COMBINING CANOPY MAPPING AND TREE DETECTION FOR URBAN TREE HERITAGE MONITORING FROM VHR IMAGES

被引:0
作者
Budin, R. [1 ]
Beguet, B. [1 ]
Rozo, C. [1 ]
Debonnaire, N. [1 ]
Lafon, V [1 ]
机构
[1] i Sea, Pessac, France
来源
IGARSS 2024-2024 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, IGARSS 2024 | 2024年
关键词
canopy mapping; tree detection; urban area; VHR images;
D O I
10.1109/IGARSS53475.2024.10642956
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Monitoring the tree heritage of large urban areas is a major new challenge for public decision-makers. The need for highly precise spatial information and annual updates, makes satellite and aerial remote sensing a preferred tool. In this article, we present the limits of two popular approaches: (1) canopy mapping by supervised classification of time series of satellite images at the pixel level and (2) automatic tree detection by DeepLearning approach. Then, we propose a strategy to combine the potential of these two approaches in an operational and reproducible system for monitoring urban tree heritage with very high precision.
引用
收藏
页码:4605 / 4609
页数:5
相关论文
共 11 条
[1]  
Beguet B., 2019, ESA PHI WEEK
[2]   Random forests [J].
Breiman, L .
MACHINE LEARNING, 2001, 45 (01) :5-32
[3]   Tree height mapping and crown delineation using LiDAR, large format aerial photographs, and unmanned aerial vehicle photogrammetry in subtropical urban forest [J].
Kwong, Ivan H. Y. ;
Fung, Tung .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2020, 41 (14) :5228-5256
[4]   Focal Loss for Dense Object Detection [J].
Lin, Tsung-Yi ;
Goyal, Priya ;
Girshick, Ross ;
He, Kaiming ;
Dollar, Piotr .
2017 IEEE INTERNATIONAL CONFERENCE ON COMPUTER VISION (ICCV), 2017, :2999-3007
[5]   Mapping of Urban Vegetation with High-Resolution Remote Sensing: A Review [J].
Neyns, Robbe ;
Canters, Frank .
REMOTE SENSING, 2022, 14 (04)
[6]   A comparative analysis of high spatial resolution IKONOS and WorldView-2 imagery for mapping urban tree species [J].
Pu, Ruiliang ;
Landry, Shawn .
REMOTE SENSING OF ENVIRONMENT, 2012, 124 :516-533
[7]   Remote sensing of urban green spaces: A review [J].
Shahtahmassebi, Amir Reza ;
Li, Chenlu ;
Fan, Yifan ;
Wu, Yani ;
Lin, Yue ;
Gan, Muye ;
Wang, Ke ;
Malik, Arunima ;
Blackburn, George Alan .
URBAN FORESTRY & URBAN GREENING, 2021, 57
[8]   The use of high-resolution imagery for identification of urban climax forest species using traditional and rule-based classification approach [J].
Sugumaran, R ;
Pavuluri, MK ;
Zerr, D .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 2003, 41 (09) :1933-1939
[9]   Urban vegetation classification: Benefits of multitemporal RapidEye satellite data [J].
Tigges, Jan ;
Lakes, Tobia ;
Hostert, Patrick .
REMOTE SENSING OF ENVIRONMENT, 2013, 136 :66-75
[10]   A Review: Individual Tree Species Classification Using Integrated Airborne LiDAR and Optical Imagery with a Focus on the Urban Environment [J].
Wang, Kepu ;
Wang, Tiejun ;
Liu, Xuehua .
FORESTS, 2019, 10 (01)