scholarly journals Estimating Hourly Full-Coverage PM2.5 Concentrations Based On MODIS Data Over The Northeast of Thailand.

2022 ◽  
Author(s):  
Wilawan Kumharn ◽  
Oradee Pilahome ◽  
Wichaya Ninsawan ◽  
Yuttapichai Jankondee
Keyword(s):  
Spatial Information ◽  
Specific Area ◽  
Predictive Performance ◽  
Plain Area ◽  
Spatial Coverage ◽  
Modis Aod ◽  
Moderate Resolution ◽  
Health Studies ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract Particulate matter (PM2.5) pollutants are a significant health issue with impacts on human health; however, monitoring of PM2.5 is very limited in developing countries. Satellite remote sensing can expand spatial coverage, potentially enhancing our ability in a specific area for estimating PM2.5; however, some have reported poor predictive performance. An innovative combination of MODIS AOD was developed to fulfill all missing aerosol optical depth (AOD) data obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS). Therefore, hourly PM2.5 concentrations were obtained in Northeastern Thailand. A Linear mixed-effects (LME) model was used to predict location-specific hourly PM2.5 levels. Hourly PM2.5 concentrations measured at 20 PM2.5 monitoring sites and 10- fold cross-validation were addressed for model validation. The observed and predicted concentrations suggested that LME obtained from MODIS AOD data and other factors are a potentially useful predictor of hourly PM2.5 concentrations (R2 >0.70), providing more detailed spatial information for local scales studies. Interestingly, PM2.5 along the Mekong River area was observed higher than in the plain area. The finding can infer that the monsoon wind brings polluted air into the province from sources outside the region. The results will be helpful to analyze air pollution-related health studies.

scholarly journals The Collection 6 MODIS aerosol products over land and ocean

2013 ◽  
Vol 6 (11) ◽  
pp. 2989-3034 ◽  
Author(s):  
R. C. Levy ◽  
S. Mattoo ◽  
L. A. Munchak ◽  
L. A. Remer ◽  
A. M. Sayer ◽  
...  
Keyword(s):  
Arid Land ◽  
Data Set ◽  
Deep Blue ◽  
New Information ◽  
Spatial Coverage ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Land Surfaces ◽  
Cloud Mask

Abstract. The twin Moderate resolution Imaging Spectroradiometer (MODIS) sensors have been flying on Terra since 2000 and Aqua since 2002, creating an extensive data set of global Earth observations. Here, we introduce the Collection 6 (C6) algorithm to retrieve aerosol optical depth (AOD) and aerosol size parameters from MODIS-observed spectral reflectance. While not a major overhaul from the previous Collection 5 (C5) version, there are enough changes that there are significant impacts to the products and their interpretation. The C6 aerosol data set will be created from three separate retrieval algorithms that operate over different surface types. These are the two "Dark Target" (DT) algorithms for retrieving (1) over ocean (dark in visible and longer wavelengths) and (2) over vegetated/dark-soiled land (dark in the visible), plus the "Deep Blue" (DB) algorithm developed originally for retrieving (3) over desert/arid land (bright in the visible). Here, we focus on DT-ocean and DT-land (#1 and #2). We have updated assumptions for central wavelengths, Rayleigh optical depths and gas (H2O, O3, CO2, etc.) absorption corrections, while relaxing the solar zenith angle limit (up to ≤ 84°) to increase poleward coverage. For DT-land, we have updated the cloud mask to allow heavy smoke retrievals, fine-tuned the assignments for aerosol type as function of season/location, corrected bugs in the Quality Assurance (QA) logic, and added diagnostic parameters such topographic altitude. For DT-ocean, improvements include a revised cloud mask for thin-cirrus detection, inclusion of wind speed dependence on the surface reflectance, updates to logic of QA Confidence flag (QAC) assignment, and additions of important diagnostic information. At the same time, we quantified how "upstream" changes to instrument calibration, land/sea masking and cloud masking will also impact the statistics of global AOD, and affect Terra and Aqua differently. For Aqua, all changes will result in reduced global AOD (by 0.02) over ocean and increased AOD (by 0.02) over land, along with changes in spatial coverage. We compared preliminary data to surface-based sun photometer data, and show that C6 should improve upon C5. C6 will include a merged DT/DB product over semi-arid land surfaces for reduced-gap coverage and better visualization, and new information about clouds in the aerosol field. Responding to the needs of the air quality community, in addition to the standard 10 km product, C6 will include a global (DT-land and DT-ocean) aerosol product at 3 km resolution.

scholarly journals Adaption of the MODIS aerosol retrieval algorithm using airborne spectral surface reflectance measurements over urban areas: a case study

2015 ◽  
Vol 8 (12) ◽  
pp. 5237-5249 ◽  
Author(s):  
E. Jäkel ◽  
B. Mey ◽  
R. Levy ◽  
X. Gu ◽  
T. Yu ◽  
...  
Keyword(s):  
Urban Areas ◽  
Retrieval Algorithm ◽  
Surface Reflectance ◽  
Airborne Measurements ◽  
Modis Aod ◽  
Urban Sample ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. MODIS (MOderate-resolution Imaging Spectroradiometer) retrievals of aerosol optical depth (AOD) are biased over urban areas, primarily because the reflectance characteristics of urban surfaces are different than that assumed by the retrieval algorithm. Specifically, the operational "dark-target" retrieval is tuned towards vegetated (dark) surfaces and assumes a spectral relationship to estimate the surface reflectance in blue and red wavelengths. From airborne measurements of surface reflectance over the city of Zhongshan, China, were collected that could replace the assumptions within the MODIS retrieval algorithm. The subsequent impact was tested upon two versions of the operational algorithm, Collections 5 and 6 (C5 and C6). AOD retrieval results of the operational and modified algorithms were compared for a specific case study over Zhongshan to show minor differences between them all. However, the Zhongshan-based spectral surface relationship was applied to a much larger urban sample, specifically to the MODIS data taken over Beijing between 2010 and 2014. These results were compared directly to ground-based AERONET (AErosol RObotic NETwork) measurements of AOD. A significant reduction of the differences between the AOD retrieved by the modified algorithms and AERONET was found, whereby the mean difference decreased from 0.27±0.14 for the operational C5 and 0.19±0.12 for the operational C6 to 0.10±0.15 and -0.02±0.17 by using the modified C5 and C6 retrievals. Since the modified algorithms assume a higher contribution by the surface to the total measured reflectance from MODIS, consequently the overestimation of AOD by the operational methods is reduced. Furthermore, the sensitivity of the MODIS AOD retrieval with respect to different surface types was investigated. Radiative transfer simulations were performed to model reflectances at top of atmosphere for predefined aerosol properties. The reflectance data were used as input for the retrieval methods. It was shown that the operational MODIS AOD retrieval over land reproduces the AOD reference input of 0.85 for dark surface types (retrieved AOD = 0.87 (C5)). An overestimation of AOD = 0.99 is found for urban surfaces, whereas the modified C5 algorithm shows a good performance with a retrieved value of AOD = 0.86.

scholarly journals A novel calibration approach of MODIS AOD data to predict PM<sub>2.5</sub> concentrations

2011 ◽  
Vol 11 (15) ◽  
pp. 7991-8002 ◽  
Author(s):  
H. J. Lee ◽  
Y. Liu ◽  
B. A. Coull ◽  
J. Schwartz ◽  
P. Koutrakis
Keyword(s):  
New England ◽  
Environmental Protection Agency ◽  
Measurement Errors ◽  
Epidemiological Studies ◽  
Cross Sectional ◽  
Spatial Coverage ◽  
Modis Aod ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Calibration Approach

Abstract. Epidemiological studies investigating the human health effects of PM2.5 are susceptible to exposure measurement errors, a form of bias in exposure estimates, since they rely on data from a limited number of PM2.5 monitors within their study area. Satellite data can be used to expand spatial coverage, potentially enhancing our ability to estimate location- or subject-specific exposures to PM2.5, but some have reported poor predictive power. A new methodology was developed to calibrate aerosol optical depth (AOD) data obtained from the Moderate Resolution Imaging Spectroradiometer (MODIS). Subsequently, this method was used to predict ground daily PM2.5 concentrations in the New England region. 2003 MODIS AOD data corresponding to the New England region were retrieved, and PM2.5 concentrations measured at 26 US Environmental Protection Agency (EPA) PM2.5 monitoring sites were used to calibrate the AOD data. A mixed effects model which allows day-to-day variability in daily PM2.5-AOD relationships was used to predict location-specific PM2.5 levels. PM2.5 concentrations measured at the monitoring sites were compared to those predicted for the corresponding grid cells. Both cross-sectional and longitudinal comparisons between the observed and predicted concentrations suggested that the proposed new calibration approach renders MODIS AOD data a potentially useful predictor of PM2.5 concentrations. Furthermore, the estimated PM2.5 levels within the study domain were examined in relation to air pollution sources. Our approach made it possible to investigate the spatial patterns of PM2.5 concentrations within the study domain.

scholarly journals INTER-COMPARISON BETWEEN MODIS SATELLITE-BASED AND AERONET GROUND-BASED AEROSOL OPTICAL DEPTH PRODUCTS IN VIETNAM

2020 ◽  
Vol 58 (3A) ◽  
pp. 124
Author(s):  
DUC LUONG NGUYEN ◽  
Thi Hieu Bui ◽  
Hoang Hiep Nguyen ◽  
Quang Trung Bui ◽  
Hoang Duong Do
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Subtropical Climate ◽  
Deep Blue ◽  
Modis Aod ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
First Time ◽  
Climatic Characteristics

Although a number of studies have extensively inter-compared the Moderate Resolution Imaging Spectroradiometer (MODIS) satellite-based aerosol optical depth (AOD) with the Aerosol Robotic Network (AERONET) ground-based AOD on both global and regional scales, almost no similar studies have been conducted for Vietnam - a humid subtropical climate region. For the first time, inter-comparison between the MODIS Terra and Aqua Collection 6.1 (C6.1) Dark Target (DT) 10 km, Deep Blue (DB) 10 km, and merged DT-DB 10 km with the AERONET AODs has been performed in different areas with different surface types and different climatic characteristics in Vietnam. Three investigated AERONET stations are Nghia Do (urban), Son La (mountainous rural), and Bac Lieu (coastal urban) with the studying periods of 2010 - 2016, 2012 - 2017, and 2010 - 2017, respectively. Our findings showed the better performances of DB algorithm than those of DT and DT-DB products in the urban area. Additionally, all MODIS AOD algorithm performed worse over the coastal area compared to those in the non-coastal areas. Generally, the ability of all the MODIS AODs to catch up the monthly-mean AERONET AODs has been expressed in this study.

scholarly journals Comparative analysis of MODIS, MISR, and AERONET climatology over the Middle East and North Africa

2019 ◽  
Vol 37 (1) ◽  
pp. 49-64 ◽  
Author(s):  
Ashraf Farahat
Keyword(s):  
Comparative Analysis ◽  
Middle East ◽  
North Africa ◽  
Geographic Location ◽  
Positive Trend ◽  
Data Sampling ◽  
Modis Aod ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Comparative analysis of Multi-angle Imaging SpectroRadiometer (MISR), Moderate Resolution Imaging Spectroradiometer (MODIS), and Aerosol Robotic Network (AERONET) aerosol optical depth (AOD) products is performed over seven AERONET stations located in the Middle East and North Africa for the period of 2000–2015. Sites are categorized into dust, biomass burning, and mixed aerosol conditions. MISR and MODIS AOD agree during high-dust seasons but MODIS tends to underestimate AOD during low-dust seasons. Over dust-dominated sites, MODIS/Terra AODs indicate a negative trend over time, while MODIS/Aqua, MISR, and AERONET depict a positive trend. A deviation between MODIS/Aqua and MODIS/Terra was observed regardless of the geographic location and data sampling. The performance of MODIS is similar over the entire region with ∼64 % of AOD within the Δτ=±0.05±0.15τAERO confidence range. MISR AOD retrievals fall within 84 % of the same confidence range for all sites examined here. Both MISR and MODIS capture aerosol climatology; however few cases were observed where one of the two sensors better captures the climatology over a certain location or AOD range than the other sensor. AERONET Level 2.0 version 3, MODIS Collection 6.1, and MISR V23 data have been used in analyzing the results presented in this study.

scholarly journals Cloud removal methodology from MODIS snow cover product

2009 ◽  
Vol 13 (7) ◽  
pp. 1361-1373 ◽  
Author(s):  
A. Gafurov ◽  
A. Bárdossy
Keyword(s):  
Snow Cover ◽  
Spatial Information ◽  
Ground Truth ◽  
Vegetation Period ◽  
Cloud Coverage ◽  
Average Accuracy ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Cloud Removal

Abstract. The Moderate Resolution Imaging Spectroradiometer (MODIS) employed by Terra and Aqua satellites provides spatially snow covered data with 500 m and daily temporal resolution. It delivers public domain data in raster format. The main disadvantage of the MODIS sensor is that it is unable to record observations under cloud covered regions. This is why this study focuses on estimating the pixel cover for cloud covered areas where no information is available. Our step to this product involves employing methodology based on six successive steps that estimate the pixel cover using different temporal and spatial information. The study was carried out for the Kokcha River basin located in northeastern part of Afghanistan. Snow coverage in catchments, like Kokcha, is very important where the melt-water from snow dominates the river discharge in vegetation period for irrigation purposes. Since no snow related observations were available from the region, the performance of the proposed methodology was tested using the cloud generated MODIS snow cover data as possible "ground truth" information. The results show successful performances arising from the methods applied, which resulted in all cloud coverage being removed. A validation was carried out for all subsequent steps, to be outlined below, where each step removes progressively more cloud coverage. Steps 2 to 5 (step 1 was not validated) performed very well with an average accuracy of between 90–96%, when applied one after another for the selected valid days in this study. The sixth step was the least accurate at 78%, but it led to the removal of all remaining cloud cover.

scholarly journals Improvement and Validation of NASA/MODIS NRT Global Flood Mapping

2019 ◽  
Vol 11 (2) ◽  
pp. 205 ◽  
Author(s):  
Li Lin ◽  
Liping Di ◽  
Junmei Tang ◽  
Eugene Yu ◽  
Chen Zhang ◽  
...  
Keyword(s):  
Information Science ◽  
Spatial Information ◽  
Standard Test ◽  
Crop Loss ◽  
Loss Assessment ◽  
Crop Loss Assessment ◽  
Spatial Information Science ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

The remote-sensing based Flood Crop Loss Assessment Service System (RF-CLASS) is a web service based system developed and managed by the Center for Spatial Information Science and Systems (CSISS). The system uses Moderate Resolution Imaging Spectroradiometer (MODIS)-based flood data, which was implemented by the Dartmouth Flood Observatory (DFO), to provide an estimation of crop loss from floods. However, due to the spectral similarity between water and shadow, a noticeable amount of false classification of shadow can be found in the DFO flood products. Traditional methods can be utilized to remove cloud shadow and part of mountain shadow. This paper aims to develop an algorithm to filter out noise from permanent mountain shadow in the flood layer. The result indicates that mountain shadow was significantly removed by using the proposed approach. In addition, the gold standard test indicated a small number of actual water surfaces were misidentified by the proposed algorithm. Furthermore, experiments also suggest that increasing the spatial resolution of the slope helped reduce more noise in mountains. The proposed algorithm achieved acceptable overall accuracy (>80%) in all different filters and higher overall accuracies were observed when using lower slope filters. This research is one of the very first discussions on identifying false flood classification from terrain shadow by using the highly efficient method.

scholarly journals Quantitative assessment of AOD from 17 CMIP5 models based on satellite-derived AOD over India

2016 ◽  
Vol 34 (8) ◽  
pp. 657-671 ◽  
Author(s):  
Amit Misra ◽  
Vijay P. Kanawade ◽  
Sachchida Nand Tripathi
Keyword(s):  
Interannual Variation ◽  
Correlation Coefficients ◽  
Quantitative Information ◽  
Cmip5 Models ◽  
Modis Aod ◽  
Longitudinal Variations ◽  
Different Seasons ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Aerosol optical depth (AOD) values from 17 CMIP5 models are compared with Moderate Resolution Imaging Spectroradiometer (MODIS) and Multiangle Imaging Spectroradiometer (MISR) derived AODs over India. The objective is to identify the cases of successful AOD simulation by CMIP5 models, considering satellite-derived AOD as a benchmark. Six years of AOD data (2000–2005) from MISR and MODIS are processed to create quality-assured gridded AOD maps over India, which are compared with corresponding maps of 17 CMIP5 models at the same grid resolution. Intercomparison of model and satellite data shows that model-AOD is better correlated with MISR-derived AOD than MODIS. The correlation between model-AOD and MISR-AOD is used to segregate the models into three categories identifying their performance in simulating the AOD over India. Maps of correlation between model-AOD and MISR-/MODIS-AOD are generated to provide quantitative information about the intercomparison. The two sets of data are examined for different seasons and years to examine the seasonal and interannual variation in the correlation coefficients. Latitudinal and longitudinal variations in AOD as simulated by models are also examined and compared with corresponding variations observed by satellites.

scholarly journals PMCAMx-2015 evaluation over Europe against AERONET and MODIS aerosol optical depth measurements

2016 ◽  
Author(s):  
Antigoni Panagiotopoulou ◽  
Panagiotis Charalambidis ◽  
Christos Fountoukis ◽  
Christodoulos Pilinis ◽  
Spyros N. Pandis
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Transport Model ◽  
Chemical Transport Model ◽  
The Balkans ◽  
Modis Aod ◽  
Moderate Resolution ◽  
Fractional Error ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. The ability of the chemical transport model (CTM) PMCAMx to reproduce aerosol optical depth (AOD) measurements by the Aerosol Robotic Network (AERONET) and the Moderate Resolution Imaging Spectroradiometer (MODIS) over Europe during a photochemically active period is evaluated. Periods with high dust levels are excluded so the analysis focuses on the ability of the model to simulate the mostly secondary aerosol and its interactions with water. PMCAMx reproduces the monthly mean MODIS and AERONET AOD values over the Iberian Peninsula, the British Isles, central Europe, and Russia with fractional bias less than 15 % and fractional error less than 30 %. However, the model overestimates the AOD over northern Europe probably due to an overestimation of organic aerosol and sulfates. On the other end, PMCAMx underestimates the monthly mean MODIS AOD over the Balkans, the Mediterranean, and the South Atlantic. These errors are probably due to an underestimation of sulfates. Sensitivity tests indicate that the evaluation results of the monthly mean AODs are quite sensitive to the relative humidity (RH) fields used by PMCAMx, but are not sensitive to the simulated size distribution and the black carbon mixing state.

scholarly journals An analysis of the collection 5 MODIS over-ocean aerosol optical depth product for its implication in aerosol assimilation

2011 ◽  
Vol 11 (2) ◽  
pp. 557-565 ◽  
Author(s):  
Y. Shi ◽  
J. Zhang ◽  
J. S. Reid ◽  
B. Holben ◽  
E. J. Hyer ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Surface Characteristics ◽  
Mean Square ◽  
Modis Aod ◽  
Moderate Resolution ◽  
Level 3 ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Empirical Corrections

Abstract. As an update to our previous use of the collection 4 Moderate Resolution Imaging Spectroradiometer (MODIS) over-ocean aerosol optical depth (AOD) data, we examined ten years of Terra and eight years of Aqua collection 5 data for its potential usage in aerosol assimilation. Uncertainties in the over-ocean MODIS AOD were studied as functions of observing conditions, such as surface characteristics, aerosol optical properties, and cloud artifacts. Empirical corrections and quality assurance procedures were developed and compared to collection 4 data. After applying these procedures, the Root-Mean-Square-Error (RMSE) in the MODIS Terra and Aqua AOD are reduced by 30% and 10–20%, respectively, with respect to AERONET data. Ten years of Terra and eight years of Aqua quality-assured level 3 MODIS over-ocean aerosol products were produced. The newly developed MODIS over-ocean aerosol products will be used in operational aerosol assimilation and aerosol climatology studies, as well as other research based on MODIS products.

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