Aerial Photography and Image Interpretation

Paine, David P.; Kiser, James D.

doi:10.1002/9781118110997

Cited by 114 publications

(104 citation statements)

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“…The main disadvantage of this process is the limited potential of identifying the bottom of a tree in densely canopied stands if the terrain surface in the vicinity of the tree is not visible (Korpela 2004, Paine & Kiser 2012. Another reason for the limited practical application is related to the amount of manual processing required when using the classical photogrammetric methods (Balenović et al 2010, Paine & Kiser 2012). Due to above-mentioned reasons it has been generally accepted that the extraction of forest and tree data from classical analogue aerial photographs has certain limitations, especially in the densely canopied forests.…”

Section: Introductionmentioning

confidence: 99%

Estimation of the mean tree height of forest stands by photogrammetric measurement using digital aerial images of high spatial resolution

et al. 2015

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. Estimation of the mean tree height of forest stands by photogrammetric measurement using digital aerial images of high spatial resolution. Ann. For. Res. 58(1): 125-143.Abstract. Tree height is one of the more fundamental measurements in forest inventories. In addition to classical field measurements, tree height may be estimated by remote sensing methods, such as by photogrammetric measurements of aerial images. Since it has been found and generally accepted that the extraction of forest and tree data from classical analogue aerial photographs has certain limitations, especially in the densely canopied forests, the usefulness of photogrammetric-based forest inventory in many countries remains a controversial issue. Therefore, this paper focuses on investigating the possibility of applying digital photogrammetric method to estimate mean stand height. Photogrammetric stereo-measurements of tree height were conducted on colour infrared images of high spatial resolution (ground sample distance -GSD -of 30 cm and 10 cm) using a digital photogrammetric workstation. The height of each tree within 183 sample plots (14 subcompartments) were calculated as the difference between the tree top elevations determined with the aerial images and the corresponding tree bottom elevations determined from the digital terrain model. To compare the photogrammetric-and field-estimated mean stand heights, the mean plot heights were calculated for both photogrammetric and field estimates of tree heights. Repeated measurements using ANOVA testing did not reveal a statistically significant difference (p > 0.05) between the field-estimated and photogrammetric-estimated mean stand heights using the 30 cm and 10 cm GSD digital aerial images. Deviations of the mean stand heights estimated using the images of both spatial resolutions were similar to the field-estimated heights. Using the 30 cm images the deviations of the photogrammetrically estimated mean stand height amounted to 0.35 m (1.59%) on average, whereas using the 10 cm images the deviations amounted to 0.31 m (1.41%) compared to the field estimation. Therefore, it can be concluded that the 30 cm GSD aerial images allow for the photogrammetric measurement of mean stand heights with accuracy similar to 10 cm GSD aerial images. In addition, 30 cm GSD aerial images are more favourable financially since the same area of interest could be covered with a considerably smaller number of images than of the 10 cm GSD aerial images.

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Section: Introductionmentioning

confidence: 99%

Estimation of the mean tree height of forest stands by photogrammetric measurement using digital aerial images of high spatial resolution

et al. 2015

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“…A photomosaic may be constructed from a set of overlapping images by identifying tie points -points that appear on two or more photographs -that allow the photographs to be aligned relative to each other (Aber et al, 2010). The mosaic is georeferenced, or related to a real-world, reference coordinate system, using ground control points (GCPs) -points on the Earth's surface that are clearly identifiable in the photographs and whose locations in the reference coordinate system can be measured (Paine, 1981). The location of GCPs can be measured using a total station, real-time kinematic global positioning system (GPS) or differential GPS on the high end, both in terms of accuracy and cost; or, GCP locations can be determined less accurately -yet more cheaply -using an uncorrected GPS signal as do consumer-grade receivers for in-car navigation or recreation.…”

Section: Introductionmentioning

confidence: 99%

Mapping with strings attached: Kite aerial photography of Durai Island, Anambas Islands, Indonesia

Currier

2014

Journal of Maps

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A 1:2,000 scale orthophoto map of the southern coast of Durai Island, Indonesia, was created using kite aerial photography and computer vision software. Photographs were taken using a consumer-grade digital camera suspended from the line of a kite that was towed by boat along Durai's coastline. Three hundred and fifty-seven aerial photographs were combined into a mosaic, orthorectified and georeferenced using Agisoft PhotoScan software with ground control points collected via a GPS field survey. The map was created in conjunction with underwater ecological surveys of the coral reefs surrounding the island, and it supports ongoing monitoring and educational outreach efforts. Kite aerial photography provides a low-cost, portable, and technologically straightforward means of collecting large-scale aerial imagery in situations where a conventional, aircraft-based photographic survey is not practical.

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“…In addition to the error matrix we used the conditional K hat coefficient of agreement to calculate the agreement between the reference and remote sensing-derived data with change agreement eliminated for an individual class for user accuracy (Congalton and Green, 1999;Paine and Kiser, 2003). For example, the conditional K i coefficient of agreement for residential land-use class in Table 2 is calculated according to Eq.…”

Section: Validation and Discussionmentioning

confidence: 99%

Classification of 10m-resolution SPOT data using a combined Bayesian Network Classifier-shape adaptive neighborhood method

Yang¹,

Wang²

2012

ISPRS Journal of Photogrammetry and Remote Sensing

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Aerial Photography and Image Interpretation

Cited by 114 publications

References 0 publications

Estimation of the mean tree height of forest stands by photogrammetric measurement using digital aerial images of high spatial resolution

Estimation of the mean tree height of forest stands by photogrammetric measurement using digital aerial images of high spatial resolution

Mapping with strings attached: Kite aerial photography of Durai Island, Anambas Islands, Indonesia

Classification of 10m-resolution SPOT data using a combined Bayesian Network Classifier-shape adaptive neighborhood method

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