Digital compensation of turbulent distortions of incoherent optical images using multiaperture systems

2018 ◽  
Keyword(s):  
Digital Compensation ◽  
Optical Images ◽  
Turbulent Distortions

Digital Compensation of IQ Imbalance for Dual-Carrier Double Conversion Receivers

2012 ◽  
Vol E95.B (5) ◽  
pp. 1612-1619 ◽  
Author(s):  
Chester Sungchung PARK ◽  
Fitzgerald Sungkyung PARK
Keyword(s):  
Digital Compensation ◽  
Iq Imbalance

Monitoring effluent quality in hypertrophic wastewater reservoirs using remote sensing

1996 ◽  
Vol 33 (8) ◽  
pp. 23-29 ◽  
Author(s):  
I. Dor ◽  
N. Ben-Yosef
Keyword(s):  
Water Quality ◽  
Theoretical Model ◽  
Principal Component ◽  
Cost Effective ◽  
Operational Parameters ◽  
Effluent Quality ◽  
Optical Images ◽  
Routine Monitoring ◽  
Cost Effective Method ◽  
Wastewater Quality

About one hundred and fifty wastewater reservoirs store effluents for irrigation in Israel. Effluent qualities differ according to the inflowing wastewater quality, the degree of pretreatment and the operational parameters. Certain aspects of water quality like concentration of organic matter, suspended solids and chlorophyll are significantly correlated with the water column transparency and colour. Accordingly optical images of the reservoirs obtained from the SPOT satellite demonstrate pronounced differences correlated with the water quality. The analysis of satellite multispectral images is based on a theoretical model. The model calculates, using the radiation transfer equation, the volume reflectance of the water body. Satellite images of 99 reservoirs were analyzed in the chromacity space in order to classify them according to water quality. Principal Component Analysis backed by the theoretical model increases the method sensitivity. Further elaboration of this approach will lead to the establishment of a time and cost effective method for the routine monitoring of these hypertrophic wastewater reservoirs.

scholarly journals Mapping Land use/land cover using a combination of Radar Sentinel-1A and Sentinel-2A optical images

2021 ◽  
Vol 652 (1) ◽  
pp. 012021
Author(s):  
T T H Nguyen ◽  
T N Q Chau ◽  
T A Pham ◽  
T X P Tran ◽  
T H Phan ◽  
...  
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Use Land Cover ◽  
Optical Images ◽  
Sentinel 2A

scholarly journals InSAR Multitemporal Data over Persistent Scatterers to Detect Floodwater in Urban Areas: A Case Study in Beletweyne, Somalia

2020 ◽  
Vol 13 (1) ◽  
pp. 37
Author(s):  
Luca Pulvirenti ◽  
Marco Chini ◽  
Nazzareno Pierdicca
Keyword(s):  
Urban Area ◽  
Urban Areas ◽  
The Other ◽  
Spatial Average ◽  
Calibration Data ◽  
Suburban Areas ◽  
Persistent Scatterers ◽  
Optical Images ◽  
Interferometric Phase ◽  
Multitemporal Data

A stack of Sentinel-1 InSAR data in an urban area where flood events recurrently occur, namely Beletweyne town in Somalia, has been analyzed. From this analysis, a novel method to deal with the problem of flood mapping in urban areas has been derived. The approach assumes the availability of a map of persistent scatterers (PSs) inside the urban settlement and is based on the analysis of the temporal trend of the InSAR coherence and the spatial average of the exponential of the InSAR phase in each PS. Both interferometric products are expected to have high and stable values in the PSs; therefore, anomalous decreases may indicate that floodwater is present in an urban area. The stack of Sentinel-1 data has been divided into two subsets. The first one has been used as a calibration set to identify the PSs and determine, for each PS, reference values of the coherence and the spatial average of the exponential of the interferometric phase under standard non-flooded conditions. The other subset has been used for validation purposes. Flood maps produced by UNOSAT, analyzing very-high-resolution optical images of the floods that occurred in Beletweyne in April–May 2018, October–November 2019, and April–May 2020, have been used as reference data. In particular, the map of the April–May 2018 flood has been used for training purposes together with the subset of Sentinel-1 calibration data, whilst the other two maps have been used to validate the products generated by applying the proposed method. The main product is a binary map of flooded PSs that complements the floodwater map of rural/suburban areas produced by applying a well-consolidated algorithm based on intensity data. In addition, a flood severity map that labels the different districts of Beletweyne, as not, partially, or totally flooded has been generated to consolidate the validation. The results have confirmed the effectiveness of the proposed method.

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