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

2015 ◽  
Vol 8 (7) ◽  
pp. 7335-7371
Author(s):  
E. Jäkel ◽  
B. Mey ◽  
R. Levy ◽  
X. Gu ◽  
T. Yu ◽  
...  
Keyword(s):  
Urban Areas ◽  
Spectral Characteristics ◽  
Mean Difference ◽  
Retrieval Algorithm ◽  
Surface Reflectance ◽  
Beijing Area ◽  
Airborne Measurements ◽  
Aerosol Retrieval ◽  
Modis Aod

Abstract. MODIS retrievals of the aerosol optical depth (AOD) are biased over urban areas, where surface reflectance is not well characterized. Since the operational MODIS aerosol retrieval for dark targets assumes fixed spectral slopes to calculate the surface reflectance at 0.47 μm, the algorithm may fail in urban areas with different spectral characteristics of the surface reflectance. To investigate this bias we have implemented variable spectral slopes into the operational MODIS aerosol algorithms of Collection 5 (C5) and C6. The variation of slopes is based on airborne measurements of surface reflectances over the city of Zhongshan, China. AOD retrieval results of the operational and the modified algorithms were compared for a MODIS measurement over Zhongshan. For this case slightly lower AOD values were derived using the modified algorithm. The retrieval methods were additionally applied to MODIS data of the Beijing area for a period between 2010–2014 when also AERONET data were available. A reduction of the differences between the AOD retrieved using the modified C5 algorithm and AERONET was found, whereby the mean difference from 0.31 ± 0.11 for the operational C5 and 0.18 ± 0.12 for the operational C6 where reduced to a mean difference of 0.09 ± 0.18 by using the modified C5 retrieval. Furthermore, the sensitivity of the MODIS AOD retrieval for several surface types was investigated. Radiative transfer simulations were performed to model reflectances at top of atmosphere for predefined aerosol properties. The reflectances were used as input for the retrieval methods. It is 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, whereby the modified C5 algorithm shows a good performance with a retrieved value of AOD = 0.86.

scholarly journals Role of coarse and fine mode aerosols in MODIS AOD retrieval: a case study

2013 ◽  
Vol 6 (5) ◽  
pp. 9109-9132 ◽  
Author(s):  
M. N. Sai Suman ◽  
H. Gadhavi ◽  
V. Ravi Kiran ◽  
A. Jayaraman ◽  
S. V. B. Rao
Keyword(s):  
South India ◽  
Retrieval Algorithm ◽  
Coarse Mode ◽  
Modis Aod ◽  
Moderate Resolution ◽  
Fine Mode ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. In the present study we have compared the MODIS (Moderate Resolution Imaging Spectroradiometer) derived aerosol optical depth (AOD) data with that obtained from operating sky-radiometer at a remote rural location in South India (Gadanki, 13.45° N, 79.18° E). While the comparison between total (coarse mode + fine mode) AOD shows R2 value of about 0.71 with a negligible bias of 0.01, if one separates the AOD into fine and coarse mode, the comparison becomes very poor, particularly for fine mode with an R2 value of 0.44. The coarse mode AOD derived from MODIS and sky-radiometer compare better with an R2 value of 0.74 and also the seasonal variation is well captured by both measurements. It is shown that the fine mode fraction derived from MODIS data is more than a factor of two smaller than that derived from the sky-radiometer data. Based on these observations we argue that the selection of aerosol types used in the MODIS retrieval algorithm are not appropriate particularly in the case of South India. Instead of selecting a moderately absorbing aerosol type (as being done currently in the MODIS retrieval) a more absorbing type aerosol is better suited for fine mode aerosols, while reverse is true for the coarse mode aerosols, where instead of using "dust aerosols" which is relatively more absorbing, usage of coarse sea-salt particles which is less absorbing is more appropriate.

scholarly journals Comparison of the cloud top heights retrieved from MODIS and AHI satellite data with ground-based Ka-band radar

2019 ◽  
Author(s):  
Juan Huo ◽  
Daren Lu ◽  
Shu Duan ◽  
Yongheng Bi ◽  
Bo Liu
Keyword(s):  
Satellite Data ◽  
Radar Data ◽  
Retrieval Algorithm ◽  
Ka Band ◽  
Retrieval Accuracy ◽  
Retrieval Algorithms ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Radar Measurements ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. To better understand the accuracy of cloud top heights (CTHs) derived from passive satellite data, ground-based Ka-band radar measurements from 2016 and 2017 in Beijing were compared with CTH data inferred from the Moderate Resolution Imaging Spectroradiometer (MODIS) and the Advanced Himawari Imager (AHI). Relative to the radar CTHs, the MODIS CTHs were found to be underestimated by −1.10 ± 2.53 km and 49 % of CTH differences were within 1.0 km. Like the MODIS results, the AHI CTHs were underestimated by −1.10 ± 2.27 km and 42 % were within 1.0 km. Both the MODIS and AHI retrieval accuracy depended strongly on the cloud depth (CD). Large differences were mainly occurring for the retrieval of thin clouds of CD  1 km, the CTH difference decreased to −0.48 ± 1.70 km for MODIS and to −0.76 ± 1.63 km for AHI. MODIS CTHs greater than 6 km showed better agreement with the radar data than those less than 4 km. Statistical analysis showed that the average AHI CTHs were lower than the average MODIS CTHs by −0.64 ± 2.36 km. The monthly accuracy of both retrieval algorithms was studied and it was found that the AHI retrieval algorithm had the largest bias in winter while the MODIS retrieval algorithm had the lowest accuracy in spring.

scholarly journals MODIS 3 km aerosol product: applications over land in an urban/suburban region

2013 ◽  
Vol 6 (1) ◽  
pp. 1683-1716 ◽  
Author(s):  
L. A. Munchak ◽  
R. C. Levy ◽  
S. Mattoo ◽  
L. A. Remer ◽  
B. N. Holben ◽  
...  
Keyword(s):  
Urban Areas ◽  
High Spectral Resolution ◽  
New Information ◽  
Land Cover Data ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Langley Research Center ◽  
High Spectral Resolution Lidar ◽  
Error Envelope

Abstract. MODerate resolution Imaging Spectroradiometer (MODIS) instruments aboard the Terra and Aqua satellites have provided a rich dataset of aerosol information at a 10 km spatial scale. Although originally intended for climate applications, the air quality community quickly became interested in using the MODIS aerosol data. However, 10 km resolution is not sufficient to resolve local scale aerosol features. With this in mind, MODIS Collection 6 is including a global aerosol product with a 3 km resolution. Here, we evaluate the 3 km product over the Baltimore/Washington D.C., USA, corridor during the summer of 2011, by comparing with spatially dense data collected as part of the DISCOVER-AQ campaign; these data were measured by the NASA Langley Research Center airborne High Spectral Resolution Lidar (HSRL) and a network of 44 sun photometers (SP) spaced approximately 10 km apart. The HSRL instrument shows that AOD can vary by up to 0.2 within a single 10 km MODIS pixel, meaning that higher resolution satellite retrievals may help to characterize aerosol spatial distributions in this region. Different techniques for validating a high-resolution aerosol product against SP measurements are considered. Although the 10 km product is more statistically reliable than the 3 km product, the 3 km product still performs acceptably, with more than two-thirds of MODIS/SP collocations falling within the expected error envelope with high correlation (R > 0.90). The 3 km product can better resolve aerosol gradients and retrieve closer to clouds and shorelines than the 10 km product, but tends to show more significant noise especially in urban areas. This urban degradation is quantified using ancillary land cover data. Overall, we show that the MODIS 3 km product adds new information to the existing set of satellite derived aerosol products and validates well over the region, but due to noise and problems in urban areas, should be treated with some degree of caution.

scholarly journals Comparison of MODIS 250 m products for early corn yield predictions: a case study in Vojvodina, Serbia

2016 ◽  
Vol 8 (1) ◽  
Author(s):  
Miro Govedarica ◽  
Dušan Jovanović ◽  
Filip Sabo ◽  
Mirko Borisov ◽  
Milan Vrtunski ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Corn Yield ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

AbstractThe aim of the paper is to compare Moderate Resolution Imaging Spectroradiometer (MODIS) Normalized Difference Vegetation Index (

scholarly journals Indirect Assessment of Sedimentation in Hydropower Dams Using MODIS Remote Sensing Images

2019 ◽  
Vol 11 (3) ◽  
pp. 314 ◽  
Author(s):  
Rita Condé ◽  
Jean-Michel Martinez ◽  
Marco Pessotto ◽  
Raúl Villar ◽  
Gérard Cochonneau ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Large Scale ◽  
Trapping Efficiency ◽  
Retrieval Algorithm ◽  
Independent Field ◽  
Hydropower Dams ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Sedimentation Processes

In this study, we used moderate resolution imaging spectroradiometer (MODIS) satellite images to quantify the sedimentation processes in a cascade of six hydropower dams along a 700-km transect in the Paranapanema River in Brazil. Turbidity field measurement acquired over 10 years were used to calibrate a turbidity retrieval algorithm based on MODIS surface reflectance products. An independent field dataset was used to validate the remote sensing estimates showing fine accuracy (RMSE of 9.5 NTU, r = 0.75, N = 138). By processing 13 years of MODIS images since 2000, we showed that satellite data can provide robust turbidity monitoring over the entire transect and can identify extreme sediment discharge events occurring on daily to annual scales. We retrieved the decrease in the water turbidity as a function of distance within each reservoir that is related to sedimentation processes. The remote sensing-retrieved turbidity decrease within the reservoirs ranged from 2 to 62% making possible to infer the reservoir type and operation (storage versus run-of-river reservoirs). The reduction in turbidity assessed from space presented a good relationship with conventional sediment trapping efficiency calculations, demonstrating the potential use of this technology for monitoring the intensity of sedimentation processes within reservoirs and at large scale.

scholarly journals Spatial distribution of dust's optical properties over the Sahara and Asia inferred from Moderate Resolution Imaging Spectroradiometer

2013 ◽  
Vol 13 (21) ◽  
pp. 10827-10845 ◽  
Author(s):  
M. Yoshida ◽  
J. M. Haywood ◽  
T. Yokohata ◽  
H. Murakami ◽  
T. Nakajima
Keyword(s):  
Optical Properties ◽  
Spatial Distribution ◽  
Single Scattering ◽  
Surface Reflectance ◽  
Carbonaceous Aerosols ◽  
Dust Aerosols ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Earth’S Climate

Abstract. There is great uncertainty regarding the role of mineral dust aerosols in Earth's climate system. One reason for this uncertainty is that the optical properties of mineral dust, such as its single scattering albedo (the ratio of scattering to total extinction), are poorly constrained because ground observations are limited to a few locations and satellite standard products are not available due to the excessively bright surface of the desert in the visible wavelength, which makes robust retrievals difficult. Here, we develop a method to estimate the spatial distributions of the aerosol single scattering albedo (ω0) and optical depth (τa), with daily 1°×1° spatial resolution using data from the Moderate Resolution Imaging Spectroradiometer (MODIS) as well as model simulations of radiative transfer. This approach is based on the "critical surface reflectance" method developed in the literature, which estimates ω0 from the top of the atmospheric radiance. We estimate the uncertainties in ω0 over the Sahara (Asia) to be approximately 0.020 and 0.010 (0.023 and 0.017) for bands 9 and 1, respectively, while the uncertainty in τa is approximately 0.235 and 0.228 (0.464 and 0.370) for bands 9 and 1, respectively. The 5–95% range of the spatial distribution of ω0 over the Sahara (Asia) is approximately 0.90–0.94 and 0.96–0.99 (0.87–0.94 and 0.89–0.97) for bands 9 and 1, respectively, and that of τa over the Sahara (Asia) is approximately 0.8–1.4 and 0.8–1.7 (0.7–2.0 and 0.7–1.9) for bands 9 and 1, respectively. The results for the Sahara indicate a good correlation between ω0 and the surface reflectance, and between ω0 and τa. However, the relationships between ω0, τa, and surface reflectance are less clear in Asia than in the Sahara, and the ω0 values are smaller than those in the Sahara. The regions with small ω0 values are consistent with the regions where coal-burning smoke and carbonaceous aerosols are reported to be transported in previous studies. Because the coal-burning and carbonaceous aerosols are known to be more absorptive and have smaller ω0 values than dust aerosols, our results indicate that the dust aerosols in Asia are contaminated by these anthropogenic aerosols. The spatial distribution of dust optical properties obtained in our work could be useful in understanding the role of dust aerosols in Earth's climate system, most likely through future collaboration with regional and global modelling studies.

scholarly journals Bayesian aerosol retrieval algorithm for MODIS AOD retrieval over land

2018 ◽  
Vol 11 (3) ◽  
pp. 1529-1547 ◽  
Author(s):  
Antti Lipponen ◽  
Tero Mielonen ◽  
Mikko R. A. Pitkänen ◽  
Robert C. Levy ◽  
Virginia R. Sawyer ◽  
...  
Keyword(s):  
Computation Time ◽  
Retrieval Algorithm ◽  
Surface Reflectance ◽  
Aerosol Retrieval ◽  
Correlation Models ◽  
Modis Aod ◽  
Uncertainty Estimates ◽  
Average Computation Time ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Aerosol Parameters

Abstract. We have developed a Bayesian aerosol retrieval (BAR) algorithm for the retrieval of aerosol optical depth (AOD) over land from the Moderate Resolution Imaging Spectroradiometer (MODIS). In the BAR algorithm, we simultaneously retrieve all dark land pixels in a granule, utilize spatial correlation models for the unknown aerosol parameters, use a statistical prior model for the surface reflectance, and take into account the uncertainties due to fixed aerosol models. The retrieved parameters are total AOD at 0.55 µm, fine-mode fraction (FMF), and surface reflectances at four different wavelengths (0.47, 0.55, 0.64, and 2.1 µm). The accuracy of the new algorithm is evaluated by comparing the AOD retrievals to Aerosol Robotic Network (AERONET) AOD. The results show that the BAR significantly improves the accuracy of AOD retrievals over the operational Dark Target (DT) algorithm. A reduction of about 29 % in the AOD root mean square error and decrease of about 80 % in the median bias of AOD were found globally when the BAR was used instead of the DT algorithm. Furthermore, the fraction of AOD retrievals inside the ±(0.05+15%) expected error envelope increased from 55 to 76 %. In addition to retrieving the values of AOD, FMF, and surface reflectance, the BAR also gives pixel-level posterior uncertainty estimates for the retrieved parameters. The BAR algorithm always results in physical, non-negative AOD values, and the average computation time for a single granule was less than a minute on a modern personal computer.

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