The maintenance of a timely, reliable and accurate spatial database on current forest ecosystem conditions and changes is essential to characterize and assess forest resources and support sustainable forest management. Information for such a database can be obtained only through a continuous forest inventory. The National Forest Continuous Inventory (NFCI) is the first level of China’s three-tiered inventory system. The NFCI is administered by the State Forestry Administration; data are acquired by five inventory institutions around the country. Several important components of the database include land type, forest classification and ageclass/ age-group. The NFCI database in China is constructed based on 5-year inventory periods, resulting in some of the data not being timely when reports are issued. To address this problem, a forest growth simulation model has been developed to update the database for years between the periodic inventories. In order to aid in forest plan design and management, a three-dimensional virtual reality system of forest landscapes for selected units in the database (compartment or sub-compartment) has also been developed based on Virtual Reality Modeling Language. In addition, a transparent internet publishing system for a spatial database based on open source WebGIS (UMN Map Server) has been designed and utilized to enhance public understanding and encourage free participation of interested parties in the development, implementation, and planning of sustainable forest management.

Application of China’s National Forest Continuous Inventory Database

Most of the largest databases currently available have a strong geospatial component and contain potentially useful information which might be of value. The discipline concerned with extracting thi ...

/pdf/data-mining-of-geospatial-data-combining-visual-and-1iqbaun0ze.pdf

Data mining of geospatial data: combining visual and automatic methods

The data storage and analysis system of the Swiss National Forest Inventory

The categorization of our environment into feature types is an essential prerequisite for cartography, geographic information retrieval, routing applications, spatial decision support systems, and data sharing in general. However, there is no a priori conceptualization of the world and the creation of features and types is an act of cognition. Humans conceptualize their environment based on multiple criteria such as their cultural background, knowledge, motivation, and particularly by space and time. Sharing and making these conceptualizations explicit in a formal, unambiguous way is at the core of semantic interoperability. One way to cope with semantic heterogeneities is by standardization, i.e., by agreeing on a shared conceptualization. This bears the danger of losing local diversity. In contrast, this work proposes the use of microtheories for Spatial Data Infrastructures, such as INSPIRE, to account for the diversity of local conceptualizations while maintaining their semantic interoperability at a global level. We introduce a novel methodology to structure ontologies by spatial and temporal aspects, in our case administrative boundaries, which reflect variations in feature conceptualization. A local, bottom-up approach, based on non-standard inference, is used to compute global feature definitions which are neither too broad nor too specific. Using different conceptualizations of rivers and other geographic feature types, we demonstrate how the present approach can improve the INSPIRE data model and ease its adoption by European member states.

/pdf/microtheories-for-spatial-data-infrastructures-accounting-22o42va08j.pdf

Microtheories for spatial data infrastructures - accounting for diversity of local conceptualizations at a global level

University of Greenwich, UK. k.rennolls@gre.ac.uk Technical University of Lisbon, Portugal. magatome@isa.utl.pt USDA Forest Service, St. Paul, USA. rmcroberts@fs.fed.us Southern Cross University, Australia. JVanclay@scu.edu.au University of British Columbia, Vancouver, Canada. Valerie.LeMay@ubc.ca National Taiwan University, Taipei, Taiwan. btguan@ntu.edu.tw University of Illinois, Urbana, USA. gertner@uiuc.edu

Potential contributions of statistics and modelling to sustainable forest management: review and synthesis.

The European Forest Information System-an Internet based interface between information providers and the user community

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The European Forest Information System-an Internet based interface between information providers and the user community