18 documents found in 188ms
# 1
Lenz-Wiedemann, Victoria • Bareth, Georg
Abstract: From 18th - 19th of November, 2010, the 'Workshop on Remote Sensing Methods for Change Detection and Process modelling' was held at the University of Cologne, Germany. This workshop was organized by the Working Group 5 'Methods for Change Detection and Process Modelling' within the Commission VII 'Thematic Processing, Modelling and Analysis or Remotely Sensed Data' of the International Society for Photogrammetry and Remote Sensing (ISPRS). Three research projects actively supported the workshop. The CRC/TR32 'Patterns in Soil-Vegetation-Atmosphere-Systems: Monitoring, Modelling, and Data Assimilation' as well as the CRC 806 'Our way to Europe: Culture-Environment Interaction and Human Mobility in the Later Quaternary', both Collaborative Research Centres of the German Research Foundation (DFG). Within the CROP.SENSe.net (funded by the German Federal Ministry of Education and Research, BMBF), sensor methods for monitoring crops are investigated. Finally, the workshop was supported by the International Centre for Agro-Informatics and Sustainable Development (ICASD), which was founded in cooperation with the China Agricultural University and the u CROP.SENSe.net University of Cologne. The goal of the workshop was to bring together scientific disciplines as disparate as geography, soil sciences, plant physiology, hydrology, meteorology, prehistory, archaeology, agronomy, remote sensing, and geoinformatics. The workshop was based on 14 invited talks and unusual long coffee breaks, parallel to poster sessions to encourage and support discussion. The diverse program attracted nearly 40 poster presentations and approximately 90 participants. The papers and abstracts of the workshop are summarized in the workshop proceedings.
Proceedings on the Workshop of Remote Sensing Methods for Change Detection and Process Modelling, 18-19 November 2010, University of Cologne, Germany, Kölner Geographische Arbeiten, 92, pp. III
# 2
Masini, Nicola • Coluzzi, Rossella • Lasaponara, Rosa
Abstract: The Airborne Laser Scanning (ALS) technology, also referred to as LIDAR (Light Detection And Ranging), represents the most relevant advancement of Earth Observation (EO) techniques applied to archaeological research in the last decade. It allows us to overcome some limits of satellite optical remote sensing in detecting archaeological remains covered by dense vegetation as well as microrelief of cultural interest in bare-ground sites. Currently, a LIDAR survey can be carried out by using two different types of ALS sensor systems: (i) conventional scanners or discrete echo scanners, and (ii) Full-Waveform (FW) scanners. The first one generally delivers only the first and last echo, thus losing many other reflections. The second one is able to detect the entire echo waveform for each emitted laser beam, thus offering improved capabilities especially in areas with complex morphology and/or dense vegetation cover. This paper shows the results obtained by processing point clouds taken from FW scanners for two emblematic study cases in Southern Italy. The first one is the abandoned medieval village of Monte Serico, located on a bare-ground hilly plateau, the second one is the Bosco dell’Incoronata. By using an approach based on the use and processing of different shaded Digital Terrain Models (DTMs), the study allowed us to improve the reconstruction of the urban fabric and the paleoenvironmental setting, respectively.
Proceedings on the Workshop of Remote Sensing Methods for Change Detection and Process Modelling, 18-19 November 2010, University of Cologne, Germany, Kölner Geographische Arbeiten, 92, pp. 79-91
# 3
Migliorini, Stefano
Abstract: The availability and the appropriate use of accurate and widespread observational information are of paramount importance in order to increase the accuracy of weather forecasts. Data assimilation techniques provide a framework to find the best initial state that is consistent with all available information about the state of the system, here considered to be the Earth’s atmosphere. In this paper, a brief introduction to both variational and ensemble based data assimilation is provided, with a focus on the main characteristics of satellite data assimilation and some of its current issues.
Proceedings on the Workshop of Remote Sensing Methods for Change Detection and Process Modelling, 18-19 November 2010, University of Cologne, Germany, Kölner Geographische Arbeiten, 92, pp. 93-99
# 4
Möller, Markus • Birger, Jens • Gläßer, Cornelia
Abstract: Optical remote sensing data are widely used for the classification of natural and agricultural vegetation classes. The distinction of phenological stages within specific and between different species requires the availability of multi-temporal data sets. New satellite systems provide both data of high geometric resolution and high repetition rates. Due to cost efficiency, the knowledge of up-to-date phenological stages is of importance for the identification of optimal temporal windows for vegetation discrimination with remote sensing. On the example of the total area of Germany and the phenological stage 'yellow ripeness' of winter wheat in 2010, the presented algorithm demonstrates how daily phenological stages can be automatically interpolated on demand, in real-time and considering interpolation accuracies. As input we use daily provided point data of temperature and phenological stages from the extensive network of the German Weather Service (DWD) as well as a SRTM digital terrain model (DTM) with a geometric resolution of 90 m x 90 m.
Proceedings on the Workshop of Remote Sensing Methods for Change Detection and Process Modelling, 18-19 November 2010, University of Cologne, Germany, Kölner Geographische Arbeiten, 92, pp. 101-108
# 5
Nowak Da Costa, Joanna Krystina • Walczynska, Agnieszka
Abstract: Measurement errors in orthorectified images are very important when it comes to checking the subsidies claims made by European farmers. The Control with a Remote Sensing (CwRS) Programme, managed by the GeoCAP and CID actions of the Monitoring Agricultural Resources Unit of the EC Joint Research Centre (JRC), requires the establishment of guidelines to be applied by Member States when using remotely sensed images to verify farmers’ claims under the EU Common Agriculture Policy (CAP) subsidies. The area of land parcels used for farming are verified based on very fine spatial resolution (VHR) orthoimages that must meet specific geometric and visual qualities. As such, all VHR orthoimages used within this context must meet or exceed the EU standard as reported in Kapnias et al. (2008), based on external quality control (EQC). EQC is based on the root mean square error (RMSE) between the true geographic position and the image position of the independent check points (ICPs). The ICPs are points not included in the sensor model parameter estimation process and are derived from an independent source, preferably of higher accuracy. This report presents the applied EQC methodology and the geometric quality results recorded for the four samples of the KOMPSAT-2 (K2) radiometrically corrected images (processing level 1R), acquired over the JRC Maussane Test Site. The key issues identified during the testing based on the limited KOMPSAT-2 sample images that were made available to us are as follows: (a) The 1D RMS errors measured on the final K2 orthoimage after the single scene correction applying either the PCI rigorous model, the PCI RPC-based or the ERDAS RPC-based model are not sensitive to the number of GCPs used if they are well-distributed and range between 9 and 15 (provided a DTM with 0.6 m vertical accuracy), and they are sensitive to the overall off-nadir angle and increase with increasing off-nadir angle, (b) The average 1D RMSE are 2.1 m and 4 m, while the maximum 1D RMSE values are 3.2 m and 6.2 m of easting and northing direction respectively, provided that a DTM with 0.6 m vertical accuracy and GCPs with mean RMSE-X (in X direction) and RMSE-Y (in Y direction) values of 0.6 m are used, and (c) The orthorectified KOMPSAT-2 images do not fall within the accuracy criteria of the CwRS 1:10000 scale requirements, i.e. an absolute 1D RMSE not exceeding 2.5 m, except where the images are characterized by an overall off-nadir angle close to zero degrees, and the rigorous model or first order Rational Polynomial sensor model is applied.
Proceedings on the Workshop of Remote Sensing Methods for Change Detection and Process Modelling, 18-19 November 2010, University of Cologne, Germany, Kölner Geographische Arbeiten, 92, pp. 109-115
# 6
Roeloffs, Anna • Linstädter, Jörg • Wiatr, Thomas • Reicherter, Klaus • Weniger, Gerd-Christian
Abstract: Caves and rock shelters are important archives for archaeological research. Prehistoric men not only sheltered in caves but also set up camps in open-air locations. Over the last 15 years a joint research group, comprising INSAP (Institut National des Sciences de l’Archéologie et du Patrimoine du Maroc), KAAK (Kommission für Archäologie Außereuropäischer Kulturen, German Archaeology Institute) and the University of Cologne, has been carrying out surveys and excavations in the area of the Eastern Rif (NE-Morocco). Huge parts of the vast working area are poorly accessible and it is now realised that the whole area can only be covered using a remote sensing approach.The aim of this project is to integrate high resolution topographical, visual and geological data in order to develop models so that site locations can be predicted. Information from remote sensing (satellite image) and Geographic Information System (GIS) is used to identify an area in which carstic caves can occur and caves featuring archaeological remains may be located. The intersection of geological and topographical maps with QuickBird satellite imagery can then be used to quantify different features of identified caves. Based on the partially existing fans of sediment in front of the carstic caves, potential locations of caves in the defined area could be discovered.
Proceedings on the Workshop of Remote Sensing Methods for Change Detection and Process Modelling, 18-19 November 2010, University of Cologne, Germany, Kölner Geographische Arbeiten, 92, pp. 121-129
# 7
Pastoors, Andreas • Weniger, Gerd-Christian
Abstract: Prehistoric archaeology is an object-oriented discipline. Archaeological objects like stone tools, bone tools or pieces of mobile art embed human behaviour. A central task of prehistoric research is to decode this information in order to reconstruct ancient human behaviour. This premise affords a defined set of tools for analysis and documentation to describe and evaluate particularly the shape of the object and its surface modifications manufactured by humans. Basis for all types of analysis is therefore a precise visual description of the object. This documentation forms part of the scientific process and should follow a generally accepted convention. Only when these rules are respected, a standardised and reproducible recognition of the object becomes possible.
Proceedings on the Workshop of Remote Sensing Methods for Change Detection and Process Modelling, 18-19 November 2010, University of Cologne, Germany, Kölner Geographische Arbeiten, 92, pp. 117-120
# 8
Sui, Haigan • Sun, K. • Gong, Jianya • Xu, C. • Wen, C.
Abstract: Aiming to improve object fragmentation and poor detection results caused by discontinuous segmentation scales in object-level change detection, a new object-level change detection method based on multi-scale segmentation is presented in this paper. Firstly, a convexity model concept to describe target- background characteristics is proposed. This model is used to implement the convexity model-based multi-scale image segmentation, in order to overcome the shortcoming that traditional single-scale image segmentation can hardly synchronously extract the objects within different scales. And then, a change detection approach by analyzing structural characteristics of image objects is introduced, in order to detect the man-made object. Experiments show that the new method is robust and that it provides an advanced tool for quantitative change detection.
Proceedings on the Workshop of Remote Sensing Methods for Change Detection and Process Modelling, 18-19 November 2010, University of Cologne, Germany, Kölner Geographische Arbeiten, 92, pp. 143-150
# 9
Sturm-Hentschel, Ulrike • Braun, Andreas C. • Hinz, Stefan • Vogt, Joachim
Abstract: A typical situation in many developing countries is sparse data availability. Thus, many issues of applied research need to be tackled in spite of poor data disposability. We exemplify these issues in the coastal area of Benin in Western Africa by a time series using a grey scale aerial image (1995), QuickBird data (2002), and a colour aerial image (2007, scale 1:20000). Coastal regions are in general areas of high attraction worldwide. Due to migration and population growth, the coastal zone of Benin, like in other developing countries, encounters extreme land use pressure, causing conflicts of interest and fast changes. Especially settlement structures show high dynamics. In order to study these, dwellings need to be detected. The multitude of appearances of dwellings makes process analysis based on remotely sensed data a challenging – yet interesting – task. This paper shows how to analyse settlement processes in developing countries with heterogeneous remote sensing data sets, combining remote sensing with pattern recognition and GIS. At first, building detection was accomplished by manual digitization. In the next step, we made an initial attempt to develop automated methods for detecting dwellings. Both approaches for building detection were then followed by GIS-based process analysis. Finally, a comparison of both detection approaches based on quality assessments is presented and a thorough evaluation of the usability of automation is given.
Proceedings on the Workshop of Remote Sensing Methods for Change Detection and Process Modelling, 18-19 November 2010, University of Cologne, Germany, Kölner Geographische Arbeiten, 92, pp. 131-142
# 10
Bareth, Georg • Bolten, Andreas • Bendig, Juliane
Abstract: The trend to minimize electronic devices also accounts for sensing and sensor technologies. In combination with the developments in the construction of low-weight unmanned airborne vehicles (UAVs), this enabled in the last years a new research and application field of low-cost and low-weight UAVs carrying all kind of sensors such as multi-spectral, hyperspectral, laserscanning, microwave, and thermal imaging devices. In the same period, the demand for local high resolution data in a spatial, temporal, and spectral context increased exponentially for all kinds of applications. Low-cost and low-weight UAVs can exactly acquire such data. Hence, it is no surprise that the deployment of Mini-UAVs in the field of environmental monitoring, agriculture, facility management and many more is growing fast.
Proceedings on the Workshop of Remote Sensing Methods for Change Detection and Process Modelling, 18-19 November 2010, University of Cologne, Germany, Kölner Geographische Arbeiten, 92, pp. 1-8
spinning wheel Loading next page