Abstract
Three-dimensional information provided by TanDEM-X interferometric phase and airborne Light Detection and Ranging (LiDAR) Digital Elevation Models (DEMs) were used to detect differences in vegetation heterogeneity through a disturbance gradient in Indonesia. The range of vegetation types developed as a consequence of fires during the 1997–1998 El Niño. Two-point statistic (wavelet variance and co-variance) was used to assess the dominant spatial frequencies associated with either topographic features or canopy structure. DEMs wavelet spectra were found to be sensitive to canopy structure at short scales (up to 8 m) but increasingly influenced by topographic structures at longer scales. Analysis also indicates that, at short scale, canopy texture is driven by the distribution of heights. Thematic class separation using the Jeffries–Matusita distance (JM) was greater when using the full wavelet signature (LiDAR: 1.29 ≤ JM ≤ 1.39; TanDEM-X: 1.18 ≤ JM ≤ 1.39) compared to using each decomposition scale individually (LiDAR: 0.1 ≤ JM ≤ 1.26; TanDEM-X: 0.1 ≤ JM ≤ 1.1). In some cases, separability with TanDEM-X was similar to the higher resolution LiDAR. The study highlights the potential of 3D information from TanDEM-X and LiDAR DEMs to explore vegetation disturbance history when analyzed using two-point statistics.
Highlights
Tropical forests are the largest and most complex forest biome on the planet covering 16% of the global land surface where pressure exerted by anthropogenic activities is high and their role in the carbon budget is of great significance [1]
Since the transect is characterized by low-lying undulating terrain (52.7 ̆ 3.2 m) and often the presence of mild slopes (12.1 ̋ ̆ 10 ̋ ) and at higher elevation (81.4 ̆ 11.2 m) and slopes (12 ̋ ̆ 4.3 ̋ ) in AG and mixed scrub (MS) plots, understanding of topographic structure is important to gain a better insight on the processes that play a role and the extent to which they influence the 3D information provided by
The wavelet variance, being a two-point statistic proxy of the structure function, bears information on the dominant correlation patterns associated with either topographic or canopy structures, these happening at different scales and can give insight into the impact of topography and canopy structure by comparison with the available Light Detection and Ranging (LiDAR) Digital Terrain Model (DTM) which carries information on ground topography (Figure 5a)
Summary
Tropical forests are the largest and most complex forest biome on the planet covering 16% of the global land surface where pressure exerted by anthropogenic activities is high and their role in the carbon budget is of great significance [1]. Forests are a substantial carbon sink sequestering 2.0 ̆ 0.4 Pg C/year globally (1990–2007 estimates) [2] and simultaneously a large carbon source through deforestation and forest degradation by contributing to approximately 7%–15% of anthropogenic emissions since. The combination of deforestation, degradation, harvesting and peat fires has been estimated as 2.01 ̆ 1.1 Pg/annum [1]. The uncertainty on these numbers, and the total flux to/from the atmosphere, is considerable. The disturbance regime, and rate of recovery following disturbance determines their effectiveness in sequestering carbon: it is important to reduce these uncertainties to allow for global-scale monitoring of the effectiveness of pledges made under the UNFCCC Paris Agreement (2015)
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