Effects of forest age on albedo in boreal forests estimated from MODIS and Landsat albedo retrievals

Kuusinen, Nea; Tomppo, Erkki; Shuai, Yanmin; Berninger, Frank

doi:10.1016/j.rse.2014.02.005

Cited by 59 publications

(44 citation statements)

References 45 publications

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“…The independent variable albedo, defined as the average solar reflectance (Liang 2000), was the main discriminating factor in the regression tree, and highest values occurred in the areas with the lowest forest biomass. Kuusinen et al (2014) obtained similar results and observed an inverse relationship between stand age and albedo, so that the value of this variable was lower in mature stands because of the lower level of incident radiation absorbed in such stands. This relationship can be used to discriminate zones with different levels of forest biomass.…”

Section: Discussionsupporting

confidence: 55%

Estimating biomass of mixed and uneven-aged forests using spectral data and a hybrid model combining regression trees and linear models

López-Serrano

López-Sánchez

Varela

et al. 2016

iForest

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The Sierra Madre Occidental mountain range (Durango, Mexico) is of great ecological interest because of the high degree of environmental heterogeneity in the area. The objective of the present study was to estimate the biomass of mixed and uneven-aged forests in the Sierra Madre Occidental by using Landsat-5 TM spectral data and forest inventory data. We used the ATCOR3 ® atmospheric and topographic correction module to convert remotely sensed imagery digital signals to surface reflectance values. The usual approach of modeling stand variables by using multiple linear regression was compared with a hybrid model developed in two steps: in the first step a regression tree was used to obtain an initial classification of homogeneous biomass groups, and multiple linear regression models were then fitted to each node of the pruned regression tree. Cross-validation of the hybrid model explained 72.96% of the observed stand biomass variation, with a reduction in the RMSE of 25.47% with respect to the estimates yielded by the linear model fitted to the complete database. The most important variables for the binary classification process in the regression tree were the albedo, the corrected readings of the short-wave infrared band of the satellite (2.08-2.35 µm) and the topographic moisture index. We used the model output to construct a map for estimating biomass in the study area, which yielded values of between 51 and 235 Mg ha -1 . The use of regression trees in combination with stepwise regression of corrected satellite imagery proved a reliable method for estimating forest biomass.

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Section: Discussionsupporting

confidence: 55%

Estimating biomass of mixed and uneven-aged forests using spectral data and a hybrid model combining regression trees and linear models

López-Serrano

López-Sánchez

Varela

et al. 2016

iForest

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“…Due to the scale differences between satellite pixels and footprints of ground measurements, data at finer spatial resolutions are needed to bridge the gap over heterogeneous landscapes for a better understanding of uncertainties of coarse-resolution products [6,7]. Moreover, there is an increasing need for the availability of medium-resolution surface albedo for applications at medium-to-fine scales (<100 m), including forest management [8][9][10], agriculture monitoring [11], and urban environment monitoring [12,13].…”

Section: Introductionmentioning

confidence: 99%

Land Surface Albedo Estimation from Chinese HJ Satellite Data Based on the Direct Estimation Approach

Liang

Wang

et al. 2015

Remote Sensing

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Abstract:Monitoring surface albedo at medium-to-fine resolution (<100 m) has become increasingly important for medium-to-fine scale applications and coarse-resolution data evaluation. This paper presents a method for estimating surface albedo directly using top-of-atmosphere reflectance. This is the first attempt to derive surface albedo for both snow-free and snow-covered conditions from medium-resolution data with a single approach. We applied this method to the multispectral data from the wide-swath Chinese HuanJing (HJ) satellites at a spatial resolution of 30 m to demonstrate the feasibility of this data for surface albedo monitoring over rapidly changing surfaces. Validation against ground measurements shows that the method is capable of accurately estimating surface albedo over both snow-free and snow-covered surfaces with an overall root mean square error (RMSE) of 0.030 and r-square (R 2 ) of 0.947. The comparison between HJ albedo estimates and the Moderate Resolution Imaging Spectral Radiometer (MODIS) albedo product suggests that the HJ data and proposed algorithm can generate robust albedo estimates over various land cover types with an RMSE of 0.011-0.014. The accuracy of HJ albedo estimation improves with the increase in view zenith angles, which further demonstrates the unique advantage of wide-swath satellite data in albedo estimation.

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“…Second, the spatiotemporal forcings of other biophysical and biogeochemical feedbacks (e.g., greenhouse gas emission, net primary production, soil respiration, and aerosol deposition) need to be explored for a comprehensive assessment. Special attention may be paid to low solar elevation and topographic effects on remote sensing fire studies (e.g., age-dependent albedo) in the high-latitude areas such as the Alaskan boreal forest (Verbyla et al 2008;Kuusinen et al 2014b).…”

Section: Discussionmentioning

confidence: 99%

Spatiotemporal variation of surface shortwave forcing from fire-induced albedo change in interior Alaska

Huang

Dahal

et al. 2015

Can. J. For. Res.

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The albedo change caused by fires and the subsequent succession is spatially heterogeneous, leading to the need to assess the spatiotemporal variation of surface shortwave forcing (SSF) as a component to quantify the climate impacts of high-latitude fires. We used an image reconstruction approach to compare postfire albedo with the albedo assuming that no fires had occurred. Combining the fire-caused albedo change from the 2001-2010 fires in interior Alaska and the monthly surface incoming solar radiation, we examined the spatiotemporal variation of SSF in the early successional stage of approximately 10 years. Our results showed that although postfire albedo generally increased in fall, winter, and spring, some burned areas could show an albedo decrease during these seasons. In summer, the albedo increased for several years and then declined again. The spring SSF distribution did not show a latitudinal decrease from south to north as previously reported. The results also indicated that although the SSF is usually largely negative in the early successional years, it may not be significant during the first postfire year. The annual 2005-2010 SSF for the 2004 fire scars was -1.30, -4.40, -3.31, -4.00, -3.42, and -2.47 W·m −2 , respectively. The integrated annual SSF map showed significant spatial variation, with a mean of -3.15 W·m −2 , a standard deviation of 3.26 watts per square metre (W·m −2 ), and 16% of burned areas having positive SSF. Our results suggest that boreal deciduous fires would be less positive for climate change than boreal evergreen fires. Future research is needed to comprehensively investigate the spatiotemporal radiative and nonradiative forcings to determine the effect of boreal fires on the climate.Résumé : La modification de l'albédo causée par les feux et la succession végétale subséquente est spatialement hétérogène. Il est donc nécessaire d'avoir accès à la variation spatio-temporelle du forçage aux courtes longueurs d'onde de la surface en tant que composante pour quantifier les impacts des feux aux latitudes élevées sur le climat. Nous avons utilisé la reconstruction d'image pour comparer l'albédo après feu à celui qu'on aurait pu mesurer s'il n'y avait pas eu de feu. En combinant la modification de l'albédo causée par les feux de 2001 à 2010 à l'intérieur de l'Alaska et le rayonnement solaire mensuel incident à la surface, nous avons étudié la variation spatio-temporelle du forçage au stade précoce de succession sur une période d'environ 10 ans. Nos résultats ont montré que, bien que l'albédo après feu ait généralement augmenté à l'automne, en hiver et au printemps, il pouvait diminuer durant ces saisons dans certaines zones brûlées. En été, l'albédo a augmenté pendant plusieurs années et diminué à nouveau par la suite. Il n'y a pas eu de diminution latitudinale de la distribution printanière du forçage, du sud vers le nord, comme cela a déjà été rapporté. Les résultats indiquent aussi que même si le forçage est habituellement largement négatif durant les premières années de la succe...

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Effects of forest age on albedo in boreal forests estimated from MODIS and Landsat albedo retrievals

Cited by 59 publications

References 45 publications

Estimating biomass of mixed and uneven-aged forests using spectral data and a hybrid model combining regression trees and linear models

Estimating biomass of mixed and uneven-aged forests using spectral data and a hybrid model combining regression trees and linear models

Land Surface Albedo Estimation from Chinese HJ Satellite Data Based on the Direct Estimation Approach

Spatiotemporal variation of surface shortwave forcing from fire-induced albedo change in interior Alaska

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