Automated predictive ecological mapping in a Forest Region of B.C., Canada, 2001–2005

MacMillan, R.A.; Moon, David E.; Coupé, R.A.

doi:10.1016/j.geoderma.2007.04.027

Cited by 62 publications

(34 citation statements)

References 26 publications

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“…In forestry applications, these techniques have been developed and applied with success in British Columbia, where ecological site types in the Biogeoclimatic Ecosystem Classification (BEC) have been predicted using knowledge-based routines for automated polygon extraction and classification (MacMillan et al 2007). These approaches have been reported to provide accurate and cost-effective tools for stratifying forest landscapes (MacMillan et al 2007). Furthermore, these approaches have been transferred to Ontario, where knowledge-based methods were used to develop a predictive ecosystem map for the Romeo Malette Forest unit near Timmins, Ontario (Silvatech Group 2006).…”

Section: Ecosite Mapping and The Link To Landscape-level Productivitymentioning

confidence: 99%

“…Many recent studies have focused on the expansion or enhancement of forest resource inventories through techniques such as individual tree classification (Gobakken andNaesset 2004, Hyyppä et al 2004), analysis of airborne LiDAR (Light Detection And Ranging) data (Lefsky et al 1999, Woods et al 2009) and imputation of missing data through model-based approaches (Van Deusen 1997, Eskelson et al 2009). In addition, better baseline data and new analysis techniques are facilitating the inclusion of ecological site classification data in forest inventories (MacMillan et al 2007). This creates the opportunity to analyze and manage forests through stratification into ecologically relevant entities (e.g., ecosites) rather than coarse-scale polygons that may incorporate multiple site conditions (Grumbine 1994).…”

Section: Introductionmentioning

confidence: 99%

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An ecological land classification approach to modeling the production of forest biomass

Pokharel¹,

Dech²

2011

The Forestry Chronicle

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Forest site classification is a prerequisite to successful integrated forest resources planning and management. Traditionally, site classification has emphasized a phytocentric approach, with tools such as the site index having a rich and long history in forest site evaluation. The concept of site index was primarily devised to assess site productivity of an even-aged, single-species stand. Site index has been the primary method of forest site evaluation in support of management for traditional forest products. However, this method of site classification has been criticized as the needs, perspectives and social values of the public regarding forest management have changed the emphasis from timber production to multiplevalue forestry practices. There are alternative approaches to forest site classification that have the potential to meet the growing demands placed on forest information for inventory and modeling purposes. Ecological Land Classification (ELC), is a phytogeocentric approach that stratifies the landscape into ecologically meaningful units (ecosites) based on substrate characteristics, moisture regime and canopy composition. This approach offers a more holistic view of site productivity evaluation; however, until recently it has been difficult to acquire data to support widespread mapping of ecosites. Remote sensing technology along with predictive modeling and interpretive mapping techniques make the application of an ecosite-based approach at the forest landscape level possible. As forest management moves towards the consideration of a broader set of resources (e.g., woody biomass), there is an opportunity to develop new tools for linking forest productivity to the sustainable production of forest bioproducts with forest ecosites as a solid foundation for segmenting the landscape.Key words: forest site classification, site index, site productivity, Ecological Land Classification (ELC), ecosites, forest biomass, bioproducts RÉSUMÉLa classification des sites forestiers est un pré-requis au succès de la planification et de l'aménagement des ressources forestières. Habituellement, la classification des sites a mise en évidence une approche phytocentrique, comptant sur des outils comme l'indice de qualité de la station qui affiche un historique riche et durable de l' évaluation des sites forestiers. Le concept d'indice de la qualité de station a été établi principalement pour évaluer la productivité de la station dans le cas d'un peuplement équienne composé d'une seule espèce. L'indice de la qualité de station a été la principale méthode d' éva-luation d'un site forestier utilisée dans le cas de l'aménagement pour les produits forestiers traditionnels. Cependant, cette méthode de classification du site a fait l' objet de critiques compte tenu que les besoins, les perspectives et les valeurs sociales du public relativement à l'aménagement forestier ont réorienté l'accent mis sur la production de bois vers des pratiques forestières considérant les multiples valeurs du milieu. Il existe des approch...

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Section: Ecosite Mapping and The Link To Landscape-level Productivitymentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

An ecological land classification approach to modeling the production of forest biomass

Pokharel¹,

Dech²

2011

The Forestry Chronicle

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“…It overcomes a limitation of the conventional soil mapping approach, as raised by Hudson (1992), which fails to highlight the soil surveyor mental model. Because this approach requires an understanding from a soil scientist's perspective of the repeating soil patterns on the landscape, as does the conventional mapping approach, it is considered to be a knowledge-driven digital soil mapping approach and it has been regarded as efficient and economical (Hudson, 1992;MacMillan et al, 2007).…”

Section: Introductionmentioning

confidence: 99%

Solum depth spatial prediction comparing conventional with knowledge-based digital soil mapping approaches

Menezes

Silva

Mello

et al. 2014

Sci. agric. (Piracicaba, Braz.)

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Solum depth and its spatial distribution play an important role in different types of environmental studies. Several approaches have been used for fitting quantitative relationships between soil properties and their environment in order to predict them spatially. This work aimed to present the steps required for solum depth spatial prediction from knowledge-based digital soil mapping, comparing the prediction to the conventional soil mapping approach through field validation, in a watershed located at Mantiqueira Range region, in the state of Minas Gerais, Brazil. Conventional soil mapping had aerial photo-interpretation as a basis. The knowledgebased digital soil mapping applied fuzzy logic and similarity vectors in an expert system. The knowledge-based digital soil mapping approach showed the advantages over the conventional soil mapping approach by applying the field expert-knowledge in order to enhance the quality of final results, predicting solum depth with suited accuracy in a continuous way, making the soillandscape relationship explicit.

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“…Although DSM has not yet been applied to state mapping, it could fill a much needed gap by increasing automation, using a greater range of data sources, and allowing for rapid updating of state maps when new data become available. Data-driven classification algorithms can greatly reduce the time needed to produce state maps because they provide a means of grouping pixels into similar units, thereby reducing the burden of hand digitizing (Laliberte 2007;MacMillan et al 2007). DSM approaches can also be scaled up or down to meet desired management objectives, which is currently difficult to do with polygon-based maps.…”

Section: Mapping State-and-transition Model Informationmentioning

confidence: 99%

State and Transition Models: Theory, Applications, and Challenges

et al. 2017

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State and transition models (STMs) are used to organize and communicate information regarding ecosystem change, especially the implications for management. The fundamental premise that rangelands can exhibit multiple states is now widely accepted and has deeply pervaded management thinking, even in the absence of formal STM development. The current application of STMs for management, however, has been limited by both the science and the ability of institutions to develop and use STMs. In this chapter, we provide a comprehensive and contemporary overview of STM concepts and applications at a global level. We first review the ecological concepts underlying STMs with the goal of bridging STMs to recent theoretical developments in ecology. We then provide a synthesis of the history of

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Automated predictive ecological mapping in a Forest Region of B.C., Canada, 2001–2005

Cited by 62 publications

References 26 publications

An ecological land classification approach to modeling the production of forest biomass

An ecological land classification approach to modeling the production of forest biomass

Solum depth spatial prediction comparing conventional with knowledge-based digital soil mapping approaches

State and Transition Models: Theory, Applications, and Challenges

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