Scaling problems in statistics
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| − | + | Our research focuses on the role of spatial scale in [[Forest Definition|forest definitions]] and [[Forest Boundary|forest edge]]. The widely used [[minimum crown cover]] criterion in forest definitions and its effects an [[estimating forest area|forest area]] estimation as a function of differently structured forests is investigated. Furthermore, the issue of scale in the context of data acquisition of Trees outside Forests (ToFs) is studied. Our goal is to improve and develop new methods to identify ToF resources from satellite images at different geometric, spatial and [[radiometric resolution]]s. In this context, various [[:category:plot design|response designs]] (point, line and area observations) at various scales are examined to improve ToF assessments. | |
[[Category:projects]] | [[Category:projects]] | ||
Latest revision as of 18:30, 7 December 2012
Project Title: Scaling issues in forest information procurement
- Funding: DFG Research training group, GRK 1644
- Duration: 2010-2013
- Coordination: Prof. Dr. Christoph Kleinn
- Project researcher: Philip Mundhenk
[edit] Background
Most activities in forestry are scale related, be it in management, policy processes, or research. While information for operational forest planning is needed on a stand level, strategic planning and policy formulation requires information on a national, regional or even global level. On each level data from various sources and thus, at different scales are used. Such information needs to be transparent, consistent, and methodically sound in order to serve as a reliable base for decision makers.
[edit] Project Goals
Our research focuses on the role of spatial scale in forest definitions and forest edge. The widely used minimum crown cover criterion in forest definitions and its effects an forest area estimation as a function of differently structured forests is investigated. Furthermore, the issue of scale in the context of data acquisition of Trees outside Forests (ToFs) is studied. Our goal is to improve and develop new methods to identify ToF resources from satellite images at different geometric, spatial and radiometric resolutions. In this context, various response designs (point, line and area observations) at various scales are examined to improve ToF assessments.
