The use of SAR backscatter time series for characterising rice phenology / von Ba Duy Nguyen
Weitere Titel
Verwendung von SAR Rückstreuungs-Zeitserien für die Charakterisierung der Reis-Phänologie
Verfasser / Verfasserin Nguyen, Ba Duy
GutachterWagner, Wolfgang
ErschienenWien, 2018
Umfangxx, 106 Seiten : Illustrationen, Diagramme, Karten
HochschulschriftTechnische Universität Wien, Dissertation, 2018
Zusammenfassung in deutscher Sprache
Abweichender Titel nach Übersetzung der Verfasserin/des Verfassers
Schlagwörter (DE)SAR / Reis / Zeitserienanalyse
Schlagwörter (EN)SAR / Rice / Time series analysis
URNurn:nbn:at:at-ubtuw:1-114530 Persistent Identifier (URN)
 Das Werk ist frei verfügbar
The use of SAR backscatter time series for characterising rice phenology [11.15 mb]
Zusammenfassung (Englisch)

Detailed knowledge of the area and location of rice cropland is of great importance to any nation whose economy depends on rice production. Research in the field of rice cropland monitoring is necessary to investigate the different factors and effects of rice cultivation. Areas of application include risk management for the insurance industry, environmental reporting, and determination of greenhouse gas emissions from rice cultivation, analysis of life and water cycles, and crop forecasts. Important sources of data for rice cropland records are space-borne active microwave instruments, due to the advantage of being non-susceptible to cloud cover. A Synthetic Aperture Radar (SAR) is an active imaging system operating in the microwave spectrum. The resulting images reflect the backscatter properties of the surface, which are determined by the physical (e.g., surface roughness, geometric structure, orientation) and electrical (e.g., dielectric constant, moisture content, conductivity) characteristics of the surface, and the radar frequency of the sensor (e.g., L-, C-, X-band). Multi-temporal SAR image analysis is a common approach for rice cropland monitoring. High variations of SAR backscatter signal during the growing of rice crop in comparison with other types of land use and land cover is therefore the most important method for rice monitoring from space. However, no study so far was able to utilize the complete Advanced Synthetic Aperture Radar (Envisat ASAR) archive to map rice fields because incidence angle dependency affects the backscatter signal. In addition, the exploitation of the potential of the Sentinel-1 mission for rice monitoring (i.e., on regional and continental scales) is still subject to ongoing research. This dissertation developed a time series backscatter analyzing method, aiming for classifying rice areas and determining the seasonality of rice crops. A phenology SAR-based approach is proposed and successfully applied for rice monitoring, allowing a more objective interpretation of rice areas from historical Envisat ASAR data (polarization: horizontal-horizontal HH) and the current Sentinel-1 SAR mission (polarization: vertical-horizontal VH).

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