- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
A Geographically and Temporally Weighted Regression Model for Ground-Level PM2.5 Estimation from Satellite-Derived 500 m Resolution AOD
摘要： Regional haze episodes have occurred frequently in eastern China over the past decades. As a critical indicator to evaluate air quality, the mass concentration of ambient fine particulate matters smaller than 2.5 μm in aerodynamic diameter (PM2.5) is involved in many studies. To overcome the limitations of ground measurements on PM2.5 concentration, which is featured in disperse representation and coarse coverage, many statistical models were developed to depict the relationship between ground-level PM2.5 and satellite-derived aerosol optical depth (AOD). However, the current satellite-derived AOD products and statistical models on PM2.5–AOD are insufficient to investigate PM2.5 characteristics at the urban scale, in that spatial resolution is crucial to identify the relationship between PM2.5 and anthropogenic activities. This paper presents a geographically and temporally weighted regression (GTWR) model to generate ground-level PM2.5 concentrations from satellite-derived 500 m AOD. The GTWR model incorporates the SARA (simplified high resolution MODIS aerosol retrieval algorithm) AOD product with meteorological variables, including planetary boundary layer height (PBLH), relative humidity (RH), wind speed (WS), and temperature (TEMP) extracted from WRF (weather research and forecasting) assimilation to depict the spatio-temporal dynamics in the PM2.5–AOD relationship. The estimated ground-level PM2.5 concentration has 500 m resolution at the MODIS satellite's overpass moments twice a day, which can be used for air quality monitoring and haze tracking at the urban and regional scale. To test the performance of the GTWR model, a case study was carried out in a region covering the adjacent parts of Jiangsu, Shandong, Henan, and Anhui provinces in central China. A cross validation was done to evaluate the performance of the GTWR model. Compared with OLS, GWR, and TWR models, the GTWR model obtained the highest value of coefficient of determination (R2) and the lowest values of mean absolute difference (MAD), root mean square error (RMSE), and mean absolute percentage error (MAPE).
关键词： GTWR model,SARA AOD,hourly ground-level PM2.5 concentration,500 m resolution,MODIS,AERONET
更新于2025-09-23 15:23:52
-
Evaluating MODIS and MISR aerosol optical depth retrievals over environmentally distinct sites in Pakistan
摘要： The Moderate resolution Imaging SpectroRadiometer (MODIS) and Multi-angle Imaging SpectroRadiometer (MISR) sensors provide aerosol observations suitable for a wide range of applications. The recently released MODIS Collection 6.1 (C061) includes several improvements compared to the previous products which are expected to minimize uncertainties in aerosol retrievals. Such collection needs to be validated and compared with previous collections form the same or other sensors before being applied for further scientific research on a regional scale. This study evaluates the performance of MODIS Collections 6 (C006) and 6.1 (C061) based on two algorithms: Dark Target (DT) and Deep Blue (DB) and the merged product (DTB) onboard the Terra (MOD04) and Aqua (MYD04) satellites, and the MISR AOD retrievals against ground-based Aerosol Robotic Network (AERONET) over two sites (Lahore and Karachi) in Pakistan during 2007–2014. Results elucidated that C061 MODIS AOD exhibited significant improvement as compared to C006, with the 10 km DT (DB) products generally overestimating (underestimating) AOD relative to AERONET AOD. The MOD04 and MYD04-DT and DB (3 and10 km) showed comparable performance over the two sites, whereas The DTB was dominated by DT (DB) pixels over Lahore (Karachi). The MISR showed better performance over Karachi with high reflecting surface than over Lahore with dense vegetation cover. The annual cycle of AOD retrieved by the two sensors were consistent with AERONET AOD, with maximum AOD observed during summer months attributed to prevailing climatic conditions. On seasonal basis, the MODIS algorithms exhibited improved performance over Lahore except during summer where DT and DTB showed relatively low performance, attributed to modulations induced by local meteorology to the prevailing surface conditions. However, the sensors exhibited distinct performance over Karachi, where MODIS-DT (10 km) showed close correspondence with AERONET during autumn and winter, whereas MODIS-DT (3 km) exhibited the converse. The MISR performed relatively well during spring over the two stations. The study gives greater insights on the performance of MODIS and MISR and forms the basis for further research on the validation of satellite derived aerosol products over Pakistan.
关键词： AOD,MISR,MODIS,AERONET
更新于2025-09-23 15:23:52
-
Aerosol uncertainty assessment: an integrated approach of remote AQUA MODIS and AERONET data
摘要： The moderate resolution imaging spectroradiometer (MODIS) is one of the widely used sensors to address environmental and climate change subjects with a daily global coverage. MODIS Collection 6 aerosol products at 10-km resolution are used in this study to monitor aerosol variability and assess its uncertainty using ground-based measurements. The aerosol optical depth (AOD) is retrieved by different algorithms based on the pixel surface, determining between land and ocean. Using data collected from Sidi Salem Aerosol Robotic Network (AERONET) station, we computed the accuracy for aerosol optical depth (AOD) retrieved from MODIS aboard the AQUA satellite using two validation methods. The results show a good agreement between MODIS and AERONET data for the study period using both the algorithms. We obtained high values of the correlation coefficient. These findings indicate that MODIS data perform well over Ben Salem AERONET station and are recommended for air quality monitoring over Tunisia. The conducted validation throughout the AERONET leads to a degree of confidence that allows a deep investigation of the AOD spatial variability over Tunisia. Then, MODIS data shows high performance with good certainty to identify the principal dust sources and typical transport paths occurring on the study region.
关键词： AQUA,Remote sensing,AOD,AERONET,Aerosol,MODIS
更新于2025-09-23 15:23:52
-
[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Assessment of Satellite Aerosol Optical Depth to Estimate Particulate Matter Distribution in Valencia City
摘要： The estimation of exposure to PM10 and PM2.5 requires the knowledge of surface concentration at high temporal and spatial resolutions. In this paper, the relation between PM10 and PM2.5 ground data and MODIS AOD satellite data has been evaluated to determine the concentration of particulate matter in Valencia, Spain. This was done using data from the Valencian Network of Surveillance and Control of Air Pollution and the scientific data set "Optical Depth Land and Ocean" from MODIS Terra and Aqua with 3km of spatial resolution. The linear regression model for PM10 provided a regression slope of 25.99 μg.m-3 and an interception of 12.07 μg.m-3 (RMSE = 8.61 μg.m-3), while for PM2.5 the slope and interception were 26.87 μg.m-3 and 5.98 μg.m-3 (RMSE = 5.5 μg.m-3).
关键词： Valencia,particulate matter,air quality,AOD,MODIS
更新于2025-09-23 15:22:29
-
MISR research-aerosol-algorithm refinements for dark water retrievals
摘要： We explore systematically the cumulative effect of many assumptions made in the Multi-angle Imaging SpectroRadiometer (MISR) research aerosol retrieval algorithm with the aim of quantifying the main sources of uncertainty over ocean, and correcting them to the extent possible. A total of 1129 coincident, surface-based sun photometer spectral aerosol optical depth (AOD) measurements are used for validation. Based on comparisons between these data and our baseline case (similar to the MISR standard algorithm, but without the “modified linear mixing” approximation), for 558 nm AOD < 0.10, a high bias of 0.024 is reduced by about one-third when (1) ocean surface under-light is included and the assumed whitecap reflectance at 672 nm is increased, (2) physically based adjustments in particle microphysical properties and mixtures are made, (3) an adaptive pixel selection method is used, (4) spectral reflectance uncertainty is estimated from vicarious calibration, and (5) minor radiometric calibration changes are made for the 672 and 866 nm channels. Applying (6) more stringent cloud screening (setting the maximum fraction not-clear to 0.50) brings all median spectral biases to about 0.01. When all adjustments except more stringent cloud screening are applied, and a modified acceptance criterion is used, the Root-Mean-Square-Error (RMSE) decreases for all wavelengths by 8–27 % for the research algorithm relative to the baseline, and is 12–36 % lower than the RMSE for the Version 22 MISR standard algorithm (SA, with no adjustments applied). At 558 nm, 87 % of AOD data falls within the greater of 0.05 or 20 % of validation values; 62 % of the 446 nm AOD data, and > 68 % of 558, 672, and 866 nm AOD values fall within the greater of 0.03 or 10 %. For the ?ngstr?m exponent (ANG), 67 % of 1119 validation cases for AOD > 0.01 fall within 0.275 of the sun photometer values, compared to 49 % for the SA. ANG RMSE decreases by 17 % compared to the SA, and the median absolute error drops by 36 %.
关键词： AOD,aerosol retrieval,MISR,dark water,?ngstr?m exponent
更新于2025-09-23 15:21:01
-
Retrieval of aerosol profiles by Raman lidar with dynamic determination of the lidar equation reference height
摘要： A reference height that often needs to be assumed in aerosol retrieval from Raman lidar tends to cause high uncertainty in retrieving the vertical distribution of aerosol optical properties. Here, a novel method is proposed to determine the height-revolved reference height, which is then used to retrieve aerosols from Raman lidar. This method can automatically avoid the atmospheric layers with the presence of aerosols, clouds and low signal to noise ratio (SNR). Based on elastic (at 355 nm) and inelastic (at 387 nm) signals collected during the period from 5 December 2016 to 5 March 2017 by a ground-based Raman lidar in Beijing, China, the aerosol optical properties, such as extinction coefficient, backscattering coefficient and lidar ratio have been successfully retrieved. Results show that the averaged nighttime aerosol optic depth (AOD) from Raman lidar is in good agreement with early morning AOD retrieved from a collocated sunphotometer. The AOD exhibits a strong diurnal variation with a peak at 1500 Beijing time. On average, the nighttime AOD at 355nm is 0.32, whereas the daytime AOD is 0.72 over Beijing during the study period. The column averaged lidar ratio is 44 sr at 355 nm, roughly consistent with previous studies. Our findings shed light on the pathways towards improving the retrieval of vertical distribution of aerosols optical properties during nighttime.
关键词： backscattering coefficients,Raman lidar,AOD,reference height
更新于2025-09-23 15:21:01
-
Comparison and evaluation of MODIS Multi-angle Implementation of Atmospheric Correction (MAIAC) aerosol product over South Asia
摘要： The Multiangle Implementation of Atmospheric Correction (MAIAC) is a new generic algorithm applied to collection 6 (C6) MODIS measurements to retrieve Aerosol Optical Depth (AOD) over land at high spatial resolution (1 km). This study is the first evaluation of the MAIAC AOD from MODIS Aqua (A) and Terra (T) satellites between 2006 and 2016 over South Asia. The retrieval accuracy of MAIAC was assessed by comparing it to ground-truth AErosol RObotic NETwork (AERONET) AOD, as well as to AOD retrieved by the two operational MODIS algorithms: Dark Target (DT) and Deep Blue (DB). MAIAC AOD showed higher spatial coverage and retrieval frequency than either the DT or the DB AOD retrievals. The high spatial resolution of the MAIAC retrievals enhances the capability to distinguish aerosol sources and to determine fine aerosol features, such as wildfire smoke plumes and haze over complex geographical regions, and provides more retrievals in conditions that are cloudy or when the surface is partially covered by snow. In comparison to AERONET AOD, MAIAC AOD shows a better accuracy than both DT and DB AOD. A higher number of MAIAC-AERONET AOD matchups demonstrate the capability of MAIAC to retrieve AOD over varied surfaces, different aerosol types and loadings. Our results demonstrate high retrieval accuracy in term of the Expected Error (EE) (A/T, EE: 72.22%, 73.50%), and low root mean square error (A/T, RMSE: 0.148, 0.164), root mean bias (RMB) (A/T, RMB: 0.978, 1.049) and mean absolute error (MAE) (A/T, MAE: 0.098, 0.096). Moreover, MAIAC has a lower bias as a function of the viewing geometry and the aerosol type among the three retrieval algorithms. MAIAC performed well over bright and vegetated land surfaces, showing the highest retrieval accuracy over dense vegetation and particularly well in retrieving smoke AOD, yet it underestimated dust AOD. In conclusion, MAIAC's ability to provide AOD at high spatial resolution appears promising over South Asia, thus having advantage over contemporary aerosol retrieval algorithms for epidemiological and climatological studies.
关键词： South Asia,AOD,MODIS,IGP,Aerosols,AERONET,MAIAC
更新于2025-09-19 17:15:36
-
[IEEE 2019 International Workshop on Fiber Optics in Access Networks (FOAN) - Sarajevo, Bosnia and Herzegovina (2019.9.2-2019.9.4)] 2019 International Workshop on Fiber Optics in Access Networks (FOAN) - How Dubai is Becoming a Smart City?
摘要： Quantitative retrieval is a growing area in remote sensing due to the rapid development of remote instruments and retrieval algorithms. The aerosol optical depth (AOD) is a significant optical property of aerosol which is involved in further applications such as the atmospheric correction of remotely sensed surface features, monitoring of volcanic eruptions or forest fires, air quality, and even climate changes from satellite data. The AOD retrieval can be computationally expensive as a result of huge amounts of remote sensing data and compute-intensive algorithms. In this paper, we present two efficient implementations of an AOD retrieval algorithm from the moderate resolution imaging spectroradiometer (MODIS) satellite data. Here, we have employed two different high performance computing architectures: multicore processors and a graphics processing unit (GPU). The compute unified device architecture C (CUDA-C) has been used for the GPU implementation for NVIDIA’s graphic cards and open multiprocessing (OpenMP) for thread-parallelism in the multicore implementation. We observe for the GPU accelerator, a maximal overall speedup of 68.x for the studied data, whereas the multicore processor achieves a reasonable 7.x speedup. Additionally, for the largest benchmark input dataset, the GPU implementation also shows a great advantage in terms of energy efficiency with an overall consumption of 3.15 kJ compared to 58.09 kJ on a CPU with 1 thread and 38.39 kJ with 16 threads. Furthermore, the retrieval accuracy of all implementations has been checked and analyzed. Altogether, using the GPU accelerator shows great advantages for an application in AOD retrieval in both performance and energy efficiency metrics. Nevertheless, the multicore processor provides the easier programmability for the majority of today’s programmers. Our work exploits the parallel implementations, the performance, and the energy efficiency features of GPU accelerators and multicore processors. With this paper, we attempt to give suggestions to geoscientists demanding for efficient desktop solutions.
关键词： High performance computing (HPC),OpenMP,quantitative remote sensing retrieval,graphics processing unit (GPU),Aerosol optical depth (AOD)
更新于2025-09-19 17:13:59
-
Impact of environmental pollution on the retrieval of AOD products from Visible Infrared Imaging Radiometer Suite (VIIRS) over wuhan
摘要： Visible Infrared Imaging Radiometer Suite (VIIRS) is a next-generation polar-orbiting operational environmental sensor, and its aerosol optical depth (AOD) data has been widely applied to ground-level PM2.5 prediction and air pollution research. However, VIIRS performance affects the accuracy of prediction. In this study, three types of VIIRS AOD products were collected from January 2014 to December 2016 to evaluate their performance under different air quality conditions. Near-surface PM2.5 concentrations were determined for the same period to categorize air quality as clean, moderate, or heavily polluted. The performance of three VIIRS AOD products was evaluated from the successful retrieval rate and AOD accuracy aspects. For clean weather days, the AODs obtained from VIIRS intermediate products (IP) had the lowest average absolute bias (0.15 ± 0.15). For the moderate and heavy pollution days, the average absolute deviations of VIIRS environmental data record (EDR) AOD (Quality Flags = 3 and > 1) products were lowest at 0.14 ± 0.14 and 0.2 ± 0.1 respectively. These results suggest that the EDR AOD, Quality Flags > 1 and = 3, products were more suitable for heavy and moderate air pollution, respectively. During clean weather, performance of _IP AODs was found to be best. Moreover, seasonal analysis indicated that the EDR AOD (Quality Flags = 3) products were more suitable for spring and autumn and the IP AOD for summer. However, the performance of the EDR AOD products (Quality flags > 1) were best during winter. To ensure accuracy of PM2.5 predictions over central China, researchers should carefully balance the needs for successful retrieval rate and accuracy of VIIRS AOD products.
关键词： AOD,VIIRS,Sun photometer,Aerosol,Air quality
更新于2025-09-12 10:27:22
-
Improving Remote Sensing of Aerosol Optical Depth over Land by Polarimetric Measurements at 1640 nm: Airborne Test in North China
摘要： An improved aerosol retrieval algorithm based on the Advanced Multi-angular Polarized Radiometer (AMPR) is presented to illustrate the utility of additional 1640-nm observations for measuring aerosol optical depth (AOD) over land using look-up table approaches. Spectral neutrality of the polarized surface reflectance over visible to short-wavelength infrared bands is verified, and the 1640-nm measurements corrected for atmospheric effects are used to estimate the polarized surface reflectance at shorter wavelengths. The AMPR measurements over the Beijing-Tianjin-Hebei region in north China reveal that the polarized surface reflectance of 670, 865 and 1640 nm are highly correlated with correlation slopes close to one (0.985 and 1.03) when the scattering angle is less than 145°. The 1640-nm measurements are then employed to estimate polarized surface reflectance at shorter wavelengths for each single viewing direction, which are then used to improve the retrieval of AOD over land. The comparison between AMPR retrievals and ground-based Sun-sky radiometer measurements during three experimental flights illustrates that this approach retrieves AOD at 865 nm with uncertainties ranging from 0.01 to 0.06, while AOD varies from 0.05 to 0.17.
关键词： airborne Advanced Multi-angle Polarized Radiometer (AMPR),aerosol optical depth (AOD),polarized surface reflectance,1640 nm
更新于2025-09-10 09:29:36