Hyperspectral remotely sensed data are useful for studying ecosystem processes and patterns. However, spatial characterization of such remotely sensed images is needed to optimize sampling procedures and address scaling issues. We have investigated spatial scaling in ground-based and airborne hyperspectral data for canopyto watershed-level ecosystem studies of southern California chaparral and ...

Regionalization is to divide a set of spatial objects into a number of spatially contiguous regions while optimizing an objective function, which is usually a homogeneity (or etereogenity) measure of the derived regions. In this paper we propose a new regionalization method for spatial functional data by means of a Dynamic Clustering Algorithm. The method optimizes a criterion of spatial associ...

Welche Erwartungen haben Landwirte an Websites und wie nutzen sie das Internet? Antworten auf diese Fragen werden im Folgenden auf der Grundlage einer Befragung von 110 Landwirten im nordwestdeutschen Raum gegeben.

In order to facilitate the integration of offshore surface antenna and reduce manufacturing cost, resonance shortening length omnidirectional radiation performance a centrally loaded whip are analyzed. By calculating impedance characteristics each part midload antenna, shortened in state is obtained; superimposed field strength far calculated its analyzed; simulation carried out by using FEKO e...

ABSTRACT- The information on the spatial properties of soil is vital to improve soil management and to increase the crop productivity. Geostatistical analysis technique is one of the most important methods for determining the spatial properties of soil. The aim of this study was to investigate spatial variability of soil chemical and physical attributes for field management in eastern Shiraz, I...

Kriging is one of the most often used prediction methods in spatial data analysis. This paper examines which steps of the underlying algorithms can be performed in parallel on a PVM cluster. It will be shown, that some properties of the so called kriging equations can be used to improve the parallelized version of the algorithm. The implementation is based on R and PVM. An example will show the...