Historical forest biomass dynamics modelled with Landsat spectral trajectories |
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| Institution: | 1. Institute of Applied Physics, National Research Council of Italy (IFAC – CNR), Via Madonna del Piano 10, 50019 Florence, Italy;2. Department of Agricultural, Food and Forestry Systems, Università degli Studi di Firenze, Via San Bonaventura 13, 50145 Florence, Italy;3. Italian Academy of Forest Sciences, P.zza Edison 11, 50133 Florence, Italy;4. Institute of Biometeorology, National Research Council of Italy (IBIMET – CNR), via Madonna del Piano 10, 50019 Florence, Italy;5. LaMMA Consortium, Via Madonna del Piano 10, 50019 Florence, Italy;1. University of Maryland, Department of Geographical Sciences, College Park, MD 20742, USA;2. Sigma Space Corp., Lanham, MD 20706, USA;3. Code 618, Biospheric Sciences Branch, NASA/Goddard Space Flight Center, Greenbelt, MD 20771, USA;4. Department of Ecology and Natural Resource Management, Norwegian University of Life Sciences, P.O. Box 5003, NO-1432 Ås, Norway;5. Sukachev Institute of Forest, Siberian Branch, Russian Academy of Sciences, Akademgorodok, Krasnoyarsk 660036, Russia;1. Department of Geography, University of Hawai''i at Mānoa, 422 Saunders Hall, 2424 Maile Way, Honolulu, HI 96822, USA;2. CMCC — Centro Mediterraneo sui i Cambiamenti Climatici, via Augusto Imperatore (Euro-Mediterranean Center for Climate Change), IAFENT Division, via Pacinotti 5, Viterbo, 01100, Italy;3. Department for Innovation in Biological, Agro-food and Forest Systems, Tuscia University, Viterbo, 01100, Italy |
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| Abstract: | Estimation of forest aboveground biomass (AGB) is informative of the role of forest ecosystems in local and global carbon budgets. There is a need to retrospectively estimate biomass in order to establish a historical baseline and enable reporting of change. In this research, we used temporal spectral trajectories to inform on forest successional development status in support of modelling and mapping of historic AGB for Mediterranean pines in central Spain. AGB generated with ground plot data from the Spanish National Forest Inventory (NFI), representing two collection periods (1990 and 2000), are linked with static and dynamic spectral data as captured by Landsat Thematic Mapper (TM) and Enhanced Thematic Mapper Plus (ETM+) sensors over a 25 year period (1984–2009). The importance of forest structural complexity on the relationship between AGB and spectral vegetation indices is revealed by the analysis of wavelet transforms. Two-dimensional (2D) wavelet transforms support the identification of spectral trajectory patterns of forest stands that in turn, are associated with traits of individual NFI plots, using a flexible algorithm sensitive to capturing time series similarity. Single-date spectral indices, temporal trajectories, and temporal derivatives associated with succession are used as input variables to non-parametric decision trees for modelling, estimation, and mapping of AGB and carbon sinks over the entire study area. Results indicate that patterns of change found in Normalized Difference Vegetation Index (NDVI) values are associated and relate well to classes of forest AGB. The Tasseled Cap Angle (TCA) index was found to be strongly related with forest density, although the related patterns of change had little relation with variability in historic AGB. By scaling biomass models through small (～2.5 ha) spatial objects defined by spectral homogeneity, the AGB dynamics in the period 1990–2000 are mapped (70% accuracy when validated with plot values of change), revealing an increase of 18% in AGB irregularly distributed over 814 km2 of pines. The accumulation of C calculated in AGB was on average 0.65 t ha?1 y?1, equivalent to a fixation of 2.38 t ha?1 y?1 of carbon dioxide. |
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| Keywords: | Remote sensing Time series Retrospective Above ground biomass Landsat Wavelet transform Dynamic Time Warping National Forest Inventory Spain |
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