By Topic

Selected Topics in Applied Earth Observations and Remote Sensing, IEEE Journal of

Issue 3 • Date Sept. 2008

Filter Results

Displaying Results 1 - 11 of 11
  • [Front cover]

    Page(s): C1
    Save to Project icon | Request Permissions | PDF file iconPDF (379 KB)  
    Freely Available from IEEE
  • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing publication information

    Page(s): C2
    Save to Project icon | Request Permissions | PDF file iconPDF (38 KB)  
    Freely Available from IEEE
  • Table of contents

    Page(s): 169
    Save to Project icon | Request Permissions | PDF file iconPDF (35 KB)  
    Freely Available from IEEE
  • Stability and Power Quality Issues in Microgrids Under Weather Disturbances

    Page(s): 170 - 179
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (1198 KB) |  | HTML iconHTML  

    In this paper, a stability study of Kythnos island power system was investigated under power generation deviation due to solar insolation variations measured from ground and Earth observation. The system was tested under disturbances, like sudden shadowing of the photovoltaic generators due to cloudiness. It was assumed that the cloud was completely covering the island. Two other disturbances for a 24-h simulation were taken from real meteorological data, one from ground measurements and the other based on satellite data. Simulation tests for the first case show that the system is generally stable for penetration lower than 50%, while it becomes unstable at higher levels. Additionally, the shadowing effect was slow enough in order to cope with it. For the second case, the system is operating very close to the limits for high PV penetration. To optimize operation a satellite based nowcasting and short-term forecasting could be used. A 15-min advance notice that cloud cover is eminent would be adequate to start up the back up systems and avoid instability or black out events. Such a strategy allows reserve need reductions in clear sky cases, as changes in weather conditions can be predicted early enough in advance. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • A Robust Built-Up Area Presence Index by Anisotropic Rotation-Invariant Textural Measure

    Page(s): 180 - 192
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (2345 KB) |  | HTML iconHTML  

    A procedure for the calculation of a texture-derived built-up presence index (PanTex) from textural characteristics of panchromatic satellite data is presented. The index is based on fuzzy rule-based composition of anisotropic textural co-occurrence measures derived from the satellite data by the gray-level co-occurrence matrix (GLCM). Examples are produced how the PanTex index reduces the edge effects of the nonbuilt-up linear features and improves capacity to discriminate between built-up and nonbuilt-up areas. The accuracy and robustness of the PanTex measure against seasonal changes, multisensor, multiscene, and data degradation by wavelet-based compression and histogram stretching is discussed with some examples. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Integrative Assessment of Informal Settlements Using VHR Remote Sensing Data—The Delhi Case Study

    Page(s): 193 - 205
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (3161 KB) |  | HTML iconHTML  

    In contrast to the last century, where more people used to live in rural areas, at present, more than half of the world's population lives in urban settlements. Hence, the 21st century is the century of the cities and of urbanization. The rapid urbanization process experienced by the majority of developing countries during the last few decades has resulted in fundamental changes to the environment and to the social structure. In most of the megacities that have grown to unprecedented size, the pace of urbanization has far exceeded the growth of necessary infrastructure and services. In order to carry out the urban planning and development tasks necessary to improve the living conditions for the poorest world-wide, a detailed spatial data basis is required. Due to the high dynamics of megacities, traditional methods such as statistical analyses or fieldwork are limited to capture the urban process. Remote sensing provides the opportunity to monitor spatial patterns of urban structures with high spatial and temporal resolution. The present study investigates the potential to use very high-resolution (VHR) remote sensing data to identify urban structures and dynamics within Delhi, India. The paper presents a semi-automated, object-oriented classification approach which allows for the identification of informal settlements within the urban area. In order to provide indicators to identify socio-economic structures and their dynamics, the image classification results are embedded in an integrative analysis concept. Information on population and water related parameters are derived. This is understood to be a first step to the development of indicators which will help to identify and understand the different shapes, actors, and processes in megacities. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • Detection, Characterization, and Modeling Vegetation in Urban Areas From High-Resolution Aerial Imagery

    Page(s): 206 - 213
    Save to Project icon | Request Permissions | Click to expandQuick Abstract | PDF file iconPDF (842 KB) |  | HTML iconHTML  

    Research in the area of 3-D city modeling from remote sensed data greatly developed in recent years with an emphasis on systems dealing with the detection and representation of man-made objects, such as buildings and streets. While these systems produce accurate representations of urban environments, they ignore information about the vegetation component of a city. This paper presents a complete image analysis system which, from high-resolution color infrared (CIR) digital images, and a Digital Surface Model (DSM), extracts, segments, and classifies vegetation in high density urban areas, with very high reliability. The process starts with the extraction of all vegetation areas using a supervised classification system based on a Support Vector Machines (SVM) classifier. The result of this first step is further on used to separate trees from lawns using texture criteria computed on the DSM. Tree crown borders are identified through a robust region growing algorithm based on tree-shape criteria. A SVM classifier gives the species class for each tree-region previously identified. This classification is used to enhance the appearance of 3-D city models by a realistic representation of vegetation according to the vegetation land use, shape and tree species. View full abstract»

    Full text access may be available. Click article title to sign in or learn about subscription options.
  • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing Information for authors

    Page(s): 214
    Save to Project icon | Request Permissions | PDF file iconPDF (30 KB)  
    Freely Available from IEEE
  • JSTARS Special issue on earth observation sensor web

    Page(s): 215 - 216
    Save to Project icon | Request Permissions | PDF file iconPDF (219 KB)  
    Freely Available from IEEE
  • IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing [publication information]

    Page(s): C3
    Save to Project icon | Request Permissions | PDF file iconPDF (25 KB)  
    Freely Available from IEEE
  • IEEE Transactions on Geoscience and Remote Sensing institutional listings

    Page(s): C4
    Save to Project icon | Request Permissions | PDF file iconPDF (97 KB)  
    Freely Available from IEEE

Aims & Scope

IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing (J-STARS) addresses current issues and techniques in applied remote and in situ sensing, their integration, and applied modeling and information creation for understanding the Earth.

Full Aims & Scope

Meet Our Editors

Editor-in-Chief
Dr. Jocelyn Chanussot
Grenoble Institute of Technology