Urban Tree Extraction Method Based on LiDAR Data and Orthophoto

Fan Xie; Fengbao Yang; hong Wei

doi:10.3788/LOP202259.0428005

[1] Klobucar B, Östberg J, Jansson M et al. Long-term validation and governance role in contemporary urban tree monitoring: a review[J]. Sustainability, 12, 5589(2020).

[2] Jagodnik P, Gazibara S B, Arbanas Ž et al. Engineering geological mapping using airborne LiDAR datasets-an example from the Vinodol Valley, Croatia[J]. Journal of Maps, 16, 855-866(2020).

[3] Gargoum S A, El Basyouny K. A literature synthesis of LiDAR applications in transportation: feature extraction and geometric assessments of highways[J]. GIScience & Remote Sensing, 56, 864-893(2019).

[4] Zhang Z J, Cheng X J, Cao Y J et al. Application of 3D reconstruction of relic sites combined with laser and vision point cloud[J]. Chinese Journal of Lasers, 47, 1110001(2020).

[5] Saganeiti L, Amato F, Nolè G et al. Early estimation of ground displacements and building damage after seismic events using SAR and LiDAR data: the case of the Amatrice earthquake in central Italy, on 24th August 2016[J]. International Journal of Disaster Risk Reduction, 51, 101924(2020).

[6] Liu L X, Coops N C, Aven N W et al. Mapping urban tree species using integrated airborne hyperspectral and LiDAR remote sensing data[J]. Remote Sensing of Environment, 200, 170-182(2017).

[7] Man Q X, Dong P L, Guo H D et al. Light detection and ranging and hyperspectral data for estimation of forest biomass: a review[J]. Journal of Applied Remote Sensing, 8, 081598(2014).

[8] Alonzo M, Bookhagen B, Roberts D A. Urban tree species mapping using hyperspectral and lidar data fusion[J]. Remote Sensing of Environment, 148, 70-83(2014).

[9] Wen C C, Yang L N, Li X et al. Directionally constrained fully convolutional neural network for airborne LiDAR point cloud classification[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 162, 50-62(2020).

[10] Yuan J Y. Learning building extraction in aerial scenes with convolutional networks[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 40, 2793-2798(2018).

[11] Zhang A W, Liu L L, Zhang X Z. Multi-feature 3D road point cloud semantic segmentation method based on convolutional neural network[J]. Chinese Journal of Lasers, 47, 0410001(2020).

[12] Huang J F, Zhang X C, Xin Q C et al. Automatic building extraction from high-resolution aerial images and LiDAR data using gated residual refinement network[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 151, 91-105(2019).

[13] Bai H, Yang F B. LiDAR data classification method based on high recognition compound derivative feature[J]. Laser & Optoelectronics Progress, 58, 0528001(2021).

[14] Zhang J Y, Zhao X L, Chen Z et al. A review of deep learning-based semantic segmentation for point cloud[J]. IEEE Access, 7, 179118-179133(2019).

[15] Biçer M, Kaşkaş A. Solution of the radiative transfer equation for Rayleigh scattering using the infinite medium Green’s function[J]. Astrophysics and Space Science, 363, 1-8(2018).

[16] Rüfenacht D, Fredembach C, Süsstrunk S. Automatic and accurate shadow detection using near-infrared information[J]. IEEE Transactions on Pattern Analysis and Machine Intelligence, 36, 1672-1678(2014).

[17] Meng Y, Hu Z H, Chen X J et al. Subtracted histogram: utilizing mutual relation between features for thresholding[J]. IEEE Transactions on Geoscience and Remote Sensing, 56, 7415-7435(2018).

[18] Lei X D, Wang H T, Wang C et al. ALS point cloud classification by integrating an improved fully convolutional network into transfer learning with multi-scale and multi-view deep features[J]. Sensors, 20, 6969(2020).

[19] Liu Y, Nguyen D M, Deligiannis N et al. Hourglass-ShapeNetwork based semantic segmentation for high resolution aerial imagery[J]. Remote Sensing, 9, 522(2017).

[20] Zhang J, Lin S F, Ding L et al. Multi-scale context aggregation for semantic segmentation of remote sensing images[J]. Remote Sensing, 12, 701(2020).

[21] Cao Z Y, Diao W H, Sun X et al. C3Net: cross-modal feature recalibrated, cross-scale semantic aggregated and compact network for semantic segmentation of multi-modal high-resolution aerial images[J]. Remote Sensing, 13, 528(2021).

[22] Marmanis D, Schindler K, Wegner J D et al. Classification with an edge: improving semantic image segmentation with boundary detection[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 135, 158-172(2018).

[23] Gerke M, Xiao J. Fusion of airborne laserscanning point clouds and images for supervised and unsupervised scene classification[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 87, 78-92(2014).

[24] Li N, Liu C, Pfeifer N. Improving LiDAR classification accuracy by contextual label smoothing in post-processing[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 148, 13-31(2019).

[25] Wang C S, Shu Q Q, Wang X Y et al. A random forest classifier based on pixel comparison features for urban LiDAR data[J]. ISPRS Journal of Photogrammetry and Remote Sensing, 148, 75-86(2019).

[26] Wu Q, Zhong R F, Zhao W J et al. A comparison of pixel-based decision tree and object-based support vector machine methods for land-cover classification based on aerial images and airborne lidar data[J]. International Journal of Remote Sensing, 38, 7176-7195(2017).