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Full-Text Articles in Engineering
Using Microwave Brightness Temperature Diurnal Cycle To Improve Emissivity Retrievals Over Land, Hamidreza Norouzi, William Rossow, Marouane Temimi, Catherine Prigent, Marzieh Azarderakhsh, Sid Boukabara, Reza Khanbilvardi
Using Microwave Brightness Temperature Diurnal Cycle To Improve Emissivity Retrievals Over Land, Hamidreza Norouzi, William Rossow, Marouane Temimi, Catherine Prigent, Marzieh Azarderakhsh, Sid Boukabara, Reza Khanbilvardi
Publications and Research
To retrieve microwave land emissivity, infrared surface skin temperatures have been used as surface physical temperature since there is no global information on physical vegetation/soil temperature profiles. However, passive microwave emissions originate fromdeeper layerswith respect to the skin temperature. So, this inconsistency in sensitivity depths between skin temperatures and microwave temperaturesmay introduce a discrepancy in the determined emissivity. Previous studies showed that this inconsistency can lead to significant differences between day and night retrievals of land emissivity which can exceed 10%. This study proposes an approach to address this inconsistency and improve the retrieval of land emissivity using microwave observations …
A Multi-Temporal Analysis Of Amsr-E Data For Flood And Discharge Monitoring During The 2008 Flood In Iowa, Marouane Temimi, Teodosio Lacava, Tarendra Lakhankar, Valerio Tramutoli, Hosni Ghedira, Riadh Ata, Reza Khanbilvardi
A Multi-Temporal Analysis Of Amsr-E Data For Flood And Discharge Monitoring During The 2008 Flood In Iowa, Marouane Temimi, Teodosio Lacava, Tarendra Lakhankar, Valerio Tramutoli, Hosni Ghedira, Riadh Ata, Reza Khanbilvardi
Publications and Research
The objective of this work is to demonstrate the potential of using passive microwave data to monitor flood and discharge conditions and to infer watershed hydraulic and hydrologic parameters. The case study is the major flood in Iowa in summer 2008. A new Polarisation Ratio Variation Index (PRVI) was developed based on a multi-temporal analysis of 37 GHz satellite imagery from the Advanced Microwave Scanning Radiometer (AMSR-E) to calculate and detect anomalies in soil moisture and/or inundated areas. The Robust Satellite Technique (RST) which is a change detection approach based on the analysis of historical satellite records was adopted. A …
Sensitivity Analysis Of B-Factor In Microwave Emission Model For Soil Moisture Retrieval: A Case Study For Smap Mission, Dugwon Seo, Tarendra Lakhankar, Reza Khanbilvardi
Sensitivity Analysis Of B-Factor In Microwave Emission Model For Soil Moisture Retrieval: A Case Study For Smap Mission, Dugwon Seo, Tarendra Lakhankar, Reza Khanbilvardi
Publications and Research
Sensitivity analysis is critically needed to better understand the microwave emission model for soil moisture retrieval using passive microwave remote sensing data. The vegetation b-factor along with vegetation water content and surface characteristics has significant impact in model prediction. This study evaluates the sensitivity of the b-factor, which is function of vegetation type. The analysis is carried out using Passive and Active L and S-band airborne sensor (PALS) and measured field soil moisture from Southern Great Plains experiment (SGP99). The results show that the relative sensitivity of the b-factor is 86% in wet soil condition and 88% in high vegetated …
Analysis Of Large Scale Spatial Variability Of Soil Moisture Using A Geostatistical Method, Tarendra Lakhankar, Andrew S. Jones, Cynthia L. Combs, Manajit Sengupta, Thomas H. Vonder Haar, Reza Khanbilvardi
Analysis Of Large Scale Spatial Variability Of Soil Moisture Using A Geostatistical Method, Tarendra Lakhankar, Andrew S. Jones, Cynthia L. Combs, Manajit Sengupta, Thomas H. Vonder Haar, Reza Khanbilvardi
Publications and Research
Spatial and temporal soil moisture dynamics are critically needed to improve the parameterization for hydrological and meteorological modeling processes. This study evaluates the statistical spatial structure of large-scale observed and simulated estimates of soil moisture under pre- and post-precipitation event conditions. This large scale variability is a crucial in calibration and validation of large-scale satellite based data assimilation systems. Spatial analysis using geostatistical approaches was used to validate modeled soil moisture by the Agriculture Meteorological (AGRMET) model using in situ measurements of soil moisture from a state-wide environmental monitoring network (Oklahoma Mesonet). The results show that AGRMET data produces larger …
Non-Parametric Methods For Soil Moisture Retrieval From Satellite Remote Sensing Data, Tarendra Lakhankar, Hosni Ghedira, Marouane Temimi, Manajit Sengupta, Reza Khanbilvardi, Reginald Blake
Non-Parametric Methods For Soil Moisture Retrieval From Satellite Remote Sensing Data, Tarendra Lakhankar, Hosni Ghedira, Marouane Temimi, Manajit Sengupta, Reza Khanbilvardi, Reginald Blake
Publications and Research
Satellite remote sensing observations have the potential for efficient and reliable mapping of spatial soil moisture distributions. However, soil moisture retrievals from active microwave remote sensing data are typically complex due to inherent difficulty in characterizing interactions among land surface parameters that contribute to the retrieval process. Therefore, adequate physical mathematical descriptions of microwave backscatter interaction with parameters such as land cover, vegetation density, and soil characteristics are not readily available. In such condition, non-parametric models could be used as possible alternative for better understanding the impact of variables in the retrieval process and relating it in the absence of …
Effect Of Land Cover Heterogeneity On Soil Moisture Retrieval Using Active Microwave Remote Sensing Data, Tarendra Lakhankar, Hosni Ghedira, Marouane Temimi, Amir E. Azar, Reza Khanbilvardi
Effect Of Land Cover Heterogeneity On Soil Moisture Retrieval Using Active Microwave Remote Sensing Data, Tarendra Lakhankar, Hosni Ghedira, Marouane Temimi, Amir E. Azar, Reza Khanbilvardi
Publications and Research
This study addresses the issue of the variability and heterogeneity problems that are expected from a sensor with a larger footprint having homogenous and heterogeneous sub-pixels. Improved understanding of spatial variability of soil surface characteristics such as land cover and vegetation in larger footprint are critical in remote sensing based soil moisture retrieval. This study analyzes the sub-pixel variability (standard deviation of subgrid pixels) of Normalized Difference Vegetation Index and SAR backscatter. Backpropagation neural network was used for soil moisture retrieval from active microwave remote sensing data from Southern Great Plains of Oklahoma. The effect of land cover heterogeneity (number …