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Airborne hyperspectral remote sensing enables not only spatial monitoring of vegetation cover, but also the derivation of individual plant constituents such as chlorophyll and nitrogen content. These are important parameters for optimised agricultural management on a field basis through the possibility of spatially differentiated fertilisation and for hydrological and vegetation yield modelling. The use of existing airborne imaging spectrometers is cost-intensive. Moreover, it is difficult to obtain these sensors for multitemporal applications. The imaging spectrometer AVIS (Airborne Visible/Near Infrared Imaging Spectrometer) was built at the Chair of Geography and Geographical Remote Sensing of the Ludwig Maximilians University Munich, Germany, to overcome these difficulties. AVIS is designed as a cost-effective tool for environmental monitoring using commonly available components. AVIS enables the deployment of a hyperspectral sensor for both scientific research and educational purposes. It is based on a direct sight spectrograph coupled to a standard B/W CCD camera. The signal received by the CCD is read out and sent via a frame grabber card to a personal computer, where the data is stored on the hard disc together with additional GPS data. The radiometric, spectral and geometric properties of AVIS resulting from the calibration procedure are summarised in Table 7-1. Table 7-1: AVIS characteristics Parameter Description Spectral range 553-999nm Spectral resolution 6nm Spectral sampling rate / resampling 2nm / 6nm Number of used bands 74 SNR 45dB (year 1999), 47dB (year 2000) Spatial resolution 300 pixels per image line Spatial sampling rate 390 pixels per image line FOV 1.19rad IFOV across track 3.1mrad IFOV along track 2.98mrad One aim of this thesis was to test the potential of AVIS for the purpose of environmental monitoring, especially of the chlorophyll and nitrogen status of plants. The land cover types under investigation were grassland, maize ( Zea mays L.) and winter wheat ( Triticum aestivum L.). Within this scope, a total of 21 AVIS flights were carried out during the vegetation periods of the years 1999 and 2000. The AVIS data were preprocessed before analysis, including dark current and flat field correction, resampling as well as atmospheric correction and reflectance calibration. The test area chosen for the validation of the AVIS data is located in the northern Bavarian foothills, 25km southwest of Munich, Germany (48° 6’ N, 11° 17’ E). It is situated between the Ammersee in the west and the Starnberger See in the east. The municipalities Gilching and Andechs define the northern and southern borders respectively. Within this area, three water protection areas were chosen as test sites. In these test sites, most of the farmers are under contract to the local agricultural office “ Amt für Landwirtschaft” resulting in detailed management data for each field. This data include useful information for the interpretation of ground and AVIS data. Two weather stations of the Bavarian network of agro-meteorological stations, namely No.72 (Gut Hüll) and No.80 (Rothenfeld), are located in the test area and provide information about precipitation, temperature and radiation. Ten and thirteen stands were selected as test fields in 1999 and 2000 respectively, including three fields each of maize and wheat in 1999 as well as three fields of maize and six fields of wheat in 2000. During both years, four meadows were investigated belonging to the same plant community ( Arrhenatherion elatioris). The meadows differ in the utilisation intensity (non-fertilised meadow with one cut, meadow with one cut, meadow with rotational grazing and meadow with four to five cuts). The ground truth campaigns included weekly measurements of plant parameters, such as height, dry and wet biomass, phenological stage, chlorophyll and nitrogen content, as well as a photographic documentation for each field. The chlorophyll and nitrogen measurements, which were derived from the sampling on ground, are available in contents per area [g/m²] and in contents per mass ([mg/g] for chlorophyll and [%DM] for nitrogen). The former can be used to evaluate the photosynthetic capacity or productivity of a canopy, which is an important input parameter for hydrological or vegetation models; the latter may be an indicator for plant physiological status or level of stress, which is a valuable source of information for optimising field management. The relationship between chlorophyll and nitrogen based on the ground measurements showed that a differentiation of the land cover types is necessary for significant correlation. When the plant species are investigated separately, the chlorophyll and nitrogen content per area are always highly correlated, especially for chlorophyll a and total chlorophyll content (r²≥0.8). For all investigated land cover types, the nitrogen and chlorophyll contents per mass are uncorrelated. For wheat, the results improve when the phenological state and the cultivar are considered (r²>0.67). For maize, distinct variations in the chlorophyll content per mass during the vegetation period reduced correlation with these parameters. The use of a fitted chlorophyll trend curve instead of the original measurements does not lead to a significant improvement of the results. For grassland, no significant correlation above r²=0.67 could be observed except for chlorophyll and nitrogen, both per area, where a decreasing strength of correlation could be monitored with increasing fertilisation level. These results lead to the conclusion that the chlorophyll and nitrogen contents per mass of the investigated land covers are decoupled when the compensation point for effective photosynthesis is exceeded. Beyond this limit the nitrogen in the plants is no longer incorporated into chlorophylls, but mainly into proteins, alkaloids and nucleic acids, whereas the proteins especially are used for internal storage of nitrogen. The derivation of the chlorophyll and nitrogen content of the plant leaves on a mean field basis was conducted using three hyperspectral spectral approaches, namely the hyperspectral NDVI (hNDVI), the Optimised Soil Adjusted Vegetation Index OSAVI as well as the relatively unknown Chlorophyll Absorption Integral CAI. The multispectral NDVITM was simulated as established reference. The results of the derivation of both chlorophyll and nitrogen content of plants with the investigated approaches depend strongly on a priori knowledge about the canopies monitored. In general, the use of contents per area rather than contents per mass has been found more suitable for the investigated remote sensing applications. A significant correlation between any index and the chlorophyll or nitrogen content for the whole sample size could not be derived. The optimal spectral approach for derivation is species-dependent, but also dependent on the cultivar. The chlorophyll and nitrogen level of the plants under observation as well as their temperature sensitivity mainly caused this dependence. The NDVITM, hNDVI and OSAVI became insensitive for high chlorophyll content above about 1g/m² (1.5mg/g) chlorophyll a and 0.2g/m² (0.4mg/g) chlorophyll b, respectively. A saturation of the indices was also found for nitrogen content above 2.5g/m². The saturation limit of nitrogen in percentage of dry matter could be rated at about 4%. The positive correlation between the indices and this parameter for wheat leads to insensitivity at values above this limit, while the negative correlation for maize results in saturation for values below 2.5%. The CAI is not affected by saturation as much as the other spectral approaches, leading to higher coefficients of determination, especially for contents per area. The CAI becomes insensitive at chlorophyll contents per area above 2g/m². The results lead to the assumption, that the flattening and narrowing of the chlorophyll absorption feature at 680nm most probably causes the saturation of the NDVITM, hNDVI and OSAVI. The ratios are directly affected by an increase in reflectance in the red wavelength region. The high correlations between the CAI and contents per area can be ascribed to the fact that the CAI is based on an integrated measurement over an area and therefore is less affected by an increase of reflectance in the red wavelengths. The CAI probably becomes insensitive at the point where the narrowing of the absorption feature leads to a shift of the red edge position towards the blue wavelength region. This saturation limit lies at approximately 2g chlorophyll per m². In contrast, the chlorophyll content per mass, which indicates the plant’s physiological status or level of stress, could be estimated more accurately using spectral indices such as hNDVI and OSAVI, especially for wheat. The low correlations derived for maize are caused by its higher temperature dependence, leading to daily variations in the chlorophyll content per mass. The chlorophyll and nitrogen contents of the grassland canopies could not be derived with the spectral approaches investigated. When the meadows were investigated separately, correlations could only be found between the CAI and the chlorophyll content per area for the most intensely utilised meadow (four to five cuts), which on the one side is characterised by the highest level of fertilisation, but on the other side is affected by the highest nutrient offtake. The low potential of the investigated indices can be mainly assigned to the fact that the chlorophyll and nitrogen values of the meadows mostly exceeded the saturation limits of the applied indices. The possibility of deriving chlorophyll and nitrogen accurately enough to map within field heterogeneities was discussed on the basis of a wheat field, which was analysed separately at three sampling points for chlorophyll and nitrogen content. The approaches found to be most suitable for the parameter estimation of wheat were applied. The CAI was used for the estimation of the chlorophyll content per area and mass as well as for the nitrogen content per area. The hNDVI was applied to estimate the canopy’s nitrogen content per mass. Both approaches were able to reproduce the chlorophyll contents of the different sampling points accurately enough to derive the differences between the measurement points when the saturation limits were not exceeded. Beyond these limits the index values decreased with increasing measurement values. The spatial pattern of the nutrient supply was discussed by comparing nitrogen pattern images, which were derived from CAI measurements acquired in 2000 with the yield measurement map of the same field. The phenological stage of stem elongation (EC 30) turned out to be most suitable for the derivation of the nitrogen pattern. On the one hand, the crop condition at these stages determine yield and on the other hand the nitrogen pattern images were able to map the inner field patterns of nitrogen supply. After anthesis the nitrogen images can map areas with different degrees of maturity. Therefore they can be used for the monitoring of maturity stages for the determination of the most favourable harvest date. As described here, AVIS is still in its early stages. It has the potential to become a costeffectiveAVIS2, which covers the spectral range of 400-900nm, has been in commercial use since 2001. tool for the monitoring of the environment. A modification of AVIS, namely