Assessing the mire conservation status of a raised bog site in Salzburg using object-based monitoring and structural analysis

Langanke, Tobias; Burnett, Charles K.; Lang, Stefan

doi:10.1016/j.landurbplan.2006.02.006

Cited by 34 publications

(42 citation statements)

References 46 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Wetland detection & delineation: studies detecting wetland presence and/or delineating their boundaries in landscapes with significant proportion of non-wetland natural and anthropogenic land cover [14][15][16]18,26,29,[38][39][40]55,63,64,73,74,[84][85][86][87]. (2).…”

Section: Research Objectives and Focusmentioning

confidence: 99%

“…(2). Typological classification of delineated wetland units: assignment of mapped wetland bodies into hydrological, geomorphological and ecological categories without detailed mapping of within-wetland cover [6,27,29,37,43,44,55,65,66,73,79,80]; (3). Classification of within-wetland cover types and/or vegetation: mapping within-wetland surface composition and vegetation types, sometimes targeting specific classes such as invasive plant species (e.g., [5,8,12,13,17,[23][24][25]28,30,32,34,41,45,[48][49][50]52,53,57,68,69,[74][75][76][77][79][80][81][82][83][84][85]); …”

Section: Research Objectives and Focusmentioning

confidence: 99%

“…Seventeen studies used the data from synthetic aperture radar (SAR) either as the primary input or in combination with Landsat or other sensors [27,37,40,43,47,53,54,71,[73][74][75][76][77][78][79][80]82] Natural log of pixel size in m overall accuracy less than 85% overall accuracy equal or greater than 85% overall accuracy not reported and ALOS PALSAR [40,79,80]; spatial resolution of these datasets varied between 10 and 100 m. Radar images as inputs to OBIA have been especially critical for wetland analyses in humid regions with frequent cloud cover limiting the availability of multi-spectral images and the consistency of seasonal time series [37,75,82]. Several high-resolution studies using multi-spectral imagery additionally incorporated light detection and ranging (lidar) datasets to facilitate the overall wetland classification or discrimination of specific classes and landscape features [6,25,28,32,59,71,77,80,89].…”

Section: General Characteristics Of Input Data and Classification Accmentioning

confidence: 99%

“…Smoothing of the local noise at object level was particularly useful in studies using SAR data to map wetland cover types in Amazon floodplain [74][75][76], Brazilian Pantanal [79,80] and northern forested regions of Canada [27] and Siberia [73]. Radar backscatter may exhibit substantial speckle due to complexity of both horizontal and vertical structure of wetland ecosystems which affects relative contributions of different scattering modes and thus the local variation of the modified signal [37,73].…”

Section: Using Image Segmentation To Address Heterogeneity and Noisementioning

confidence: 99%

“…Radar backscatter may exhibit substantial speckle due to complexity of both horizontal and vertical structure of wetland ecosystems which affects relative contributions of different scattering modes and thus the local variation of the modified signal [37,73]. Averaging of the radar pixel values at the object level often facilitated delineation of wetland units and vegetation types and enhanced their correspondence to semantic objects of interest across the gradients of inundation [27,37,54,74,75,80].…”

Section: Using Image Segmentation To Address Heterogeneity and Noisementioning

confidence: 99%

See 4 more Smart Citations

Object-Based Image Analysis in Wetland Research: A Review

2015

View full text Add to dashboard Cite

Abstract:The applications of object-based image analysis (OBIA) in remote sensing studies of wetlands have been growing over recent decades, addressing tasks from detection and delineation of wetland bodies to comprehensive analyses of within-wetland cover types and their change. Compared to pixel-based approaches, OBIA offers several important benefits to wetland analyses related to smoothing of the local noise, incorporating meaningful non-spectral features for class separation and accounting for landscape hierarchy of wetland ecosystem organization and structure. However, there has been little discussion on whether unique challenges of wetland environments can be uniformly addressed by OBIA across different types of data, spatial scales and research objectives, and to what extent technical and conceptual aspects of this framework may themselves present challenges in a complex wetland setting. This review presents a synthesis of 73 studies that applied OBIA to different types of remote sensing data, spatial scale and research objectives. It summarizes the progress and scope of OBIA uses in wetlands, key benefits of this approach, factors related to accuracy and uncertainty in its applications and the main research needs and directions to expand the OBIA capacity in the future wetland studies. Growing demands for higher-accuracy wetland characterization at both regional and local scales together with advances in very high resolution remote sensing and novel tasks in wetland restoration monitoring will likely continue active exploration of the OBIA potential in these diverse and complex environments.

show abstract

Section: Research Objectives and Focusmentioning

confidence: 99%

Section: Research Objectives and Focusmentioning

confidence: 99%

Section: General Characteristics Of Input Data and Classification Accmentioning

confidence: 99%

Section: Using Image Segmentation To Address Heterogeneity and Noisementioning

confidence: 99%

Section: Using Image Segmentation To Address Heterogeneity and Noisementioning

confidence: 99%

See 3 more Smart Citations

Object-Based Image Analysis in Wetland Research: A Review

2015

View full text Add to dashboard Cite

show abstract

Mapping Changes in Land Cover Composition and Pattern for Comparing Mediterranean Rangeland Restoration Alternatives

2015

View full text Add to dashboard Cite

The limited amount of studies addressing the long-term effectiveness of restoration actions to combat land degradation is a constraint for current landscape restoration planning and implementation. Remote sensing data provide a unique opportunity for gathering information on the spatial and temporal variability of restoration processes and may contribute to fill this knowledge gap. The aim of this study is to compare different management actions undertaken in Mediterranean degraded rangelands (i.e. dense pine plantations, thinned pine plantations, protection and passive management) by analysing landscape composition and pattern change assessed from object-based classification of aerial photograph of 1954, 1977 and 2006. Results show a clear link between landscape composition and structure and the different restoration actions, allowing comparison between their spatial and temporal dynamics. All restoration actions promoted an increase in woody vegetation cover compared with non-restored areas. However, only protection and passive management favoured the restoration of dense, complex and well-connected patches of native Mediterranean maquis. The proposed methodology is discussed with respect to its applicability for future Mediterranean landscape restoration planning in a wider geographic and ecological perspective.

show abstract