GF-7卫星多角度特征作物识别
Crop recognition by multiangle features of GF-7 satellite
- 2023年27卷第9期 页码：2127-2138
收稿：2021-10-22，
纸质出版：2023-09-07
DOI： 10.11834/jrs.20221644
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摘要
多角度遥感对地观测能够提供更加丰富、多方向的遥感特征，提高地类之间的可区分性，为地物覆盖的精确识别打下坚实的数据基础。GF-7是中国继ZY-3卫星后的首颗亚米级测绘卫星，这为利用多角度特性解决“异物同谱”的问题，提高作物的识别精度带来了机遇。本文利用GF-7前视、后视全色及后视多光谱数据，各种特征组合输入到支撑向量机分类器进行分类，相对于光谱、纹理等特征，分析多角度特征对作物识别精度的作用。结果表明，较仅应用光谱特征，光谱与角差特征组合使用大蒜和冬小麦的制图精度分别提高了4.07%和3.15%，用户精度分别提高了6.73%和2.12%；较应用光谱与纹理特征，光谱、纹理与角差特征组合使用大蒜和冬小麦的制图精度分别提高了3.14%和1.01%，用户精度分别提高了5.11%和0.67%。通过McNemar检验分析，这种分类精度的提高是稳定的，角差特征使用能有效提高作物的识别精度。究其原因，多角度特征对不同作物类型在多角度观测时的光谱响应具备特有的差异性，这种差异提高了作物之间的可分性，从而保证作物遥感识别的精度。
Abstract
Multiangle remote sensing can provide richer
multidirectional features for ground object observation
improve the distinguishability between land types
and lay a solid data foundation for the accurate identification of ground cover. GF-7 is the first domestic sub meter surveying and mapping satellite after ZY-3 satellite
which brings an opportunity to solve the problem of “foreign matter homospectrum” using multiangle characteristics and to improve the identification accuracy of crops. In this paper
GF-7 forward-looking and backward-looking panchromatic and backward-looking multispectral data are used
and various features combinations are input to the support vector machine classifier to analyze the influence of multiangle features on crop recognition accuracy relative to the spectral and texture features. Results show that compared with only spectral features
with the addition of the angle difference feature
the production accuracy of garlic and winter wheat increased by 4.07% and 3.15%
respectively
and the user accuracy increased by 6.73% and 2.12%
respectively. Compared with the combination of spectral and texture features
with the addition of the angle difference feature
the production accuracy of garlic and winter wheat increased by 3.14% and 1.01%
respectively
and the user accuracy increased by 5.11% and 0.67%
respectively. Through the analysis of McNemar test
the improvement of classification accuracy is stable
angle difference feature can effectively improve the identification accuracy of crops. Tracing it to its cause
the multiangle characteristics of GF-7 satellite have unique differences in the spectral response of different crop types during multiangle observation. The difference improves the separability between crops to ensure the accuracy of crop remote sensing mapping.
关键词
Keywords
references
Alshehhi R , Marpu P R , Woon W L and Mura M D . 2017 . Simultaneous extraction of roads and buildings in remote sensing imagery with convolutional neural networks . ISPRS Journal of Photogrammetry and Remote Sensing , 130 : 139 - 149 [ DOI: 10.1016/j.isprsjprs.2017.05.002 http://dx.doi.org/10.1016/j.isprsjprs.2017.05.002 ]
Chang C C and Lin C J . 2011 . LIBSVM: a library for support vector machines . ACM Transactions on Intelligent Systems and Technology , 2 ( 3 ): 27 [ DOI: 10.1145/1961189.1961199 http://dx.doi.org/10.1145/1961189.1961199 ]
Chopping M , Moisen G G , Su L H , Laliberte A , Rango A , Martonchik J V and Peters D P C . 2008 . Large area mapping of southwestern forest crown cover, canopy height, and biomass using the NASA Multiangle Imaging Spectro-Radiometer . Remote Sensing of Environment , 112 ( 5 ): 2051 - 2063 [ DOI: 10.1016/j.rse.2007.07.024 http://dx.doi.org/10.1016/j.rse.2007.07.024 ]
Clayton D G . 1971 . Algorithm AS 46: gram-Schmidt Orthogonalization . Applied Statistics , 20 ( 3 ): 335 - 338 [ DOI: 10.2307/2346771 http://dx.doi.org/10.2307/2346771 ]
Congalton R G . 1991 . A review of assessing the accuracy of classifications of remotely sensed data . Remote Sensing of Environment , 37 ( 1 ): 35 - 46 [ DOI: 10.1016/0034-4257(91)90048-B http://dx.doi.org/10.1016/0034-4257(91)90048-B ]
Dehghan H and Ghassemian H . 2006 . Measurement of uncertainty by the entropy: application to the classification of MSS data . International Journal of Remote Sensing , 27 ( 18 ): 4005 - 4014 [ DOI: 10.1080/01431160600647225 http://dx.doi.org/10.1080/01431160600647225 ]
Duro D C , Franklin S E and Dubé M G . 2012 . A comparison of pixel-based and object-based image analysis with selected machine learning algorithms for the classification of agricultural landscapes using SPOT-5 HRG imagery . Remote Sensing of Environment , 118 : 259 - 272 [ DOI: 10.1016/j.rse.2011.11.020 http://dx.doi.org/10.1016/j.rse.2011.11.020 ]
Foody G M . 2002 . Status of land cover classification accuracy assessment . Remote Sensing of Environment , 80 ( 1 ): 185 - 201 [ DOI: 10.1016/S0034-4257(01)00295-4 http://dx.doi.org/10.1016/S0034-4257(01)00295-4 ]
Foody G M and Atkinson P M . 2002 . Uncertainty in Remote Sensing and GIS . Chichester : John Wiley and Sons [ DOI: 10.1002/0470035269 http://dx.doi.org/10.1002/0470035269 ]
Haralick R M . 1979 . Statistical and structural approaches to texture . Proceedings of the IEEE , 67 ( 5 ): 786 - 804 [ DOI: 10.1109/proc.1979.11328 http://dx.doi.org/10.1109/proc.1979.11328 ]
Huang X , Chen H J and Gong J Y . 2018 . Angular difference feature extraction for urban scene classification using ZY-3 multi-angle high-resolution satellite imagery . ISPRS Journal of Photogrammetry and Remote Sensing , 135 : 127 - 141 [ DOI: 10.1016/j.isprsjprs.2017.11.017 http://dx.doi.org/10.1016/j.isprsjprs.2017.11.017 ]
Huang X , Lu Q K and Zhang L P . 2014 . A multi-index learning approach for classification of high-resolution remotely sensed images over urban areas . ISPRS Journal of Photogrammetry and Remote Sensing , 90 : 36 - 48 [ DOI: 10.1016/j.isprsjprs.2014.01.008 http://dx.doi.org/10.1016/j.isprsjprs.2014.01.008 ]
Khatami R , Mountrakis G and Stehman S V . 2016 . A meta-analysis of remote sensing research on supervised pixel-based land-cover image classification processes: general guidelines for practitioners and future research . Remote Sensing of Environment , 177 : 89 - 100 [ DOI: 10.1016/j.rse.2016.02.028 http://dx.doi.org/10.1016/j.rse.2016.02.028 ]
Lan Z Y and Liu Y . 2018 . Study on multi-scale window determination for GLCM texture description in high-resolution remote sensing image geo-analysis supported by GIS and domain knowledge . ISPRS International Journal of Geo-Information , 7 ( 5 ): 175 [ DOI: 10.3390/ijgi7050175 http://dx.doi.org/10.3390/ijgi7050175 ]
Li L , She M Y and Luo H . 2014 . Comparison on fusion algorithms of ZY-3 panchromatic and multi-spectral images . Transactions of the Chinese Society of Agricultural Engineering , 30 ( 16 ): 157 - 165
李霖 , 佘梦媛 , 罗恒 . 2014 . ZY-3卫星全色与多光谱影像融合方法比较 . 农业工程学报 , 30 ( 16 ): 157 - 165 [ DOI: 10.3969/j.issn.1002-6819.2014.16.021 http://dx.doi.org/10.3969/j.issn.1002-6819.2014.16.021 ]
Li X J , Chen W T , Cheng X W and Wang L Z . 2016 . A comparison of machine learning algorithms for mapping of complex surface mined and agricultural landscapes using ZiYuan-3 stereo satellite imagery . Remote Sensing , 8 ( 6 ): 514 [ DOI: 10.3390/rs8060514 http://dx.doi.org/10.3390/rs8060514 ]
Liu H F , Yang Y B , Yu S , Kong L T and Zhang Y . 2014 . Adaptability evaluation of different fusion methods on ZY-3 and Landsat8 images . Remote Sensing For Land and Resources , 26 ( 4 ): 63 - 70
刘会芬 , 杨英宝 , 于双 , 孔令婷 , 章勇 . 2014 . 遥感图像不同融合方法的适应性评价——以ZY-3和Landsat8图像为例 . 国土资源遥感 , 26 ( 4 ): 63 - 70 [ DOI: 10.6046/gtzyyg.2014.04.11 http://dx.doi.org/10.6046/gtzyyg.2014.04.11 ]
Liu X S . 2015 . Study on soil bidirectional reflectance characteristics and application of soil standard spectral library . Wuhan : Huazhong Agricultural University
刘小珊 . 2015 . 土壤二向反射特性研究与标准光谱库的应用 . 武汉 : 华中农业大学
Matasci G , Longbotham N , Pacifici F , Kanevski M and Tuia D . 2015 . Understanding angular effects in VHR imagery and their significance for urban land-cover model portability: a study of two multi-angle in-track image sequences . ISPRS Journal of Photogrammetry and Remote Sensing , 107 : 99 - 111 [ DOI: 10.1016/j.isprsjprs.2015.05.004 http://dx.doi.org/10.1016/j.isprsjprs.2015.05.004 ]
Roujean J L , Leroy M and Deschamps P Y . 1992 . A bidirectional reflectance model of the Earth's surface for the correction of remote sensing data . Journal of Geophysical Research: Atmospheres , 97 ( D18 ): 20455 - 20468 [ DOI: 10.1029/92JD01411 http://dx.doi.org/10.1029/92JD01411 ]
Schaepman-Strub G , Schaepman M E , Painter T H , Dangel S and Martonchik J V . 2006 . Reflectance quantities in optical remote sensing—definitions and case studies . Remote Sensing of Environment , 103 ( 1 ): 27 - 42 [ DOI: 10.1016/j.rse.2006.03.002 http://dx.doi.org/10.1016/j.rse.2006.03.002 ]
Song D J , Zhang C M , Yang X X , Li F , Han Y J , Gao S and Dong H Y . 2020 . Extracting winter wheat spatial distribution information from GF-2 image . Journal of Remote Sensing (Chinese) , 24 ( 5 ): 596 - 608
宋德娟 , 张承明 , 杨晓霞 , 李峰 , 韩颖娟 , 高帅 , 董海燕 . 2020 . 高分二号遥感影像提取冬小麦空间分布 . 遥感学报 , 24 ( 5 ): 596 - 608 [ DOI: 10.11834/jrs.20208285 http://dx.doi.org/10.11834/jrs.20208285 ]
Su L H , Chopping M J , Rango A , Martonchik J V and Peters D P C . 2007 . Support vector machines for recognition of semi-arid vegetation types using MISR multi-angle imagery . Remote Sensing of Environment , 107 ( 1/2 ): 299 - 311 [ DOI: 10.1016/j.rse.2006.05.023 http://dx.doi.org/10.1016/j.rse.2006.05.023 ]
Tian J , Reinartz P , d’Angelo P and Ehlers M . 2013 . Region-based automatic building and forest change detection on Cartosat-1 stereo imagery . ISPRS Journal of Photogrammetry and Remote Sensing , 79 : 226 - 239 [ DOI: 10.1016/j.isprsjprs.2013.02.017 http://dx.doi.org/10.1016/j.isprsjprs.2013.02.017 ]
Waldner F , Canto G S and Defourny P . 2015 . Automated annual cropland mapping using knowledge-based temporal features . ISPRS Journal of Photogrammetry and Remote Sensing , 110 : 1 - 13 [ DOI: 10.1016/j.isprsjprs.2015.09.013 http://dx.doi.org/10.1016/j.isprsjprs.2015.09.013 ]
Wu J Y , Liu X L , Bo Y X , Shi Z T and Fu Z . 2019 . Plastic greenhouse recognition based on GF-2 data and multi-texture features . Transactions of the Chinese Society of Agricultural Engineering , 35 ( 4 ): 106 - 113
吴锦玉 , 刘晓龙 , 柏延臣 , 史正涛 , 付卓 . 2019 . 基于GF-2数据结合多纹理特征的塑料大棚识别 . 农业工程学报 , 35 ( 12 ): 173 - 183 [ DOI: 10.11975/j.issn.1002-6819.2019.12.021 http://dx.doi.org/10.11975/j.issn.1002-6819.2019.12.021 ]
Yang Y J , Tian Q J , Zhan Y L , Tao B and Xu K J . 2018 . Effects of spatial resolution and texture features on multi-spectral remote sensing classification . Journal of Geo-Information Science , 20 ( 1 ): 99 - 107
杨闫君 , 田庆久 , 占玉林 , 陶波 , 徐凯健 . 2018 . 空间分辨率与纹理特征对多光谱遥感分类的影响 . 地球信息科学学报 , 20 ( 1 ): 99 - 107 [ DOI: 10.12082/dqxxkx.2018.170177 http://dx.doi.org/10.12082/dqxxkx.2018.170177 ]
Yu W W , Xu K J , Zhao P , Shen P J and Zhao Y J . 2021 . Influence of red-edge spectrum of sentinel-2 image on identification of dominant tree species in different growing periods . Geography and Geo-Information Science , 37 ( 3 ): 42 - 49
于婉婉 , 徐凯健 , 赵萍 , 申鹏举 , 赵月娇 . 2021 . Sentinel-2影像红边谱段对不同生长期区域优势树种识别的影响 . 地理与地理信息科学 , 37 ( 3 ): 42 - 49 [ DOI: 10.3969/j.issn.1672-0504.2021.03.007 http://dx.doi.org/10.3969/j.issn.1672-0504.2021.03.007 ]
Zhang D J , Pan Y Z , Zhang J S , Hu T G , Zhao J H , Li N and Chen Q . 2020 . A generalized approach based on convolutional neural networks for large area cropland mapping at very high resolution . Remote Sensing of Environment , 247 : 111912 [ DOI: 10.1016/j.rse.2020.111912 http://dx.doi.org/10.1016/j.rse.2020.111912 ]
Zhang J S , Pan Y Z , Han L J , Su W and He Y C . 2007 . Land Use/cover Change Detection with Multi-source Data , ( 04 ): 500 - 510
张锦水 , 潘耀忠 , 韩立建 等 . 光谱与纹理信息复合的土地利用/覆盖变化动态监测研究 . 遥感学报 , 2007 ( 04 ): 500 - 510 [ doi: 10.11834/jrs.20070470 http://dx.doi.org/10.11834/jrs.20070470 ]
Zhu S , Zhang J S , Shuai G Y and Yu Q Y . 2014 . Winter wheat mapping by soft and hard land use / cover change detection , 18 ( 02 ): 476 - 496
朱爽 , 张锦水 , 帅冠元 等 . 通过软硬变化检测识别冬小麦 . 遥感学报 , 2014 , 18 ( 02 ): 476 - 496 [ doi: 10.11834/jrs.20143078 http://dx.doi.org/10.11834/jrs.20143078 ]
Zhu X F , Li S B and Xiao G F . 2019 . Method on extraction of area and distribution of plastic-mulched farmland based on UAV images . Transactions of the Chinese Society of Agricultural Engineering , 35 ( 4 ): 106 - 113
朱秀芳 , 李石波 , 肖国峰 . 2019 . 基于无人机遥感影像的覆膜农田面积及分布提取方法 . 农业工程学报 , 35 ( 4 ): 106 - 113 [ DOI: 10.11975/j.issn.1002-6819.2019.04.013 http://dx.doi.org/10.11975/j.issn.1002-6819.2019.04.013 ]
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相关作者
孙智虎 中国地质大学(北京)土地科学技术学院
张锦水 遥感科学国家重点实验室 北京师范大学;北京市陆表遥感数据产品工程技术研究中心;北京师范大学地理科学学部遥感科学与工程研究院
洪友堂 中国地质大学(北京)土地科学技术学院
杨珺雯 遥感科学国家重点实验室 北京师范大学;北京市陆表遥感数据产品工程技术研究中心;北京师范大学地理科学学部遥感科学与工程研究院
朱爽 北京工业职业技术学院
王士俊 山东科技大学 测绘与空间信息学院
刘苗 山东科技大学 测绘与空间信息学院
赵钰 北京市农林科学院信息技术研究中心 农业农村部农业遥感机理与定量遥感重点实验室
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山东科技大学 测绘与空间信息学院
北京市农林科学院信息技术研究中心 农业农村部农业遥感机理与定量遥感重点实验室
中南大学 智能信息处理及系统研究所
山东省农业科学院 农业信息与经济研究所
中国科学院空天信息创新研究院 遥感卫星应用国家工程实验室
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