Annual mapping of large forest disturbances across Canada's forests using 250 m MODIS imagery from 2000 to 2011

被引:53
|
作者
Guindon, L. [1 ]
Bernier, P. Y. [1 ]
Beaudoin, A. [1 ]
Pouliot, D. [2 ]
Villemaire, P. [1 ]
Hall, R. J. [3 ]
Latifovic, R. [2 ]
St-Amant, R. [1 ]
机构
[1] Nat Resources Canada, Canadian Forest Serv, Laurentian Forestry Ctr, Stn St Foy, PQ G1V 4C7, Canada
[2] Canada Ctr Mapping & Earth Observat, Ottawa, ON K1A 0E4, Canada
[3] Nat Resources Canada, Canadian Forest Serv, Northern Forestry Ctr, Edmonton, AB T6H 3S5, Canada
关键词
boreal forest; National Burned Area Composite; remote sensing; regression tree; decision tree; change detection; LAND-COVER; BOREAL FOREST; AREA; RESOLUTION; ACCURACY;
D O I
10.1139/cjfr-2014-0229
中图分类号
S7 [林业];
学科分类号
0829 ; 0907 ;
摘要
Disturbances such as fire and harvesting shape forest dynamics and must be accounted for when modelling forest properties. However, acquiring timely disturbance information for all of Canada's large forest area has always been challenging. Therefore, we developed an approach to detect annual forest change resulting from fire, harvesting, or flooding using Moderate Resolution Imaging Spectroradiometer (MODIS) imagery at 250 m spatial resolution across Canada and to estimate the withinpixel fractional change (FC). When this approach was applied to the period from 2000 to 2011, the accuracy of detection of burnt, harvested, or flooded areas against our validation dataset was 82%, 80%, and 85%, respectively. With FC, 77% of the area burnt and 82% of the area harvested within the validation dataset were correctly identified. The methodology was optimized to reduce the commission error but tended to omit smaller disturbances as a result. For example, the omitted area for harvest blocks greater than 80 ha was less than 14% but increased to between 38% and 50% for harvest blocks of 20 to 30 ha. Detection of burnt and harvested areas in some regions was hindered by persistent haze or cloud cover or by insect outbreaks. All resulting data layers are available as supplementary material.
引用
收藏
页码:1545 / 1554
页数:10
相关论文
共 29 条
  • [1] DECADAL FOREST COVER LOSS ANALYSIS OVER INDIAN FORESTS USING MODIS 250M IMAGERY
    Reddy, R. Suraj
    Srivastava, Gaurav
    Rajashekar, G.
    Jha, C. S.
    Dadhwal, V. K.
    ISPRS TECHNICAL COMMISSION VIII SYMPOSIUM, 2014, 40-8 : 645 - 649
  • [2] Tracking forest attributes across Canada between 2001 and 2011 using a k nearest neighbors mapping approach applied to MODIS imagery
    Beaudoin, A.
    Bernier, P. Y.
    Villemaire, P.
    Guindon, L.
    Guo, X. Jing
    CANADIAN JOURNAL OF FOREST RESEARCH, 2018, 48 (01) : 85 - 93
  • [3] Mapping attributes of Canada's forests at moderate resolution through kNN and MODIS imagery
    Beaudoin, A.
    Bernier, P. Y.
    Guindon, L.
    Villemaire, P.
    Guo, X. J.
    Stinson, G.
    Bergeron, T.
    Magnussen, S.
    Hall, R. J.
    CANADIAN JOURNAL OF FOREST RESEARCH, 2014, 44 (05) : 521 - 532
  • [4] Variations of Annual Minimum Snow and Ice Extent over Canada and Neighboring Landmass Derived from MODIS 250-m Imagery for 2000-2014
    Trishchenko, Alexander P.
    Leblanc, Sylvain G.
    Wang, Shusen
    Li, Junhua
    Ungureanu, Calin
    Luo, Yi
    Khlopenkov, Konstantin V.
    Fontana, Fabio
    CANADIAN JOURNAL OF REMOTE SENSING, 2016, 42 (03) : 214 - 242
  • [5] Development and assessment of a 250 m spatial resolution MODIS annual land cover time series (2000-2011) for the forest region of Canada derived from change-based updating
    Pouliot, Darren
    Latifovic, Rasim
    Zabcic, Natalie
    Guindon, Luc
    Olthof, Ian
    REMOTE SENSING OF ENVIRONMENT, 2014, 140 : 731 - 743
  • [6] Systematic mapping of Leaf Area Index across Canada using 250-meter MODIS data
    Rochdi, Nadia
    Fernandes, Richard
    REMOTE SENSING OF ENVIRONMENT, 2010, 114 (05) : 1130 - 1135
  • [7] Mapping evergreen forests in the Brazilian Amazon using MODIS and PALSAR 500-m mosaic imagery
    Sheldon, Sage
    Xiao, Xiangming
    Biradar, Chandrashekhar
    ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING, 2012, 74 : 34 - 40
  • [8] Evaluation of annual forest disturbance monitoring using a static decision tree approach and 250 m MODIS data
    Pouliot, Darren
    Latifovic, Rasim
    Fernandes, Richard
    Olthof, Ian
    REMOTE SENSING OF ENVIRONMENT, 2009, 113 (08) : 1749 - 1759
  • [9] Monitoring the river plume induced by heavy rainfall events in large, shallow, Lake Taihu using MODIS 250 m imagery
    Zhang, Yunlin
    Shi, Kun
    Zhou, Yongqiang
    Liu, Xiaohan
    Qin, Boqiang
    REMOTE SENSING OF ENVIRONMENT, 2016, 173 : 109 - 121
  • [10] Detection of annual burned forest area using change metrics constructed from MODIS data in Manitoba, Canada
    Chen, Jian
    Sheng, Shijie
    Liu, Zhenbo
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2015, 36 (15) : 3913 - 3931