Imaging Spectroscopy of Forest Ecosystems: Perspectives for the Use of Space-borne Hyperspectral Earth Observation Systems

Hill, Joachim; Buddenbaum, Henning; Townsend, Philip A.

doi:10.1007/s10712-019-09514-2

Cited by 49 publications

(24 citation statements)

References 165 publications

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“…Since the inversion problem is ill-posed, multiple sets of parameters can yield similar reflectances. A common estimation method is to consider the mean values from the q best sets of parameters as the final solution [53,54]. Various cost functions were tested: Root mean square error (RMSE, Equation (4)), spectral angle (SAM, Equation 5) and vegetation index (VI) differences (D V I , Equation 6).…”

Section: Inversion Stategiesmentioning

confidence: 99%

Monitoring LAI, Chlorophylls, and Carotenoids Content of a Woodland Savanna Using Hyperspectral Imagery and 3D Radiative Transfer Modeling

et al. 2019

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Leaf pigment contents, such as chlorophylls a and b content (C a b ) or carotenoid content (Car), and the leaf area index (LAI) are recognized indicators of plants’ and forests’ health status that can be estimated through hyperspectral imagery. Their measurement on a seasonal and yearly basis is critical to monitor plant response and adaptation to stress, such as droughts. While extensively done over dense canopies, estimation of these variables over tree-grass ecosystems with very low overstory LAI (mean site LAI < 1 m 2 /m 2 ), such as woodland savannas, is lacking. We investigated the use of look-up table (LUT)-based inversion of a radiative transfer model to retrieve LAI and leaf C a b and Car from AVIRIS images at an 18 m spatial resolution at multiple dates over a broadleaved woodland savanna during the California drought. We compared the performances of different cost functions in the inversion step. We demonstrated the spatial consistency of our LAI, C a b , and Car estimations using validation data from low and high canopy cover parts of the site, and their temporal consistency by qualitatively confronting their variations over two years with those that would be expected. We concluded that LUT-based inversions of medium-resolution hyperspectral images, achieved with a simple geometric representation of the canopy within a 3D radiative transfer model (RTM), are a valid means of monitoring woodland savannas and more generally sparse forests, although for maximum applicability, the inversion cost functions should be selected using validation data from multiple dates. Validation revealed that for monitoring use: The normalized difference vegetation index (NDVI) outperformed other indices for LAI estimations (root mean square error (RMSE) = 0.22 m 2 /m 2 , R 2 = 0.81); the band ratio ρ 0.750 μ m ρ 0.550 μ m retrieved C a b more accurately than other chlorophylls indices (RMSE = 5.21 μ g/cm 2 , R 2 = 0.73); RMSE over the 0.5–0.55 μ m interval showed encouraging results for Car estimations.

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Section: Inversion Stategiesmentioning

confidence: 99%

Monitoring LAI, Chlorophylls, and Carotenoids Content of a Woodland Savanna Using Hyperspectral Imagery and 3D Radiative Transfer Modeling

et al. 2019

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“…Measurements from space are the result of the complex physical interaction between electromagnetic radiation and vegetated surfaces at different wavelengths-an "electromagnetic signature" that encodes fundamental information on vegetation states, function, and structure. Signatures from the visible to shortwave infrared spectral region are related to the biophysical and biochemical properties of top canopy leaves [10,11]. In the thermal infrared region, instead, one can infer canopy surface temperatures from which canopy transpiration rates can be further estimated [12].…”

Section: What Do Satellites Measure?mentioning

confidence: 99%

Monitoring Plant Functional Diversity Using the Reflectance and Echo from Space

Migliavacca

Wirth

et al. 2020

Remote Sensing

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Plant functional diversity (FD) is an important component of biodiversity. Evidence shows that FD strongly determines ecosystem functioning and stability and also regulates various ecosystem services that underpin human well-being. Given the importance of FD, it is critical to monitor its variations in an explicit manner across space and time, a highly demanding task that cannot be resolved solely by field data. Today, high hopes are placed on satellite-based observations to complement field plot data. The promise is that multiscale monitoring of plant FD, ecosystem functioning, and their services is now possible at global scales in near real-time. However, non-trivial scale challenges remain to be overcome before plant ecology can capitalize on the latest advances in Earth Observation (EO). Here, we articulate the existing scale challenges in linking field and satellite data and further elaborated in detail how to address these challenges via the latest innovations in optical and radar sensor technologies and image analysis algorithms. Addressing these challenges not only requires novel remote sensing theories and algorithms but also urges more effective communication between remote sensing scientists and field ecologists to foster mutual understanding of the existing challenges. Only through a collaborative approach can we achieve the global plant functional diversity monitoring goal.

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“…Secondly, although multispectral data have been shown to be of use (e.g. Dash et al 2018), the coarse spectral resolution and limited spectral range of these data do not allow for a detailed assessment of the wavelengths that are most closely correlated with physiological change and needle necrosis (Asner and Martin 2009;Hill et al 2019). Overcoming these limitations requires the use of hyperspectral data with a finer spectral resolution and greater spectral range that can be used to more comprehensively examine changes in photosynthesis and needle death associated with herbicide application.…”

Section: Introductionmentioning

confidence: 99%

Hyperspectral VNIR-spectroscopy and imagery as a tool for monitoring herbicide damage in wilding conifers

et al. 2019

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Wilding conifers, the naturally regenerated scions of exotic conifer species, are a major ecological and economic issue in New Zealand. Hyperspectral imagery could provide a useful means of monitoring the efficacy of wilding control measures but little research has examined this possibility. Data were collected from an experiment, that included thirty-nine young Pinus contorta (Douglas) trees allocated to a control and two herbicide treatments (triclopyr butoxyethyl ester and diquat dibromide monohydrate). The objectives of this research were to examine the temporal impacts of herbicide on needle discolouration, spectral properties and tree physiology and to develop models to predict photosynthetic parameters from hyperspectral data. In accordance with obvious discolouration on the first day after treatment, values of net photosynthesis rate (A), electron transport rate (ETR), stomatal conductance (G) and optimal quantum yield of photosystem II (F v /F m) declined rapidly for plants treated with diquat. Discolouration following application of triclopyr was not evident before the second week, and values of A, ETR, G and F v /F m declined slower than those of diquat. Of the tested narrow-band spectral indices calculated from needle spectra photochemical reflectance index (PRI) exhibited the strongest correlation with the four photosynthetic parameters and R 2 values between PRI and A, F v / F m , ETR and G were, respectively, 0.53, 0.46, 0.68 and 0.29. Models that used raw spectra as inputs showed that sparse partial least squares (SPLS) outperformed the three other approaches tested (PLS, Support Vector Machines, Elastic Net) and R 2 values using this approach for A, F v /F m , ETR and G were, respectively, 0.64, 0.62, 0.65 and 0.42.

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Imaging Spectroscopy of Forest Ecosystems: Perspectives for the Use of Space-borne Hyperspectral Earth Observation Systems

Cited by 49 publications

References 165 publications

Monitoring LAI, Chlorophylls, and Carotenoids Content of a Woodland Savanna Using Hyperspectral Imagery and 3D Radiative Transfer Modeling

Monitoring LAI, Chlorophylls, and Carotenoids Content of a Woodland Savanna Using Hyperspectral Imagery and 3D Radiative Transfer Modeling

Monitoring Plant Functional Diversity Using the Reflectance and Echo from Space

Hyperspectral VNIR-spectroscopy and imagery as a tool for monitoring herbicide damage in wilding conifers

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