Stereology for Multitemporal Images with an Application to Flooding View Full Text


Ontology type: schema:Chapter     


Chapter Info

DATE

2009-06-13

AUTHORS

Alfred Stein , Petra Budde , Mamushet Zewuge Yifru

ABSTRACT

This paper presents stereology for flooded areas observed on a multitemporal remote sensing image. Stereology is a mathematical method to quantify objects at one dimension from simulated objects at a lower dimension. It was initially developed for geological and soil objects. Here it is applied to objects on multitemporal remote sensing images, i.e. for image mining. Image mining considers the chain from object identification from remote sensing images through modeling, tracking a series of images and prediction, towards communication to stakeholders. The paper introduces the estimation of the area size of the same object observed at various moments in time. It is illustrated with a case study on flooding of the Tongle Sap lake in from Cambodia. More... »

PAGES

135-150

References to SciGraph publications

  • 2008-04. Modern developments in image mining in SCIENCE IN CHINA SERIES E: TECHNOLOGICAL SCIENCES
  • 2008-03. Analysis of dependence of decision quality on data quality in JOURNAL OF GEOGRAPHICAL SYSTEMS
  • Book

    TITLE

    Research Trends in Geographic Information Science

    ISBN

    978-3-540-88243-5
    978-3-540-88244-2

    Identifiers

    URI

    http://scigraph.springernature.com/pub.10.1007/978-3-540-88244-2_10

    DOI

    http://dx.doi.org/10.1007/978-3-540-88244-2_10

    DIMENSIONS

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