Monitoring tree-level insect population dynamics with multi-scale and multi-source remote sensing

被引:21
|
作者
Wulder, M. A. [1 ]
Ortlepp, S. M. [1 ]
White, J. C. [1 ]
Coops, N. C. [2 ]
Coggins, S. B. [2 ]
机构
[1] Nat Resources Canada, Canadian Forest Serv, Pacific Forestry Ctr, Victoria, BC V8Z 1M5, Canada
[2] Univ British Columbia, Dept Forest Resource Management, Vancouver, BC V6T 1Z4, Canada
关键词
high spatial resolution; QuickBird; digital aerial photography; insect; monitoring; mountain pine beetle;
D O I
10.1080/14498596.2008.9635135
中图分类号
P9 [自然地理学];
学科分类号
0705 ; 070501 ;
摘要
Long term monitoring of the rate-of-change of mountain pine beetle (Dendroctonus ponderosae Hopkins) populations requires detailed tree-level information over large areas. This information is used to assess the status of an infestation (e.g., increasing, stable or decreasing), and to select and evaluate mitigation approaches. In this research project, we develop and demonstrate a prototype monitoring system, which enables the extrapolation of tree level estimates of beetle damage from field data to a larger study area using a double sampling approach, and multi-scale, multi-source, high spatial resolution remotely sensed data.
引用
收藏
页码:49 / 61
页数:13
相关论文
共 50 条
  • [1] Multi-Scale PIIFD for Registration of Multi-Source Remote Sensing Images
    Gao, Chenzhong
    Li, Wei
    [J]. Journal of Beijing Institute of Technology (English Edition), 2021, 30 (02): : 113 - 124
  • [2] Multi-Scale PIIFD for Registration of Multi-Source Remote Sensing Images
    Chenzhong Gao
    Wei LiChen
    [J]. Journal of Beijing Institute of Technology, 2021, 30 (02) : 113 - 124
  • [3] Analysing and Correcting the Differences between Multi-Source and Multi-Scale Spatial Remote Sensing
    Dong, Yingying
    Luo, Ruisen
    Feng, Haikuan
    Wang, Jihua
    Zhao, Jinling
    Zhu, Yining
    Yang, Guijun
    [J]. PLOS ONE, 2014, 9 (11):
  • [4] THE MULTI-LEVEL AND MULTI-SCALE FACTOR ANALYSIS FOR SOIL MOISTURE INFORMATION EXTRACTION BY MULTI-SOURCE REMOTE SENSING DATA
    Yu, F.
    Li, H. T.
    Jia, Y.
    Han, Y. S.
    Gu, H. Y.
    [J]. 3RD ISPRS IWIDF 2013, 2013, 40-7-W1 : 167 - 171
  • [5] Estimation of multi-scale urban vegetation coverage based on multi-source remote sensing images
    Gao Yong-Gang
    Xu Han-Qiu
    [J]. JOURNAL OF INFRARED AND MILLIMETER WAVES, 2017, 36 (02) : 225 - 234
  • [6] Temporal dynamic analysis of a mountain ecosystem based on multi-source and multi-scale remote sensing data
    Ibarrola-Ulzurrun, Edurne
    Marcello, Javier
    Gonzalo-Martin, Consuelo
    Luis Martin-Esquivel, Jose
    [J]. ECOSPHERE, 2019, 10 (06):
  • [7] Fusion of Multi-source and Multi-scale Remote Sensing Data for Water Availability Assessment in a Metropolitan Region
    Chang, N. B.
    Yang, Y. J.
    Daranpob, A.
    [J]. REMOTE SENSING FOR ENVIRONMENTAL MONITORING, GIS APPLICATIONS, AND GEOLOGY IX, 2009, 7478
  • [8] MULTI-SOURCE MULTI-SCALE HIERARCHICAL CONDITIONAL RANDOM FIELD MODEL FOR REMOTE SENSING IMAGE CLASSIFICATION
    Zhang, Z.
    Yang, M. Y.
    Zhou, M.
    [J]. PIA15+HRIGI15 - JOINT ISPRS CONFERENCE, VOL. II, 2015, 2-3 (W4): : 293 - 300
  • [9] Study on wetlands with multi-scale based on multi-source remote sensing data in Dongting Lake basin
    Zhang, Meng
    [J]. Cehui Xuebao/Acta Geodaetica et Cartographica Sinica, 2020, 49 (08):
  • [10] Monitoring Ghost Cities at Prefecture Level from Multi-source Remote sensing Data
    Ma, Xiaolong
    Tong, Xiaohua
    Ma, Zhaoting
    Liu, Sicong
    [J]. 2017 INTERNATIONAL WORKSHOP ON REMOTE SENSING WITH INTELLIGENT PROCESSING (RSIP 2017), 2017,