Developing a more accurate method for individual plant segmentation of urban tree and shrub communities using LiDAR technology

References

• Ahmad, H. (2007). The development of multi-layer herbaceous plant communities for use in urban parks and green spaces [PhD thesis]. University of Sheffield.
   Google Scholar
• Alexander, C. (2009). Delineating tree crowns from airborne laser scanning point cloud data using delaunay triangulation. International Journal of Remote Sensing, 30(14), 3843–3848. doi:10.1080/01431160902842318
   Web of Science ®Google Scholar
• Burkman, C. E., & Gardiner, M. M. (2014). Urban greenspace composition and landscape context influence natural enemy community composition and function. Biological Control, 75, 58–67. doi:10.1016/j.biocontrol.2014.02.015
   Web of Science ®Google Scholar
• Chamberlain, C. P., Sánchez Meador, A. J., & Thode, A. E. (2021). Airborne lidar provides reliable estimates of canopy base height and canopy bulk density in southwestern Ponderosa pine forests. Forest Ecology and Management, 481, 118695. doi:10.1016/j.foreco.2020.118695
   Web of Science ®Google Scholar
• Chen, Q., Baldocchi, D., Gong, P., & Kelly, M. (2006). Isolating individual trees in a savanna woodland using small footprint lidar data. Photogrammetric Engineering & Remote Sensing, 72(8), 923–932. doi:10.14358/PERS.72.8.923
   Web of Science ®Google Scholar
• Chen, Q., Gong, P., Baldocchi, D., & Tian, Y. Q. (2007). Estimating basal area and stem volume for individual trees from lidar data. Photogrammetric Engineering & Remote Sensing, 73(12), 1355–1365. doi:10.14358/PERS.73.12.1355
   Web of Science ®Google Scholar
• Chen, X., Jiang, K., Zhu, Y., Wang, X., & Yun, T. (2021). Individual tree crown segmentation directly from UAV-borne LiDAR data using the pointnet of deep learning. Forests, 12(2), 131–153. doi:10.3390/f12020131
   Web of Science ®Google Scholar
• Chisholm, R. A., Cui, J., Lum, S. K. Y., & Chen, B. M. (2013). UAV LiDAR for below-canopy forest surveys. Journal of Unmanned Vehicle Systems, 01 (01), 61–68. doi:10.1139/juvs-2013-0017
   Google Scholar
• Côté, J. F., Fournier, R. A., & Egli, R. (2011). An architectural model of trees to estimate forest structural attributes using terrestrial LiDAR. Environmental Modelling & Software, 26(6), 761–777. doi:10.1016/j.envsoft.2010.12.008
   Web of Science ®Google Scholar
• Dunnett, N., & Hitchmough, J. (2004). The dynamic landscape: Design, ecology and management of naturalistic urban planting. London: Taylor & Francis.
   Google Scholar
• Falkowski, M. J., Hudak, A. T., Crookston, N. L., Gessler, P. E., Uebler, E. H., & Smith, A. M. S. (2010). Landscape-scale parameterization of a tree-level forest growth model: A k-nearest neighbor imputation approach incorporating LiDAR data. Canadian Journal of Forest Research, 40(2), 184–199. doi:10.1139/X09-183
   Web of Science ®Google Scholar
• Guo, Q., Li, W., Yu, H., & Alvarez, O. (2010). Effects of topographic variability and lidar sampling density on several DEM interpolation methods. Photogrammetric Engineering & Remote Sensing, 76(6), 701–712. doi:10.14358/PERS.76.6.701
   Web of Science ®Google Scholar
• Hitchmough, J., & Fieldhouse, K. (2003). Plant user handbook: A guide to effective specifying. Oxford: Blackwell Pub.
   Google Scholar
• Hollenbeck, J. P., Olsen, M. J., & Haig, S. M. (2014). Using terrestrial laser scanning to support ecological research in the rocky intertidal zone. Journal of Coastal Conservation, 18(6), 701–714. doi:10.1007/s11852-014-0346-8
   Web of Science ®Google Scholar
• Holmgren, J. (2004). Prediction of tree height, basal area and stem volume in forest stands using airborne laser scanning. Scandinavian Journal of Forest Research, 19(6), 543–553. doi:10.1080/02827580410019472
   Web of Science ®Google Scholar
• Hopkinson, C., Lovell, J., Chasmer, L., Jupp, D., Kljun, N., & van Gorsel, E. (2013). Integrating terrestrial and airborne lidar to calibrate a 3D canopy model of effective leaf area index. Remote Sensing of Environment, 136, 301–314. doi:10.1016/j.rse.2013.05.012
   Web of Science ®Google Scholar
• Hyyppä, J., Yu, X., Hyyppä, H., Vastaranta, M., Holopainen, M., Kukko, A., … Alho, P. (2012). Advances in forest inventory using airborne laser scanning. Remote Sensing, 4(5), 1190–1207. doi:10.3390/rs4051190
   Web of Science ®Google Scholar
• Korpela, I., Dahlin, B., Schäfer, H., Bruun, E., Haapaniemi, F., Honkasalo, J., … Mustonen, J. (2007). Single-tree forest inventory using lidar and aerial images for 3D treetop positioning, species recognition, height and crown width estimation. ISPRS, XXXVI, 227–233.
   Google Scholar
• Kwak, D. A., Lee, W. K., Lee, J. H., Biging, G. S., & Gong, P. (2007). Detection of individual trees and estimation of tree height using LiDAR data. Journal of Forest Research, 12(6), 425–434. doi:10.1007/s10310-007-0041-9
   Web of Science ®Google Scholar
• Lang, S., Tiede, D., Maier, B., & Blaschke, T. (2006). 3D forest structure analysis from optical and LIDAR data análise 3D da estrutura da floresta com dados ópticos e da LIDAR. Ambiência, 2(3), 95–110. doi:10.11834/jrs.20143091.
   Google Scholar
• Lee, H., Slatton, K. C., Roth, B. E., & Cropper, W. P. (2010). Adaptive clustering of airborne LiDAR data to segment individual tree crowns in managed pine forests. International Journal of Remote Sensing, 31(1), 117–139. doi:10.1080/01431160902882561
   Web of Science ®Google Scholar
• Li, W., Guo, Q., Jakubowski, M. K., & Kelly, M. (2012). A new method for segmenting individual trees from the lidar point cloud. Photogrammetric Engineering & Remote Sensing, 78(1), 75–84. doi:10.14358/PERS.78.1.75
   Web of Science ®Google Scholar
• Lim, K., Treitz, P., Wulder, M., St-Onge, B., & Flood, M. (2003). LiDAR remote sensing of forest structure. Progress in Physical Geography: Earth and Environment, 27(1), 88–106. doi:10.1191/0309133303pp360ra
   Google Scholar
• Liu, L., Pang, Y., Li, Z., Xu, G., Li, D., & Zheng, G. (2014). Retrieving structural parameters of individual tree through terrestrial laser scanning data. Journal of Remote Sensing, 18, 365–377. doi:10.11834/jrs.20143091.
   Google Scholar
• López, J. P. A. (2012). Object-based methods for mapping and monitoring of urban trees with multitemporal image analysis. Faculty of Geo-Information Science and Earth Observation, 176. Retrieved from http://www.itc.nl/library/papers_2012/phd/ardila.pdf
   Google Scholar
• Lovell, J. L., Haverd, V., Jupp, D. L. B., & Newnham, G. J. (2012). The canopy semi-analytic pgap and radiative transfer (CanSPART) model: Validation using ground based lidar. Agricultural and Forest Meteorology, 158-159, 1–12. doi:10.1016/j.agrformet.2012.01.020
   Web of Science ®Google Scholar
• Miehe, G., Miehe, S., Böhner, J., Bäumler, R., & Pendry, C. (2016). Nepal: An introduction to the natural history, ecology and human environment in the himalayas. Mountain Research and Development, 36(4), 563–564. doi:10.1659/mrd.mm194.
   Google Scholar
• Pascu, I. S., Dobre, A. C., Badea, O., & Tanase, M. A. (2020). Retrieval of forest structural parameters from terrestrial laser scanning: A romanian case study. Forests, 11(4), 392. doi:10.3390/f11040392
   Web of Science ®Google Scholar
• Popescu, S. C., & Wynne, R. H. (2004). Seeing the trees in the forest: Using lidar and multispectral data fusion with local filtering and variable window size for estimating tree height. Photogrammetric Engineering & Remote Sensing, 70(5), 589–604. doi:10.14358/PERS.70.5.589
   Web of Science ®Google Scholar
• Reitberger, J., Schnörr, C., Krzystek, P., & Stilla, U. (2009). 3D segmentation of single trees exploiting full waveform LIDAR data. ISPRS Journal of Photogrammetry and Remote Sensing, 64(6), 561–574. doi:10.1016/j.isprsjprs.2009.04.002
   Web of Science ®Google Scholar
• Riaño, D., Chuvieco, E., Condés, S., González-Matesanz, J., & Ustin, S. L. (2004). Generation of crown bulk density for Pinus sylvestris L. from lidar. Remote Sensing of Environment, 92(3), 345–352. doi:10.1016/j.rse.2003.12.014
   Web of Science ®Google Scholar
• Sankey, J. B., Glenn, N. F., Germino, M. J., Gironella, A. I. N., & Thackray, G. D. (2010). Relationships of aeolian erosion and deposition with LiDAR-derived landscape surface roughness following wildfire. Geomorphology, 119(1–2), 135–145. doi:10.1016/j.geomorph.2010.03.013
   Web of Science ®Google Scholar
• Shu-Hua, L. (2010). Symbiosis and circulation − The basic thought of urban green space construction under low-carbon economic society. Chinese Landscape Architecture, 6, 14.
   Google Scholar
• Solberg, S., Naesset, E., & Bollandsas, O. M. (2006). Single tree segmentation using airborne laser scanner data in a structurally Heterogeneous spruce forest. Photogrammetric Engineering & Remote Sensing, 72(12), 1369–1378. doi:10.14358/PERS.72.12.1369
   Web of Science ®Google Scholar
• Tao, S., Wu, F., Guo, Q., Wang, Y., Li, W., Xue, B., Hu, X., Li, P., … Fang, J. (2015). Segmenting tree crowns from terrestrial and mobile LiDAR data by exploring ecological theories. ISPRS Journal of Photogrammetry and Remote Sensing, 110, 66–76. doi:10.1016/j.isprsjprs.2015.10.007
   Web of Science ®Google Scholar
• Tomaštík, J., Mokroš, M., Saloň, Š., Chudý, F., & Tunák, D. (2017). Accuracy of photogrammetric UAV-based point clouds under conditions of partially-open forest canopy. Forests, 8(5), 151. doi:10.3390/f8050151
   Web of Science ®Google Scholar
• Torresan, C., Carotenuto, F., Chiavetta, U., Miglietta, F., Zaldei, A., & Gioli, B. (2020). Individual tree crown segmentation in two-layered dense mixed forests from UAV LiDAR data. Drones, 4(2), 10. doi:10.3390/drones4020010
   Google Scholar
• Tzoulas, K., Korpela, K., Venn, S., Yli-Pelkonen, V., Kaźmierczak, A., Niemela, J., & James, P. (2007). Promoting ecosystem and human health in urban areas using Green Infrastructure: A literature review. Landscape and Urban Planning, 81(3), 167–178. doi:10.1016/j.landurbplan.2007.02.001
   Web of Science ®Google Scholar
• Vepakomma, U., St-Onge, B., & Kneeshaw, D. (2011). Response of a boreal forest to canopy opening: Assessing vertical and lateral tree growth with multi-temporal lidar data. Ecological Applications : a Publication of the Ecological Society of America, 21(1), 99–121. doi:10.1890/09-0896.1.
   PubMed Web of Science ®Google Scholar
• Wang, X. H., Zhang, Y. Z., & Xu, M. M. (2019). A multi-threshold segmentation for tree-level parameter extraction in a deciduous forest using small-footprint airborne LiDAR data. Remote Sensing, 11(18), 2109. doi:10.3390/rs11182109
   Web of Science ®Google Scholar
• Wang, X. D., Yang, Q. S., & Zhang, Q. F. (2016). Research on the construction of landscape plant communities and management in the urban green space. Chinese Landscape Architecture, 1, 1–16.
   Google Scholar
• Yao, W., Krzystek, P., & Heurich, M. (2012). Tree species classification and estimation of stem volume and DBH based on single tree extraction by exploiting airborne full-waveform LiDAR data. Remote Sensing of Environment, 123, 368–380. doi:10.1016/j.rse.2012.03.027
   Web of Science ®Google Scholar
• Yokoya, N., Nakazawa, S., Matsuki, T., & Iwasaki, A. (2014). Fusion of hyperspectral and LiDAR data for landscape visual quality assessment. IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 7(6), 2419–2425. doi:10.1109/JSTARS.2014.2313356
   Web of Science ®Google Scholar
• Yu, X., Hyyppä, J., Vastaranta, M., Holopainen, M., & Viitala, R. (2011). Predicting individual tree attributes from airborne laser point clouds based on the random forests technique. ISPRS Journal of Photogrammetry and Remote Sensing, 66(1), 28–37. doi:10.1016/j.isprsjprs.2010.08.003
   Web of Science ®Google Scholar
• Yusup, A., Halik, Ü., Abliz, A., & Keyimu - Märdan Keyum, M. (2020). Terrestrial laser scanning for retrieving the structural parameters of Populus euphratica riparian forests in the lower reaches of the Tarim River, China. Acta Ecologica Sinica, 40(13), 4555–4565. doi:10.5846/stxb201911162475.
   Google Scholar
• Zaforemska, A., Xiao, W., & Gaulton, R. (2019). Individual tree detection from UAV lidar data in a mixed species woodland. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, XLII-2/W13, 657–663. doi:10.5194/isprs-archives-XLII-2-W13-657-2019
   Google Scholar
• Zellweger, F., Morsdorf, F., Purves, R. S., Braunisch, V., & Bollmann, K. (2014). Improved methods for measuring forest landscape structure: LiDAR complements field-based habitat assessment. Biodiversity and Conservation, 23(2), 289–307. doi:10.1007/s10531-013-0600-7
   Web of Science ®Google Scholar
• Zhang, C.-Y., Hu, Y.-M., Liu, M., & Li, C.-L. (2019). Research progress on three-dimensional pattern in landscape ecology. Ying Yong Sheng Tai Xue Bao = the Journal of Applied Ecology, 30(12), 4353–4360.
   PubMedGoogle Scholar
• Zhengzhou Meteorological Bureau. (2019). Remote sensing information of agricultural meteorological in Zhengzhou. Zhengzhou: Zhengzhou Meteorological Bureau.
   Google Scholar