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SPATIAL DATA INFRASTRUCTURE FOR
SOIL-VEGETATION-ATMOSPHERE MODELLING:
SET-UP OF A SPATIAL DATABASE FOR A RESEARCH PROJECT (SFB/TR32)
C. Curdt 3 ’*, D. Hoffmeister a , G. Waldhoff a , G. Bareth 3
a Dept. of Geography (GIS & RS), University of Cologne, Albertus-Magnus-Platz, 50923 Cologne, Germany -
(c.curdt, dirk.hoffmeister, guido.waldhoff, g.bareth)@uni-koeln.de
Working Group IV/1
KEY WORDS: Spatial Data Infrastructure, Data Management, Computer Vision, Interoperability, Environmental Monitoring,
Spatial Database, Internet GIS, Metadata
ABSTRACT:
Data storage and data exchange is a key issue of interdisciplinary research projects which focus on environmental field studies and
regional modelling. The overall success of such projects depends on the well organized data management and data exchange
between all involved sub-projects. This includes the organization of data, the implementation of a database for and the maintenance
of such a system for intensive data exchange between the project sections. The project database ensures the sustainable use of
collected measurement data and research results of long-term research projects. Especially, projects which focus on spatial
modelling of soil, vegetation and atmosphere interactions rely on data exchange of geo and attribute data. In this contribution, the
design and set up of a spatial data infrastructure for a research project (TR32) that focuses on soil-vegetation-atmosphere modelling
is presented. The introduced data management design enables web-based (i) up- and (ii) download of data, implementation of
different (iii) user views, interactive input of (iv) metadata and the integration of a (v) WebGIS.
1. INTRODUCTION
Spatial data management including data storage and data
exchange (between several project sections) is particular
important for interdisciplinary research projects which focus on
environmental field studies and regional modelling (Muckschel
and Nieschulze 2004). Especially Transregional Collaborative
Research Centers (TR) which focus on spatial data modelling
need a well organized data management. They are characterized
as research projects that are based at separate locations, operate
for up to 12 years and combine cross-disciplinary research
interests and material resources. Therefore, it is essential to
store and backup the multiplicity of different interdisciplinary
project data and the huge amount of data gathered during the
project phases in a well organized structure (Muckschel et al.
2007). These research'projects are funded by the German
Research Foundation (DFG) and have the requirement to
contain a project section (SP) that is responsible for data
management. The TR has the duties and responsibilities in
terms of ‘Good Scientific Practice’ to store, manage, maintain
and backup the whole research data in a permanent, sustainable
and stable system in cooperation with the local computing
center. Project data has to be stored during the project activities
and up to 10 years after the project is finished (DFG 1998).
In this context, we introduce the data management approach of
the inter- and multidisciplinary research project “Transregional
Collaborative Research Centre 32: Pattern in Soil-Vegetation-
Atmosphere Systems: Monitoring, Modelling, and Data
Assimilation” (TR32) funded by the DFG
(http://www.dfg.de/en/). The TR32 is a joint project between
the Universities of Aachen, Bonn, Cologne, and the Research
Centre Jiilich. Now the TR32 is situated in the second year of
the first of the three phases, each running for four years. The
research area of the TR32 is the watershed of the river Rur
which is situated in Western Germany and partly in Belgium
and the Netherlands. In the first phase, the field research is
focused on three sub watersheds that represent three typical
land use forms (forest, arable, and grass land).
The TR32 works on exchange processes between the soil,
vegetation, and the adjacent atmospheric boundary layer (SVA).
The overall project is subdivided into four project areas
(clusters). The clusters (A, B, C, and D) differ by the subsystem
(SVA) on which they concentrate and also by the spatial scale
range, they deal with (laboratory - region). The clusters are split
up into project sections. Within the whole TR32, 13 SPs work
on research. Furthermore, cluster overlapping cross-cutting-
groups were set up to arrange the exchange of information
between the clusters.
The overall research goal is to yield improved numerical SVA-
models for the prediction of water-, C0 2 - and energy-transfer
by accounting for the patterns occurring at various scales. The
hypothesis of the TR32 covers the explicit consideration of
patterns and structures which lead to a common methodological
framework. This will increase our understanding and our
capability of describing and predicting the SVA system in a
comprehensive manner. The research partners of the various
participating affiliations are from the fields of soil and plant
science, remote sensing, hydrology, meteorology, and
mathematics. They will approach the SVA continuum under
this new paradigm (TR32-Wiki 2007).
Corresponding author.
