Retrieving forest structure variables based on image texture analysis and IKONOS-2 imagery

Francois, Kayitakire; Hamel, Cyril; Defourny, Pierre

doi:10.1016/j.rse.2006.02.022

Cited by 293 publications

(233 citation statements)

References 31 publications

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“…In general, as rule of thumb, 25-30 m SAR spatial resolution or 25 m LiDAR footprint diameter are required to capture vegetation structure for biodiversity application (Bergen et al 2009). Other promising alternatives to active sensor data have included multispectral or hyperspectral data, mainly using neighbourhood statistics, spectral indices, or texture features (Wolter et al 2009;Kayitakire et al 2006;Cho et al 2009;White et al 2010;Petrou et al 2012).…”

Section: Forestry Monitoringmentioning

confidence: 99%

Remote sensing for biodiversity monitoring: a review of methods for biodiversity indicator extraction and assessment of progress towards international targets

2015

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Recognizing the imperative need for biodiversity protection, the Convention on Biological Diversity (CBD) has recently established new targets towards 2020, the so-called Aichi targets, and updated proposed sets of indicators to quantitatively monitor the progress towards these targets. Remote sensing has been increasingly contributing to timely, accurate, and cost-effective assessment of biodiversity-related characteristics and functions during the last years. However, most relevant studies constitute individual research efforts, rarely related with the extraction of widely adopted CBD biodiversity indicators. Furthermore, systematic operational use of remote sensing data by managing authorities has still been limited. In this study, the Aichi targets and the related CBD indicators whose monitoring can be facilitated by remote sensing are identified. For each headline indicator a number of recent remote sensing approaches able for the extraction of related properties are reviewed. Methods cover a wide range of fields, including: habitat extent and condition monitoring; species distribution; pressures from unsustainable management, pollution and climate change; ecosystem service monitoring; and conservation status assessment of protected areas. The advantages and limitations of different remote sensing data and algorithms are discussed. Sorting of the methods based on their reported accuracies is attempted, when possible. The extensive literature survey aims at reviewing highly performing methods that can be used for large-area, effective, and timely biodiversity assessment, to encourage the more systematic use of remote sensing solutions in monitoring progress towards the Aichi targets, and to decrease the gaps between the remote sensing and management communities.

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Section: Forestry Monitoringmentioning

confidence: 99%

Remote sensing for biodiversity monitoring: a review of methods for biodiversity indicator extraction and assessment of progress towards international targets

2015

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“…IKO-NOS images, with their submetric resolution, have been used in previous studies to analyze forest structure (Kayitakire et al 2006), the size of tree crowns (Song et al 2010) and the severity of wind disturbance (Rich et al 2010). This breakthrough for small-scale mapping with satellite images was followed by the launch of other satellites such as QuickBird, GeoEye-1, WorldView-1, and WorldView-2 (Jacobsen 2012).…”

Section: Introductionmentioning

confidence: 99%

Gap pattern of the largest primeval beech forest of Europe revealed by remote sensing

et al. 2015

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Abstract. Little is known about the gap pattern of primeval beech forests, since large-scale studies with continuous coverage are lacking. Analyses of forest structural patterns have benefitted from advances in remote sensing, especially with the launch of satellites providing data of submetric ground resolution. These developments can strongly advance our knowledge of natural forest dynamics and disturbance regimes. The Uholka-Shyrokyi Luh forest in the Ukrainian Carpathians, the largest remnant of primeval European beech (Fagus sylvatica L.) covering 102.8 km 2 , is an outstanding object to analyze the frequency distribution of gap sizes and to infer processes of forest dynamics. A stereo pair of very high-resolution WorldView-2 satellite images was used to characterize the forest's gap pattern. Canopy gaps were first digitized stereoscopically based on the image pair. In a second step, spectral properties in the red and yellow frequency bands were used to distinguish the stereoscopically mapped gap areas from non-gap areas, which enabled gap mapping over the entire study area. To validate the spectral gap mapping 338 randomly distributed samples were assigned manually to gap and non-gap areas based on the orthoimages. We found excellent agreement except for an overestimation of gaps close to clouds due to diffuse image areas. The frequency distribution of gap size revealed the forest to be structured by a small-scale mosaic of gaps mainly ,200 m 2 (98% of the gaps). Only a few large, stand-replacing events were detected, most probably caused by a wind storm in March 2007 and a heavy wet snow fall in October 2009. The small canopy gaps reflect fine-scale processes shaping forest structure, i.e., the death of single trees or groups of a few trees and is in line with the findings of the terrestrial forest inventory. We conclude that remote sensing approaches based on very high-resolution satellite images are highly useful to characterize even small-scale forest disturbance regimes and to study long-term gap dynamics. Stereo satellite images provide two viewing angles of the study area, thus allowing for a highly accurate mapping of canopy gaps in forests with a complex topography.

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“…HDI was analysed using a Pearson correlation coefficient. Where P [ 0.05, the relevant variable was considered to have a normal distribution (Kalayci 2006;Kayitakire et al 2006).…”

Section: Discussionmentioning

confidence: 99%

Assessment of landscape silhouette value in urban forests based on structural diversity indices

Özkan

Özdemir

2015

Int. J. Environ. Sci. Technol.

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Urban forests form an important component of the urban environment. They make a significant contribution to landscape silhouettes due to species diversity and the differences observed within forest communities such as tree composition, size and form. Visual effects such as these are referred as aesthetic value. Therein, quantitative assessments of targeted forest structures that will optimize aesthetic values are vital during urban forest planning. However, the silhouette effect, which is an important component of aesthetic value, has not been extensively studied to date. This study aims to reveal the relationship between forest structure, the visual quality of tree composition and the different forms and sizes that create the silhouette effect. To this end, virtual landscapes of different structures were created using computer-assisted images. The forest structure was characterized by a Form Mingling Index (FMI) and Height Dominance Index (HDI). A Pearson correlation was applied in order to find the relationship between the landscape silhouette values through a perceptual test as well as the FMI and HDI. The results of the analyses showed that there was a strong positive relationship between the FMI and HDI (r = 0.78, r = 0.75, P \ 0.01, respectively) and landscape silhouette values. The combined effect of FMI ? HDI was found to have the highest relationship with landscape silhouette values (r = 0.80, P \ 0.01). In conclusion, FMI and HDI offer a rapid, cost-effective method which can be used by managers to assess the silhouette value of an urban forest landscape.

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Retrieving forest structure variables based on image texture analysis and IKONOS-2 imagery

Cited by 293 publications

References 31 publications

Remote sensing for biodiversity monitoring: a review of methods for biodiversity indicator extraction and assessment of progress towards international targets

Remote sensing for biodiversity monitoring: a review of methods for biodiversity indicator extraction and assessment of progress towards international targets

Gap pattern of the largest primeval beech forest of Europe revealed by remote sensing

Assessment of landscape silhouette value in urban forests based on structural diversity indices

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