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Recent NDVI-Based Variation in Growth of Boreal Intact Forest Landscapes and Its Correlation with Climatic Variables

Author

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  • Jiaxin Jin

    (Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Xianlin Road 163, Nanjing 210023, China
    International Institute for Earth System Science, Nanjing University, Xianlin Road 163, Nanjing 210023, China)

  • Ying Wang

    (Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Xianlin Road 163, Nanjing 210023, China
    International Institute for Earth System Science, Nanjing University, Xianlin Road 163, Nanjing 210023, China)

  • Hong Jiang

    (Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Xianlin Road 163, Nanjing 210023, China
    International Institute for Earth System Science, Nanjing University, Xianlin Road 163, Nanjing 210023, China)

  • Min Cheng

    (Jiangsu Provincial Key Laboratory of Geographic Information Science and Technology, Nanjing University, Xianlin Road 163, Nanjing 210023, China
    International Institute for Earth System Science, Nanjing University, Xianlin Road 163, Nanjing 210023, China)

Abstract

Intact Forest Landscape (IFL) is of great value in protecting biodiversity and supporting core ecological processes. It is important to analyze the spatial variation in the growth dynamics of IFL. This study analyzed the change of the Normalized Difference Vegetation Index (NDVI) during the growing season (April–October) for boreal (45° N–70° N) IFLs and the correlation with climatic variables over the period of 2000–2013. Our results show 85.5% of boreal IFLs did not show a significant change in the NDVI after 2000, and only 10.2% and 4.3% exhibited a statistically significant increase (greening) or decrease (browning) in NDVI, respectively. About 60.9% of the greening boreal IFLs showed that an increasing NDVI was significantly correlated to climatic variables, especially an increasing growing season temperature (over 47.0%). For browning boreal IFLs, a decrease in temperature or an increase in dormancy period precipitation could be the prime reason for a significant decrease in the NDVI. However, about 64.6% of the browning boreal IFLs were insensitive to any of the climatic variables, indicating other factors, such as fire, had caused the browning. Although it did not show a significant trend, the NDVI of 51.3% of no-change boreal IFLs significantly correlated to climatic variables, especially growing season temperatures (over 37.6%).

Suggested Citation

  • Jiaxin Jin & Ying Wang & Hong Jiang & Min Cheng, 2016. "Recent NDVI-Based Variation in Growth of Boreal Intact Forest Landscapes and Its Correlation with Climatic Variables," Sustainability, MDPI, vol. 8(4), pages 1-10, April.
    • Handle: RePEc:gam:jsusta:v:8:y:2016:i:4:p:326-:d:67369
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    References listed on IDEAS

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    1. Shilong Piao & Jianguang Tan & Anping Chen & Yongshuo H. Fu & Philippe Ciais & Qiang Liu & Ivan A. Janssens & Sara Vicca & Zhenzhong Zeng & Su-Jong Jeong & Yue Li & Ranga B. Myneni & Shushi Peng & Mia, 2015. "Leaf onset in the northern hemisphere triggered by daytime temperature," Nature Communications, Nature, vol. 6(1), pages 1-8, November.
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    Cited by:

    1. Lei Zhang & Yanfang Liu & Xiaojian Wei, 2017. "Forest Fragmentation and Driving Forces in Yingkou, Northeastern China," Sustainability, MDPI, vol. 9(3), pages 1-19, March.
    2. CholHyok Kang & Yili Zhang & Zhaofeng Wang & Linshan Liu & Huamin Zhang & Yilgwang Jo, 2017. "The Driving Force Analysis of NDVI Dynamics in the Trans-Boundary Tumen River Basin between 2000 and 2015," Sustainability, MDPI, vol. 9(12), pages 1-19, December.
    3. Zhifang Pei & Shibo Fang & Wunian Yang & Lei Wang & Mingyan Wu & Qifei Zhang & Wei Han & Dao Nguyen Khoi, 2019. "The Relationship between NDVI and Climate Factors at Different Monthly Time Scales: A Case Study of Grasslands in Inner Mongolia, China (1982–2015)," Sustainability, MDPI, vol. 11(24), pages 1-17, December.

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