Wide Spatial Coverage Research Articles

Warm ionized gas in CALIFA early-type galaxies

The morphological, spectroscopic and kinematical properties of the warm interstellar medium (wim) in early-type galaxies (ETGs) hold key observational constraints to nuclear activity and the buildup history of these massive, quiescent systems. High-quality integral field spectroscopy (IFS) data with a wide spectral and spatial coverage, such as those from the CALIFA survey, offer an unprecedented opportunity for advancing our understanding of the wim in ETGs. This article centers on a 2D investigation of the wim component in 32 nearby (<~150Mpc) ETGs from CALIFA, complementing a previous 1D analysis of the same sample (Papaderos et al. 2013; P13). We include here H\alpha\ intensity and equivalent width (EW) maps and radial profiles, diagnostic emission-line ratios, besides ionized-gas and stellar kinematics. This study is supplemented by \tau-ratio maps as an efficient means to quantify the role of photoionization by pAGB stars, as compared to other mechanisms (e.g., AGN, low-level star formation). Additionally, we extend the tentative classification proposed in P13 by the type i+, which is assigned to a subset of type i ETGs exhibiting ongoing low-level star-formation (SF) in their periphery. This finding along with faint traces of localized SF in the extranuclear component of several of our sample ETGs points to a non-negligible contribution by OB stars to the total ionizing budget. We also demonstrate that, at the typical emission-line detection threshold of ~2\AA in previous studies, most of the extranuclear wim emission in an ETG may evade detection, which could in turn prompt its classification as an entirely gas-devoid system. This study adds further observational evidence for a considerable heterogeneity among ETGs with regard to the physical properties and 2D kinematics of the wim component, and underscores the importance of IFS studies over their entire optical extent.

Dynamics of Snake-like Swarming Behavior of Vibrio alginolyticus

Swarming represents a special case of bacterial behavior where motile bacteria migrate rapidly and collectively on surfaces. Swarming and swimming motility of bacteria has been studied well for rigid, self-propelled rods. In this study we report a strain of Vibrio alginolyticus, a species that exhibits similar collective motility but a fundamentally different cell morphology with highly flexible snake-like swarming cells. Investigating swarming dynamics requires high-resolution imaging of single cells with coverage over a large area: thousands of square microns. Researchers previously have employed various methods of motion analysis but largely for rod-like bacteria. We employ temporal variance analysis of a short time-lapse microscopic image series to capture the motion dynamics of swarming Vibrio alginolyticus at cellular resolution over hundreds of microns. Temporal variance is a simple and broadly applicable method for analyzing bacterial swarming behavior in two and three dimensions with both high-resolution and wide-spatial coverage. This study provides detailed insights into the swarming architecture and dynamics of Vibrio alginolyticus isolate B522 on carrageenan agar that may lay the foundation for swarming studies of snake-like, nonrod-shaped motile cell types.

Challenges and successes in engaging citizen scientists to observe snow cover: from public engagement to an educational collaboration

Whereas the evolution of snow cover across forested mountain watersheds is difficult to predict or model accurately, the presence or absence of snow cover is easily observable and these observations contribute to improved snow models. We engaged citizen scientists to collect observations of the timing of distributed snow disappearance over three snow seasons across the Pacific Northwest, U.S.A. . The primary goal of the project was to build a more spatially robust dataset documenting the influence of forest cover on the timing of snow disappearance, and public outreach was a secondary goal. Each year's effort utilized a different strategy, building on the lessons of the previous year. We began by soliciting our professional networks to contribute observations via electronic or paper forms, moved to a public outreach effort to collect geotagged photographs, and finally settled on close collaboration with an outdoor science school that was well-positioned to collect the needed data. Whereas the outreach efforts garnered abundant enthusiasm and publicity, the resulting datasets were sparse. In contrast, direct collaboration with an outdoor science school that was already sending students to make weekly snow observations proved fruitful in both data collection and educational outreach. From a data collection standpoint, the shift to an educational collaboration was successful because it essentially traded wide spatial coverage combined with sparse temporal coverage for dense temporal coverage at a single, but important location. From a public engagement standpoint, the partnership allowed for more intensive participation by more people and enhanced the science curriculum at the collaborating school.

Whole-brain perfusion imaging with balanced steady-state free precession arterial spin labeling.

Recently, balanced steady-state free precession (bSSFP) readout has been proposed for arterial spin labeling (ASL) perfusion imaging to reduce susceptibility artifacts at a relatively high spatial resolution and signal-to-noise ratio (SNR). However, the main limitation of bSSFP-ASL is the low spatial coverage. In this work, methods to increase the spatial coverage of bSSFP-ASL are proposed for distortion-free, high-resolution, whole-brain perfusion imaging. Three strategies of (i) segmentation, (ii) compressed sensing (CS) and (iii) a hybrid approach combining the two methods were tested to increase the spatial coverage of pseudo-continuous ASL (pCASL) with three-dimensional bSSFP readout. The spatial coverage was increased by factors of two, four and six using each of the three approaches, whilst maintaining the same total scan time (5.3 min). The number of segments and/or CS acceleration rate (R) correspondingly increased to maintain the same bSSFP readout time (1.2 s). The segmentation approach allowed whole-brain perfusion imaging for pCASL-bSSFP with no penalty in SNR and/or total scan time. The CS approach increased the spatial coverage of pCASL-bSSFP whilst maintaining the temporal resolution, with minimal impact on the image quality. The hybrid approach provided compromised effects between the two methods. Balanced SSFP-based ASL allows the acquisition of perfusion images with wide spatial coverage, high spatial resolution and SNR, and reduced susceptibility artifacts, and thus may become a good choice for clinical and neurological studies. Copyright © 2015 John Wiley & Sons, Ltd.

Spatial representativeness of air quality monitoring stations: A grid model based approach

A methodology for quantifying areas of spatial representativeness of air quality monitoring station is here proposed, exploiting the wide spatial and temporal coverage of chemical transport models results. The method is based on the analysis of time series of model concentrations, extracted at monitoring sites and around, by means of a Concentration Similarity Function (CSF). The method was tested on AMS-MINNI model results, covering Italy and three reference years (2003, 2005, 2007), for assessing the spatial representativeness of PM2.5 and O3 rural background monitoring stations. The CSF methodology shows good performances in describing both the extension and the shape of representativeness areas, taking into account the difference between pollutants and the dependence on averaging time and temporal interval of concentration data. Results show a large variability in the size and shape of the selected stations in Italy, ranging from 220 to 4500 km2. This confirms the importance of carrying out ad-hoc analyses on monitoring stations, as general a priori classifications and qualitative assessments of spatial representativeness are not able to fully capture the complexity of different territorial contexts.

IDENTIFICATION AND CLASSIFICATION OF LAKE BOTTOM SURFACE AND AQUATIC VEGETATION IN LAUT TAWAR LAKE, ACEH

Identification and classification of benthic habitats in Lake of Laut Tawar, Aceh by using hydro acoustic method can provide data and information on types of substrate and aquatic vegetation in a short time and wide spatial coverage, as done in the present work. Data acoustic collection was performed in 2013 using quantitative echosounder with split beam frequency of 120 kHz, and through a visual observation. The later is destined to look at the bottom types and macrophytes that lie on the line transect of acoustic survey. Analysis of data is to extract the value of bottom volume backscattering for each transect of 0.5-1 km. Classification of the bottom type was done based on the value of Sv using geospatial models. Results show the interval value of Sv for soft bottom ranged between -24.00 dB and -32.00 dB, the type of hard bottom (e.g. rocks, rocky sand substrate) ranged between -14.00 dB and -22.00 dB, whereas the Sv value of macrophyte ranged between- 45.00 dB and -54.00 dB. The percent covers were about 42.90%, 44.71% and 12.93% for hard bottom type, soft bottom and macrophytes, respectively. The types of aquatic vegetation commonly found in the lake were two genera belonging Hydrocharitaceaea and Gramineae. The current work is still lack of information on the classification of organisms into genera scales. Therefore, more signal verification and algorithms verification would be needed in order to estimate macrophytes biomass by comparing with other visual observation.

Quadruple‐feed beam‐controlled antenna array for the localisations of ultra‐high‐frequency radio‐frequency identification tags

Item-level tagging has been required to the retail market with densely placed items as well as the production line. Owing to the multi-path fading, the blind spots where the tag is non-responsive can be created. Furthermore, in case of the indoor radio-frequency identification (RFID) localisation system, additional circuits and localisation algorithms are indispensable for accurate localisation of RFID tags. In this study, in order to solve this problem, the beam-controlled antenna array with a quadruple beamforming network which generates multiple beams is presented for ultra-high-frequency (UHF) RFID systems. The proposed quadruple-feed antenna array can cover the wide spatial coverage, and the main beam directions of the proposed array can be controlled by selecting the appropriate input port of the quadruple network. The fabricated antenna array with the quadruple-feed network operates at the 902-928 MHz band and produces scannable multiple beams for UHF RFID localisation system within the wide interrogation zone.

Validation of CM SAF Surface Solar Radiation Datasets over Finland and Sweden

Accurate determination of the amount of incoming solar radiation at Earth’s surface is important for both climate studies and solar power applications. Satellite-based datasets of solar radiation offer wide spatial and temporal coverage, but careful validation of their quality is a necessary prerequisite for reliable utilization. Here we study the retrieval quality of one polar-orbiting satellite-based dataset (CLARA-A1) and one geostationary satellite-based dataset (SARAH), using in situ observations of solar radiation from the Finnish and Swedish meteorological measurement networks as reference. Our focus is on determining dataset quality over high latitudes as well as evaluating daily mean retrievals, both of which are aspects that have drawn little focus in previous studies. We find that both datasets are generally capable of retrieving the levels and seasonal cycles of solar radiation in Finland and Sweden well, with some limitations. SARAH exhibits a slight negative bias and increased retrieval uncertainty near the coverage edge, but in turn offers better precision (less scatter) in the daily mean retrievals owing to the high sampling rate of geostationary imaging.

Localized polar cap flow enhancement tracing using airglow patches: Statistical properties, IMF dependence, and contribution to polar cap convection

AbstractRecent radar observations have suggested that polar cap flows are highly structured and that localized flow enhancements can lead to nightside auroral disturbances. However, knowledge of these flows is limited to available echo regions. Utilizing wide spatial coverage by an all‐sky imager at Resolute Bay and simultaneous Super Dual Auroral Radar Network measurements, we statistically determined properties of such flows and their interplanetary magnetic field (IMF) dependence. We found that narrow flow enhancements are well collocated with airglow patches with substantially larger velocities (≥200 m/s) than the weak large‐scale background flows. The flow azimuthal widths are similar to the patch widths. During the evolution across the polar cap, the flow directions and speeds are consistent with the patch propagation directions and speeds. These correspondences indicate that patches can optically trace localized flow enhancements reflecting the flow width, speed, and direction. Such associations were found common (~67%) in statistics, and the typical flow speed, propagation time, and width within our observation areas are 600 m/s, tens of minutes, and 200–300 km, respectively. By examining IMF dependence of the occurrence and properties of these flows, we found that they tend to be observed under By‐dominated IMF. Flow speeds are large under oscillating IMF clock angles. Localized flow enhancements are usually observed as a channel elongated in the noon‐midnight meridian and directed toward premidnight (postmidnight) for +By (−By). The potential drops across localized flow enhancements account for ~10–40% of the cross polar cap potential, indicating that they significantly contribute to polar cap plasma transport.

Seasonal and Spatial Variability of SST Using MODIS Data: the Case Study of Aegean Sea

This paper focuses on the analysis of spatial and temporal variability of Sea Surface Temperature (SST) derived from Aqua Moderate Imaging Spectrometer (MODIS) infrared imagery in the Aegean Sea. Data were organized to examine both seasonal and monthly variation of SST during 2005 - 2008. The four year period was chosen as a first approach to address and describe this phenomenon. A descriptive statistical analysis was performed, while hot spots and SST anomalies for each month and season were identified. The results show a smooth monthly variation of SST with February to be the coldest month while July the hottest as expected. The year with the higher average SST value was 2007 with 25.1 o C while 2006 presents the minimum average value. In addition, the high resolution maps of 1 km that extracted from the analysis with a wide spatial coverage, allows to the detail representation of SST in the region. This helps to produce a rich eddy field and it allows monitoring the outflow of Black Sea Waters through the Dardanelles Strait.

Geology of the Dhaulagiri-Annapurna-Manaslu Himalaya, Western Region, Nepal. 1:200,000

Geological mapping of mountains belts is fundamental to understanding their structure and evolution. Here, a 1:200,000 scale geological map of the central Himalaya of Western Region, Nepal is presented. This map represents a compilation of previously published maps, integrated with new geological field data. The wide spatial coverage of the map and the accompanying cross sections reveal the detailed structure of the Dhaulagiri-Annapurna-Manaslu Himalaya. The addition of modern topographic and infrastructure data makes this map suitable for navigation through the region.

Simulation of the capabilities of an orbiter for monitoring the entry of interplanetary matter into the terrestrial atmosphere

In comparison with existing ground-based camera networks for meteors monitoring, a space-based optical system would escape dependency on weather and atmospheric conditions and would offer a wide spatial coverage and an unrestricted and extinction-free spectral domain. The potential rates of meteor detections by such systems are evaluated in this paper as a function of observations parameters (optical system capabilities, orbital parameters) and considering a reasonable range of meteoroids properties (e.g., mass, velocity, composition) determining their luminosity. A numerical tool called SWARMS (Simulator for Wide Area Recording of Meteors from Space) has been developed. SWARMS is also intended to be used in an operational phase to facilitate the comparison of observations with up-do-date constraints on the flux and characteristics of the interplanetary matter entering our planet׳s atmosphere. The laws governing the conversion of a fraction of the meteor kinetic energy into radiation during atmospheric entry have been revisited and evaluated based on an analysis of previously published meteor trajectories. Rates of detection were simulated for two different systems: the SPOSH (Smart Panoramic Optical Sensor Head) camera optimized for the observation of transient luminous events, and the JEM-EUSO (Japanese Experiment Module-Extreme Universe Space Observatory) experiment on the ISS (International Space Station). We conclude that up to 6 events per hour in the case of SPOSH, and up to 0.67 events in the case of JEM-EUSO may be detected. The optimal orbit for achieving such rates of detections depends on the mass index of the meteoroid populations. The determination of this parameter appears therefore critical before an optimal orbiting system might be designed for meteors monitoring.

Deriving Changjiang coastal zone wind from C-band SAR and its application to salinity simulation

Wind plays an important role in hydrodynamic processes such as the expansion of Changjiang (Yangtze) River Diluted Water (CDW), and shelf circulation in the Changjiang estuary. Thus, it is essential to include wind in the numerical simulation of these phenomena. Synthetic aperture radar (SAR) with high resolution and wide spatial coverage is valuable for measuring spatially inhomogeneous ocean surface wind fields. We have collected 87 ERS-2 SAR images with wind-induced streaks that cover the Changjiang coastal area, to verify and improve the validity of wind direction retrieval using the 2D fast Fourier transform method. We then used these wind directions as inputs to derive SAR wind speeds using the C-band model. To demonstrate the applicability of the algorithms, we validated the SAR-retrieved wind fields using QuikSCAT measurements and the atmospheric Weather Research Forecasting model. In general, we found good agreement between the datasets, indicating the reliability and applicability of SAR-retrieved algorithms under different atmospheric conditions. We investigated the main error sources of this process, and conducted sensitivity analyses to estimate the wind speed errors caused by the effect of speckle, uncertainties in wind direction, and inaccuracies in the normalized radar cross section. Finally, we used the SAR-retrieved wind fields to simulate the salinity distribution off the Changjiang estuary. The findings of this study will be valuable for wind resource assessment and the development of future numerical ocean models based on SAR images.

Extended nebular emission in CALIFA early-type galaxies

AbstractThe morphological, spectroscopic and kinematical properties of the warm interstellar medium (wim) in early-type galaxies (ETGs) hold key observational constraints to nuclear activity and the buildup history of these massive quiescent systems. High-quality integral field spectroscopy (IFS) data with a wide spectral and spatial coverage, such as those from the CALIFA survey, offer a precious opportunity for advancing our understanding in this respect. We use deep IFS data from CALIFA (califa.caha.es) to study thewimover the entire extent and optical spectral range of 32 nearby ETGs. We find that all ETGs in our sample show faint (Hα equivalent width EW(Hα)∼0.5 … 2 Å) extranuclear nebular emission extending out to ≥2 Petrosian50radii. Confirming and strengthening our conclusions in Papaderoset al. (2013, hereafter P13) we argue that ETGs span a broadcontinuoussequence with regard to the properties of theirwim, and they can be roughly subdivided into two characteristic classes. The first one (type i) comprises ETGs with a nearly constant EW(Hα)∼1–3 Å in their extranuclear component, in quantitative agreement with (even though, no proof for) the hypothesis of photoionization by the post-AGB stellar component being the main driver of extendedwimemission. The second class (type ii) consists of virtuallywim-evacuated ETGs with a large Lyman continuum (Lyc) photon escape fraction and a very low (≤0.5 Å) EW(Hα) in their nuclear zone. These two ETG classes appear indistinguishable from one another by their LINER-specific emission-line ratios. Additionally, here we extend the classification by P13 by the class i+ which stands for a subset of type i ETGs with low-level star-forming activity in contiguous spiral-arm like features in their outermost periphery. These faint features, together with traces of localized star formation in several type i&amp;i+ systems point to a non-negligible contribution from young massive stars to the global ionizing photon budget in ETGs.

Examinations of cloud variability and future change in the coupled model intercomparison project phase 3 simulations

Low-level cloud variability is critical to the radiation balance of Earth due to its wide spatial coverage. Using the adjusted International Satellite Cloud Climatology Project (ISCCP) observations of Clement et al. (2009), and the Coupled Model Intercomparison Project Phase 3 (CMIP3) model simulations, this study examines the observed and the simulated low-cloud variations and their relationships with large-scale environmental variables. From the observational analysis, significant correlations are found between low clouds and those of sea surface temperature (SST), lower tropospheric stability (LTS), and sea level pressure (SLP) over tropical marine areas of low cloud prevailing regions during most of the year. Increase of SST coincides with the reduction of LTS and increased vertical motion, which tends to reduce low-level clouds in subtropical oceans. Among the 14 models investigated, CGCM3 and HadGEM1 exhibit more realistic representation of the observed relationship between low-level clouds and large-scale environments. In future climate projection, these two models show a good agreement in the reduction of low-cloud throughout much of the global oceans in response to greenhouse gas forcing, suggesting a positive low-cloud feedback in a climate change context.

Using delta generalized additive models to produce distribution maps for spatially explicit ecosystem models

Spatial ecosystem models, such as OSMOSE, have become integral tools in achieving ecosystem-based management for their ability to thoroughly describe predator–prey dynamics in a spatially explicit context. Distribution maps, which define the initial spatial allocation of functional groups abundance, can have a large effect on the predator–prey dynamics that spatially explicit ecosystem models simulate. Here, we introduce the delta GAM approach we developed to be able to produce distribution maps for an OSMOSE model of the West Florida Shelf (Gulf of Mexico), OSMOSE-WFS. This delta GAM approach predicts the spatial distribution of different life stages of the multiple functional groups represented in OSMOSE-WFS (‘life-stage groups’) at different seasons, over the entire Gulf of Mexico (GOM) shelf including areas where abundance estimates do not exist, using different research survey datasets and regional environmental and habitat features. Our delta GAM approach consists of fitting two independent models, a binomial GAM and a quasi-Poisson GAM, whose predictions are then combined using the delta method to yield spatial abundance estimates. To validate delta GAMs, bootstraps are used and Spearman's correlation coefficients (Spearman's ρ’s) between predicted and observed abundance values are estimated and tested to be significantly different from zero. We use pink shrimp (Farfantepenaeus duorarum) to demonstrate our delta GAM approach by predicting the summer distribution of this species over the GOM shelf and the West Florida Shelf. Predictions of the delta GAM reflect existing empirical research related to pink shrimp habitat preferences and predictions of a negative binomial GAM previously designed for the GOM. We find that using a delta rather than a negative binomial GAM saves significant computation time at the expense of a slight reduction in GAM performance. A positive and highly significant Spearman's ρ between observed and predicted abundance values indicates that our delta GAM can reliably be used to predict pink shrimp spatial distribution. Spearman's ρ was also positive and highly significant in every life-stage group represented in OSMOSE-WFS and season, though often low. Therefore, delta GAMs fitted for the different life-stage groups and seasons correctly predict qualitative differences between low- and high-abundance areas and are deemed appropriate for generating distribution maps for OSMOSE-WFS. The delta GAM approach we developed is a simple, convenient method to create distribution maps to be fed into spatially explicit ecosystem models, where wide spatial and taxonomic coverage is desired while benefits of high precision estimates are lost at run-time.

New Approach for Unambiguous High-Resolution Wide-Swath SAR Imaging

The high-resolution wide-swath (HRWS) SAR system uses a small antenna for transmitting waveform and multiple antennas both in elevation and azimuth for receiving echoes. It has the potential to achieve wide spatial coverage and fine azimuth resolution, while it suffers from elevation pattern loss caused by the presence of topographic height and impaired azimuth resolution caused by nonuniform sampling. A new approach for HRWS SAR imaging based on compressed sensing (CS) is introduced. The data after range compression of multiple elevation apertures are used to estimate direction of arrival (DOA) of targets via CS, and the adaptive digital beamforming in elevation is achieved accordingly, which avoids the pattern loss of scan-on-receive (SCORE) algorithm when topographic height exists. The effective phase centers of the system are nonuniformly distributed when displaced phase center antenna (DPCA) technology is adopted, which causes Doppler ambiguities under traditional SAR imaging algorithms. Azimuth reconstruction based on CS can resolve this problem via precisely modeling the nonuniform sampling. Validation with simulations and experiment in an anechoic chamber are presented.

Feasibility of using Geostationary Ocean Colour Imager (GOCI) data for land applications after atmospheric correction and bidirectional reflectance distribution function modelling

Korea's Geostationary Ocean Colour Imager (GOCI) has very high temporal resolution as well as wide spatial coverage. There is thus great interest in testing its applicability for monitoring land areas in addition to ocean areas. GOCI has eight spectral bands, from blue to near-infrared. These bands can be sensitive to vegetation change, but their wavelength ranges are slightly different from those of the extensively studied Moderate Resolution Imaging Spectroradiometer (MODIS). This study examines whether GOCI data can be applied for land monitoring and how GOCI data should be processed so as to reflect the spectral characteristics of land surfaces as detected by polar-orbit satellite sensors. Several image processing steps were performed for the GOCI data, including atmospheric correction and semi-empirical bidirectional reflectance distribution function modelling, before the results were compared with the MODIS land-surface product. Among the four GOCI normalized difference vegetation index (NDVI) products tested in this study, the GOCI NDVI with viewing-angle-adjusted reflectance showed the best agreement with MODIS NDVI calculated from normalized reflectance, with the lowest root mean square error of 0.126. Additionally, its temporal trends over forest and mixed vegetation areas were similar to those of MODIS NDVI during the study period from September to December.

On the characteristics of earthquake stress release variations in Japan

The amount of stress released during earthquakes is a fundamental characteristic of the earthquake rupture process. As such, it represents a key parameter for improving our understanding of earthquake source physics and for reliable ground motion prediction. Large earthquake populations usually show variations in stress release as large as three orders of magnitude, but the underlying mechanisms have remained largely elusive, and particularly the dependence of stress release on earthquake size is still a matter of debate. Here I use a unique dataset from Japan encompassing earthquakes of a wide magnitude range and spatial coverage to show that stress release variations of crustal earthquakes are strongly correlated with heat flow variations, indicating that they are thermally controlled. In contrast, subcrustal events depict highest stress release in regions of strong subduction-interface coupling and overall less pronounced variability as compared with crustal earthquakes. Stress release is overall only weakly dependent on earthquake size, but at local scales (i.e., within individual earthquake sequences) the dependence can be very strong and apparently varies with stress regime. Accounting for these systematic variations reduces the stress release variability on local scale by a factor of two to three as compared with the full earthquake population, a finding that is of key significance in the endeavor to reduce the uncertainties in future ground motion predictions.

A robust calibration approach for PM&amp;lt;sub&amp;gt;10&amp;lt;/sub&amp;gt; prediction from MODIS aerosol optical depth

Abstract. Investigating the human health effects of atmospheric particulate matter (PM) using satellite data are gaining more attention due to their wide spatial coverage and temporal advantages. Such epidemiological studies are, however, susceptible to bias errors and resulted in poor predictive output in some locations. Current methods calibrate aerosol optical depth (AOD) retrieved from MODIS to further predict PM. The recent satellite-based AOD calibration uses a mixed effects model to predict location-specific PM on a daily basis. The shortcomings of this daily AOD calibration are for areas of high probability of persistent cloud cover throughout the year such as in the humid tropical region along the equatorial belt. Contaminated pixels due to clouds causes radiometric errors in the MODIS AOD, thus causes poor predictive power on air quality. In contrary, a periodic assessment is more practical and robust especially in minimizing these cloud-related contaminations. In this paper, a simple yet robust calibration approach based on monthly AOD period is presented. We adopted the statistical fitting method with the adjustment technique to improve the predictive power of MODIS AOD. The adjustment was made based on the long-term observation (2001–2006) of PM10-AOD residual error characteristic. Furthermore, we also incorporated the ground PM measurement into the model as a weighting to reduce the bias of the MODIS-derived AOD value. Results indicated that this robust approach with monthly AOD calibration reported an improved average accuracy of PM10 retrieval from MODIS data by 50% compared to widely used calibration methods based on linear regression models, in addition to enabling further spatial patterns of periodic PM exposure to be undertaken.