Abstract
In vegetation canopies cross-shading between finite dimensional leaves leads to a peak in reflectance in the retro-illumination direction. This effect is called the hot spot in optical remote sensing. The hotspot region in reflectance of vegetated surfaces represents the most information-rich directions in the angular distribution of canopy reflected radiation. This paper presents a new approach for generating hot spot signatures of equatorial forests from synergistic analyses of multiangle observations from the Multiangle Imaging SpectroRadiometer (MISR) on Terra platform and near backscattering reflectance data from the Earth Polychromatic Imaging Camera (EPIC) onboard NOAA’s Deep Space Climate Observatory (DSCOVR). A canopy radiation model parameterized in terms of canopy spectral invariants underlies the theoretical basis for joining Terra MISR and DSCOVR EPIC data. The proposed model can accurately reproduce both MISR angular signatures acquired at 10:30 local solar time and diurnal courses of EPIC reflectance (NRMSE < 9%, R2 > 0.8). Analyses of time series of the hot spot signature suggest its ability to unambiguously detect seasonal changes of equatorial forests.
Highlights
The global forest ecosystem absorbs about 25% of the total anthropogenic CO2 emission from atmosphere via carbon accumulation to forest biomass (Reichstein et al, 2013)
For vegetation canopies with a dark background, or sufficiently dense vegetation where the impact of canopy background is negligible, the Directional Area Scattering Function (DASF) can be accurately approximated from the BRF in the weakly absorbing spectral intervals without involving canopy reflectance models, prior knowledge, or ancillary information regarding leaf scattering properties (Knyazikhin et al., 2013)
The DASF becomes independent on spectral band composition of a sensor acquiring surface reflectance data, which is an important prerequisite for achieving consistency and complementarity between DSCOVR EPIC and Terra MISR observations
Summary
The global forest ecosystem absorbs about 25% of the total anthropogenic CO2 emission from atmosphere via carbon accumulation to forest biomass (Reichstein et al, 2013). Studies on Amazon forest seasonality based on Vegetation Angular Signatures of Equatorial Forests analyses of data from single-viewing sensors disagree on whether there is more greenness in the dry season than in the wet season: the observed increase in vegetation indices were explained by an increase in leaf area, an artifact of sun-sensor-geometry and changes in leaf age through the leaf flush (Huete et al, 2006; Brando et al, 2010; Samanta et al, 2012; Morton et al, 2014; Saleska et al, 2016). The impact of droughts on Amazon forests has been debated (Saleska et al, 2007; Samanta et al, 2010; Samanta et al, 2011; Xu et al, 2011) Conflicting conclusions among these studies arose from different interpretations of surface reflectance data acquired under saturation conditions (Bi et al, 2015). Developing methodologies that allow us to unambiguously interpret reflectance of dense forests is worthy of special attention
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