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Brandenburg an der Havel, Germany

The article at hand reveals the methodology and results of a research and development project in the field of applied remote sensing in forest protection and bark beetle monitoring. It was found that using multi-temporal RapidEye imagery, the ground truth data of bark beetle infestation and the application of datamining techniques allow for the recognition and separation of different infestation stages. The analysis suggests a weak trend for the identification of infested groups of trees, which are still widely green. In contrast, the classification of reddish-coloured deteriorating or dead tree groups shows a high accuracy (97% user's, 82 % producer's, kappa: 0.89). © 2010 E. Schweizerbart'sche Verlagsbuchhandlung, Stuttgart, Germany. Source

Eitel J.U.H.,University of Idaho | Vierling L.A.,University of Idaho | Litvak M.E.,University of New Mexico | Long D.S.,Columbia Plateau Conservation Research Center | And 4 more authors.
Remote Sensing of Environment | Year: 2011

Multiple plant stresses can affect the health, esthetic condition, and timber harvest value of conifer forests. To monitor spatial and temporal dynamic forest stress conditions, timely, accurate, and cost-effective information is needed that could be provided by remote sensing. Recently, satellite imagery has become available via the RapidEye satellite constellation to provide spectral information in five broad bands, including the red-edge region (690-730. nm) of the electromagnetic spectrum. We tested the hypothesis that broadband, red-edge satellite information improves early detection of stress (as manifest by shifts in foliar chlorophyll a. +. b) in a woodland ecosystem relative to other more commonly utilized band combinations of red, green, blue, and near infrared band reflectance spectra. We analyzed a temporally dense time series of 22 RapidEye scenes of a piñon-juniper woodland in central New Mexico acquired before and after stress was induced by girdling. We found that the Normalized Difference Red-Edge index (NDRE) allowed stress to be detected 13. days after girdling - between and 16. days earlier than broadband spectral indices such as the Normalized Difference Vegetation Index (NDVI) and Green NDVI traditionally used for satellite based forest health monitoring. We conclude that red-edge information has the potential to considerably improve forest stress monitoring from satellites and warrants further investigation in other forested ecosystems. © 2011 Elsevier Inc. Source

Stoll E.,RapidEye AG | D'Souza B.,RapidEye AG | Virgili B.B.,Robert Bosch GmbH | Merz K.,Robert Bosch GmbH | Krag H.,Robert Bosch GmbH
IEEE Aerospace Conference Proceedings | Year: 2013

Collision avoidance is a topic of increasing importance. The number of satellites in Earth orbit is steadily growing and with the high amount of space debris, either crossing through or resident in orbit, collision probabilities between two such objects can become critical. Small satellite missions usually operate with limited capabilities when it comes to locating potential collision occurrences and deriving the associated collision probability. Accordingly, they have to rely on external organizations, such as the Joint Space Operation Center (JSpOC) and their information system to plan for contingency operations. This paper reviews the benefits of using such an external service for a small satellite constellation. It analyses the relevant data for use in daily operations and shows collision avoidance approaches based on the available data. Conjunction summaries for the RapidEye satellite constellation are evaluated and their influence on the planning of collision avoidance maneuvers is shown. © 2013 IEEE. Source

Zillmann E.,RapidEye AG | Weichelt H.,RapidEye AG
MultiTemp 2013 - 7th International Workshop on the Analysis of Multi-Temporal Remote Sensing Images: "Our Dynamic Environment", Proceedings | Year: 2013

Grasslands cover large areas of the earth's surface and have been extensively converted to other uses such as cultivation and urbanization. The monitoring of grasslands is needed for any land use planning and environmental management. Remote Sensing techniques are suitable to provide detailed spatial information on grassland to support this process. The RapidEye satellite constellation represents a unique potential of multi-temporal acquisition of high resolution image data, therefore, offering a reliable data source for detailed multi-temporal analysis. In the presented study a semi-automatic land-cover classification approach with emphasis on the identification of grassland was developed. The methodology is based on the analysis of multi-temporal RapidEye images using the supervised decision tree (DT) classifier C5 in combination with prepended image segmentation. The results presented correspond to an area of 2500 km2 in the State of Brandenburg / Germany. The classification accuracy was assessed by using randomly distributed independent reference points and the confusion matrix to derive users' and producers' accuracies. The grassland classification of the test area reached an overall accuracy of about 90%. © 2013 IEEE. Source

Thiele M.,RapidEye AG | Anderson C.,RapidEye AG | Brunn A.,RapidEye AG
International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences - ISPRS Archives | Year: 2012

Radiometric calibration of the RapidEye Multispectral Imager (MSI) as with all other remote sensing instruments is an essential task in the quantitative assessment of sensor image quality and the production of accurate data products for a wide range of geo-spatial applications. Spatially and temporally pseudo-invariant terrestrial targets have long been used to quantify and provide a consistent record of the radiometric performance of Earth observation systems. The RapidEye cross-calibration approach combines temporal and relative calibration to ensure temporal stability in spectral response between it's 5 identical MSI over time by using a large number of repetitive collects of many pseudo-invariant calibration sites. The approach is characterized by its known reliability which is based on the purely statistical analysis of many ground collects with ground infrastructure or measurement systems not being necessary. The results show that the in-band percent difference in the measured response among all RapidEye sensors is less than two percent. Although the results show some offsets between the different sensors, the response of the RapidEye constellation over a three-year period is very stable. Source

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