The Roles of Aerial Photographs in Forestry Remote Sensing Image Analysis

Hall, Ronald J.

doi:10.1007/978-1-4615-0306-4_3

Cited by 28 publications

(22 citation statements)

References 30 publications

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“…Manual methods of stereophotogrammetry have been used in forestry since the 1940s [37]; however, the evolution of computing technology and digital imagery have facilitated automation of the sterophotogrammetric measurement process and such methods began to emerge in Canada in the early 1990s [38]. Digital image systems (referred to as softcopy) have greatly streamlined forest inventory procedures [39].…”

Section: Image-based Point Cloudsmentioning

confidence: 99%

The Utility of Image-Based Point Clouds for Forest Inventory: A Comparison with Airborne Laser Scanning

White

Wulder

Vastaranta

et al. 2013

Forests

274

217

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Airborne Laser Scanning (ALS), also known as Light Detection and Ranging (LiDAR) enables an accurate three-dimensional characterization of vertical forest structure. ALS has proven to be an information-rich asset for forest managers, enabling the generation of highly detailed bare earth digital elevation models (DEMs) as well as estimation of a range of forest inventory attributes (including height, basal area, and volume). Recently, there has been increasing interest in the advanced processing of high spatial resolution digital airborne imagery to generate image-based point clouds, from which vertical information with similarities to ALS can be produced. Digital airborne imagery is typically less costly to acquire than ALS, is well understood by inventory practitioners, and in addition to enabling the derivation of height information, allows for visual interpretation of attributes that are currently problematic to estimate from ALS (such as species, health status, and maturity). At present, there are two limiting factors associated OPEN ACCESSForests 2013, 4 519 with the use of image-based point clouds. First, a DEM is required to normalize the image-based point cloud heights to aboveground heights; however DEMs with sufficient spatial resolution and vertical accuracy, particularly in forested areas, are usually only available from ALS data. The use of image-based point clouds may therefore be limited to those forest areas that already have an ALS-derived DEM. Second, image-based point clouds primarily characterize the outer envelope of the forest canopy, whereas ALS pulses penetrate the canopy and provide information on sub-canopy forest structure. The impact of these limiting factors on the estimation of forest inventory attributes has not been extensively researched and is not yet well understood. In this paper, we review the key similarities and differences between ALS data and image-based point clouds, summarize the results of current research related to the comparative use of these data for forest inventory attribute estimation, and highlight some outstanding research questions that should be addressed before any definitive recommendation can be made regarding the use of image-based point clouds for this application.

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Section: Image-based Point Cloudsmentioning

confidence: 99%

The Utility of Image-Based Point Clouds for Forest Inventory: A Comparison with Airborne Laser Scanning

White

Wulder

Vastaranta

et al. 2013

Forests

274

217

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“…For example, Canada's new National Forest Inventory is based on a 1% sample of the 401.9 million hectare of Canada's forests and other wooded lands (Gillis et al 2005). Aerial photography has played an important role in the development of forest inventories (Hall 2003), and more recently, light detection and ranging (LIDAR) instruments have emerged as useful tools for collecting vertical forest structure information (McRoberts and Tomppo 2007).…”

Section: Introductionmentioning

confidence: 99%

Implications of differing input data sources and approaches upon forest carbon stock estimation

Wulder

White

Stinson

et al. 2009

Environ Monit Assess

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Site index is an important forest inventory attribute that relates productivity and growth expectation of forests over time. In forest inventory programs, site index is used in conjunction with other forest inventory attributes (i.e., height, age) for the estimation of stand volume. In turn, stand volumes are used to estimate biomass (and biomass components) and enable conversion to carbon. In this research, we explore the implications and consequences of different estimates of site index on carbon stock characterization for a 2,500-ha Douglas-fir-dominated landscape located on Eastern Vancouver Island, British Columbia, Canada. We compared site index estimates from an existing forest inventory to estimates generated from a combination of forest inventory and light detection and ranging (LIDAR)-derived attributes and then examined the resultant differences in biomass estimates generated from a carbon budget model (Carbon Budget Model of the Canadian Forest Sector (CBM-CFS3)). Significant differences were found between the original and LIDAR-derived site indices for all species types and for the resulting 5-m site classes (p < 0.001). The LIDAR-derived site class was greater than the original site class for 42% of stands; however, 77% of stands were within ±1 site class of the original class. Differences in biomass estimates between the model scenarios were significant for both total stand biomass and biomass per hectare ( p < 0.001); differences for Douglas-fir-dominated stands (representing 85% of all stands) were not significant ( p = 0.288). Overall, the relationship between the two biomass estimates was strong (R 2 = 0.92, p < 0.001), suggesting that in certain circumstances, LIDAR may have a role to play in site index estimation and biomass mapping.

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“…Aerial photographs are the most frequently used source of information for forest inventory and mapping (Hall 2003), although more recently, high spatial resolution satellite imagery has emerged as a potential data source for forest inventory (Culvenor 2003). Advances in digital camera technology have also made digital aerial photography more widely available for forest inventory applications (McRoberts and Tomppo 2007).…”

Section: Introductionmentioning

confidence: 99%

“…Advances in digital camera technology have also made digital aerial photography more widely available for forest inventory applications (McRoberts and Tomppo 2007). Despite these advances, however, there currently exists no digital system that can match the spatial resolution, data storage, and hardcopy output capabilities of analog photo systems combined with film scanners (Hall 2003). Furthermore, image processing methodologies commonly applied to digital remotely sensed data are not directly transferable to digital air photos Pekkarinen 2004, 2005).…”

Section: Introductionmentioning

confidence: 99%

Towards automated segmentation of forest inventory polygons on high spatial resolution satellite imagery

Wulder¹,

White²,

Hay³

et al. 2008

The Forestry Chronicle

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High spatial resolution satellite imagery, with pixel sizes of one metre or less, are increasingly available. These data provide an accessible and flexible source of information for forest inventory purposes. In addition, the digital nature of these data provides an opportunity for automated and computer-assisted approaches for forest stand delineation to be considered. Specifically, automation has the potential to realize cost savings by minimizing the time required for manual delineation of forest stands; however, inappropriate automation could result in increased costs due to time-consuming revisions of automated delineations. The aim of this research is to present, through example, investigations of an automated segmentation approach for delineating homogeneous forest stands on high spatial resolution satellite imagery. An evaluation of the suitability of IKONOS 1-m panchromatic data for this application is also presented, along with several key issues that must be considered regarding automated segmentation approaches.Key words: forest inventory, segmentation, automation, IKONOS, high spatial resolution satellite, photo interpretation, stand delineation, object RÉSUMÉLes images par satellite à haute résolution spatiale, caractérisées par des espacements des pixels d'un mètre ou moins, sont de plus en plus disponibles. Ces données procurent une source de renseignements accessibles et souples aux fins d'inventaire forestier. De plus, la nature numérique de ces données offre la possibilité d' étudier diverses approches automatisées et assistées par ordinateur pour effectuer la délimitation des peuplements forestiers. L'automatisation a, plus particulière-ment, le potentiel de permettre de réaliser des économies en minimisant le temps nécessaire pour procéder à une délim-itation à la main des peuplements forestiers; cependant, une automatisation inadéquate pourrait se solder par une augmentation des coûts en raison de la quantité de temps considérable nécessaire pour effectuer les révisions des délimitations automatisées. L' objectif de cette recherche est de présenter, au moyen d'un exemple, les enquêtes réalisées sur une approche de segmentation automatisée en vue de la délimitation des peuplements forestiers homogènes sur des images par satellite à haute résolution spatiale. Ce document présente également une évaluation du caractère adéquat des données panchromatiques produites par IKONOS 1-m pour cette application, de même que plusieurs questions clés qui doivent être prises en considération relativement aux approches de segmentation automatisée.Mots clés : inventaire forestier, segmentation, automatisation, IKONOS, satellite à haute résolution spatiale, interprétation de photos, délimitation des peuplements, objet 1Canadian Forest Service (Pacific Forestry Centre), Natural Resources Canada, Victoria, British Columbia. 2 Corresponding author. 506 West Burnside Rd., Victoria, British Columbia V8Z 1M5.

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The Roles of Aerial Photographs in Forestry Remote Sensing Image Analysis

Cited by 28 publications

References 30 publications

The Utility of Image-Based Point Clouds for Forest Inventory: A Comparison with Airborne Laser Scanning

The Utility of Image-Based Point Clouds for Forest Inventory: A Comparison with Airborne Laser Scanning

Implications of differing input data sources and approaches upon forest carbon stock estimation

Towards automated segmentation of forest inventory polygons on high spatial resolution satellite imagery

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