Rice crop monitoring using new generation Synthetic Aperture Radar (SAR) imagery
PhD Thesis
Title | Rice crop monitoring using new generation Synthetic Aperture Radar (SAR) imagery |
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Type | PhD Thesis |
Authors | |
Author | Lam-Dao, Nguyen |
Supervisor | Apan, Armando |
Institution of Origin | University of Southern Queensland |
Qualification Name | Doctor of Philosophy |
Number of Pages | 198 |
Year | 2009 |
Abstract | [Abstract]: Rice cultivation systems in various countries of the world have been changing in recent years. These changes have been observed in the Mekong River Ground data collection and in situ measurement of rice crop parameters were conducted at 35 sampling fields in An Giang province, Mekong River Delta, Vietnam. The average values of the radar backscattering coefficients that The methods were examined for rice identification and mapping in the study area by using ASAR APP and Wide Swath (WS) imagery. ASAR APP data were firstly used to determine the best method with high accuracy for rice delineation. By using multiple regression analysis (rather than using an agrometeorological model found unsuitable for modern rice cultural practices), the correlation between backscattering coefficients of multi-date ASAR APP images This study showed that the radar backscattering behaviour was much different from that of the traditional rice reported in previous studies, due to changes brought by modern cultural practices. HH, VV and HH/VV radar values were not significantly related to biomass (maximum r2 = 0.494) due to the effect of water management, plant density and structure. Using the polarisation ratio and VV data of rice fields during a long period of the rice season, the thresholding method based on empirical relationships demonstrated a relatively simple but effective tool to accurately derive the rice/non-rice classes. The results using Envisat ASAR APP This study concluded that time-series Envisat ASAR imagery can generate accurate maps of rice planted areas. Since radar backscattering coefficients were found uncorrelated with plant biomass in the study area, the use of SAR imagery for agro-meteorological (crop growth) modelling for rice yield prediction will be less reliable. Conversely, the use of statistical modelling (regression approach) was found highly accurate to generate rice production forecasts. Further work is needed to |
Keywords | rice; cultivation; rice cultivation; Vietnam; remote sensing; radar data |
ANZSRC Field of Research 2020 | 401304. Photogrammetry and remote sensing |
Byline Affiliations | Faculty of Engineering and Surveying |
https://research.usq.edu.au/item/9z73z/rice-crop-monitoring-using-new-generation-synthetic-aperture-radar-sar-imagery
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