Quantifying structural physical habitat attributes using LIDAR and hyperspectral imagery

Hall, Robert King; Watkins, Russell; Heggem, Daniel T.; Jones, Kevin B.; Kaufmann, Philip R.; Moore, Steven B.; Gregory, Sandra J.

doi:10.1007/s10661-008-0613-y

Cited by 42 publications

(41 citation statements)

References 36 publications

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“…Previous studies also show the potential of LiDAR data to describe riparian vegetation; but most of these are focused on forest applications (Farid et al, 2006(Farid et al, , 2008Greenberg et al, 2012;Wasser et al, 2013). Only a few studies can be found on the potential of LiDAR data to describe the ecological attributes of riparian zone (Hall et al, 2009;Johansen et al, 2010).…”

Section: Introductionmentioning

confidence: 99%

LiDAR derived ecological integrity indicators for riparian zones: Application to the Houille river in Southern Belgium/Northern France

Michez¹,

Piégay²,

Toromanoff³

et al. 2013

Ecological Indicators

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a b s t r a c tRiparian zones are central landscape features providing several ecosystem services and are exceptionally rich in biodiversity. Despite their relatively low area coverage, riparian zones consequently represent a major concern for land and water resource managers confirmed within several European directives. These directives involve effective multi-scale monitoring to assess their conditions and their ability to carry out their functions. The objective of this research was to develop automated tools to provide from a single aerial LiDAR dataset new mapping tools and keystone riparian zone attributes assessing the ecological integrity of the riparian zone at a network scale (24 km).Different metrics were extracted from the original LiDAR point cloud, notably the Digital Terrain Model and Canopy Height Model rasters, allowing the extraction of riparian zones attributes such as the wetted channel (0.89 m; mean residual) and floodplain extents (6.02 m; mean residual). Different riparian forest characteristics were directly extracted from these layers (patch extent, overhanging character, longitudinal continuity, relative water level, mean and relative standard deviation of tree height). Within the riparian forest, the coniferous stands were distinguished from deciduous and isolated trees, with high accuracy (87.3%, Kappa index).Going further the mapping of the indicators, our study proposed an original approach to study the riparian zone attributes within different buffer width, from local scale (50 m long channel axis reach) to a network scale (ca. 2 km long reaches), using a disaggregation/re-agraggation process. This novel approach, combined to graphical presentations of the results allow natural resource managers to visualise the variation of upstream-downstream attributes and to identify priority action areas.In the case study, results showed a general decrease of the riparian forests when the river crosses built-up areas. They also highlighted the lower flooding frequency of riparian forest patches in habitats areas.Those results showed that LiDAR data can be used to extract indicators of ecological integrity of riparian zones in temperate climate zone. They will enable the assessment of the ecological integrity of riparian zones to be undertaken at the regional scale (13,000 km, completely covered by an aerial LIDAR survey in 2014).

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Section: Introductionmentioning

confidence: 99%

LiDAR derived ecological integrity indicators for riparian zones: Application to the Houille river in Southern Belgium/Northern France

Michez¹,

Piégay²,

Toromanoff³

et al. 2013

Ecological Indicators

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“…For decades, remote sensing has enabled synoptic views of entire rivers and their catchments at increasingly fine resolutions. It can now provide data at resolutions that capture reach-scale riparian and instream habitat structuring (Hall et al 2009). …”

Section: Methods and Data In Land Use Analysismentioning

confidence: 99%

Land Use

Trautwein¹,

Pletterbauer²

2018

Riverine Ecosystem Management

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Dendritic stream-river networks are the backbone of most landscapes on earth’s surface and determine linkages between terrestrial and aquatic ecosystems. These networks are hierarchically organized from microhabitats to the scale of whole catchments (Frissell et al. 1986). Accordingly, many processes of lotic freshwater ecosystems are determined by this hierarchically nested structure of river networks and their interlinkages. Hynes (1975) emphasized the importance of the linkage between the conditions within a river catchment and the flows of energy, materials, and organisms in the river as a dynamic ecosystem. These flows are interwoven in complex, cross-linked relationships of ecosystem functioning. Up to now, it is a prime challenge to understand these functions in detail and to robustly manage riverine landscapes in a sustainable manner. Starting with the work of Hynes (1975), the scale of riverine management was understood to occur over entire river catchments or even river basins with several concepts that integrated this perception (Vannote et al. 1980; Frissell et al. 1986; Ward 1989; Poff 1997; Fausch et al. 2002; Ward et al. 2002; Burcher et al. 2007). These theoretical frameworks seek to understand and to quantify interactions between landscape conditions over large spatial extents and instream responses. Ultimately, the catchment approach was even implemented into legal frameworks, such as the Water Framework Directive (WFD), which recognizes the river basin as relevant management scale (European Parliament 2000).

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“…Recent successes in manned-aircraft RS of riverine environments demonstrates spatial and spectral resolutions that may meet accuracy requirements for measuring many rPHA variables, thus suggesting that similar results can be achieved with drone-based RS [33]. While drone-based spatial and spectral technologies can supply many rPHA quantitative data, determining the most appropriate drone-based sensor(s) to enhance the development of rPHA requires further research.…”

Section: Challenges Using Geographic Information Systems and Remote Smentioning

confidence: 99%

“…Contemporary GIS/RS approaches are being developed to scale down from the watershed or basin level to the stream reach, including in some cases, characterization of channel morphology and other physical habitat attributes [32,33]. For example, Reference [33] demonstrated the integration of airborne Light Detecting and Ranging (LiDAR) technology and hyperspectral imagery to produce high spatial resolution geospatial data of topography, channel dimensions/complexity (e.g., width, depth, slope, riffles/pool spacing), hydraulic roughness, riparian integrity, and anthropogenic alterations.…”

Section: Challenges Using Geographic Information Systems and Remote Smentioning

confidence: 99%

“…For example, Reference [33] demonstrated the integration of airborne Light Detecting and Ranging (LiDAR) technology and hyperspectral imagery to produce high spatial resolution geospatial data of topography, channel dimensions/complexity (e.g., width, depth, slope, riffles/pool spacing), hydraulic roughness, riparian integrity, and anthropogenic alterations. Similarly, Reference [32] revealed that helicopter-based RS and Structure-from-Motion (SfM) photogrammetry hold great promise for detailed riverscape mapping, including many parameters necessary for rPHA.…”

Section: Challenges Using Geographic Information Systems and Remote Smentioning

confidence: 99%

See 1 more Smart Citation

Challenges in Aquatic Physical Habitat Assessment: Improving Conservation and Restoration Decisions for Contemporary Watersheds

et al. 2017

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Attribution of in-stream biological impairment to anthropogenic activities and prioritization for restoration and/or conservation can be challenging in contemporary mixed-land-use watersheds. Critical information necessary to improve decision making can be costly and labor intensive, and thus unobtainable for many municipalities. A reduced cost, rapid stream physical habitat assessment (rPHA) can yield information that, when paired with land use data may reveal causal patterns in aquatic physical habitat degradation, and thus assist targeting sites for restoration. However, a great deal of work is needed to reduce associated costs, and validate the potential of rPHA for documenting fine-scale incremental change in physical habitat conditions in complex contemporary watersheds. The following commentary serves to draw attention to rPHA challenges and research needs including (but not limited to) field-based validation and optimization of new remote sensing technologies, evaluation of the accuracy and representativeness of rapid vegetation survey methods, refinement of analytical methods, and consideration of legacy land use impacts and hydrologic system evolution in rPHA results interpretation. Considering the value of rPHA-generated data for improvement of watershed resource management, such challenges constitute timely, high-impact research opportunities for investigators wishing to advance complex, contemporary aquatic ecosystem management.

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Quantifying structural physical habitat attributes using LIDAR and hyperspectral imagery

Cited by 42 publications

References 36 publications

LiDAR derived ecological integrity indicators for riparian zones: Application to the Houille river in Southern Belgium/Northern France

LiDAR derived ecological integrity indicators for riparian zones: Application to the Houille river in Southern Belgium/Northern France

Land Use

Challenges in Aquatic Physical Habitat Assessment: Improving Conservation and Restoration Decisions for Contemporary Watersheds

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