基于无人机可见光遥感影像的耕地精准分类方法研究
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摘要
无人机可见光遥感具有使用成本低、操作简单、实时获取遥感影像、地面分辨率高等优势。提出了一种利用无人机可见光遥感影像进行耕地精准分类的方法,以广东省惠州市惠东县铁涌镇石桥村部分耕地的可见光遥感影像为研究对象,对耕地的面积信息、形状信息以及位置信息进行监测和提取,采用面向对象法对影像中两种基于可见光波段的植被指数、纹理信息、形状信息进行分析,研究出分类提取耕地信息的较佳方案。经过反复实验确定分割尺度45、合并尺度90为分割参数,同时利用波段信息和纹理信息对未种植作物耕地和其他地物进行分离。该方法总体精度为89.23%,Kappa系数为0.72。实验结果表明利用无人机可见光遥感数据对耕地进行分类虽然存在一些细碎地块被错提、误提的情况,但总体精度仍然保持在一个很高的水准,可以为耕地作物分类提供参考,为实现精准农业提供精准的数据基础。
Visible remote sensing of UAV has advantages of low cost,simple operation,real-time acquisition of remote sensing images and high ground resolution. This paper proposed a method of precise classification of cultivated land based on UAV visible remote sensing image. Taking the visible remote sensing image of some cultivated land in Shiqiao Village,Tieyong Town,Huidong County,Guangdong Province as the research object,the area information,shape information and location information of cultivated land were monitored and extracted. Two kinds of vegetation based on visible wave band were used in the image by object-oriented method. Based on the analysis of index,texture and shape information,the better scheme of extracting cultivated land information by classification was studied. After repeated experiments,the segmentation scale 45 and the merging scale 90 were determined as the segmentation parameters. At the same time,the non-planted cropland and other land objects were separated using band information and texture information. The overall accuracy of the method was 89.23%,and the Kappa coefficient was 0.72. The experimental results showed that although there were some cases of mistaken lifting and mistaken lifting of fine plots in the classification of cultivated land using UAV visible remote sensing data,the overall accuracy remained at a high level,which provided a reference for crop classification of cultivated land,and provided precise data basis for precision agriculture.
Visible remote sensing of UAV has advantages of low cost,simple operation,real-time acquisition of remote sensing images and high ground resolution. This paper proposed a method of precise classification of cultivated land based on UAV visible remote sensing image. Taking the visible remote sensing image of some cultivated land in Shiqiao Village,Tieyong Town,Huidong County,Guangdong Province as the research object,the area information,shape information and location information of cultivated land were monitored and extracted. Two kinds of vegetation based on visible wave band were used in the image by object-oriented method. Based on the analysis of index,texture and shape information,the better scheme of extracting cultivated land information by classification was studied. After repeated experiments,the segmentation scale 45 and the merging scale 90 were determined as the segmentation parameters. At the same time,the non-planted cropland and other land objects were separated using band information and texture information. The overall accuracy of the method was 89.23%,and the Kappa coefficient was 0.72. The experimental results showed that although there were some cases of mistaken lifting and mistaken lifting of fine plots in the classification of cultivated land using UAV visible remote sensing data,the overall accuracy remained at a high level,which provided a reference for crop classification of cultivated land,and provided precise data basis for precision agriculture.
引文
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[15]李敏.基于RS和GIS的县域棉花信息提取及分区管理研究-以山东省夏津县为例[D].山东泰安:山东农业大学硕士论文,2012.Li M.County cotton information extraction and zoning management based on RS and GIS:A case study of Xiajin County,Shandong Province[D].Shandong Tai'an:Shandong Agricultural University,Master Dissertation,2012.
[16]牛亚晓,张立元,韩文霆,等.基于无人机遥感与植被指数的冬小麦覆盖度提取方法[J].农业工程学报,2018,49(4):213-221.Niu Y X,Zhang L Y,Han W T,et al..Extraction method of winter wheat coverage based on UAV remote sensing and vegetation index[J].Trans.Chin.Soc.Agric.Machinery,2018,49(4):213-221.
[17]韩文霆,李广,苑梦婵,等.基于无人机遥感技术的玉米种植信息提取方法研究[J].农业机械学报,2017,48(1):140-147.Han W T,Li G,Yuan M C,et al..Research on information extraction method of maize planting based on UAV remote sensing technology[J].Trans.Chin.Soc.Agric.Machinery,2017,48(1):140-147.
[18]Verrelst J,Schaepman M E,Koetz B,et al..Angular sensitivity analysis of vegetation indices derived from CHRIS/PROBA data[J].Remote Sensing Environ.,2018,112(5):2341-2353.
[19]吴金胜,刘红丽,张锦水.无人机遥感影像面向对象分类方法估算市域水稻面积[J].农业工程学报,2011,34(1):70-77.Wu J S,Liu H L,Zhang J S.Estimation of urban rice area by object oriented classification method of UAV remote sensing image[J].Trans.Chin.Soc.Agric.Machinery,2011,34(1):70-77.
[20]李秦,高锡章,张涛,等.最优分割尺度下的多层次遥感地物分类实验分析[J].地球信息科学学报,2011,12(3):409-417.Li Q,Gao X Z,Zhang Tao,et al..Experimental analysis of multilevel remote sensing surface classification under optimal segmentation scale[J].J.Geo-Inform.Sci.,2011,12(3):409-417.
[2]Zhang J,Feng L,Yao F.Improved maize cultivated area estimation over a large scale combining MODIS-EVI time series dara and crop phenological information[J].ISPRS J.Photogram.Remote Sensing,2014,94:218-223.
[3]Lv T,Liu C.Study on extraction of crop information using time-series MODIS data in Chao Phraya Basin of Thailand[J].Adv.Space Res.,2010,45(6):775-784.
[4]韩文霆,张立元,张海鑫,等.基于无人机遥感与面向对象法的田间渠系分布信息提取[J].农业机械学报,2015,48(3):206-214.Han W T,Zhang L Y,Zhang H X,et al..Information extraction of field canal system based on UAV remote sensing and object oriented method[J].Trans.Chin.Soc.Agric.Machinery,2015,48(3):206-214.
[5]汪沛,罗锡文,周志艳,等.基于微小型无人机的遥感信息获取关键技术综述[J].农业工程学报,2014,30(18):1-12.Wang P,Luo X W,Zhou Z Y,et al..Key technologies of remote sensing information acquisition based on micro UAV[J].Trans.Chin.Soc.Agric.Machinery,2014,30(18):1-12.
[6]Bryson M,Reid A,Ramos F,et al..Airborne vision-based mapping and classification of large farmland environments[J].J.Field Robotics,2010,27(5):632-655.
[7]Torres-Sanchez J,Pena J M,de Castro A I,et al..Multitemporal mapping of the vegetation fraction in early-season wheat fields using images from UAV[J].Comp.Electron.Agric.,2014,103(2):104-113.
[8]Gomez-Candon D,de Castro A I,Lopez-Granados F.Assessing the accuracy of mosaics from unmanned aerial vehicle(UAV)imagery for precision agriculture purposes in wheat[J].Precision Agric,2014,15(1):44-56.
[9]Mesas-Carrascosa F J,Norarion-Garcia M D,Larriva J E M D,et al..Validation of measurements of land plot area using UAVimagery[J].Int.J.Appl.Earth Observation Geoinformation,2014,33(1):270-279.
[10]汪小钦,王苗苗,王绍强,等.基于可见光波段无人机遥感的植被信息提取[J].农业工程学报,2015,31(5):152-157.Wang X Q,Wang M M,Wang S Q,et al..Vegetation information extraction based on UAV remote sensing in visible band[J].Trans.Chin.Soc.Agric.Machinery,2015,31(5):152-157.
[11]刘峰,刘素红,向阳.园地植被覆盖度的无人机遥感监测研究[J].农业机械学报,2014,45(11):250-257.Liu F,Liu S H,Xiang Y.UAV remote sensing monitoring of vegetation coverage in gardens[J].Trans.Chin.Soc.Agric.Machinery,2014,45(11):250-257.
[12]董梅,苏建东,刘广玉,等.面向对象的无人机遥感影像烟草种植面积提取和监测[J].测绘科学,2014,39(9):87-90.Dong M,Su J D,Liu G Y,et al..Object oriented UAV remote sensing image extraction and monitoring of tobacco planting area[J].Sci.Surveying Mapping,2014,39(9):87-90.
[13]吴玮,秦其明,范一大.基于无人机可见光遥感影像的救灾帐篷信息提取[J].地理与地理信息科学,2015,31(2):20-23.Wu W,Qin Q M,Fan Y D.Information extraction of relief tent based on UAV visible light remote sensingimages[J].Geography Geo-Inform.Sci.,2015,31(2):20-23.
[14]李宗南,陈仲新,王利民等.基于小型无人机遥感的玉米倒伏面积提取[J].农业工程学报,2014,30(19):207-213.Li Z N,Chen Z X,Wang L M,et al..Extraction of corn lodging area based on small UAV remote sensing[J].Trans.Chin.Soc.Agric.Machinery,2014,30(19):207-213.
[15]李敏.基于RS和GIS的县域棉花信息提取及分区管理研究-以山东省夏津县为例[D].山东泰安:山东农业大学硕士论文,2012.Li M.County cotton information extraction and zoning management based on RS and GIS:A case study of Xiajin County,Shandong Province[D].Shandong Tai'an:Shandong Agricultural University,Master Dissertation,2012.
[16]牛亚晓,张立元,韩文霆,等.基于无人机遥感与植被指数的冬小麦覆盖度提取方法[J].农业工程学报,2018,49(4):213-221.Niu Y X,Zhang L Y,Han W T,et al..Extraction method of winter wheat coverage based on UAV remote sensing and vegetation index[J].Trans.Chin.Soc.Agric.Machinery,2018,49(4):213-221.
[17]韩文霆,李广,苑梦婵,等.基于无人机遥感技术的玉米种植信息提取方法研究[J].农业机械学报,2017,48(1):140-147.Han W T,Li G,Yuan M C,et al..Research on information extraction method of maize planting based on UAV remote sensing technology[J].Trans.Chin.Soc.Agric.Machinery,2017,48(1):140-147.
[18]Verrelst J,Schaepman M E,Koetz B,et al..Angular sensitivity analysis of vegetation indices derived from CHRIS/PROBA data[J].Remote Sensing Environ.,2018,112(5):2341-2353.
[19]吴金胜,刘红丽,张锦水.无人机遥感影像面向对象分类方法估算市域水稻面积[J].农业工程学报,2011,34(1):70-77.Wu J S,Liu H L,Zhang J S.Estimation of urban rice area by object oriented classification method of UAV remote sensing image[J].Trans.Chin.Soc.Agric.Machinery,2011,34(1):70-77.
[20]李秦,高锡章,张涛,等.最优分割尺度下的多层次遥感地物分类实验分析[J].地球信息科学学报,2011,12(3):409-417.Li Q,Gao X Z,Zhang Tao,et al..Experimental analysis of multilevel remote sensing surface classification under optimal segmentation scale[J].J.Geo-Inform.Sci.,2011,12(3):409-417.
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