1):144-148.
[21] Van Niel T G, Mcvicar T R. Determining temporal windows for crop discrimination with remote sensing:a case study in southeastern Australia[J].Computers and Electronics in Agriculture,2004,45(1):91-108.
[22] Hartfield K A, Marsh S E, Kirk C D, et al. Contemporary and historical classification of crop types in Arizona[J].International Journal of Remote Sensing,2013,34(17):6024-6036.
[23]郑长春,王秀珍,黄敬峰.基于特征波段的SPOT-5卫星影像水稻面积信息自动提取的方法研究[J].遥感技术与应用,2008,23(3):294-299.
[24] Jia K, Wu B, Li Q. Crop classification using HJ satellite multispectral data in the North China Plain[J].Journal of Applied Remote Sensing,2013,7(1):073576.
[25]林忠辉,莫兴国.NDVI时间序列谐波分析与地表物候信息获取[J].农业工程学报,2006,22(12):138-144.
[26]杨小唤,张香平,江东.基于MODIS时序NDVI特征值提取多作物播种面积的方法[J].资源科学,2004,26(6):17-22.
[27]刘良云,张兵,郑兰芬,等.利用温度和植被指数进行地物分类和土壤水分反演[J].红外与毫米波学报,2002,21(4):269-273.
[28]宫鹏.遥感科学与技术中的一些前沿问题[J].遥感学报,2009,13(1):13-23.
[29] Ozdogan M. The spatial distribution of crop types from MODIS data:Temporal unmixing using Independent Component Analysis[J].Remote Sensing of Environment,2010,114(6):1190-1204.
[30] Hongbo Q, Dengfa C. Application of EOS/MODIS-NDVI at different time sequences on monitoring winter wheat acreage in Henan Province[J].Agricultural Science&Technology,2008,2(27):113-115.
[31]蒋楠,李卫国,杜培军.不同遥感数据融合方法在南方水稻面积监测中的应用研究[J].西南大学学报,2012,34(6):20-24.
[32]张锦水,申克建,潘耀忠,等.HJ-1号卫星数据与统计抽样相结合的冬小麦区域面积估算[J].中国农业科学,2010,43(16):3306-3315.
[33]刘磊,江东,徐敏,等.基于多光谱影像和专家决策法的作物分类研究[J].安徽农业科学,2011,39(25):15809-15811.
[34]赵英时.遥感应用分析原理与方法[M].北京:科学出版社,2003.
[35] Ballantine J A C, Okin G S, Prentiss D E, et al. Mapping north African landforms using continental scale unmixing of MODIS imagery[J].Remote Sensing of Environment,2005,97(4):470-483.
[36] Busetto L, Meroni M, Colombo R. Combining medium and coarse spatial resolution satellite data to improve the estimation of subpixel NDVI time series[J].Remote Sensing of Environment,2008,112(1):118-131.
[37]蔡薇,郭洪海,隋学艳,等.基于混合像元分解提取小麦种植面积的技术与方法研究[J].山东农业科学,2009(5):12-16.
[38]王启田,林祥国,王志军,等.利用面向对象分类方法提取冬小麦种植面积的研究[J].测绘科学,2008,33(2):143-146.
[39]许文波,张国平,范锦龙,等.利用MODIS遥感数据监测冬小麦种植面积[J].农业工程学报,2007,23(12):144-149,325.
[40]朱长明,骆剑承,沈占锋,等.基于地块特征基元与多时相遥感数据的冬小麦播种面积快速提取[J].农业工程学报,2011,27(9):94-99.
[41]李乐,张锦水,朱文泉,等.地块支持下MODIS-NDVI时间序列冬小麦种植面积测量研究[J].光谱学与光谱分析,2011,31(5):1379-1383.
[42]王久玲,黄进良,王立辉,等.面向对象的多时相HJ星影像甘蔗识别方法[J].农业工程学报,2014,30(11):145-151.
[43]范磊,程永正,王来刚,等.基于多尺度分割的面向对象分类方法提取冬小麦种植面积[J].中国农业资源与区划,2010,31(6):44-51.
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