Remote Sensing of Environment

Volume 247 (7~8 / 55)

15 September 2020

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• 7. Assessing satellite-derived fire patches with functional diversity trait methods (AR)

  ★★☆☆☆

  • Intro

    • Context

      Fire disturbance is a significant component of the climate system.

      Analysis of satellite-derived burned areas → allowed the identification of fire patches and their morphology = a new resource for tracking fire spread to improve fire models

      A critical parameter (used to create fire patches) of the flood-fill algorithm is the cut-off (in days) below which it aggregates two contiguous burned pixels to the same fire patch.

      However, the current level of validation is insufficient to understand the effect of the cut-off values and sensor resolutions on the subsequent fire-patch morphology.

    • Objectives

  • M&M

    • Data

      The FRY v1.0 database of functional fire-patch traits (e.g., size, elongation, and direction)

      FRY database emanates from the analyses of two global burned-area products derived from MODIS and MERIS sensors with different spatial and temporal resolutions and with cut-off values of 3, 5, 9, and 14 days.

    • Approach

      We propose a new functional diversity trait-based approach, which compares the satellite-derived fire patches to forest service perimeters as reference data

      ⇒ to evaluate whether the FRY products are accurately identifying the spatial features of fire patches and what are the most realistic cut-off values to use in different sub-regions of North America

  • Results & Contributions

    This paper shows the accuracy of the FRY fire patches ≥300 ha in North America during 2005–2011.

    Our analysis demonstrates that fire patches with a high cut-off of 14 days and those derived from the MODIS sensor, with their high temporal resolution, better identify the fire diversity in North America.

    In conclusion, our statistical framework can be used for assessing satellite-derived fire patches.

    Furthermore, the temporal resolution of satellite sensors is the most important factor in identifying fire patches — thus space agencies should consider it when planning the future development of cost-effective climate observation systems.

 

• 8. Coupling high-resolution field monitoring and MODIS for reconstructing wetland historical hydroperiod at a high temporal frequency (AR)

  ★★☆☆☆

  • Intro

    • Context

      Historical wetland hydrology data are instrumental to support the design of wetland management and restoration strategies but are rarely available

    • Objectives

      tested the capabilities and limitations of a simple methodological framework based on publicly available MODIS Land Reflectance Products to estimate wetland soil surface saturation and inundation spatiotemporal dynamics

  • M&M

    Supervised learning & high-resolution groundwater and surface water elevation data

    ⇒ the framework searches for spectral algorithms : wet/dry wetland status classifier (WSC) and the continuous wetland dynamics identifier (WDI) that best predict upper soil layer wetness status

    Utilized Google Earth Engine (GEE) → fast access & processing (full range of MODIS)

    GEE → readily conduct a comparative assessment of the MODIS 8-day composite and daily collections and test various pixel-level quality filters to select reliable data at the highest possible temporal resolution. 무슨 필터를 썼을까?

    We then applied the WSC and WDI to map the 2000-2016 sub-weekly wetland hydroperiod at 500m resolution, achieving a temporal resolution rarely matched in remote sensing for wetland studies

  • Results & Contributions

    We tested the framework on the internationally-recognized Ramsar site Palo Verde National Park wetland in Costa Rica, and we obtained good results (overall prediction accuracy of 86.6% and kappa coefficient of 0.7 for the WSC; r2 of 0.71 for the WDI).

    High-resolution water level data allowed us to assess the challenges, promises and limitations of using MODIS products for wetland hydrology applications.

    The analysis of the end-products, combined with the field water elevation data, provided new insights into the drivers controlling the spatiotemporal dynamics of hydroperiod within the Palo Verde wetland and did not reveal any significant temporal trends

    The WSC and WDI framework developed here can be useful for reconstructing long-term hydroperiod variability and uncovering its drivers for other wetland systems globally

 

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• TIL