Rainer Laudien

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Diseases associated with viruses also found in environmental samples cause major health problems in developing countries. Little is known about the frequency and pattern of viral contamination of drinking water sources in these resource-poor settings. We established a method to analyze 10 liters of water from drinking water sources in a rural area of Benin(More)
Every year sugar beet diseases cause lower sugar beet yields and qualities compared to the average. For that reason, high resolution field and airborne hyperspectral data is used to recognize a fungal sugar beet disease in a study area of south Germany. For the airborne part of the study, multitemporal hyperspectral remote sensing data is provided by an(More)
The sustainable use of agricultural land resources with concern to food security is essential, particularly in developing countries, where yields depend primarily on the biophysical conditions. To support decision making concerning national agricultural land usage, a computer based Spatial Decision Support System (SDSS) was developed. Within this SDSS,(More)
This paper shows the programming and usage of computer based interfaces to embed models in modern SDSSs. The special focus is on the development and implementation of non-Java based interfaces which couple already existing Microsoft (MS) Excel-based models to individual designed SDSSs. To access MS Excel files within these developed systems, Java API(More)
This paper presents a software development approach to customize the GIS software ArcGIS (by ESRI) for spatial decision support. For the case study, example data of the Quémé catchment in Benin (Africa) is used to program such a system which will be used to plan the establishment of potential small water reservoirs. Therefore, a new user menu in ArcGIS is(More)
Measuring within-field variability is essential for precision farming, and remote sensing is an important tool to obtain the needed information. The objective of this study was to evaluate rice (Oryza sativa L., irrigated lowland rice) growth variability in Qixing farm considering different fields, management practice and cultivars using high resolution(More)
Due to the immense amount of data, models and expert knowledge, decisions in the field of management and planning are no longer easy to make. As modern computers are able to process comprehensive data, innovative decision support functionalities and processors can be used to maintain such complex decisions. As soon as spatial data is included in the(More)
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