Exploring Landscape Change in Mountain Environments With the Mountain Legacy Online Image Analysis Toolkit

Sanseverino, Mary; Whitney, Michael J.; Higgs, Eric

doi:10.1659/mrd-journal-d-16-00038.1

Cited by 11 publications

(17 citation statements)

References 19 publications

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“…In such cases, oblique photographs may have a more appropriate angle of incidence, capturing a significant amount of detail on slopes that overhead images miss (Delaney ; Sanseverino et al. ). Fourth, oblique photographs often provide much greater resolution than typical satellite products (Chandler et al.…”

Section: Introductionmentioning

confidence: 99%

“…We hypothesized that: (1) there is a positive linear relationship between land cover proportions quantified by oblique photographs and those quantified by satellite images for most classes, although (2) classes characteristic of steep slopes would represent a higher proportion of the landscape in oblique images than in overhead images because of the different angles of incidence (Delaney ; Sanseverino et al. ), and (3) oblique images would capture a greater amount of detail in the landscape due to their higher resolution (Chandler et al. ).…”

Section: Introductionmentioning

confidence: 99%

“…Third, in mountainous landscapes with steep slopes and cliffs, the assumption that orthogonal images are perpendicular to the Earth's surface is violated. In such cases, oblique photographs may have a more appropriate angle of incidence, capturing a significant amount of detail on slopes that overhead images miss (Delaney 2008;Sanseverino et al 2016). Fourth, oblique photographs often provide much greater resolution than typical satellite products (Chandler et al 2002;Lef evre et al 2017).…”

Section: Introductionmentioning

confidence: 99%

“…The photographs have been preserved on large format glass plates, mainly at Library and Archives Canada. Over the years, the MLP has repeated over 7000 of the historic images, and has built a suite of custom tools for classification and analysis of oblique images (Gat et al 2011;Jean et al 2015b;Sanseverino et al 2016).…”

Section: Introductionmentioning

confidence: 99%

“…Given that both types of imagery are optical representations of the same landscape, we expected land cover composition to be fairly consistent between the two, with discrepancies reflecting inherent differencesbut not necessarily biasesin the way the data sources sample the landscape. We hypothesized that: (1) there is a positive linear relationship between land cover proportions quantified by oblique photographs and those quantified by satellite images for most classes, although (2) classes characteristic of steep slopes would represent a higher proportion of the landscape in oblique images than in overhead images because of the different angles of incidence (Delaney 2008;Sanseverino et al 2016), and (3) oblique images would capture a greater amount of detail in the landscape due to their higher resolution (Chandler et al 2002). We further present an example analyzing long-term change in landscape composition in a mountain ecosystem using paired historical and repeat oblique photographs.…”

Section: Introductionmentioning

confidence: 99%

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Estimates of landscape composition from terrestrial oblique photographs suggest homogenization of Rocky Mountain landscapes over the last century

Fortin

Fisher

Rhemtulla

et al. 2018

Remote Sens Ecol Conserv

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While orthogonal (i.e., aerial or satellite) imagery has become the more conventional source of land cover data because it can yield spatially accurate land cover maps, terrestrial oblique photographs present a valuable, relatively untapped source of raw optical data for studies of land cover change. We present a case study contrasting how these two types of imagery sample landscape composition and using repeat oblique photographs to evaluate long‐term land cover change in a remote region of the Canadian Rocky Mountains. We classified 46 historical oblique photographs and their corresponding modern repeats using the same discrete land cover classes employed in a Landsat‐based map of the same area. We compared landscape‐level composition estimates from both sources and regressed the land cover proportions from Landsat against the modern oblique images, hypothesizing a linear relationship for most classes. We found that the two sources sampled the landscape in broadly similar ways, with near‐concordance for dominant land cover classes, yet that oblique photographs more frequently detected narrow landscape features and estimated higher proportions of rock compared to satellite imagery, possibly due to the higher spatial resolution of the oblique photographs, and to their angle of incidence against steep slopes. We then evaluated land cover change from corresponding historical and repeat photographs and found that the landscape has homogenized over the past century via increased coniferous forest cover. Our work shows that terrestrial oblique photographs can be used to estimate landscape composition, particularly in mountain environments. This is helpful for analyzing past landscape conditions in historical photographs, monitoring decadal‐span landscape change and assessing habitat to model biodiversity through time.

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Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

Estimates of landscape composition from terrestrial oblique photographs suggest homogenization of Rocky Mountain landscapes over the last century

Fortin

Fisher

Rhemtulla

et al. 2018

Remote Sens Ecol Conserv

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Assessing the accuracy of georeferenced landcover data derived from oblique imagery using machine learning

Tricker,

Wright,

Rose

et al. 2024

Remote Sens Ecol Conserv

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Repeat photography offers distinctive insights into ecological change, with ground‐based oblique photographs often predating early aerial images by decades. However, the oblique angle of the photographs presents challenges for extracting and analyzing ecological information using traditional remote sensing approaches. Several innovative methods have been developed for analyzing repeat photographs, but none offer a comprehensive end‐to‐end workflow incorporating image classification and georeferencing to produce quantifiable landcover data. In this paper, we provide an overview of two new tools, an automated deep learning classifier and intuitive georeferencing tool, and describe how they are used to derive landcover data from 19 images associated with the Mountain Legacy Project, a research team that works with the world's largest collection of systematic high‐resolution historic mountain photographs. We then combined these data to produce a contemporary landcover map for a study area in Jasper National Park, Canada. We assessed georeferencing accuracy by calculating the root‐mean‐square error and mean displacement for a subset of the images, which was 4.6 and 3.7 m, respectively. Overall classification accuracy of the landcover map produced from oblique images was 68%, which was comparable to landcover data produced from aerial imagery using a conventional classification method. The new workflow advances the use of repeat photographs for yielding quantitative landcover data. It has several advantages over existing methods including the ability to produce quick and consistent image classifications with little human input, and accurately georeference and combine these data to generate landcover maps for large areas.

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Automatic detection of woody vegetation in repeat landscape photographs using a convolutional neural network

Bayr

Puschmann

2019

Ecological Informatics

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Exploring Landscape Change in Mountain Environments With the Mountain Legacy Online Image Analysis Toolkit

Abstract: BioOne Complete (complete.BioOne.org) is a full-text database of 200 subscribed and open-access titles in the biological, ecological, and environmental sciences published by nonprofit societies, associations, museums, institutions, and presses.

Cited by 11 publications

References 19 publications

Estimates of landscape composition from terrestrial oblique photographs suggest homogenization of Rocky Mountain landscapes over the last century

Estimates of landscape composition from terrestrial oblique photographs suggest homogenization of Rocky Mountain landscapes over the last century

Assessing the accuracy of georeferenced landcover data derived from oblique imagery using machine learning

Automatic detection of woody vegetation in repeat landscape photographs using a convolutional neural network

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