Historical Land Use/Land Cover Classification Using Remote Sensing
A Case Study of the Euphrates River Basin in Syria
(Sprache: Englisch)
Although the development of remote sensing techniques focuses greatly on construction of new sensors with higher spatial and spectral resolution, it is advisable to also use data of older sensors (especially, the LANDSAT-mission) when the historical mapping...
Voraussichtlich lieferbar in 3 Tag(en)
versandkostenfrei
Buch (Kartoniert)
53.49 €
- Lastschrift, Kreditkarte, Paypal, Rechnung
- Kostenlose Rücksendung
- Ratenzahlung möglich
Produktdetails
Produktinformationen zu „Historical Land Use/Land Cover Classification Using Remote Sensing “
Although the development of remote sensing techniques focuses greatly on construction of new sensors with higher spatial and spectral resolution, it is advisable to also use data of older sensors (especially, the LANDSAT-mission) when the historical mapping of land use/land cover and monitoring of their dynamics are needed. Using data from LANDSAT missions as well as from Terra (ASTER) Sensors, the authors shows in his book maps of historical land cover changes with a focus on agricultural irrigation projects.
The kernel of this study was whether, how and to what extent applying the various remotely sensed data that were used here, would be an effective approach to classify the historical and current land use/land cover, to monitor the dynamics of land use/land cover during the last four decades, to map the development of the irrigation areas, and to classify the major strategic winter- and summer-irrigated agricultural crops in the study area of the Euphrates River Basin.
The kernel of this study was whether, how and to what extent applying the various remotely sensed data that were used here, would be an effective approach to classify the historical and current land use/land cover, to monitor the dynamics of land use/land cover during the last four decades, to map the development of the irrigation areas, and to classify the major strategic winter- and summer-irrigated agricultural crops in the study area of the Euphrates River Basin.
Klappentext zu „Historical Land Use/Land Cover Classification Using Remote Sensing “
Although the development of remote sensing techniques focuses greatly on construction of new sensors with higher spatial and spectral resolution, it is advisable to also use data of older sensors (especially, the LANDSAT-mission) when the historical mapping of land use/land cover and monitoring of their dynamics are needed. Using data from LANDSAT missions as well as from Terra (ASTER) Sensors, the authors shows in his book maps of historical land cover changes with a focus on agricultural irrigation projects.The kernel of this study was whether, how and to what extent applying the various remotely sensed data that were used here, would be an effective approach to classify the historical and current land use/land cover, to monitor the dynamics of land use/land cover during the last four decades, to map the development of the irrigation areas, and to classify the major strategic winter- and summer-irrigated agricultural crops in the study area of the Euphrates River Basin.
Inhaltsverzeichnis zu „Historical Land Use/Land Cover Classification Using Remote Sensing “
Theoretical background and literature review / state of the art.- Overview of study area.- Data and tools.- Research methodology.- Results, analysis and discussions.- Summary, concluding remarks and recommendations.
Bibliographische Angaben
- Autor: Wafi Al- Fares
- 2013, 2013, XVIII, 204 Seiten, 86 farbige Abbildungen, Maße: 15,9 x 23,3 cm, Kartoniert (TB), Englisch
- Verlag: Springer, Berlin
- ISBN-10: 3319006231
- ISBN-13: 9783319006239
Sprache:
Englisch
Kommentar zu "Historical Land Use/Land Cover Classification Using Remote Sensing"
0 Gebrauchte Artikel zu „Historical Land Use/Land Cover Classification Using Remote Sensing“
Zustand | Preis | Porto | Zahlung | Verkäufer | Rating |
---|
Schreiben Sie einen Kommentar zu "Historical Land Use/Land Cover Classification Using Remote Sensing".
Kommentar verfassen