A nationwide annual characterization of 25 years of forest disturbance and recovery for Canada using Landsat time series

被引:281
|
作者
White, Joanne C. [1 ]
Wulder, Michael A. [1 ]
Hermosilla, Txomin [2 ]
Coops, Nicholas C. [2 ]
Hobart, Geordie W. [1 ]
机构
[1] Nat Resources Canada, Canadian Forest Serv, Pacific Forestry Ctr, Victoria, BC V8Z 1M5, Canada
[2] Univ British Columbia, Forest Sci Ctr, Dept Forest Resource Management, 2424 Main Mall, Vancouver, BC V6T 1Z4, Canada
基金
加拿大自然科学与工程研究理事会;
关键词
Canada; Forest; Monitoring; Landsat; Image processing; Regeneration; Recovery; Disturbance; Wildfire; Harvest; AMERICAN BOREAL FOREST; POSTFIRE VEGETATION; BURN SEVERITY; MULTITEMPORAL LANDSAT; TEMPORAL PATTERNS; DETECTING TRENDS; CARBON DYNAMICS; UNITED-STATES; BARK BEETLE; WILDFIRE;
D O I
10.1016/j.rse.2017.03.035
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
In the context of complex demands on forest resources and climate change, synoptic and spatially-explicit base-line data characterizing national trends in forest disturbance and subsequent return of vegetation (and eventual return to forest) are increasingly required. Time series analyses of remotely sensed data enable the retrospective generation of baseline data depicting both forest disturbance and recovery, enabling a more holistic examination of forest dynamics. In this research, we utilize the outputs of the Composite2Change, or C2C, algorithm that lever-ages the extensive Landsat archive to produce annual, gap-free, surface reflectance composites to date and label disturbance types and to characterize vegetation recovery over the >650 million ha of Canada's forested ecosystems. From 1985 to 2010, 57.5 Mha or 10.75% of Canada's net forested ecosystem area (exclusive of water) were disturbed by either wildfire or harvest, representing an annual rate of disturbance of approximately 0.43% per year. Wildfire accounted for 2.5 times more area disturbed than harvest. On average, wildfire disturbed 1.6 Mha annually and had greater inter-annual variability with a standard deviation of 1.1 Mha, compared to the 0.65 Mha disturbed annually by harvesting (sigma = 0.1 Mha). Herein, we defined a longer-term measure of spectral recovery (the number of years it took for a pixel to attain 80% of its pre-disturbance Normalized Burn Ratio or NBR value), which indicated that harvested areas are recovering more consistently over time relative to areas disturbed by wildfire, with 78.6% of harvested areas requiring <= 10 years to recover, compared to only 35.5% of wildfire areas. A shorter-term (5-year) measure of spectral recovery, also based on the NBR, indicated that vegetation in wildfire areas returned more rapidly than harvested areas; however, when the magnitude of the disturbance was incorporated into the metric, with magnitude typically larger and more variable for wildfire areas, harvested areas were found to be recovering more rapidly on average in the short-term. Overall, < 1% of the areas disturbed by wildfire and harvest were identified as non-recovering by all three spectral measures of recovery used in our analysis. Regionally, trends in disturbance and recovery largely echoed trends found at the national level, although the relative amounts and rates of wildfire or harvest varied by ecozone. Time series Landsat composites provide an opportunity to characterize relative trends in disturbance and recovery at a national scale, by disturbance type and ecozone, in a spatially explicit manner and at a level of spatial detail that is relevant to both forest management and science. Crown Copyright 2017 Published by Elsevier Inc.
引用
收藏
页码:303 / 321
页数:19
相关论文
共 50 条
  • [1] Boreal Shield forest disturbance and recovery trends using Landsat time series
    Frazier, Ryan J.
    Coops, Nicholas C.
    Wulder, Michael A.
    REMOTE SENSING OF ENVIRONMENT, 2015, 170 : 317 - 327
  • [2] Mapping forest disturbance across the China-Laos border using annual Landsat time series
    Tang, Dongmei
    Fan, Hui
    Yang, Kun
    Zhang, Yao
    INTERNATIONAL JOURNAL OF REMOTE SENSING, 2019, 40 (08) : 2895 - 2915
  • [3] Using Intra-Annual Landsat Time Series for Attributing Forest Disturbance Agents in Central Europe
    Oeser, Julian
    Pflugmacher, Dirk
    Senf, Cornelius
    Heurich, Marco
    Hostert, Patrick
    FORESTS, 2017, 8 (07):
  • [4] Examining Forest Disturbance and Recovery in the Subtropical Forest Region of Zhejiang Province Using Landsat Time-Series Data
    Liu, Shanshan
    Wei, Xinliang
    Li, Dengqiu
    Lu, Dengsheng
    REMOTE SENSING, 2017, 9 (05)
  • [5] Detecting Forest Disturbance and Recovery in Primorsky Krai, Russia, Using Annual Landsat Time Series and Multi-Source Land Cover Products
    Hu, Yang
    Hu, Yunfeng
    REMOTE SENSING, 2020, 12 (01)
  • [6] Mapping forest disturbance and recovery for forest dynamics over large areas using Landsat time-series remote sensing
    Huy Trung Nguyen
    Soto-Berelov, Mariela
    Jones, Simon D.
    Haywood, Andrew
    Hislop, Samuel
    REMOTE SENSING FOR AGRICULTURE, ECOSYSTEMS, AND HYDROLOGY XIX, 2017, 10421
  • [7] United States Forest Disturbance Trends Observed Using Landsat Time Series
    Jeffrey G. Masek
    Samuel N. Goward
    Robert E. Kennedy
    Warren B. Cohen
    Gretchen G. Moisen
    Karen Schleeweis
    Chengquan Huang
    Ecosystems, 2013, 16 : 1087 - 1104
  • [8] United States Forest Disturbance Trends Observed Using Landsat Time Series
    Masek, Jeffrey G.
    Goward, Samuel N.
    Kennedy, Robert E.
    Cohen, Warren B.
    Moisen, Gretchen G.
    Schleeweis, Karen
    Huang, Chengquan
    ECOSYSTEMS, 2013, 16 (06) : 1087 - 1104
  • [9] Characterizing forest disturbance and recovery with thermal trajectories derived from Landsat time series data
    Barta, Karola Anna
    Hais, Martin
    Heurich, Marco
    REMOTE SENSING OF ENVIRONMENT, 2022, 282
  • [10] MAPPING FOREST DISTURBANCE TYPES IN CHINA WITH LANDSAT TIME SERIES
    Huo, Lian-Zhi
    Tang, Ping
    IGARSS 2023 - 2023 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, 2023, : 3086 - 3089