遥感技术与应用 2019, Vol. 34 Issue (4): 694-703 DOI: 10.11873/j.issn.1004-0323.2019.4.0694 |
CNN 专栏 |
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基于CNN和农作物光谱纹理特征进行作物分布制图 |
周壮1,2,3(),李盛阳1,2,张康1,2,3,邵雨阳1,2 |
1. 中国科学院空间应用工程与技术中心 北京 100094 2. 中国科学院太空应用重点实验室 北京 100094 3. 中国科学院大学 北京 100049 |
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Crop Mapping Using Remotely Sensed Spectral and Context Features based on CNN |
Zhuang Zhou1,2,3(),Shengyang Li1,2,Kang Zhang1,2,3,Yuyang Shao1,2 |
1. Technology and Engineering Center for Space Utilization, Chinese Academy of Sciences, Beijing 100094, China 2. Key Laboratory of Space Utilization, Chinese Academy of Sciences, Beijing 100094, China 3. University of Chinese Academy of Sciences, Beijing 100049, China |
引用本文:
周壮,李盛阳,张康,邵雨阳. 基于CNN和农作物光谱纹理特征进行作物分布制图[J]. 遥感技术与应用, 2019, 34(4): 694-703.
Zhuang Zhou,Shengyang Li,Kang Zhang,Yuyang Shao. Crop Mapping Using Remotely Sensed Spectral and Context Features based on CNN. Remote Sensing Technology and Application, 2019, 34(4): 694-703.
链接本文:
http://www.rsta.ac.cn/CN/10.11873/j.issn.1004-0323.2019.4.0694
或
http://www.rsta.ac.cn/CN/Y2019/V34/I4/694
|
1 |
TangHuajun, WuWenbin, YangPeng, et al. Recent Progresses in Monitoring Crop Spatial Patterns by Using Remote Sensing Technologies[J]. Scientia Agricultura Sinica, 2010, 43(14): 2879-2888.
|
1 |
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.
|
2 |
XiaoX, BolesS, FrolkingS, et al. Mapping Paddy Rice Agriculture in South and Southeast Asia Using Multi-temporal MODIS Images[J]. Remote Sensing of Environment, 2006, 100(1): 95-113.
|
3 |
CaoWeibin, YangBangjie, SongJinpeng. Spectral Information based Model for Cotton Identification on Landsat TM Image[J]. Transactions of the CSAE, 2004, 20(4): 112-116.
|
3 |
曹卫彬, 杨邦杰, 宋金鹏. TM影像中基于光谱特征的棉花识别模型[J]. 农业工程学报, 2004, 20(4):112-116.
|
4 |
JiaKun, LiQiangzi, TianYichen, et al. Accuracy Improvement of Spectral Classification of Crop Using Microwave Backscatter Data[J]. Spectroscopy and Spectral Analysis, 2011, 31(2):483-487.
|
4 |
贾坤, 李强子, 田亦陈,等. 微波后向散射数据改进农作物光谱分类精度研究[J]. 光谱学与光谱分析, 2011,31(2): 483-487.
|
5 |
YangC, EverittJ H, MurdenD. Evaluating High Resolution SPOT 5 Satellite Imagery for Crop Identification[J]. Computers and Electronics in Agriculture, 2011, 75(2): 347-354.
|
6 |
LiuKebao, LiuShubin, LiZhongjun. Extraction on Cropping Structure based on High Spatial Resolution Remote Sensing Data[J]. Chinese Journal of Agricultural Resources and Regional Planning, 2014, 35(1): 21-26.
|
6 |
刘克宝, 刘述彬, 陆忠军,等. 利用高空间分辨率遥感数据的农作物种植结构提取[J]. 中国农业资源与区划, 2014, 35(1):21-26.
|
7 |
ZhuDengsheng, PanJiazhi, HeYong. Identification Methods of Crop and Weeds based on VIs/NIR spectroscopy and RBF-NN model[J]. Spectroscopy and Spectral Analysis, 2008, 28(5): 1102-1106.
|
7 |
朱登胜, 潘家志, 何勇. 基于光谱和神经网络模型的作物与杂草识别方法研究[J]. 光谱学与光谱分析, 2008, 28(5): 1102-1106.
|
8 |
PengGuangxiong, GongAdu, CuiWeihong. Study on Methods Comparision of Typical Remote Sensing Classification based on Multi-temporal Images[J]. Journal of Geo-Information Science, 2012, 11(2): 20-26.
|
8 |
彭光雄, 宫阿都, 崔伟宏, 等. 多时相影像的典型区农作物识别分类方法对比研究[J]. 地球信息科学学报, 2012, 11(2): 225-230.
|
9 |
XiongQinxue, HuangJingfeng. Estimation of Autumn Harvest Crop Planting Area based on NDVI Sequential Characteristics[J]. Transactions of the Chinese Society of Agricultural Engineering, 2009, 25(1): 144-148.
|
9 |
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.
|
10 |
FoersterS, KadenK, FoersterM, et al. Crop Type Mapping Using Spectral-temporal Profiles and Phenological Information[J]. Computers and Electronics in Agriculture, 2012, 89: 30-40.
|
11 |
WangLianxi, XuShengnan, LiQi, et al. Extraction of Winter Wheat Planted Area in Jiangsu Province Using Decision tree and Mixed-pixel Methods[J]. Transactions of the Chinese Society of Agricultural Engineering, 2016, 32(5): 182-187.
|
11 |
王连喜, 徐胜男, 李琪,等. 基于决策树和混合像元分解的江苏省冬小麦种植面积提取[J]. 农业工程学报, 2016(5):182-187.
|
12 |
WangWenjing, ZhangXia, ZhaoYinde, et al. Cotton Extraction Method of Integrated Multi-features based on Multi-temporal Landsat 8 Images[J]. Journal of Remote Sensing, 2017, 21(1):115-124.
|
12 |
王文静, 张霞, 赵银娣, 等. 综合多特征的 Landsat 8 时序遥感图像棉花分类方法[J]. 遥感学报, 2017, 21(1): 115-124.
|
13 |
LiuJikai, ZhongShiquan, LiangWenhai,et al. Extraction on Crops Planting Structure based on Multi-temporal Landsat 8 OLI Images[J]. Remote Sensing Technology and Application, 2015, 30(4): 775-783.
|
13 |
刘吉凯, 钟仕全, 梁文海. 基于多时相Landsat 8 OLI影像的作物种植结构提取[J]. 遥感技术与应用, 2015, 30(4):775-783.
|
14 |
LiXiaohui, WangHong, LiXiaobing, et al. Study on Crops Remote Sensing Classification based on Multi-temporal Landsat 8 OLI Images[J]. Remote Sensing Technology and Application, 2019, 34(2):384-397.
|
14 |
李晓慧, 王宏, 李晓兵, 等.基于多时相Landsat 8 OLI 影像的农作物遥感分类研究[J]. 遥感技术与应用,2019,34(2):387-397.
|
15 |
ZhangRi, MaJianwen. A Feature Selection Algorithm for Hyperspectual Data with SVM-RFE[J]. Geomatics and Information Science of Wuhan University, 2009, 34(7):834-837.
|
15 |
张睿, 马建文. 一种SVM-RFE高光谱数据特征选择算法[J]. 武汉大学学报(信息科学版), 2009, 34(7):834-837.
|
16 |
ShiFeifei, GaoXiaohong, YangLingyu, et al. Research on Jypical Crop Classification based on HJ-1A Hyperspectral Data in the Huangshui River Basin[J]. Remote Sensing Technology and Application, 2017, 32(2): 206-217.
|
16 |
史飞飞,高小红,杨灵王,等.基于HJ-1A高光谱遥感数据的湟水流域典型农作物分类研究[J]. 遥感技术与应用,2017,32(2):201-217.
|
17 |
PingYaopeng, ZangShuying. Crop Identification based on MODIS NDVI Time-series Data and Phenological Characteristics[J]. Journal of Natural Resources, 2016, 31(3): 503-513.
|
17 |
平跃鹏, 臧淑英. 基于 MODIS 时间序列及物候特征的农作物分类[J]. 自然资源学报, 2016, 31(3): 503-513.
|
18 |
KhatamiR, MountrakisG, StehmanS V. A Meta-analysis of Remote Sensing Research on Supervised Pixel-based Land-cover Image Classification Processes: General Guidelines for Practitioners and Future Research[J]. Remote Sensing of Environment, 2016, 177: 89-100.
|
19 |
KrizhevskyA, SutskeverI, HintonG E. Imagenet Classification with Deep Convolutional Neural Networks[C]⫽Advances in Neural Information Processing Systems. 2012: 1097-1105.
|
20 |
MakantasisK, KarantzalosK, DoulamisA, et al. Deep Supervised Learning for Hyperspectral Data Classification Through Convolutional Neural Networks[C]⫽2015 IEEE International Geoscience and Remote Sensing Symposium(IGARSS), 2015: 4959-4962.
|
21 |
ZhangF, DuB, ZhangL. Saliency-Guided Unsupervised Feature Learning for Scene Classification[J]. IEEE Transactions on Geoscience & Remote Sensing, 2015, 53(4):2175-2184.
|
22 |
ZhangKang, BaoqingHei, ZhouZhuang, et al. CNN with Coefficient of Variation-based Dimensionality Reduction for Hyperspectral Remote Sensing Images Classification[J]. Journal of Remote Sensing, 2018, 22(1):87-96.
|
22 |
张康,黑保琴, 周壮,等. 变异系数降维的CNN高光谱遥感图像分类[J]. 遥感学报, 2018, Journal of Remote Sensing, 2018, 22(1):87-96.
|
23 |
HuangYun, TangLinbo, LiZhen, et al. Research on Peanut Planting Area Classification Technology Using Remote Sensing Image based Deep Learning [J]. Journal of Signal Processing, 2019,35(4):617-622.
|
23 |
黄云,唐林波,李震,等.采用深度学习的遥感图像花生种植区域分类技术研究[J].信号处理,2019,35(4):617-622.
|
24 |
MaLi. Extracting Corn Planting Area by Multi-source Data with SVM Mixed-field Decomposed Method[D]. Xi'an: Xi'an University of Science and Technology, 2009.
|
24 |
马丽. 多源信息复合的 SVM 混合地块分解法提取玉米种植面积[D]. 西安: 西安科技大学, 2009.
|
25 |
LecunY, BottouL, BengioY, et al. Gradient-based Learning Applied to Document Recognition[J]. Proceedings of the IEEE, 1998, 86(11): 2278-2324.
|
26 |
HintonG E, SalakhutdinovR R. Reducing the Dimensionality of Data with Neural Networks[J]. Science, 2006, 313(5786): 504-507.
|
27 |
HuW, HuangY, WeiL, et al. Deep Convolutional Neural Networks for Hyperspectral Image Classification[J]. Journal of Sensors, 2015: 1-12.
|
28 |
YueJ, ZhaoW, MaoS, et al. Spectral–spatial Classification of Hyperspectral Images Using Deep Convolutional Neural Networks[J]. Remote Sensing Letters, 2015, 6(6): 468-477.
|
29 |
LiYandong, HaoZongbo, LeiHang. Survey of Convolutional Neural Network[J]. Journal of Computer Applications, 2016(9): 2508-2515.
|
29 |
李彦冬, 郝宗波, 雷航. 卷积神经网络研究综述[J]. 计算机应用, 2016, 36(9): 2508-2515.
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