22.5.11.1 Urban Trees, Individual Trees, Street Trees

Chapter Contents (Back)
Trees. Urban Trees. See also Trees, Individual Trees, Tree Crowns. See also Trees, Forest, Stem Volume, Biomass Measurements.

Zhang, Y.[Yun],
Texture-Integrated Classification of Urban Treed Areas in High-Resolution Color-Infrared Imagery,
PhEngRS(67), No. 12, December 2001, pp. 1359-1366. To effectively extract tree textural features and eliminate noise, use conditional variance detection. It consists of a directional variance detection and a local variance detection.
WWW Link. 0201
BibRef

Ouma, Y.O.[Yashon O.], Tateishi, R.,
Urban-trees extraction from Quickbird imagery using multiscale spectex-filtering and non-parametric classification,
PandRS(63), No. 3, May 2008, pp. 333-351.
Elsevier DOI 0711
Quickbird; Urban-trees; Multiscale texture; Multiscale spectex-filtering; Non-parametric classification BibRef

Ardila, J.P.[Juan P.], Tolpekin, V.A.[Valentyn A.], Bijker, W.[Wietske], Stein, A.[Alfred],
Markov-random-field-based super-resolution mapping for identification of urban trees in VHR images,
PandRS(66), No. 6, November 2011, pp. 762-775.
Elsevier DOI 1112
Image classification; Markov random field; Super resolution mapping; Urban trees; Contextual classification BibRef

Ardila, J.P.[Juan P.], Bijker, W.[Wietske], Tolpekin, V.A.[Valentyn A.], Stein, A.[Alfred],
Quantification of crown changes and change uncertainty of trees in an urban environment,
PandRS(74), No. 1, November 2012, pp. 41-55.
Elsevier DOI 1212
Change detection; Fuzzy change; Object change detection; Tree crown detection; Urban trees BibRef

Höfle, B.[Bernhard], Hollaus, M.[Markus], Hagenauer, J.[Julian],
Urban vegetation detection using radiometrically calibrated small-footprint full-waveform airborne LiDAR data,
PandRS(67), No. 1, January 2012, pp. 134-147.
Elsevier DOI 1202
Laser scanning; LiDAR; Calibration; Vegetation; Object based image analysis; Full-waveform BibRef

Shrestha, R., Wynne, R.,
Estimating Biophysical Parameters of Individual Trees in an Urban Environment Using Small Footprint Discrete-Return Imaging Lidar,
RS(4), No. 2, February 2012, pp. 484-508.
DOI Link 1203
BibRef

Zhang, K., Hu, B.,
Individual Urban Tree Species Classification Using Very High Spatial Resolution Airborne Multi-Spectral Imagery Using Longitudinal Profiles,
RS(4), No. 6, June 2012, pp. 1741-1757.
DOI Link 1208
BibRef

Agarwal, S., Vailshery, L., Jaganmohan, M., Nagendra, H.,
Mapping Urban Tree Species Using Very High Resolution Satellite Imagery: Comparing Pixel-Based and Object-Based Approaches,
IJGI(2), No. 1, 2013, pp. 220-236.
DOI Link 1303
BibRef

Wu, B., Yu, B., Yue, W., Shu, S., Tan, W., Hu, C., Huang, Y., Wu, J., Liu, H.,
A Voxel-Based Method for Automated Identification and Morphological Parameters Estimation of Individual Street Trees from Mobile Laser Scanning Data,
RS(5), No. 2, February 2013, pp. 584-611.
DOI Link 1303
BibRef

Zhou, J.H.[Jian-Hua], Yu, B.[Bailang], Qin, J.[Jun],
Multi-Level Spatial Analysis for Change Detection of Urban Vegetation at Individual Tree Scale,
RS(6), No. 9, 2014, pp. 9086-9103.
DOI Link 1410
BibRef

Zhang, C.Y.[Cai-Yun], Zhou, Y.H.[Yu-Hong], Qiu, F.[Fang],
Individual Tree Segmentation from LiDAR Point Clouds for Urban Forest Inventory,
RS(7), No. 6, 2015, pp. 7892.
DOI Link 1507
BibRef

Li, D.[Dan], Ke, Y.H.[Ying-Hai], Gong, H.[Huili], Li, X.J.[Xiao-Juan],
Object-Based Urban Tree Species Classification Using Bi-Temporal WorldView-2 and WorldView-3 Images,
RS(7), No. 12, 2015, pp. 15861.
DOI Link 1601
BibRef

Li, L.[Lin], Li, D.[Dalin], Zhu, H.[Haihong], Li, Y.[You],
A dual growing method for the automatic extraction of individual trees from mobile laser scanning data,
PandRS(120), No. 1, 2016, pp. 37-52.
Elsevier DOI 1610
Individual tree BibRef

Guan, H.Y.[Hai-Yan], Cao, S., Yu, Y.T.[Yong-Tao], Li, J.[Jonathan], Liu, N., Chen, P., Li, Y.,
Street-Scene Tree Segmentation from Mobile Laser Scanning Data,
ISPRS16(B3: 221-225).
DOI Link 1610
BibRef

Li, Y.[You], Li, L.[Lin], Li, D.[Dalin], Yang, F.[Fan], Liu, Y.[Yu],
A Density-Based Clustering Method for Urban Scene Mobile Laser Scanning Data Segmentation,
RS(9), No. 4, 2017, pp. xx-yy.
DOI Link 1705
BibRef

Yu, Y.T.[Yong-Tao], Li, J.[Jonathan], Guan, H.Y.[Hai-Yan], Wang, C.[Cheng], Wen, C.,
Bag of Contextual-Visual Words for Road Scene Object Detection From Mobile Laser Scanning Data,
ITS(17), No. 12, December 2016, pp. 3391-3406.
IEEE DOI 1612
Automobiles BibRef

Yu, Y.T.[Yong-Tao], Li, J.[Jonathan], Guan, H.Y.[Hai-Yan], Wang, C.[Cheng], Cheng, M.[Ming],
A Marked Point Process for Automated Tree Detection from Mobile Laser Scanning Point Cloud Data,
CVRS12(140-145).
IEEE DOI 1302
See also Automated Detection of Three-Dimensional Cars in Mobile Laser Scanning Point Clouds Using DBM-Hough-Forests. See also Traffic Sign Occlusion Detection Using Mobile Laser Scanning Point Clouds. BibRef

Yu, Y.T.[Yong-Tao], Li, J., Guan, H.[Haiyan], Zai, D., Wang, C.,
Automated Extraction of 3D Trees from Mobile LiDAR Point Clouds,
CloseRange14(629-632).
DOI Link 1411
BibRef

Louarn, M.L.[Marine Le], Clergeau, P.[Philippe], Briche, E.[Elodie], Deschamps-Cottin, M.[Magali],
'Kill Two Birds with One Stone': Urban Tree Species Classification Using Bi-Temporal Pléiades Images to Study Nesting Preferences of an Invasive Bird,
RS(9), No. 9, 2017, pp. xx-yy.
DOI Link 1711
BibRef

Branson, S.[Steve], Wegner, J.D.[Jan Dirk], Hall, D.[David], Lang, N.[Nico], Schindler, K.[Konrad], Perona, P.[Pietro],
From Google Maps to a fine-grained catalog of street trees,
PandRS(135), No. Supplement C, 2018, pp. 13-30.
Elsevier DOI 1712
Award, U.V. Helava, ISPRS. Deep learning, Image interpretation, Urban areas, Street trees, Very high resolution BibRef

Herfort, B.[Benjamin], Höfle, B.[Bernhard], Klonner, C.[Carolin],
3D micro-mapping: Towards assessing the quality of crowdsourcing to support 3D point cloud analysis,
PandRS(137), 2018, pp. 73-83.
Elsevier DOI 1802
LiDAR, Urban trees, Crowdsourcing, Point cloud classification, Quality BibRef

Zhang, Y.L.[Yong-Lin], Dong, R.C.[Ren-Cai],
Impacts of Street-Visible Greenery on Housing Prices: Evidence from a Hedonic Price Model and a Massive Street View Image Dataset in Beijing,
IJGI(7), No. 3, 2018, pp. xx-yy.
DOI Link 1804
BibRef

Lin, Y.[Yi], Jiang, M.[Miao],
A New Algorithm for MLS-Based DBH Mensuration and Its Preliminary Validation in an Urban Boreal Forest: Aiming at One Cornerstone of Allometry-Based Forest Biometrics,
RS(10), No. 5, 2018, pp. xx-yy.
DOI Link 1806
BibRef

Adeline, K.R.M., Briottet, X., Ceamanos, X., Dartigalongue, T., Gastellu-Etchegorry, J.P.,
ICARE-VEG: A 3D physics-based atmospheric correction method for tree shadows in urban areas,
PandRS(142), 2018, pp. 311-327.
Elsevier DOI 1807
Atmospheric correction, Radiative transfer, Hyperspectral, High spatial resolution, Tree shadows, Urban areas BibRef

Singh, K.K.[Kunwar K.], Chen, Y.H.[Yin-Hsuen], Smart, L.[Lindsey], Gray, J.[Josh], Meentemeyer, R.K.[Ross K.],
Intra-annual phenology for detecting understory plant invasion in urban forests,
PandRS(142), 2018, pp. 151-161.
Elsevier DOI 1807
Biological invasion, Vegetation indices, Vegetation phenology, Normalized difference vegetation index, , Chinese privet, Random forest BibRef

Vahidi, H.[Hossein], Klinkenberg, B.[Brian], Johnson, B.A.[Brian A.], Moskal, L.M.[L. Monika], Yan, W.[Wanglin],
Mapping the Individual Trees in Urban Orchards by Incorporating Volunteered Geographic Information and Very High Resolution Optical Remotely Sensed Data: A Template Matching-Based Approach,
RS(10), No. 7, 2018, pp. xx-yy.
DOI Link 1808
BibRef

Hu, R.H.[Rong-Hai], Bournez, E.[Elena], Cheng, S.[Shiyu], Jiang, H.[Hailan], Nerry, F.[Françoise], Landes, T.[Tania], Saudreau, M.[Marc], Kastendeuch, P.[Pierre], Najjar, G.[Georges], Colin, J.[Jérôme], Yan, G.[Guangjian],
Estimating the leaf area of an individual tree in urban areas using terrestrial laser scanner and path length distribution model,
PandRS(144), 2018, pp. 357-368.
Elsevier DOI 1809
Individual tree, Leaf area, Foliage area volume density, Terrestrial laser scanner, Urban areas, Path length distribution BibRef

Wu, J.W.[Jian-Wei], Yao, W.[Wei], Polewski, P.[Przemyslaw],
Mapping Individual Tree Species and Vitality along Urban Road Corridors with LiDAR and Imaging Sensors: Point Density versus View Perspective,
RS(10), No. 9, 2018, pp. xx-yy.
DOI Link 1810
BibRef

Mozgeris, G.[Gintautas], Juodkiene, V.[Vytaute], Jonikavicius, D.[Donatas], Straigyte, L.[Lina], Gadal, S.[Sébastien], Ouerghemmi, W.[Walid],
Ultra-Light Aircraft-Based Hyperspectral and Colour-Infrared Imaging to Identify Deciduous Tree Species in an Urban Environment,
RS(10), No. 10, 2018, pp. xx-yy.
DOI Link 1811
BibRef

Aval, J.[Josselin], Demuynck, J.[Jean], Zenou, E.[Emmanuel], Fabre, S.[Sophie], Sheeren, D.[David], Fauvel, M.[Mathieu], Adeline, K.[Karine], Briottet, X.[Xavier],
Detection of individual trees in urban alignment from airborne data and contextual information: A marked point process approach,
PandRS(146), 2018, pp. 197-210.
Elsevier DOI 1812
Street tree, Urban remote sensing, Airborne data, Geographic information system, Marked point process. BibRef

Zhang, R.[Rong], Chen, J.[Jiquan], Park, H.[Hogeun], Zhou, X.[Xuhui], Yang, X.[Xuchao], Fan, P.[Peilei], Shao, C.L.[Chang-Liang], Ouyang, Z.[Zutao],
Spatial Accessibility of Urban Forests in the Pearl River Delta (PRD), China,
RS(11), No. 6, 2019, pp. xx-yy.
DOI Link 1903
BibRef

Li, X.[Xun], Chen, W.Y.[Wendy Y.], Sanesi, G.[Giovanni], Lafortezza, R.[Raffaele],
Remote Sensing in Urban Forestry: Recent Applications and Future Directions,
RS(11), No. 10, 2019, pp. xx-yy.
DOI Link 1906
BibRef

Brabant, C.[Charlotte], Alvarez-Vanhard, E.[Emilien], Laribi, A.[Achour], Morin, G.[Gwénaël], Nguyen, K.T.[Kim Thanh], Thomas, A.[Alban], Houet, T.[Thomas],
Comparison of Hyperspectral Techniques for Urban Tree Diversity Classification,
RS(11), No. 11, 2019, pp. xx-yy.
DOI Link 1906
BibRef


Gobeawan, L., Lin, E.S., Tandon, A., Yee, A.T.K., Khoo, V.H.S., Teo, S.N., Yi, S., Lim, C.W., Wong, S.T., Wise, D.J., Cheng, P., Liew, S.C., Huang, X., Li, Q.H., Teo, L.S., Fekete, G.S., Poto, M.T.,
Modeling Trees for Virtual Singapore: From Data Acquisition To Citygml Models,
GeoInfo18(55-62).
DOI Link 1901
BibRef

Hofierka, J., Gallay, M., Kanuk, J., Šupinský, J., Šašak, J.,
High-resolution Urban Greenery Mapping for Micro-climate Modelling Based On 3D City Models,
GeoInfo17(7-12).
DOI Link 1805
BibRef

Wegner, J.D., Branson, S., Hall, D., Schindler, K., Perona, P.,
Cataloging Public Objects Using Aerial and Street-Level Images: Urban Trees,
CVPR16(6014-6023)
IEEE DOI 1612
BibRef

Dogon-Yaro, M.A., Kumar, P., Abdul Rahman, A., Buyuksalih, G.,
Semi-Automated Approach for Mapping Urban Trees from Integrated Aerial Lidar Point Cloud and Digital Imagery Datasets,
GGT16(127-134).
DOI Link 1612
BibRef

Böhm, J., Bredif, M., Gierlinger, T., Krämer, M., Lindenberg, R., Liu, K., Michel, F., Sirmacek, B.,
The Iqmulus Urban Showcase: Automatic Tree Classification And Identification In Huge Mobile Mapping Point Clouds,
ISPRS16(B3: 301-307).
DOI Link 1610
BibRef

Moradi, A., Satari, M., Momeni, M.,
Individual Tree Of Urban Forest Extraction From Very High Density Lidar Data,
ISPRS16(B3: 337-343).
DOI Link 1610
BibRef

Monnier, F., Vallet, B., Soheilian, B.,
Trees Detection From Laser Point Clouds Acquired In Dense Urban Areas By A Mobile Mapping System,
AnnalsPRS(I-3), No. 2012, pp. 245-250.
HTML Version. 1209
BibRef

Liberge, S.[Sterenn], Soheilian, B.[Bahman], Chehata, N.[Nesrine], Paparoditis, N.[Nicolas],
Extraction of vertical posts in 3D laser point clouds acquired in dense urban areas by a Mobile Mapping System,
PCVIA10(B:126).
PDF File. 1009
BibRef

Kramer, H., Oldengarm, J.,
URBTREE: A Tree Growth Model for the Urban Environment,
GEOBIA10(xx-yy).
PDF File. 1007
BibRef

van der Sande, C.J.,
Automatic Object Recognition and Change Detection of Urban Trees,
GEOBIA10(xx-yy).
PDF File. 1007
BibRef

Ardila, J.P.[Juan Pablo], Tolpekin, V.A.[Valentyn A.], Bijker, W.[Wietske],
Context-Sensitive Extraction of Tree Crown Objects in Urban Areas Using VHR Satellite Images,
GEOBIA10(xx-yy).
PDF File. 1007
BibRef

Tolpekin, V.A.[Valentyn A.], Ardila, J.P.[Juan Pablo], Bijker, W.[Wietske],
Super-Resolution Mapping for Extraction of Urban Tree Crown Objects from VHR Satellite Images,
GEOBIA10(xx-yy).
PDF File. 1007
BibRef

Bijker, W.[Wietske], Ardila, J.P.[Juan Pablo], Tolpekin, V.A.[Valentyn A.],
Change Detection and Uncertainty in Fuzzy Tree Crown Objects in an Urban Environment,
GEOBIA10(xx-yy).
PDF File. 1007
BibRef

Yang, Y.[Yun], Lin, Y.[Ying],
A Novel Deformable Model for Urban Vegetation Detection Using LiDAR Data,
CISP09(1-5).
IEEE DOI 0910
BibRef

Huang, H.[Hai],
Terrestrial Image Based 3D Extraction of Urban Unfoliaged Trees of Different Branching Types,
ISPRS08(B3a: 253 ff).
PDF File. 0807
BibRef

Huang, H.[Hai], Mayer, H.[Helmut],
Extraction of 3D Unfoliaged Trees from Image Sequences Via a Generative Statistical Approach,
DAGM07(385-394).
Springer DOI 0709
BibRef

Carlberg, M.[Matthew], Gao, P.R.[Pei-Ran], Chen, G.[George], Zakhor, A.[Avideh],
Classifying urban landscape in aerial LiDAR using 3D shape analysis,
ICIP09(1701-1704).
IEEE DOI 0911
BibRef

Chen, G.[George], Zakhor, A.[Avideh],
2D tree detection in large urban landscapes using aerial LiDAR data,
ICIP09(1693-1696).
IEEE DOI 0911
BibRef

Secord, J., Zakhor, A.,
Tree Detection in Aerial LiDar and Image Data,
ICIP06(2317-2320).
IEEE DOI 0610
BibRef
And:
Tree detection in LiDAR data,
Southwest06(86-90).
IEEE DOI 0603
BibRef

Chapter on Remote Sensing, Cartography, Aerial Images, Buildings, Roads, Terrain, ATR continues in
Trees, Forest Canopy Analysis .


Last update:Jun 24, 2019 at 10:45:36