Laser & Optoelectronics Progress, Volume. 59, Issue 24, 2428005(2022)

Remote Sensing Vegetation Classification Method Based on Vegetation Index and Convolution Neural Network

Mingzhu Xu1, Hao Xu2, Peng Kong2, and Yanlan Wu1,3,4、*
Author Affiliations
  • 1School of Resources and Environmental Engineering, Anhui University, Hefei 230601, Anhui, China
  • 2Institute of Spacecraft System Engineering, Beijing 100094, China
  • 3Information Materials and Intelligent Sensing Laboratory of Anhui Province, Hefei 230601, Anhui, China
  • 4Anhui Engineering Research Center for Geographical Information Intelligent Technology, Hefei 230601, Anhui, China
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    References(29)

    [1] Nunes A N, de Almeida A C, Coelho C O A. Impacts of land use and cover type on runoff and soil erosion in a marginal area of Portugal[J]. Applied Geography, 31, 687-699(2011).

    [2] Li L, Wen Q, Wang B et al. Water body extraction from high-resolution remote sensing images based on scaling EfficientNets[J]. Journal of Physics: Conference Series, 1894, 012100(2021).

    [3] Zhang Y. Fine classification of crops using satellite hyperspectral remote sensing imagery[D](2021).

    [4] Shi W X, Bao J H, Yao Y. Remote sensing image target detection and identification based on deep learning[J]. Journal of Computer Applications, 40, 3558-3562(2020).

    [5] Liu H Y, Jiang Z H, Dai J Y et al. Rock crevices determine woody and herbaceous plant cover in the Karst critical zone[J]. Scientia Sinica (Terrae), 49, 1974-1981(2019).

    [6] Han L G. Research on winter wheat planting area extraction method based on GF-1 image[D](2019).

    [7] Yang S. Study on the classification and spatial and temporal changes of main tree species in the greater Xing’an mountains based on Landsat data[D](2020).

    [8] Shi F F, Gao X H, Yang L Y et al. Research on typical crop classification based on HJ-1A hyperspectral data in the Huangshui River Basin[J]. Remote Sensing Technology and Application, 32, 206-217(2017).

    [9] Nan Y F, Zhang Y L, Zhu R. Cooperative spectrum sensing algorithm based on kernel space optimization support vector machine[J]. Acta Scientiarum Naturalium Universitatis Nankaiensis, 54, 8-14(2021).

    [10] Xing X Y, Yang X C, Xu B et al. Remote sensing estimation of grassland aboveground biomass based on random forest[J]. Journal of Geo-Information Science, 23, 1312-1324(2021).

    [11] Gu X T, Gao X H, Ma H J et al. Comparison of machine learning methods for land use/land cover classification in the complicated terrain regions[J]. Remote Sensing Technology and Application, 34, 57-67(2019).

    [12] Liu Y, Yang K. Credit fraud detection for extremely imbalanced data based on ensembled deep learning[J]. Journal of Computer Research and Development, 58, 539-547(2021).

    [13] Ozdarici-Ok A, Ok A, Schindler K. Mapping of agricultural crops from single high-resolution multispectral images: data-driven smoothing vs. parcel-based smoothing[J]. Remote Sensing, 7, 5611-5638(2015).

    [14] Kang C, Li W X, Huang S et al. Research on active optical correction algorithm based on deep learning[J]. Acta Optica Sinica, 41, 0611004(2021).

    [15] Zhuang Q S, He Z W, Zhang C X et al. Polarization recognition through scattering media based on deep-learning[J]. Acta Optica Sinica, 41, 2229001(2021).

    [16] Zhang L, Xu X B, Cao C F et al. Robot pose estimation method based on image and point cloud fusion with dynamic feature elimination[J]. Chinese Journal of Lasers, 49, 0610001(2022).

    [17] Huang H S, Lan Y B, Deng J Z et al. A semantic labeling approach for accurate weed mapping of high resolution UAV imagery[J]. Sensors, 18, 2113(2018).

    [18] Yang M D, Tseng H H, Hsu Y C et al. Semantic segmentation using deep learning with vegetation indices for rice lodging identification in multi-date UAV visible images[J]. Remote Sensing, 12, 633(2020).

    [19] Ma H Y, Zhang T Y, Dai Q L et al. Extracting urban vegetation from high-resolution remote sensing image based on I-FCN model[J]. Journal of Southwest Forestry University (Natural Sciences), 39, 117-123(2019).

    [20] Alhassan V, Henry C, Ramanna S et al. A deep learning framework for land-use/land-cover mapping and analysis using multispectral satellite imagery[J]. Neural Computing and Applications, 32, 8529-8544(2020).

    [21] Lin J H, Chen Y Z, Wang X Q. Road greening level evaluation of Gulou district in Fuzhou based on visible green index[J]. Journal of Chinese Urban Forestry, 19, 73-77, 84(2021).

    [22] Gui Y Y, Li W, Wang Y N et al. Woodland detection using most-sure strategy to fuse segmentation results of deep learning[C], 6724-6727(2019).

    [23] Morales G, Kemper G, Sevillano G et al. Automatic segmentation of Mauritia flexuosa in unmanned aerial vehicle (UAV) imagery using deep learning[J]. Forests, 9, 736(2018).

    [24] Zhu Q H. ACDNet with ASPP for camouflaged object detection[J]. Journal of Physics: Conference Series, 1982, 012082(2021).

    [25] Yao X D, Yang H, Wu Y L et al. Land use classification of the deep convolutional neural network method reducing the loss of spatial features[J]. Sensors, 19, 2792(2019).

    [27] Sun K, Xiao B, Liu D et al. Deep high-resolution representation learning for human pose estimation[C](2019).

    [28] Chen L C, Zhu Y K, Papandreou G et al. Encoder-decoder with atrous separable convolution for semantic image segmentation[M]. Ferrari V, Hebert M, Sminchisescu C, et al. Computer vision-ECCV 2018, 11211, 833-851(2018).

    [29] Wu Y X, He K M. Group normalization[J]. International Journal of Computer Vision, 128, 742-755(2020).

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    Mingzhu Xu, Hao Xu, Peng Kong, Yanlan Wu. Remote Sensing Vegetation Classification Method Based on Vegetation Index and Convolution Neural Network[J]. Laser & Optoelectronics Progress, 2022, 59(24): 2428005

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    Paper Information

    Category: Remote Sensing and Sensors

    Received: Sep. 14, 2021

    Accepted: Nov. 3, 2021

    Published Online: Nov. 28, 2022

    The Author Email: Wu Yanlan (wuyanlan@ahu.edu.cn)

    DOI:10.3788/LOP202259.2428005

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