Stereology for multitemporal images with an application to flooding

A. Stein, P.E. Budde, Mamushet Zewuge Yifru

Research output: Chapter in Book/Report/Conference proceedingChapterAcademicpeer-review

2 Citations (Scopus)
25 Downloads (Pure)

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.
Original languageEnglish
Title of host publicationResearch Trends in Geographic Information Science
EditorsGerhard Navratil
Place of PublicationBerlin, Germany
PublisherSpringer
Pages135-150
ISBN (Electronic)978-3-540-88244-2
ISBN (Print)978-3-540-88243-5, 978-3-642-09997-7
DOIs
Publication statusPublished - 2009

Publication series

NameLecture Notes in Geoinformation and Cartography
PublisherSpringer
ISSN (Print)1863-2246
ISSN (Electronic)1863-2351

Keywords

  • ADLIB-ART-348
  • EOS
  • 2023 OA procedure

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