S vector data
a next step as
| management.
ample. The N-
calculated for
g agricultural
er. etc.) The
nship is based
ind use classes
ons by law for
nes or special
ipplied for the
' Zones and the
yr!)
nang
ships
Kilometer
of N-fertilizer
Allgäu”
The result of the spatial and land use coupled N-fertilizer input
regionalization for the “Wiirttembergisches Allgäu” is shown in
Fig. 3. It is clearly visible that there is no large difference
between the townships, except for Tettnang (far Southwest),
which has a significant lower input due to comparable low
livestock numbers resulting in a comparable low N-input from
manure. The administrative border gives a strong spatial
footprint which is usually the case for administrative based
maps. The other townships are pasture dominated and the
amount of animals per land unit is also comparable. In general,
the area of arable land in the region is sparse which results in a
lower input of mineral fertilizer compared to arable land regions
like the “Kraichgau”. The latter is described in the next case
study.
3.2. Arable Land Region “Kraichgau”
The “Kraichgau” is located in Southern Germany in the North-
West of Baden-Wiirttemberg which is the South-Western state
of Germany. In the South-West of the “Kraichgau”, the Black
Forest and in the North the Odenwald are adjoining. In the west
the Rhine River and in the North-East the Neckar River frame
the study area. The “Kraichgau” is the second case study and
was investigated by Rohierse (2004) and Rohierse and Bareth
(2004).
For the MDA, four IRS-1C images were purchased for the years
2000 and 2001 and a multitemporal land use classification was
carried out (Rohierse and Bareth, 2004). In Fig. 4, the result of
the analyses is shown. It is clearly visible, that compared to the
land use map of the “Württembergisches Allgäu”, crop types
were identified. But the differentiation between winter cereals
and summer cereals was not satisfying. Therefore, all cereals are
generalized in one land use class.
Land Use “Kraichgau” 2001
Legend
LL] Townships Boundary Maize
Residentialindustrial HS Sugar Beet
Forest Cereal
Lakes
Garden/Sportsground 3 Pasture
Clover
Speci ü x 15 Kime
gero S uS e
Figure 4. Crop type map for the “Kraichgau” (Rohierse, 2004)
The generated crop type data is essential for improving the
regional disaggregation of N-fertilizer input data. The improved
method is presented in Fig. 5 and was developed by Rohierse
(2004) and Rohierse et al. (2002). As mentioned before, the
MDA produces disaggregated land use data which can be used
to link N-fertilizer input according to spatial-based rules. The
spatial-based rules assume that the farmers' management is
carried out according to good practice. This includes avoiding
over-fertilization and satisfying laws regulating management in
protection or special management zones. The advantage of this
more detailed approach is the loss of the footprint of
administrative units. The latter is visualized in Fig. 6, 7, and 8.
N-input
Distribution
according to
good practise
Base Multi-Data Final
Geodata Approach Land Use
Generated
Geodatabase
regionalization
* satellite data implementation of
* ATKIS data agricultural statistics
* soil map
* DEM
Figure 5. MDA for the “Kraichgau” (Rohierse, 2004)
In Fig. 6 and Fig. 7, the MDA-based spatially disaggregated N-
input from animal waste and mineral fertilizer are displayed.
While the animal waste map still shows clearly administrative
units, the mineral fertilizer map does not. The latter is caused by
the distribution of N according to good practice in dependence
of crop type. The N-input was spatially distributed according to
N-removal and soil-N availability. Additionally, protection
areas were considered as before for the “Wiirttembergisches
Allgáu". The strong administrative footprint of the animal waste
in Fig. 6 is caused by the data source, the livestock numbers per
administrative unit.
Arable Land Region “Kraichgau™
Legend
ii Township Border
Animal Waste-N Fertilization
UO: wenplow
N
9m 1& Kamat
‚EEE
Figure 6. Animal waste N-input (Rohierse, 2004)
A
A 30 76 Wives
KEN
Figure 7. Mineral N-input (Rohierse, 2004)