Modeling forest biomass using Very-High-Resolution data—Combining textural, spectral and photogrammetric predictors derived from spaceborne stereo images

Maack, Joachim; Kattenborn, Teja; Fassnacht, Fabian Ewald; Enßle, Fabian; Hernández, Jaime; Corvalán, Patricio; Koch, Bárbara

doi:10.5721/eujrs20154814

Cited by 44 publications

(40 citation statements)

References 37 publications

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“…It is potentially also well suited for updating existing inventories, which often are based on more expensive ALS. The presented approach can likely be used similarly in large parts of the boreal forests, as similar results were obtained across the test sites, and moreover, the results obtained in this study confirm other studies from for example, German and Canadian forests, which contain a higher degree of deciduous forest (St-Onge, Hu, and Vega 2008;Maack et al 2015). The plotlevel results of about 6% to 10% RMSE are better than traditional field inventory methods currently used by many Swedish forest companies.…”

Section: Discussionsupporting

confidence: 84%

Assessment of boreal forest height from WorldView-2 satellite stereo images

Persson

Perko

2016

Remote Sensing Letters

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WorldView-2 data are sometimes unstable for canopy top height estimations (ALS height percentile 100, p100) and that the reconstructed heights are generally located below the actual top height. The WorldView-2 p60 was found to correlate best with ALS p70 in Remningstorp, while WorldView-2 p95 was found to correlate best with ALS p70 in Krycklan, and it moreover reached the highest correlation for all other estimated variables, at both test sites. It was concluded, that WorldView-2 p95 height data overall represents approximately the forest height ALS p70. The overall high correlation coefficients above 0.90 at both test sites, with different forest conditions, indicate that stereo matching of WorldView-2 satellite images is suitable for forest height mapping.

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Section: Discussionsupporting

confidence: 84%

Assessment of boreal forest height from WorldView-2 satellite stereo images

Persson

Perko

2016

Remote Sensing Letters

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“…It is a way of extracting second-order statistical texture features, while the spectral derivatives can be considered first-order features, as they do not consider pixel neighbour relationships. GLCM was developed by Haralick, Shanmugam, and Dinstein [31], and has commonly been applied in remote sensing studies [15,17,19,22,32,33]. Ten common textural attributes (contrast, dissimilarity, homogeneity, second moment, energy, max probability, entropy, average, variance, and correlation) were computed using the Sentinel Application Platform (SNAP; http://step.esa.int/main/toolboxes/snap) commissioned by the European Space Agency (ESA).…”

Section: Textural Metricsmentioning

confidence: 99%

“…The model combining height metrics and spectral derivatives had 47 tons·ha −1 (24%) RMSE at the German test site and 59 tons·ha −1 (36%) at the test site in Chile. Both Immitzer et al [21] and Maack et al [22] obtained their main model contributions from the height metrics, while the spectral/textural contributions were rather limited. In Finland, Yu et al [7] used WorldView-2 data to evaluate forest attributes in boreal forest.…”

Section: Introductionmentioning

confidence: 99%

“…In its simplest form, the same objects (pixels) are detected in at combination of using both spectral and height data to be the best, corresponding to the R 2 being 0.53 and the RMSE for VOL was 120 m 3 ·ha −1 (32%) at plot level. Maack et al [22] used WorldView-2 imagery for a German test site and Pléiades data for a test site located in Chile in order to estimate AGB. They emphasized the evaluation of combining spectral derivatives, textural metrics, in addition to image matched height metrics.…”

Section: Introductionmentioning

confidence: 99%

“…From the review of past articles, few papers [20,22] have evaluated Pléiades satellite data for forestry purposes. The objective for this study is therefore to examine the use of Pléiades satellite data for estimating forest attributes in boreal forest, when a high-resolution DTM from ALS is available.…”

Section: Introductionmentioning

confidence: 99%

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Estimation of Boreal Forest Attributes from Very High Resolution Pléiades Data

Persson

2016

Remote Sensing

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Abstract:In this study, the potential of using very high resolution Pléiades imagery to estimate a number of common forest attributes for 10-m plots in boreal forest was examined, when a high-resolution terrain model was available. The explanatory variables were derived from three processing alternatives. Height metrics were extracted from image matching of the images acquired from different incidence angles. Spectral derivatives were derived by performing principal component analysis of the spectral bands and lastly, second order textural metrics were extracted from a gray-level co-occurrence matrix, computed with an 11 × 11 pixels moving window. The analysis took place at two Swedish test sites, Krycklan and Remningstorp, containing boreal and hemi-boreal forest. The lowest RMSE was estimated with 1.4 m (7.7%) for Lorey's mean height, 1.7 m (10%) for airborne laser scanning height percentile 90, 5.1 m 2 ·ha −1 (22%) for basal area, 66 m 3 ·ha −1 (27%) for stem volume, and 26 tons·ha −1 (26%) for above-ground biomass, respectively. It was found that the image-matched height metrics were most important in all models, and that the spectral and textural metrics contained similar information. Nevertheless, the best estimations were obtained when all three explanatory sources were used. To conclude, image-matched height metrics should be prioritised over spectral metrics when estimation of forest attributes is concerned.

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Review on the Possibilities of Mapping Old-Growth Temperate Forests by Remote Sensing in Europe

Hirschmugl

Sobe

Filippo

et al. 2023

Environ Model Assess

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Old-growth forests (OGF) provide valuable ecosystem services such as habitat provision, carbon sequestration or recreation maintaining biodiversity, carbon storage, or human well-being. Long-term human pressure caused OGFs in Europe to be rare and scattered. Their detailed extent and current status are largely unknown. This review aims to identify potential methods to map temperate old-growth forests (tOGF) by remote sensing (RS) technology, highlights the potentials and benefits, and identifies main knowledge gaps requesting further research. RS offers a wide range of data and methods to map forests and their properties, applicable from local to continental scale. We structured existing mapping approaches in three main groups. First, parameter-based approaches, which are based on forest parameters and usually applied on local to regional scale using detailed data, often from airborne laser scanning (ALS). Second, direct approaches, usually employing machine learning algorithms to generate information from RS data, with high potential for large-area mapping but so far lacking operational applications and related sound accuracy assessment. Finally, indirect approaches integrating various existing data sets to predict OGF existence. These approaches have also been used for large area mapping with a main drawback of missing physical evidence of the identified areas to really hold OGFs as compared to the likelihood of OGF existence. In conclusion, studies dealing with the mapping of OGF using remote sensing are quite limited, but there is a huge amount of knowledge from other forestry-related applications that is yet to be leveraged for OGF identification. We discuss two scenarios, where different data and approaches are suitable, recognizing that one single system cannot serve all potential needs. These may be hot spot identification, detailed area delineation, or status assessment. Further, we pledge for a combined method to overcome the identified limitations of the individual approaches.

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Modeling forest biomass using Very-High-Resolution data—Combining textural, spectral and photogrammetric predictors derived from spaceborne stereo images

Cited by 44 publications

References 37 publications

Assessment of boreal forest height from WorldView-2 satellite stereo images

Assessment of boreal forest height from WorldView-2 satellite stereo images

Estimation of Boreal Forest Attributes from Very High Resolution Pléiades Data

Review on the Possibilities of Mapping Old-Growth Temperate Forests by Remote Sensing in Europe

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