A new forest light interaction model in support of forest monitoring

Rosema, A.; Verhoef, W.; Noorbergen, H.H.S.; Borgesius, J.J.

doi:10.1016/0034-4257(92)90065-r

Cited by 110 publications

(59 citation statements)

References 13 publications

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“…The model is based on FLIM [25], combined with SAILH (SAIL model with hot) [11,45], and PROSPECT (a radiative transfer model based on Alle's generalized "plate model" that represents the optical properties of plant leaves from 400 nm to 2500 nm) [46].…”

Section: Informmentioning

confidence: 99%

“…This computationally simple model takes into account the effects of shadowing and crown transmittance as well as the effects of leaf geometry and leaf optical properties on the crown transmittance. The impact of leaf geometry and leaf optical properties were neglected by the forest-light interaction model (FLIM) [25] on which INFORM builds.…”

Section: Introductionmentioning

confidence: 99%

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Estimating Forest fAPAR from Multispectral Landsat-8 Data Using the Invertible Forest Reflectance Model INFORM

Yuan

Atzberger

et al. 2015

Remote Sensing

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Abstract:The estimation of the Fraction of Absorbed Photosynthetically Active Radiation in forests (forest fAPAR) from multi-spectral Landsat-8 data is investigated in this paper using a physically based radiative transfer model (Invertible Forest Reflectance Model, INFORM) combined with an inversion strategy based on artificial neural nets (ANN). To derive the forest fAPAR for the Dabie mountain test site in China in 30 m spatial resolution (size approximately 3000 km 2 ), a database of forest canopy spectral reflectances was simulated with INFORM taking into account structural variables such as leaf area index (LAI), crown coverage and stem density as well as leaf composition. To establish the relationship between forest fAPAR and the reflectance modeled by INFORM, a logarithmic relationship between LAI and fAPAR was used previously established using on-site field measurements. On this basis, predictive models between Landsat-8 reflectance and fAPAR were established using an artificial neural network. After calibrating INFORM for the test site, forty-two forest stands were used to validate the performance of the method. The results show that spectral signatures modeled by INFORM correspond reasonably well with the forest canopy reflectance spectra derived from Landsat data. Deviations increase with increasing angle between surface normal of the hilly terrain and OPEN ACCESS Remote Sens. 2015, 7 7426 sun incidence. The comparison of estimated and measured fAPAR (R 2 = 0.47, RMSE = 0.11) demonstrates that INFORM can be inverted using neural nets to provide acceptable estimates of forest fAPAR. The accuracy of the predictions increased significantly when excluding pixels located in very steep terrain. This demonstrates that the applied topographic correction was not sufficiently accurate and should be improved for making optimum use of radiative transfer models such as INFORM.

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Section: Informmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Estimating Forest fAPAR from Multispectral Landsat-8 Data Using the Invertible Forest Reflectance Model INFORM

Yuan

Atzberger

et al. 2015

Remote Sensing

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“…The geometric-optical radiative transfer model InFoRM is a combination of the leaf reflectance models PROSPECT [60,89], the homogeneous canopy model SAILH [90,91], and the forest light interaction model FLIM [92].…”

Section: Compensation Of Canopy Volume Effectsmentioning

confidence: 99%

The Potential of EnMAP and Sentinel-2 Data for Detecting Drought Stress Phenomena in Deciduous Forest Communities

et al. 2015

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Given the importance of forest ecosystems, the availability of reliable, spatially explicit information about the site-specific climate sensitivity of tree species is essential for implementing suitable adaptation strategies. In this study, airborne hyperspectral data were used to assess the response of deciduous species (dominated by European beech and Sessile and Pedunculate oak) to water stress during a summery dry spell. After masking canopy gaps, shaded crown areas and non-deciduous species, potentially indicative spectral indices, the Photochemical Reflectance Index (PRI), Moisture Stress Index (MSI), Normalized Difference Water Index (NDWI), and Chlorophyll Index (CI), were analyzed with respect to available maps of site-specific soil moisture regimes. PRI provided an important indication of site-specific photosynthetic stress on leaf level in relation to limitations in soil water availability. The CI, MSI and NDWI revealed statistically significant differences in total chlorophyll and water concentration at the canopy level. However, after reducing the canopy effects by normalizing these indices with respect to the structure-sensitive simple ratio (SR) vegetation index, it was not yet possible to identify site-specific concentration differences in leaf level at this early stage of the drought. The selected indicators were also tested with simulated EnMAP and Sentinel-2 data (derived from the original airborne data set). While PRI proved to be useful also in the spatial resolution of EnMAP (GSD = 30 m), this was not the case with Sentinel-2, owing to the lack of adequate spectral bands; the remaining indicators (MSI, CI, SR) were also OPEN ACCESS Remote Sens. 2015, 7 14228 successfully produced with Sentinel-2 data at superior spatial resolution (GSD = 10 m). The study confirms the importance of using earth observation systems for supplementing traditional ecological site classification maps, particularly during dry spells and heat waves when ecological gradients are increasingly reflected in the spectral response at the tree crown level. It also underlined the importance of using Sentinel-2 and EnMAP in synergy, as soon as both systems become available.

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“…LIBERTY coupled with a canopy RTM was used to simulate the optical properties of sunlit or shaded components (soil and crown). INFORM was a GORT model combining the forest light interaction model (FLIM [46]), SAILH [31], and a suitable leaf model (e.g., PROSPECT or LIBERTY). The INFORM model was suitable to simulate sparse forest because, firstly, it accounts for the effects of shadowing, canopy geometric structure, crown transmittance, the hotspot and the clumping of leaves in crowns on the forest reflectance.…”

Section: Introductionmentioning

confidence: 99%

Detection of Shoot Beetle Stress on Yunnan Pine Forest Using a Coupled LIBERTY2-INFORM Simulation

Qiu

Huang

et al. 2018

Remote Sensing

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Yunnan pine shoot beetles (PSB), Tomicus yunnanensis and Tomicus minor have spread through southwestern China in the last five years, leading to millions of hectares of forest being damaged. Thus, there is an urgent need to develop an effective approach for accurate early warning and damage assessment of PSB outbreaks. Remote sensing is one of the most efficient methods for this purpose. Despite many studies existing on the mountain pine beetle (MPB), very little work has been undertaken on assessing PSB stress using remote sensing. The objective of this paper was to develop a spectral linear mixing model aided by radiative transfer (RT) and a new Yellow Index (YI) to simulate the reflectance of heterogeneous canopies containing damaged needles and quantitatively inverse their PSB stress. The YI, the fraction of dead needles, is a physically-explicit stress indicator that represents the plot shoots damage ratio (plot SDR). The major steps of this methods include: (1) LIBERTY2 was developed to simulate the reflectance of damaged needles using YI to linearly mix the green needle spectra with the dead needle spectra; (2) LIBERTY2 was coupled with the INFORM model to scale the needle spectra to the canopy scale; and (3) a look-up table (LUT) was created against Sentinel 2 (S2) imagery and inversed leaf chlorophyll content (LCC), green leaf area index (LAI) and plot SDR. The results show that (1) LIBERTY2 effectively simulated the reflectance spectral values on infested needles (mean relative error (MRE) = 1.4-18%), and the YI can indicate the degrees of needles damage; (2) the coupled LIBERTY2-INFORM model is suitable to estimate LAI (R 2 = 0.73, RMSE = 0.17 m m −2 , NRMSE = 11.41% and the index of agreement (IOA) = 0.92) and LCC (R 2 = 0.49, RMSE = 56.24 mg m −2 , NRMSE = 25.22% and IOA = 0.72), and is better than the original LIBERTY model (LAI: R 2 = 0.38, RMSE = 0.43 m m −2 , NRMSE = 28.85% and IOA = 0.68; LCC: R 2 = 0.34, RMSE = 76.44 mg m −2 , NRMSE = 34.23% and IOA = 0.57); and (3) the inversed YI is positively correlated with the measured plot SDR (R 2 = 0.40, RMSE = 0.15). We conclude that the LIBERTY2 model improved the reflectance simulation accuracy of both the needles and canopies, making it suitable for assessing PSB stress. The YI has the potential to assess PSB damage.

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A new forest light interaction model in support of forest monitoring

Cited by 110 publications

References 13 publications

Estimating Forest fAPAR from Multispectral Landsat-8 Data Using the Invertible Forest Reflectance Model INFORM

Estimating Forest fAPAR from Multispectral Landsat-8 Data Using the Invertible Forest Reflectance Model INFORM

The Potential of EnMAP and Sentinel-2 Data for Detecting Drought Stress Phenomena in Deciduous Forest Communities

Detection of Shoot Beetle Stress on Yunnan Pine Forest Using a Coupled LIBERTY2-INFORM Simulation

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