黑土区田块尺度遥感精准管理分区
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摘要
基于格网采样与空间插值的精准管理分区方法精度高,但时效性差、成本高。本文以东北农垦地区红星农场农田为研究对象,提出一种基于遥感影像的精准管理分区方法:以裸土高空间分辨率遥感影像作为数据源,结合田间格网采样数据,基于裸土反射光谱特征与黑土主要理化性质的显著相关关系,运用面向对象分割、空间统计分析方法,对典型黑土区田块进行精准管理分区研究,并利用土壤理化性质和农作物生理参数,对分区结果进行评价。得出如下结论:(1)典型黑土区田块内部土壤养分含量空间变异显著;(2)基于裸土影像与面向对象的精准管理分区方法精度高,增强了分区之间的土壤养分与归一化植被指数(NDVI)差异性、分区内部各属性的一致性;(3)基于2015年4月1日和2015年5月20日单期影像分区和两期影像波段叠加(Layer stacking)分区,区间变异系数与区内变异系数之比分别为1.42、1.39和7.63,基于两期影像综合信息的分区结果显著优于基于单期影像分区;(4)基于裸土影像面向对象分割的精准管理分区方法时效性强、成本低、精度高。研究成果为田间变量施肥、发展精准农业、实现农业可持续发展提供依据。
Although the precision management-partition method, which is based on grid sampling and spatial interpolation, is highly precise,It has poor timeliness and high costs. Thus, this study proposes a precise management-partition method based on remote sensing images.Hongxing farm fields in the northeast agricultural reclamation area are used as the research objects. High-resolution remote sensing images of bare soil and grid sampling data in the field are utilized as data sources. This study focuses onsite-specific management zone in atypical black soil area. Management is based on the significant correlation between the spectral reflectance characteristics of bare soil and the main physical and chemical properties of black soil. In addition, the zoning result is evaluated using the soil's physical and chemical properties and physical physiological parameters of crops. The object-oriented segmentation and spatial statistical analysis methods are utilized in this study. The following conclusions are drawn:(1) The spatial variation of soil nutrients is significantly distinct in the typical black soil field.(2) The site-specific management zone, which is based on a bare soil image and highly accurate object-oriented segmentation, enhances the differences of soil nutrients, the normalized difference vegetation indexes between zones, and the consistency in zones.(3) The two images obtained on May 20 th and April 1stare processed into single image and double image partitions. The ratios of inter zone to in zone variable coefficients is 1.42, 1.39, and 7.63, which prove that the result of the site-specific management zone that is based on double images is better than those based on a single image.(4) The precision management-partition method that is based on the bare soil image and segmentation technique has strong timeliness, low cost, and good accuracy. Results of the study provide the basis for field variable fertilization, development of intelligent precision agriculture, and sustainable agricultural development.
Although the precision management-partition method, which is based on grid sampling and spatial interpolation, is highly precise,It has poor timeliness and high costs. Thus, this study proposes a precise management-partition method based on remote sensing images.Hongxing farm fields in the northeast agricultural reclamation area are used as the research objects. High-resolution remote sensing images of bare soil and grid sampling data in the field are utilized as data sources. This study focuses onsite-specific management zone in atypical black soil area. Management is based on the significant correlation between the spectral reflectance characteristics of bare soil and the main physical and chemical properties of black soil. In addition, the zoning result is evaluated using the soil's physical and chemical properties and physical physiological parameters of crops. The object-oriented segmentation and spatial statistical analysis methods are utilized in this study. The following conclusions are drawn:(1) The spatial variation of soil nutrients is significantly distinct in the typical black soil field.(2) The site-specific management zone, which is based on a bare soil image and highly accurate object-oriented segmentation, enhances the differences of soil nutrients, the normalized difference vegetation indexes between zones, and the consistency in zones.(3) The two images obtained on May 20 th and April 1stare processed into single image and double image partitions. The ratios of inter zone to in zone variable coefficients is 1.42, 1.39, and 7.63, which prove that the result of the site-specific management zone that is based on double images is better than those based on a single image.(4) The precision management-partition method that is based on the bare soil image and segmentation technique has strong timeliness, low cost, and good accuracy. Results of the study provide the basis for field variable fertilization, development of intelligent precision agriculture, and sustainable agricultural development.
引文
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Liu H J,Zhang B,Liu Z M,Song K S,Wang Z M and Duan H T.2007.Spectral analysis of soils in Songnen plain,northeastern China.Journal of the Graduate School of the Chinese Academy of Sciences,24(4):439-445(刘焕军,张柏,刘志明,宋开山,王宗明,段洪涛.2007.松嫩平原主要土壤光谱特征分析.中国科学院研究生院学报,24(4):439-445)[DOI:10.3969/j.issn.1002-1175.2007.04.006]
Liu H J,Zhao C J,Wang J H,Huang W J and Zhang X L.2011.Soil organic matter predicting with remote sensing image in typicalblacksoil area of Northeast China.Transactions of the CSAE,27(8):211-215(刘焕军,赵春江,王纪华,黄文江,张新乐.2011.黑土典型区土壤有机质遥感反演.农业工程学报,27(8):211-215)[DOI:10.3969/j.issn.1002-6819.2011.08.036]
Liu J F.2015.Research of spatial heterogeneity of soil organic matters and the influencing factors in Mangang section of Heshan farm.Daqing:Heilongjiang Bayi Agricultural University(刘剑飞.2015.鹤山农场漫岗地块土壤养分空间变异及影响因素分析.大庆:黑龙江八一农垦大学)
Milne A E,Webster R,Ginsburg D and Kindred D.2012.Spatial multivariate classification of an arable field into compact management zones based on past crop yields.Computers and Electronics in Agriculture,80:17-30[DOI:10.1016/j.compag.2011.10.007]
Mkhabela M S,Bullock P,Raj S,Wang S and Yang Y.2011.Crop yield forecasting on the Canadian prairies using MODIS NDVIdata.Agricultural and Forest Meteorology,151(3):385-393[DOI:10.1016/j.agrformet.2010.11.012]
Ostergaard H S.1999.Agronomic consequences of variable N fertilization//Stafford J V,ed.Proceedings of the 1st European Conference on Precision Agriculture.Oxford,UK:BIOS Scientific Publishers Ltd,145-153
Peng J,Zhou Q,Zhang Y Z and Xiang H Y.2013.Effect of soil organic matter on spectral characteristics of soil.Acta Pedologica Sinica,50(3):517-524(彭杰,周清,张杨珠,向红英.2013.有机质对土壤光谱特性的影响研究.土壤学报,50(3):517-524)[DOI:10.11766/trxb201207080277]
Shi G B.2011.Application of GPS and GIS technology in monitoring system of precision agriculture.Hubei Agricultural Science,50(10):1948-1950(史国滨.2011.GPS和GIS技术在精准农业监控系统中的应用研究进展.湖北农业科学,50(10):1948-1950)[DOI:10.3969/j.issn.0439-8114.2011.10.002]
Song X Y,Wang J H,Huang W J,Yan G J and Chang H.2009.Monitoring spatial variance of winter wheat growth and grain qualityunder variable-rate fertilization conditions by remote sensing data.Transactions of the CSAE,25(9):155-162(宋晓宇,王纪华,黄文江,阎广建,常红.2009.变量施肥条件下冬小麦长势及品质变异遥感监测.农业工程学报,25(9):155-162)[DOI:10.3969/j.issn.1002-6819.2009.09.028]
Song X Y,Wang J H,Liu L Y,Huang W J,Shen T and Yu Z Z.2007.Research of management zones generating based on Quickbird imagery.Scientia Agricultura Sinica,40(9):1996-2006(宋晓宇,王纪华,刘良云,黄文江,沈涛,喻铮铮.2007.基于Quickbird遥感影像的农田管理分区划分研究.中国农业科学,40(9):1996-2006)[DOI:10.3321/j.issn:0578-1752.2007.09.020]
Song X Y,Wang J H,Xue X Z,Liu L Y,Chen L P and Zhao C J.2004.Assessment of the influence of soil nitrogen supplies and variable fertilization on winter wheat growth condition using airborne hyperspectral image.Transactions of the CSAE,20(4):45-49(宋晓宇,王纪华,薛绪掌,刘良云,陈立平,赵春江.2004.利用航空成像光谱数据研究土壤供氮量及变量施肥对冬小麦长势影响.农业工程学报,20(4):45-49)[DOI:10.3321/j.issn:1002-6819.2004.04.010]
Wang S Q,Zhu S L and Zhou C H.2001.Characteristics of spatial variability of soil thickness in China.Geographical Research,20(2):161-169(王绍强,朱松丽,周成虎.2001.中国土壤土层厚度的空间变异性特征.地理研究,20(2):161-169)[DOI:10.3321/j.issn:1000-0585.2001.02.005]
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Chen C L and Wu G.2011.Evaluation of optimal segmentation scale with object-oriented method in remote sensing.Remote Sensing Technology and Application,26(1):96-102(陈春雷,武刚.2011.面向对象的遥感影像最优分割尺度评价.遥感技术与应用,26(1):96-102)
Chen Y and LüX.2008.Definition of management zones of soil nutrients based on FCM algorithmin in oasis field.Scientia Agricultura Sinica,41(7):2016-2024(陈彦,吕新.2008.基于FCM的绿洲农田养分管理分区研究.中国农业科学,41(7):2016-2024)[DOI:10.3864/j.issn.0578-1752.2008.07.019]
Fleming K L,Westfall D G,Wiens D W and Brodahl.2000.Evaluating farmer defined management zone maps for variable rate fertilizer application.Precision Agriculture,2(2):201-215[DOI:10.1023/A:1011481832064]
Frogbrook Z L and Oliver M A.2007.Identifying management zones in agricultural fields using spatially constrained classification of soil and ancillary data.Soil Use and Management,23(1):40-51[DOI:10.1111/j.1475-2743.2006.00065.x]
Hasegawa K,Matsuyama H,Tsuzuki H and Sweda T.2010.Improving the estimation of leaf area index by using remotely sensed NDVI with BRDF signatures.Remote Sensing Environment,114(3):514-519[DOI:10.1016/j.rse.2009.10.005]
Li F J,Song Z W,Liu S W,Wang J C and LüX J.2010.Study on monitoring system in facility agriculture.Tianjin Agricultural Sciences,16(1):127-129(李凤菊,宋治文,刘绍伟,王建春,吕雄杰.2010.监控系统在设施农业中的应用研究.天津农业科学,16(1):127-129)[DOI:10.3969/j.issn.1006-6500.2010.01.040]
Li M,Zhao G X,Cai M Q,Zhao Q Q and Tang J.2012.Extraction of cotton information using remote sensing and precision management zoning at county scale.Journal of Natural Resources,27(11):1971-1980(李敏,赵庚星,蔡明庆,赵倩倩,唐建.2012.县域棉花信息遥感提取与棉田精确化管理分区研究.自然资源学报,27(11):1971-1980)
Li X,Pan Y C,Ma J Y,Zhao C J and Wang J H.2007.Soil nutrientsbased zoning for management of precision agriculture.Acta Pedologica Sinica,44(1):14-20(李翔,潘瑜春,马景宇,赵春江,王纪华.2007.基于多种土壤养分的精准管理分区方法研究.土壤学报,44(1):14-20)[DOI:10.3321/j.issn:0564-3929.2007.01.003]
Li X,Pan Y C,Zhao C J,Wang J H,Bao Y S and Wang J D.2005a.Delineation and scale effect of precision agriculture management zones using yield monitor data over four years.Scientia Agricultura Sinica,38(9):1825-1833(李翔,潘瑜春,赵春江,王纪华,鲍艳松,王锦地.2005a.基于多年产量数据的精准农业管理分区提取与尺度效应评价.中国农业科学,38(9):1825-1833)[DOI:10.3321/j.issn:0578-1752.2005.09.017]
Li X,Pan Y C,Zhao C J,Wang J H,Bao Y S,Liu L Y and Wang J D.2005b.Delineating precision agriculture management zones based on spatial contiguous clustering algorithm.Transactions of the Chinese Society of Agricultural Engineering,21(8):78-82(李翔,潘瑜春,赵春江,王纪华,鲍艳松,刘良云,王锦地.2005b.基于空间连续性聚类算法的精准农业管理分区研究.农业工程学报,21(8):78-82)[DOI:10.3321/j.issn:1002-6819.2005.08.017]
Liu H J,Yu W T,Zhang X L,Ma Q,Zhou H and Jiang Z S.2009.Study on the main influencing factors of black soil spectral characteristics.Spectroscopy and Spectral Analysis,29(11):3019-3022(刘焕军,宇万太,张新乐,马强,周桦,姜子绍.2009.黑土反射光谱特征影响因素分析.光谱学与光谱分析,2 9(1 1):3019-3022)[DOI:10.3964/j.issn.1000-0593(2009)11-3019-04]
Liu H J,Zhang B,Liu Z M,Song K S,Wang Z M and Duan H T.2007.Spectral analysis of soils in Songnen plain,northeastern China.Journal of the Graduate School of the Chinese Academy of Sciences,24(4):439-445(刘焕军,张柏,刘志明,宋开山,王宗明,段洪涛.2007.松嫩平原主要土壤光谱特征分析.中国科学院研究生院学报,24(4):439-445)[DOI:10.3969/j.issn.1002-1175.2007.04.006]
Liu H J,Zhao C J,Wang J H,Huang W J and Zhang X L.2011.Soil organic matter predicting with remote sensing image in typicalblacksoil area of Northeast China.Transactions of the CSAE,27(8):211-215(刘焕军,赵春江,王纪华,黄文江,张新乐.2011.黑土典型区土壤有机质遥感反演.农业工程学报,27(8):211-215)[DOI:10.3969/j.issn.1002-6819.2011.08.036]
Liu J F.2015.Research of spatial heterogeneity of soil organic matters and the influencing factors in Mangang section of Heshan farm.Daqing:Heilongjiang Bayi Agricultural University(刘剑飞.2015.鹤山农场漫岗地块土壤养分空间变异及影响因素分析.大庆:黑龙江八一农垦大学)
Milne A E,Webster R,Ginsburg D and Kindred D.2012.Spatial multivariate classification of an arable field into compact management zones based on past crop yields.Computers and Electronics in Agriculture,80:17-30[DOI:10.1016/j.compag.2011.10.007]
Mkhabela M S,Bullock P,Raj S,Wang S and Yang Y.2011.Crop yield forecasting on the Canadian prairies using MODIS NDVIdata.Agricultural and Forest Meteorology,151(3):385-393[DOI:10.1016/j.agrformet.2010.11.012]
Ostergaard H S.1999.Agronomic consequences of variable N fertilization//Stafford J V,ed.Proceedings of the 1st European Conference on Precision Agriculture.Oxford,UK:BIOS Scientific Publishers Ltd,145-153
Peng J,Zhou Q,Zhang Y Z and Xiang H Y.2013.Effect of soil organic matter on spectral characteristics of soil.Acta Pedologica Sinica,50(3):517-524(彭杰,周清,张杨珠,向红英.2013.有机质对土壤光谱特性的影响研究.土壤学报,50(3):517-524)[DOI:10.11766/trxb201207080277]
Shi G B.2011.Application of GPS and GIS technology in monitoring system of precision agriculture.Hubei Agricultural Science,50(10):1948-1950(史国滨.2011.GPS和GIS技术在精准农业监控系统中的应用研究进展.湖北农业科学,50(10):1948-1950)[DOI:10.3969/j.issn.0439-8114.2011.10.002]
Song X Y,Wang J H,Huang W J,Yan G J and Chang H.2009.Monitoring spatial variance of winter wheat growth and grain qualityunder variable-rate fertilization conditions by remote sensing data.Transactions of the CSAE,25(9):155-162(宋晓宇,王纪华,黄文江,阎广建,常红.2009.变量施肥条件下冬小麦长势及品质变异遥感监测.农业工程学报,25(9):155-162)[DOI:10.3969/j.issn.1002-6819.2009.09.028]
Song X Y,Wang J H,Liu L Y,Huang W J,Shen T and Yu Z Z.2007.Research of management zones generating based on Quickbird imagery.Scientia Agricultura Sinica,40(9):1996-2006(宋晓宇,王纪华,刘良云,黄文江,沈涛,喻铮铮.2007.基于Quickbird遥感影像的农田管理分区划分研究.中国农业科学,40(9):1996-2006)[DOI:10.3321/j.issn:0578-1752.2007.09.020]
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