Sea surface temperature retrieval using TRMM microwave imager satellite data in the South China Sea

The passive microwave TRMM Microwave Imager (TMI) sensor which is one of the payloads of the Tropical Rainfall Measurement Mission (TRMM) satellite was launched in 1997 by the National Aeronautics and Space Administration (NASA) and National Space Development Agency of Japan (NASDA). The TMI provides daily maps, 3 day average, weekly and monthly binary data via internet that can be used to retrieve geophysical parameters such as sea surface temperature (SST), 10 meter surface wind speed using 11 GHz channel, 10 meter surface wind speed using 37 GHz channel, atmospheric water vapour, liquid cloud water and precipitation rates. The SST study over the South China Sea was carried out using the 10.7 GHz channel of the TMI. The advantage of using this data is that the SST can be measured through clouds that are nearly transparent on this channel. This is a distinct advantage over the traditional infrared SST observations that require a cloud-free field of view. In this study, multitemporal TMI binary data were processed using FORTRAN Programming Language to evaluate the SST variations with time over the study area. The 3-day, weekly and monthly binary files are similar to the daily TMI binary files. All data consists of six maps with grid size of 0.25o by 0.25o and each file can be read as a 1440, 320, 6 array. For the data processing, the data values fall between 0 and 250 that need to be scaled to obtain meaningful geophysical data. The TMI scanning system causes striping that contains 0 or invalid data. In-situ temperature values were taken at locations where useful satellite data are available i.e. no striping. Regression analysis was carried out using the SST from TMI data and in-situ data obtained from the Meteorological Department of Malaysia. The two-dimensional scatter plot between TMI data and in-situ data gives a R2 value of 0.92 and RMSE of 0.3oC. The SST during the north east monsoon period was slightly lower than the SST during the south west monsoon. The study shows that TMI satellite data can be used to derive SST over large areas of the sea

Practical analytical backscatter error bars for elastic one-component lidar inversion algorithm

Postprint (published version

Morphological tools for range-interval segmentation of elastic lidar signals

This article presents a preliminary semi-automated range-interval segmentation toolset for the identification of: 1) the apparent range of full overlap, 2) the clear-sky level (i.e., the molecular level), and cloud layers (cloud-base, cloud-peak, and cloud-top range), and 3) apparent homogeneous extinction intervals.Peer ReviewedPostprint (published version

A short review on persistent scatterer interferometry techniques for surface deformation monitoring

Technology advancement has urged the development of Interferometric Synthetic Aperture Radar (InSAR) to be upgraded and transformed. The main contribution of the InSAR technique is that the surface deformation changes measurements can achieve up to millimetre level precision. Environmental problems such as landslides, volcanoes, earthquakes, excessive underground water production, and other phenomena can cause the earth's surface deformation. Deformation monitoring of a surface is vital as unexpected movement, and future behaviour can be detected and predicted. InSAR time series analysis, known as Persistent Scatterer Interferometry (PSI), has become an essential tool for measuring surface deformation. Therefore, this study provides a review of the PSI techniques used to measure surface deformation changes. An overview of surface deformation and the basic principles of the four techniques that have been developed from the improvement of Persistent Scatterer Interferometric Synthetic Aperture Radar (PSInSAR), which is Small Baseline Subset (SBAS), Stanford Method for Persistent Scatterers (StaMPS), SqueeSAR and Quasi Persistent Scatterer (QPS) were summarised to perceive the ability of these techniques in monitoring surface deformation. This study also emphasises the effectiveness and restrictions of each developed technique and how they suit Malaysia conditions and environment. The future outlook for Malaysia in realising the PSI techniques for structural monitoring also discussed in this review. Finally, this review will lead to the implementation of appropriate techniques and better preparation for the country's structural development

Comparison between the Kalman and the non-linear least-squares estimators in low signal-to-noise ratio lidar inversion

This works departs from previously published results of the authors and focus on joint estimation and time evolution of the atmospheric backscatter profile and a range-independent lidar ratio by means of 1) adaptive extended Kalman filtering (EKF) and 2) non-linear least-squares (NLSQ), under moderate-to-low signal-to-noise ratios (SNR<100 at the starting sounding range). A Rayleigh/Mie atmosphere and a calibrated lidar system are considered. Performance parameters studied are data sufficiency, tracking of the optical parameter time fluctuations, inversion errors, power estimation, and noise impact. The EKF inversion solution is, in turn, compared with Klett's method as a reference. Finally, it is shown that the EKF outweighs the NSLQ in noisy environments.Peer ReviewedPostprint (published version

On the lidar ratio estimation from the synergy between aeronet sun-photometer data and elastic lidar inversion

Postprint (published version

Lidar ratio estimation using a two-point calibration in an turbid layer aloft

Postprint (published version

A wind speed and fluctuation simulator for characterizing the wind lidar correlation method

Aerosol distribution in the atmosphere is used as a wind-tracer by lidars since it is drifted by the wind and respond to its changes. Two methods are used: the correlation and the Doppler method. This first one is easier and cheaper to implement than the latter. It makes it competitive for retrieving wind speed profiles or estimating wind turbulence. However, its accuracy decreases significantly as the distance from the optical radiation source increases, hence the need to characterize the method by means of wind field profile simulations and validate it by comparing the retrieval of real wind velocities with that of cooperative instruments such as radiosoundings. In this paper, the bases of a 2D lidar signal simulator are presented. The relationship between wind fields and the aerosol concentration dynamics, and the way they relate to lidar signal returns is explained. The first results of the application of the correlation method for the retrieval of wind velocities from real data at the UPC are presented and compared to radiosoundings measurements.Peer ReviewedPostprint (published version

Spatial and temporal variations of Biological Production in the Asia-Pacific Marginal Seas

This research project consists several main activities which are considered to be able to improve research capability in the Asia-Pacific region, especially in the collaborating countries. In terms of research, the project focused on discerning spatial and temporal variations of marine biological production in the Asia-Pacific marginal seas (the East China Sea, the South China Sea, the Strait of Malacca, and the Gulf of Thailand) utilizing multisensor satellite observations and coupled hydrodynamic-biogeochemical model. As part of the research achievements, one paper was accepted (in press) for publication in Remote Sensing. Other three or four papers are now under preparation for submission to high impact journals. To achieve research objectives, four (4) young scientists from collaborating countries were also involved in the project, that at once allowing them to improve their research capability and to enter international scientific community. In order to expand international networking and/or research collaboration in the near future, international mini-workshop on the western Pacific Ocean and marginal seas biogeochemical variability was also held in Japan Agency for Marine-Earth Science and Technology (JAMSTEC) in February 2014. As feedback of this research project and research continuation, it has been discussed and planned to propose Japan Society for the Promotion of Science (JSPS) Postdoctoral Fellowships for foreign researchers.Project Reference Number: ARCP2012-21NSY-Siswanto, Final Report submitted to APN ; The original publication is available at APN via http://www.apn-gcr.org/resources/items/show/176

Spatial Variability Assessment on The High-resolution Chlorophyll-a Extraction from Landsat 8 and Sentinel 2 Imageries in Johor Waters

High resolution Chlorophyll-a (Chl-a) can indicate the trophic status of the water and provide useful information on optical features of water body in water quality monitoring. Remote sensing has great potential to offer the spatial and temporal coverage needed. Over the last decades the SeaWIFS and MODIS were applied, but not suitable due to the low spatial resolution for monitoring Chl-a in coastal area. However, the retrieval of Chl-a in the coastal region is usually challenging due to the other in-water substances regardless of Chl-a, hence resulting in the satellite retrieved Chl-a overestimation. By the advancement of the Sentinel-2 and Landsat 8 satellites, continuous high resolution optical imageries have served for remarkable coastal mapping capability thanks to the spectroscopic capability certain spectral bands and as high as 10-meter spatial resolution. This paper aims to evaluate the performance of the SEADASS and SNAP processor for Chl-a estimation from the Operational Land Imager (OLI) and MultiSpectral Instrument (MSI) data in Johor waters. The representative models, in standard algorithm OC3 and C2RCC, were adapted to retrieve Chl-a concentration. The statistical regression has shown that these algorithms give an acceptable Chl-a estimation at medium and high resolution with R2 = 0.44 from OC3 and R2 = 0.55 from C2RCC comparing to the in-situ data. Despite of the spatial, temporal and spectral variability, this paper shows that OLI and MSI could provide Chl-a mapping capability at suitable Chl-a estimation techniques