At least in the visible and near infrared spectral region the basic principles about the bi-directional reflectance distribution function (BRDF) have achieved an advanced state. This basic knowledge has been summarized by international well known scientists and firstly published in a book. A CD-ROM data base is attached to the book. For this paper these data have been used for a very first statistical synopsis. The measurement results of different scientists for similar targets and similar geometric conditions differ partly to a great extent. Hence mean values and variances cannot presently be used to describe the BRDF of different surfaces. The anisotropy factor defined by Sandmeier seems appropriate to be used in some investigations. The data sets are not sufficient for serious statistical analyses. Further measurements are essential to overcome the gap from examples to confidential statistical evaluations.
In the last section the measurement methods planned by the University of Stuttgart for a ground measuring device and by target pointing of a small satellite are discussed.
Remote sensing instruments of the present and future generations include a variety of multi-angular off-nadir measuring facilities. In order to fully exploit their possibilities a thorough understanding of the anisotropic angular reflection properties of terrestrial surfaces is required. These are generally quantified in terms of the bi-directional reflectance distribution function (BRDF). We report on near infrared BRDF measurements of various vegetative surfaces including several crops performed with a CCD camera. While many of the investigated vegetation types show a rather similar reflection behavior, there are also distinct differences observed in some cases. For a quantitative analysis of the results we introduce several statistical measures which describe the characteristic properties of the reflectance distribution. We use these parameters as the input for an unsupervised cluster analysis algorithm. As a result the method provides suggestions for grouping different vegetation types into classes according to their angular reflection properties. This is helpful for evaluating which properties of the plants or the plant canopy structure cause recognizable reflectance features. The results can therefore be used to develop adapted observation strategies for the retrieval of biophysical parameters in agricultural or environmental studies.
The interpretation of the reflected radiation measured by wide angle instruments or in off-nadir directions requires the knowledge of the bi-directional reflectance distribution function (BRDF). By using atmospheric radiative transfer calculations we demonstrate how several vegetation indices are influenced by the BRDF and by the atmosphere. We present two methods to retrieve the leaf area index (LAI) using bi-directional reflectance factors in the near infrared spectral domain. Firstly we use a newly defined Off-Nadir Vegetation Index (ONVI) and a multiple regression analysis. The method was tested on a synthetic data set with a LAI varying between 0 and 10. We achieved a root mean square error of 1.54. Secondly we trained a neural network with synthetic data computed with the BRDF model of Roujean et aL Using observations in backward scattering direction the root mean square error for LAI retrieval was 1.2. To obtain more comprehensive information on the characteristic and stochastic properties of the BRDF a new measuring method was developed. It employs a rotating CCD-line camera mounted on an extendible boom. The data of our field campaigns together with the measurements performed by other groups are arranged in a BRDF catalog.
Joint development work by DLR and LH Systems has produced a new camera concept called Airborne Digital Sensor which is using forward-, nadir- and backward-looking linear arrays on the focal plane. The camera system provides panchromatic and stereo information using three CCD lines and up to five more lines for multispectral imagery including two NIR channels. Each CCD array for panchromatic measurements has 24000 elements, resulting in a field of view of 64 degrees (across track FOV) by using a focal length of 62.5 mm. The sensitivity covers a dynamic range of 12 bit with a recording interval time of 1.2 ms per line. The performance of the camera allows a 3D and multispectral image with a ground sample distance of 25 cm for an area of 300 square miles within a flight time shorter than one hour.
Soil moisture plays a key role in the hydrological cycle. Because of its heterogeneous distribution satellite measurements can be favorable for arriving at mean areal values. For bare soil such values of soil moisture can be derived from active microwave measurements. However a commonly recognized method for estimating soil moisture under vegetation using remote sensing data does not exist at present. Carlson proposed a method to estimate soil moisture of the upper layer under the vegetation. This method involves using VIS-, NIR-, and TIR data and simulations of a Soil- Vegetation-Atmosphere-Transfer (SVAT)-model. The original method is enhanced and tested in theory and practical application. Comparison of derived soil moisture with field measurements shows good agreement. It is shown that microwave measurements can be included in the analysis in a meaningful way.
Hydrophilic silicon phthalocyanines derivatives with diaxial polyethyleneglycolmonomethylether ligand with different chain lengths were synthesized. Water soluble SiPc(OmPEG 5000)2 shows a completely monomeric UV/VIS spectrum in water. No influence of the ligand's chain length on photophysical properties, e.g., singlet oxygen quantum yield was found. First aspects of the photosensitizing properties were gained by photohemolyse experiments with human erythrocytes. SiPc(OmPEG 5000)2 is far more active than other water soluble phthalocyanines which are aggregated in water.
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