Comparison of satellite images with different spatial resolutions to estimate stand structural diversity in urban forests

Özkan, Ulaş Yunus; Özdemir, İbrahim; Demirel, Tufan; Sağlam, Serhun; Yeşil, Ahmet

doi:10.1007/s11676-016-0353-8

Cited by 12 publications

(4 citation statements)

References 34 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…In addition to UAVs, other remote sensing data sets have also been used in estimating structural diversity. In [70], plot-level tree size diversity was modelled through ALS-based features, whereas in [71], structural diversity of urban forests was estimated with various satellite imagery. Both studies conclude that the used remote sensing data sets can be utilized in characterizing structural diversity.…”

Section: Discussionmentioning

confidence: 99%

Assessing Biodiversity in Boreal Forests with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging

et al. 2018

View full text Add to dashboard Cite

Forests are the most diverse terrestrial ecosystems and their biological diversity includes trees, but also other plants, animals, and micro-organisms. One-third of the forested land is in boreal zone; therefore, changes in biological diversity in boreal forests can shape biodiversity, even at global scale. Several forest attributes, including size variability, amount of dead wood, and tree species richness, can be applied in assessing biodiversity of a forest ecosystem. Remote sensing offers complimentary tool for traditional field measurements in mapping and monitoring forest biodiversity. Recent development of small unmanned aerial vehicles (UAVs) enable the detailed characterization of forest ecosystems through providing data with high spatial but also temporal resolution at reasonable costs. The objective here is to deepen the knowledge about assessment of plot-level biodiversity indicators in boreal forests with hyperspectral imagery and photogrammetric point clouds from a UAV. We applied individual tree crown approach (ITC) and semi-individual tree crown approach (semi-ITC) in estimating plot-level biodiversity indicators. Structural metrics from the photogrammetric point clouds were used together with either spectral features or vegetation indices derived from hyperspectral imagery. Biodiversity indicators like the amount of dead wood and species richness were mainly underestimated with UAV-based hyperspectral imagery and photogrammetric point clouds. Indicators of structural variability (i.e., standard deviation in diameter-at-breast height and tree height) were the most accurately estimated biodiversity indicators with relative RMSE between 24.4% and 29.3% with semi-ITC. The largest relative errors occurred for predicting deciduous trees (especially aspen and alder), partly due to their small amount within the study area. Thus, especially the structural diversity was reliably predicted by integrating the three-dimensional and spectral datasets of UAV-based point clouds and hyperspectral imaging, and can therefore be further utilized in ecological studies, such as biodiversity monitoring.

show abstract

Section: Discussionmentioning

confidence: 99%

Assessing Biodiversity in Boreal Forests with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging

et al. 2018

View full text Add to dashboard Cite

show abstract

“…Best estimations peaked when models contained 3-5 predictors for most GLCMs and window sizes, after which accuracies remained unchanged or decreased slightly and progressively (Fig 3). Logically, multiple individual spectral bands, should be preferable for effective identification of plant species composition [80,[83][84][85]. This is justified by the fact that different species…”

Section: Importance Of Predictor Size and Window Size On Species Divementioning

confidence: 99%

Estimation of woody plant species diversity during a dry season in a savanna environment using the spectral and textural information derived from WorldView-2 imagery

et al. 2020

View full text Add to dashboard Cite

Remote sensing techniques are useful in the monitoring of woody plant species diversity in different environments including in savanna vegetation types. However, the performance of satellite imagery in assessing woody plant species diversity in dry seasons has been understudied. This study aimed to assess the performance of multiple Gray Level Co-occurrence Matrices (GLCM) derived from individual bands of WorldView-2 satellite imagery to quantify woody plant species diversity in a savanna environment during the dry season. Woody plant species were counted in 220 plots (20 m radius) and subsequently converted to a continuous scale of the Shannon species diversity index. The index regressed against the GLCMs using the all-possible-subsets regression approach that builds competing models to choose from. Entropy GLCM yielded the best overall accuracy (adjusted R 2 : 0.41−0.46; Root Mean Square Error (RMSE): 0.60−0.58) in estimating species diversity. The effect of the number of predicting bands on species diversity estimation was also explored. Accuracy generally increased when three-five bands were used in models but stabilised or gradually decreased as more than five bands were used. Despite the peak accuracies achieved with three-five bands, performances still fared well for models that used fewer bands, showing the relevance of few bands for species diversity estimation. We also assessed the effect of GLCM window size (3×3, 5×5 and 7×7) on species diversity estimation and generally found inconsistent conclusions. These findings demonstrate the capability of GLCMs combined with high spatial resolution imagery in estimating woody plants species diversity in a savanna environment during the dry period. It is important to test the performance of species diversity estimation of similar environmental setups using widely available moderate-resolution imagery.

show abstract

“…A modified fractal dimension index is suggested to measure the landscape diversity for a Landsat TM image (Olsen et al 1993). Vegetation diversity is a frequent subject of remote sensing studies, and successful examples of spectral and textural measures of the biological and structural diversity of urban forests were presented recently (Ozkan et al 2016(Ozkan et al , 2017. Vegetation and land cover/land use changes are also frequently examined through the lens of the landscape metrics change (Velli et al 2018).…”

Section: Indicators Of Heterogeneity and Diversitymentioning

confidence: 99%

Deconstructing landscape pattern: applications of remote sensing to physiognomic landscape mapping

2019

View full text Add to dashboard Cite

In 1939, Carl Troll pointed out that "air photo interpretation is to a large extent landscape ecology". From that time forward, remote sensing has been applied across different disciplines to comprehend the holistic and dynamic spatial layout of the visual Earth environment. However, its applicability in the domain of landscape character assessment, landscape design and planning is still questionable. The purpose of this paper was to synthesise some historical and current applications of remote sensing for the decomposition of the continual visual landscape from a bird's eye perspective and to explore the potential for bridging geographic processes with visual perception and an appreciation of the landscape pattern. From the point of view of landscape ecology, the organisation of the landscape pattern (namely, the size, shape (form), number, density and diversity, the complexity of landscape elements, and colours and textures of the land cover) is crucial for the cognition of both the visual landscape experience and the geographic processes. There are numerous pieces of evidence from the literature that remote sensing data are widely implemented in the modelling of physiognomic landscape. The synthesis of the literature concludes with perspective directions of remote sensing applications, such as mapping the status of the ecosystem (landscape) services provision, the delineation of the boundaries of the protected areas based on the quality of the Title visual environment, and the assessment of the sustainability of the land use practices, regarding their impact on landscape aesthetics extent.

show abstract

Comparison of satellite images with different spatial resolutions to estimate stand structural diversity in urban forests

Cited by 12 publications

References 34 publications

Assessing Biodiversity in Boreal Forests with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging

Assessing Biodiversity in Boreal Forests with UAV-Based Photogrammetric Point Clouds and Hyperspectral Imaging

Estimation of woody plant species diversity during a dry season in a savanna environment using the spectral and textural information derived from WorldView-2 imagery

Deconstructing landscape pattern: applications of remote sensing to physiognomic landscape mapping

Contact Info

Product

Resources

About