Wavelet estimation of plant spatial patterns in multitemporal aerial photography

Strand, Eva K.; Smith, Alistair M. S.; Bunting, Stephen C.; Vierling, Lee A.; Hann, David; Gessler, Paul E.

doi:10.1080/01431160500444764

Cited by 74 publications

(70 citation statements)

References 9 publications

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“…One-dimensional analyses of forest vegetation primarily involve continuous, rather than binary, data and consider heterogeneity in terms of variance as a function of scale [31,78]. Wavelet analysis, for example, is a multi-scale approach [101] that can incorporate remote sensing data to identify hierarchical patterns in horizontal attributes like canopy gap structure [102,103] and tree crown diameter [104,105]. Here the line-intercept sampling of both shrub and canopy layers produced sets of binary data for each of these strata, and enabled direct comparisons of their heterogeneity through the calculation of their respective fractal dimensions.…”

Section: Relationships Between Spatial Heterogeneity Of the Forest Camentioning

confidence: 99%

Spatial Heterogeneity of the Forest Canopy Scales with the Heterogeneity of an Understory Shrub Based on Fractal Analysis

Denny

Nielsen

2017

Forests

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Spatial heterogeneity of vegetation is an important landscape characteristic, but is difficult to assess due to scale-dependence. Here we examine how spatial patterns in the forest canopy affect those of understory plants, using the shrub Canada buffaloberry (Shepherdia canadensis (L.) Nutt.) as a focal species. Evergreen and deciduous forest canopy and buffaloberry shrub presence were measured with line-intercept sampling along ten 2-km transects in the Rocky Mountain foothills of west-central Alberta, Canada. Relationships between overstory canopy and understory buffaloberry presence were assessed for scales ranging from 2 m to 502 m. Fractal dimensions of both canopy and buffaloberry were estimated and then related using box-counting methods to evaluate spatial heterogeneity based on patch distribution and abundance. Effects of canopy presence on buffaloberry were scale-dependent, with shrub presence negatively related to evergreen canopy cover and positively related to deciduous cover. The effect of evergreen canopy was significant at a local scale between 2 m and 42 m, while that of deciduous canopy was significant at a meso-scale between 150 m and 358 m. Fractal analysis indicated that buffaloberry heterogeneity positively scaled with evergreen canopy heterogeneity, but was unrelated to that of deciduous canopy. This study demonstrates that evergreen canopy cover is a determinant of buffaloberry heterogeneity, highlighting the importance of spatial scale and canopy composition in understanding canopy-understory relationships.

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Section: Relationships Between Spatial Heterogeneity Of the Forest Camentioning

confidence: 99%

Spatial Heterogeneity of the Forest Canopy Scales with the Heterogeneity of an Understory Shrub Based on Fractal Analysis

Denny

Nielsen

2017

Forests

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“…By varying the threshold for discrimination across the image by an image segmentation procedure using the local standard deviation, smaller crowns that are increasingly confused with snow because of reflection from ground beneath the canopy can be identified while providing good definition of the forest boundary in denser areas. Four main techniques have been developed for automatic crown delineation in images: valley following (Gougeon 1995), pattern matching (Pollock 1996), crown centroid identification (Culvenor 2002), and wavelet analysis (Strand et al 2006). The crown centroid method used here is described by Bunting and Lucas (2006).…”

Section: April 2008 E S S E R Y E T a Lmentioning

confidence: 99%

Radiative Transfer Modeling of a Coniferous Canopy Characterized by Airborne Remote Sensing

Essery

Bunting

Hardy

et al. 2008

Journal of Hydrometeorology

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Solar radiation beneath a forest canopy can have large spatial variations, but this is frequently neglected in radiative transfer models for large-scale applications. To explicitly model spatial variations in subcanopy radiation, maps of canopy structure are required. Aerial photography and airborne laser scanning are used to map tree locations, heights, and crown diameters for a lodgepole pine forest in Colorado as inputs to a spatially explicit radiative transfer model. Statistics of subcanopy radiation simulated by the model are compared with measurements from radiometer arrays, and scaling of spatial statistics with temporal averaging and array size is discussed. Efficient parameterizations for spatial averages and standard deviations of subcanopy radiation are developed using parameters that can be obtained from the model or hemispherical photography.

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“…Aerial photography can be used to quantify the size classes and distributions of individual trees [60] and in some cases to identify trees to species based on color, size, shape, and texture [53]. Using more sophisticated imaging spectrometers capable of measuring hundreds of spectral bands, relationships may be established between individual tree spectral diversity and chemical properties, and as a result, the spectral tools to identify plants even within dense canopies are constantly improving [61].…”

Section: Detection Of Individualsmentioning

confidence: 99%

Remote Sensing and Ecosystem Services: Current Status and Future Opportunities for the Study of Bees and Pollination-Related Services

2015

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An unprecedented array of observing systems, coupled with ever increasing computing capacity, makes this a golden era for ecologists to study and quantify ecosystem services using remote sensing technology. Here, we review recent studies that utilize remote sensing to understand the supply and demand of ecosystem services, with a specific focus on pollination services by bees in forested and agroforestry contexts. Pollination by bees is a globally threatened ecosystem service that supports the production of food crops and maintains plant biodiversity. We explore how studies that use remote sensing to characterize landscapes, monitor individual organisms, measure biodiversity proxies or species habitat, and describe ecosystem processes may improve modeling of pollination services on spatial scales that match large-scale management efforts, such as forest conservation policy. We then discuss future research opportunities, such as exploring LiDAR and radar for 3-D habitat measurements, mapping phenology in space and time, and direct measurement of pollination events and outcomes.

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Wavelet estimation of plant spatial patterns in multitemporal aerial photography

Cited by 74 publications

References 9 publications

Spatial Heterogeneity of the Forest Canopy Scales with the Heterogeneity of an Understory Shrub Based on Fractal Analysis

Spatial Heterogeneity of the Forest Canopy Scales with the Heterogeneity of an Understory Shrub Based on Fractal Analysis

Radiative Transfer Modeling of a Coniferous Canopy Characterized by Airborne Remote Sensing

Remote Sensing and Ecosystem Services: Current Status and Future Opportunities for the Study of Bees and Pollination-Related Services

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