Precision farming using GIS to improve Soil variability



INTRODUCTION
For the part of precision farming as a productive tool, but environmentally friendly agriculture, in addition to current state surveys on Plant population, above all, the local site characteristics required (mapping Approach). At the field scale, this means the knowledge of Pedotopmusters. Past maps such as bottom estimate or mittelmabstabige soil maps (1:25,000), these not provide high spatial resolution information. Is the basic idea of our approach
collection of planar podenrelevanter information? The creation of a soil or Map this location does not require any interpolations, as in the transmission of (Drilling) point information are essential in the area. Rather, only the determine soil science content of designated sub-areas (holes).
Soil variability on all scales can be used in a predictable and a random Share split (HALL & Olson, 1991; SUMMER & SCHLICHTINO, 1997). The predictable Part is controlled by the soil-forming factors (Jenny, 1941; BIRKELAND, 1999). At Knowledge of the factors and their spatial variability of the properties of soils in the room with a blow to the divisional management sufficient accuracy be predicted. Under the terms of the 'tertiary hill country' should include four Pedotopmuster factors in the experimental farm and the wider catchment area of control: Starting material, relief, hydrological conditions and human activity.

A quantitative analysis of relief units and properties is done with the
"Automatic system for terrain analysis" (SARA) on the basis of DEM 5 (Kleefisch & KOTHE, 1993). SUMMER & Murschel (1999) have already succeeded in creating a forecast colluvial soils in a loess landscape using terrain analysis. Based on an elevation model (DHM 50) they succeeded in getting about 70% of Kolluvisols alluvial soils, and spatial accuracy with the help of Terrain analysis to predict. Since the resolution in the FAM-study area significantly higher (DHM is 5), are also significantly more accurate forecasts possible. Thus, there is adistinction founded hope, hill slopes, knolls and parietal areas further. An impression of the possible relief of differentiation provides Fig.1. The relationship between the relief features or units and soil types to develop by local expertise. Thus, for example, steep, convex relief elementsa stronger result in soil erosion and thus have less well-developed soil on. On the other hand used for agricultural purposes, converged landscape elements are by Sedimentation and thus Kolluvien characterized. From the terrain analysis can therefore corresponding differences in water and nutrient balances shown on the field scale will

Figure 1: Relief with SARA analysis based on a DEM 5, Metoki Scheyern, and dark gray: concave
Landscape elements (convergent flow, light gray: convex landscape elements) (divergent flow).


Fig.2: Daedalusaufnahme a stroke A5 (in the monastery Scheyern winter wheat, 11.7.95, channels 3, 5, 6); dark areas = low reflections = higher biomass

n addition, previous work in the FAM promising indications have shown that remote sensing of vegetation cover (bio-indication) Site characteristics can be mapped surface wise and high resolution (LENZ ETAL., 1997): soils with low water storage show low biomass and a chronologically earlier water stress during drought. This is v.a. for culture" Winter Wheat". The water storage capacity is essentially determined by the Substrate structure determined. Scanner images of winter wheat (and grassland) are used to the spatial mapping of the factor 'substrate'. Differences in the substrate structure result in the remote sensing images to patterns at the field scale (see Fig.2).
Local is a calibration of remote sensing data (gray values of individual Spectral regions) with vegetation parameters (eg, above-ground biomass).For operational use of remote sensing are both methods to derive
the land surface parameters from remote sensing data as well as customized math Develop methods for image analysis (see the article by KURZ ET AL.) This band. The found links between relief, vegetation and soils are in a Rules as "if-then" conditions "entered. Further investigationse.g. geophysical surveys (EM 38) or GIS information anthropogenic interference (gravel, clay mining, management, history, complementary, etc.), the Rules. Holes in the Experimental Farm and the wider catchment area to serve the Calibration and validation of the rules and regulations. Final product for the user, its high-resolution digital map of the floor and location of units.

Literature
BIRKELAND, P. (1999): Soils and Geomorphology. Oxford University Press, Oxford.
HALL, G.F.; OLSON, C.G. (1991): Predicting variability of soils from landscape models. Chapter 2., P.9-24. In: M.J. Mausbach & L.P. Wilding (Ed): Spatial variabilities of soils and landforms. SSSA Spec. Publ. 28, Madison, WI.
JENNY, H. (1941): Factors of Soil Formation. McGraw Hill, New York. Kleefisch, B.; KOTHE, R. (1993): Pathways to the computerized interpretation of digitalRelief data. Geol Jb, F 27: 59-122.
SHORT, F.; EHRICH, S.; HINZ, S. (2000): Possibilities and limitations of vision in the characterization of heterogeneity of vegetation using remote sensing methods.
GIL-Tagung 2000, this volume. LENZ, R.; BLESSED, T; TRACKED Strauch, J.; Wehrhan, M. (1997): Characterization of Site characteristics using remote sensing methods. FAM Annual Report 1997: 157 --167.
SOMMER, M.; Murschel, B. (1999): Erosion and Nährstoffabtrag. In: Dabbert, S., Herrmann, S., Kaul, G., Sommer, M.: Landscape Modeling for environmental planning. P.68-79. Springer Verlag, Berlin. SOMMER, M.; SCHLICHTINO, E. (1997): Archetypes of Catena in respect to matter - a conceptfor structuring and grouping Catenas. Geoderma 76: 1-33.

ABSTRACT
Precision farming is now having an impact on agriculture throughout the world. It is clear that the underlying principles remain the same but the implementation changes between crops and countries. This paper sets out to identify the underlying principles of Precision Farming to enable researchers and practitioners to adapt them for their own conditions.