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mined in cooperation between the Russian and German part-
ners, all in the Siberian corn belt to the South East of the city of
Tyumen (fig. 6), named according to populated places nearby.
Figure 6 Localization of SASCHA test sites (Western Siberia)
(left: Kaskara, middle: Omutinsky, right: Ishin)
id
24.2 Monitoring of Changes in Agriculture, Biodiversity
and Carbon Stocks for Landscape Planning: The second
project phase is dedicated to the implementation of monitoring
tools for a wise and sustainable future land use in the region. As
already identified by relevant European directives such as
INSPIRE (Infrastructure for Spatial Information in Europe),
Water-framework directive, and Habitat directive, land use and
land cover (LULC) datasets are an indispensible prerequisite
for the support of stakeholders in environmental policy.
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences, Volume XXXIX-B8, 2012
XXII ISPRS Congress, 25 August — 01 September 2012, Melbourne, Australia
^ un e E
/ X
i j : Project
Monitoring i Subprojects ; {Output & Local
| Implementation
{ Hydrclogy & Madellina | |
{ Climatology & GHG-fluxes | |
Land Use ! i S ;
Land Cover [. Agricultural Management 4 indie
from
{ Biodiversity & Carbon Stocks | & Adaption
Strategies to
i Climate
| Landscape Planning | ; Change
| i Institutians, Property Rights... 1 ;
meses : iJ e.
Figure 7 Acquisition of land use changes with
remote sensing data in the SASCHA project
Derived from this experience, the efficient collection of reliable
up-to-date LULC data is one major issue in the context of the
development and implementation of a sustainable land
management system for the pilot region, theTyumen Oblast.
Figure 7 depicts the interoperability of the monitoring system
With the planned project results, and the potential for local
implementation through the different approaches of the
subprojects, all serving the achievement of the common results
(cf. Voelker 2011).
The SASCHA subproject ‘Analysis and Monitoring of Land
Cover and current Land-Use Change’ has started to develop,
evaluate and implement a prototype system for the extraction of
LULC information from remote sensing images. A core issue is
the development of change detection methods and the
implementation of adequate image analysis algorithms,
especially for agricultural LULC changes, such as the
expansion and intensification of arable land. The system adapts
existing technologies from the Global Monitoring for
Environment and Security (GMES) initiative to region-specific
LULC classes and aims to enable a (semi-)automatic detection
and quantification of future LULC changes with a software
interface that is user-friendly and easy to use: the ALIS ©
interface (cf. fig. 2). The system development will be driven by
user needs collected from stakeholders of the Oblast’s
Departments for Environmental Protection and Agriculture.
Figure 8 Change detection of agricultural land use in the
SASCHA test site of Omutinsky (Tillmann 2012)
To monitor the assumed northward shift of agriculture the tech-
nique of remote sensing is considered to be appropriate to the
large extend of agricultural schemes in Western Siberia. The
first results of the ongoing project are taken from Tillmann
2012 using available archive data from 1987 and 2009 of the
Landsat satellites (cf. fig. 8). The land use changes give evi-
dence to a considerable increase of agricultural use and rela-
tively few abandoned sites. Detailed investigations have started
and will include additional parameters from the other subpro-
jects in order to detect driving factors for the spatial changes.
Only with a reliable spatial analysis of the current threats and
factors for change will it be possible to develop sustainable land
use practices and promising adaption strategies to environ-
mental changes, in cooperation with the regional authorities and
stakeholders.
2.5 Advances in Remote Sensing Methods and Potentials
for Transfer
Advances in remote sensing from related research have been
used, improved and incorporated in operational processing
chains. The related investigations on this topic from Calvet
2010, Listner 2011 and Mariotto 2011 have been reflected to
improve the own knowledge based methodologies, when devel-
oping the ALIS © interface, which serves already in different
working environments. The close cooperation of universities,
R&D companies and administrative users has lead to stable
