Beside the demonstration of new technologies the Flying Laptop will use its payloads for earth observation application. The geometrical resolution of the cameras is comparable to the resolution of Landsat's Enhanced Thematic Mapper (ETM+), so that e.g. time series started by Landsat can be continued. This section will give further information about the different experiments in the field of remote sensing currently planned for the Flying Laptop.

Topics of special interest include:

The reflectance of most surfaces shows anisotropic behavior, which means the reflectance varies with solar and viewing positions. This effect is shown in the figure below and is mathematically described by the bi-directional reflectance distribution function (BRDF). For a scene with given properties it characterizes, how the reflectance observed varies with the angles of observation and illumination:

L is the radiance reflected into view directiondefined by the zenith angleand azimuth angle, E is the irradiance from the sun directionandthe wavelength of radiation. The dimension of the BRDF is given in sr-1. Commonly used is the bi-directional reflectance factor, which has no dimension.
In order to measure the BDRF, the Flying Laptop will take images of a specified target under different viewing angles in the target-pointing mode. The extension of the observed area should be noticeable larger than twice the maximum pixel size at the maximum viewing zenith angle. In addition the target is assumed to be homogeneous, hence large forests or desert areas are of interest for this kind of measurement.
Soil and vegetation normally show different reflectance characteristics. Generally, natural surfaces are rough. Soil consists of grains which are separated by pores containing water and gas. The reflectance properties of soils are attributed by the coherent scattering of the particles, by the incoherent radiative transfer propagation between the different particles and by the shadow hiding. The latter generates mainly the sharp peak in the bi-directional reflectance at zero phase angle, called hot spot or opposition effect. Vegetation exhibits anisotropic reflectance caused mainly by the very complex volumetric scattering within the leaves canopy and also shadow casting. For vegetated surfaces the composition of shadowed and illuminated components depends highly on the canopy architecture, which is affected by the type of plant species, the growing stage, and the health conditions.

Bi-directional reflectance effect of grass (source: University of Zurich).

The necessity of an angular correction of satellite data and the normalization to standard viewing and illumination conditions was the driving force of the experimental and theoretical investigation of the BRDF. The BRDF correction allows to compare different images and to improve the classification accuracy.
Despite the investigation of the BRDF in the multispectral region, the Flying Laptop will cary out the same measurement with the thermal infrared camera. Like the reflectance in the visible spectrum, the thermal radiance also depends on directional distribution. Mixtures of foliages and soil are thermally heterogeneous and the measured angular distribution of the surface brightness temperature depends on the viewing and the sun position. Our knowledge about the Temperature Directional Distribution (TDD), also called Directional Brightness Temperature (DBT), is still very poor. But this information is essential both for the data use of wide angle sensors and for a correct validation and calibration.

We will test a new method for precipitation measurement using the attenuation of the Ka- and Ku-band. Experiments have shown that the differential radio signal attenuation in a horizontal path through rain in thesetwo different frequency ranges is linearly dependent on the rain rate. It has been shown that a strong linear relationship between the rain rate and the differential attenuation of the Ku- and Ka-frequency bands exists. The acquisition of the data will be performed in the target pointing mode using a Ka-band and a Ku-band signal. The strength of the method analyzed in theoretical studies is the independence from the drop size distribution or other rainfall characteristics.
Today, networks of rain gauges and precipitation radars are utilized in meteorology for precipitation measurements. However, our knowledge on precipitation is still inadequate, especially over sea and in the mountains. Remote sensing of precipitation is widely used to obtain increased spatial and temporal accuracy.