scholarly journals Validation of MODIS C6.1 and MERRA-2 AOD Using AERONET Observations: A Comparative Study over Turkey

Atmosphere ◽  
2020 ◽  
Vol 11 (9) ◽  
pp. 905
Author(s):  
Midyan Aldabash ◽  
Filiz Bektas Balcik ◽  
Paul Glantz
Keyword(s):  
Absolute Error ◽  
Coefficient Of Determination ◽  
Space Agency ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
The Mean ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Modern Era ◽  
Relative Root ◽  
Better Than

This study validated MODIS (Moderate Resolution Imaging Spectroradiometer) of the National Aeronautics and Space Agency, USA, Aqua and Terra Collection 6.1, and MERRA-2 (Modern-ERA Retrospective Analysis for Research and Application) Version 2 of aerosol optical depth (AOD) at 550 nm against AERONET (Aerosol Robotic Network) ground-based sunphotometer observations over Turkey. AERONET AOD data were collected from three sites during the period between 2013 and 2017. Regression analysis showed that overall, seasonally and daily statistics of MODIS are better than MERRA-2 by the mean of coefficient of determination (R2), mean absolute error (MAE), and relative root mean square deviation (RMSDrel). MODIS combined Terra/Aqua AOD and MERRA-2 AOD corresponding to morning and noon hours resulted in better results than individual sub datasets. A clear annual cycle in AOD was detected by the three platforms. However, overall, MODIS and MERRA-2 tend to overestimate and underestimate AOD, respectively, in comparison with AERONET. MODIS showed higher efficiency in detecting extreme events than MERRA-2. There was no clear relation found between the accuracy in MODIS/MERRA-2 AOD and surface relative humidity (RH).

scholarly journals Development of a remote sensing-based rice yield forecasting model

2016 ◽  
Vol 14 (3) ◽  
pp. e0907 ◽  
Author(s):  
Mostafa K. Mosleh ◽  
Quazi K. Hassan ◽  
Ehsan H. Chowdhury
Keyword(s):  
Remote Sensing ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Rice Yield ◽  
Decision Makers ◽  
Coefficient Of Determination ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Boro Rice

This study aimed to develop a remote sensing-based method for forecasting rice yield by considering vegetation greenness conditions during initial and peak greenness stages of the crop; and implemented for “boro” rice in Bangladeshi context. In this research, we used Moderate Resolution Imaging Spectroradiometer (MODIS)-derived two 16-day composite of normalized difference vegetation index (NDVI) images at 250 m spatial resolution acquired during the initial (January 1 to January 16) and peak greenness (March 23/24 to April 6/7 depending on leap year) stages in conjunction with secondary datasets (i.e., boro suitability map, and ground-based information) during 2007-2012 period. The method consisted of two components: (i) developing a model for delineating area under rice cultivation before harvesting; and (ii) forecasting rice yield as a function of NDVI. Our results demonstrated strong agreements between the model (i.e., MODIS-based) and ground-based area estimates during 2010-2012 period, i.e., coefficient of determination (R2); root mean square error (RMSE); and relative error (RE) in between 0.93 to 0.95; 30,519 to 37,451 ha; and ±10% respectively at the 23 district-levels. We also found good agreements between forecasted (i.e., MODIS-based) and ground-based yields during 2010-2012 period (R2 between 0.76 and 0.86; RMSE between 0.21 and 0.29 Mton/ha, and RE between -5.45% and 6.65%) at the 23 district-levels. We believe that our developments of forecasting the boro rice yield would be useful for the decision makers in addressing food security in Bangladesh.

scholarly journals A high spatial resolution retrieval of NO<sub>2</sub> column densities from OMI: method and evaluation

2011 ◽  
Vol 11 (4) ◽  
pp. 12411-12440 ◽  
Author(s):  
A. R. Russell ◽  
A. E. Perring ◽  
L. C. Valin ◽  
E. Bucsela ◽  
E. C. Browne ◽  
...  
Keyword(s):  
Boundary Layer ◽  
The Arctic ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Aircraft Observations ◽  
Vertical Column Density ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Better Than

Abstract. We present a new retrieval of tropospheric NO2 vertical column density from the Ozone Monitoring Instrument (OMI) based on high spatial and temporal resolution terrain and profile inputs. We find non-negligible impacts on the retrieved NO2 column for terrain pressure (±20%), albedo (±40%), and NO2 vertical profile (−75%–+10%). We compare our NO2 product, the Berkeley High-Resolution (BEHR) product, with operational retrievals and find that the operational retrievals are biased high (30%) over remote areas and biased low (8%) over urban regions. We validate the operational and BEHR products using boundary layer aircraft observations from the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS-CA) field campaign which occurred in June 2008 in California. Results indicate that columns derived using our boundary layer extrapolation method show good agreement with satellite observations (R2 = 0.65–0.83; N = 68) and provide a more robust validation of satellite-observed NO2 column than those determined using full vertical spirals (R2 = 0.26; N = 5) as in previous work. Agreement between aircraft observations and the BEHR product (R2 = 0.83) is better than agreement with the operational products (R2 = 0.65–0.72). We also show that agreement between satellite and aircraft observations for all products can be further improved (e.g. BEHR: R2 = 0.91) using cloud information from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument instead of the OMI cloud product. These results indicate that much of the variance in the operational products can be attributed to coarse resolution terrain and profile parameters.

scholarly journals Estimation of Daily Sunshine Duration from Terra and Aqua MODIS Data

2014 ◽  
Vol 2014 ◽  
pp. 1-9 ◽  
Author(s):  
H. M. Kandirmaz ◽  
K. Kaba
Keyword(s):  
Cloud Cover ◽  
Sunshine Duration ◽  
Quadratic Model ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Daily Sunshine ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Relative Sunshine ◽  
Relative Sunshine Duration ◽  
Better Than

Some studies have shown that the estimation of global sunshine duration can be done with the help of geostationary satellites because they can record several images of the same location in a day. In this paper, images obtained from the MODIS (Moderate Resolution Imaging Spectroradiometer) sensors of polar orbiting satellites Aqua and Terra were used to estimate daily global sunshine duration for any region in Turkey. A new quadratic correlation between daily mean cloud cover index and relative sunshine duration was also introduced and compared with the linear correlation. Results have shown that polar orbiting satellites can be used for the estimation of sunshine duration. The quadratic model introduced here works better than the linear model especially for the winter months in which very low sunshine duration values were recorded at the ground stations for many days.

scholarly journals A high spatial resolution retrieval of NO<sub> 2</sub> column densities from OMI: method and evaluation

2011 ◽  
Vol 11 (16) ◽  
pp. 8543-8554 ◽  
Author(s):  
A. R. Russell ◽  
A. E. Perring ◽  
L. C. Valin ◽  
E. J. Bucsela ◽  
E. C. Browne ◽  
...  
Keyword(s):  
Boundary Layer ◽  
The Arctic ◽  
Ozone Monitoring Instrument ◽  
Vertical Column ◽  
Aircraft Observations ◽  
Vertical Column Density ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Better Than

Abstract. We present a new retrieval of tropospheric NO2 vertical column density from the Ozone Monitoring Instrument (OMI) based on high spatial and temporal resolution terrain and profile inputs. We compare our NO2 product, the Berkeley High-Resolution (BEHR) product, with operational retrievals and find that the operational retrievals are biased high (30 %) over remote areas and biased low (8 %) over urban regions. Additionally, we find non-negligible impacts on the retrieved NO2 column for terrain pressure (±20 %), albedo (±40 %), and NO2 vertical profile (−75 %–+10 %). We validate the operational and BEHR products using boundary layer aircraft observations from the Arctic Research of the Composition of the Troposphere from Aircraft and Satellites (ARCTAS-CA) field campaign which occurred in June 2008 in California. Results indicate that columns derived using our boundary layer extrapolation method show good agreement with satellite observations (R2 = 0.65–0.83; N = 68) and provide a more robust validation of satellite-observed NO2 column than those determined using full vertical spirals (R2 = 0.26; N = 5) as in previous work. Agreement between aircraft observations and the BEHR product (R2 = 0.83) is better than agreement with the operational products (R2 = 0.65–0.72). We also show that agreement between satellite and aircraft observations can be further improved (e.g. BEHR: R2 = 0.91) using cloud information from the Moderate Resolution Imaging Spectroradiometer (MODIS) instrument instead of the OMI cloud product. These results indicate that much of the variance in the operational products can be attributed to coarse resolution terrain pressure, albedo, and profile parameters implemented in the retrievals.

Assessing the RST_VOLC algorithm implementation on infrared Sentinel 3 SLSTR data

2020 ◽  
Author(s):  
Alfredo Falconieri ◽  
Francesco Marchese ◽  
Giuseppe Mazzeo ◽  
Nicola Pergola ◽  
Valerio Tramutoli
Keyword(s):  
Land Surface ◽  
European Space Agency ◽  
Space Agency ◽  
Mt Etna ◽  
Multi Temporal ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
New Generation ◽  
Algorithm Implementation

&lt;p&gt;RSTVOLC is a multi-temporal algorithm developed for detecting volcanic hotspots that was successfully used to monitor active volcanoes located in different geographic areas exploiting both polar and geostationary satellite data. The algorithm runs operationally at the Institute of Methodologies for Environmental Analysis (IMAA) to monitor Italian volcanoes in near-real time by means of Advanced Very-High-Resolution Radiometer (AVHRR) and Moderate Resolution Imaging Spectroradiometer (MODIS) data. In this study, we assess the possible RSTVOLC implementation on data from the Sea and Land Surface Temperature Radiometer (SLSTR). The latter is a new generation sensor flying onboard the ESA (European Space Agency) Sentinel-3 mission, offering some spectral channels in the infrared bands particularly suited to identify high temperature surfaces such as lava flows. Here, we verify the RSTVOLC implementation on SLSTR data despite the absence of a multiannual time series of satellite records, by using synthetic spectral reference fields. Results achieved by investigating recent eruptions of Mt. Etna and Stromboli (Italy) volcanoes are presented and discussed.&lt;/p&gt;

scholarly journals Retrieval of aerosol fine-mode fraction over China from satellite multiangle polarized observations: validation and comparison

2021 ◽  
Vol 14 (2) ◽  
pp. 1655-1672
Author(s):  
Yang Zhang ◽  
Zhengqiang Li ◽  
Zhihong Liu ◽  
Yongqian Wang ◽  
Lili Qie ◽  
...  
Keyword(s):  
Optical Parameter ◽  
Absolute Error ◽  
Retrieval Algorithm ◽  
Polarization Data ◽  
Moderate Resolution ◽  
Fine Mode ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Remote Sensing Methods ◽  
Observation Results

Abstract. The aerosol fine-mode fraction (FMF) is an important optical parameter of aerosols, and the FMF is difficult to accurately retrieve by traditional satellite remote sensing methods. In this study, FMF retrieval was carried out based on the multiangle polarization data of Polarization and Anisotropy of Reflectances for Atmospheric Science coupled with Observations from Lidar (PARASOL), which overcame the shortcomings of the FMF retrieval algorithm in our previous research. In this research, FMF retrieval was carried out in China and compared with the AErosol RObotic NETwork (AERONET) ground-based observation results, Moderate Resolution Imaging Spectroradiometer (MODIS) FMF products, and Generalized Retrieval of Aerosol and Surface Properties (GRASP) FMF results. In addition, the FMF retrieval algorithm was applied, a new FMF dataset was produced, and the annual and quarterly average FMF results from 2006 to 2013 were obtained for all of China. The research results show that the FMF retrieval results of this study are comparable with the AERONET ground-based observation results in China and the correlation coefficient (r), mean absolute error (MAE), root mean square error (RMSE), and the proportion of results that fall within the expected error (Within EE) are 0.770, 0.143, 0.170, and 65.01 %, respectively. Compared with the MODIS FMF products, the FMF results of this study are closer to the AERONET ground-based observations. Compared with the FMF results of GRASP, the FMF results of this study are closer to the spatial variation in the ratio of PM2.5 to PM10 near the ground.

scholarly journals Theoretical uncertainties for global satellite-derived burned area estimates

2019 ◽  
Vol 16 (16) ◽  
pp. 3147-3164 ◽  
Author(s):  
James Brennan ◽  
Jose L. Gómez-Dans ◽  
Mathias Disney ◽  
Philip Lewis
Keyword(s):  
European Space Agency ◽  
Quantitative Information ◽  
Burned Area ◽  
Spatially Explicit ◽  
Space Agency ◽  
Uncertainty Estimates ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Area Product

Abstract. Quantitative information on the error properties of global satellite-derived burned area (BA) products is essential for evaluating the quality of these products, e.g. against modelled BA estimates. We estimate theoretical uncertainties for three widely used global satellite-derived BA products using a multiplicative triple collocation error model. The approach provides spatially unique uncertainties at 1∘ for the Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 burned area product (MCD64), the MODIS Collection 5.1 (MCD45) product, and the European Space Agency (ESA) Climate Change Initiative Fire product version 5.0 (FireCCI50) for 2001–2013. The uncertainties on mean global burned area for three products are 3.76±0.15×106 km2 for MCD64, 3.70±0.17×106 km2 for FireCCI50, and 3.31±0.18×106 km2 for MCD45. These correspond to relative uncertainties of 4 %–5.5 % and also indicate previous uncertainty estimates to be underestimated. Relative uncertainties are 8 %–10 % in Africa and Australia, for example, and larger in regions with less annual burned area. The method provides uncertainties that are likely to be more consistent with modelling and data analysis studies due to their spatially explicit properties. These properties are also intended to allow spatially explicit validation of current burned area products.

scholarly journals Evaluation of Terra-MODIS C6 and C6.1 Aerosol Products against Beijing, XiangHe, and Xinglong AERONET Sites in China during 2004-2014

2019 ◽  
Vol 11 (5) ◽  
pp. 486 ◽  
Author(s):  
Muhammad Bilal ◽  
Majid Nazeer ◽  
Janet Nichol ◽  
Zhongfeng Qiu ◽  
Lunche Wang ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Deep Blue ◽  
Moderate Resolution ◽  
Level 3 ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Terra Modis ◽  
Level 2 ◽  
Better Than

In this study, Terra-MODIS (Moderate Resolution Imaging Spectroradiometer) Collections 6 and 6.1 (C6 & C6.1) aerosol optical depth (AOD) retrievals with the recommended high-quality flag (QF = 3) were retrieved from Dark-Target (DT), Deep-Blue (DB) and merged DT and DB (DTB) level–2 AOD products for verification against Aerosol Robotic Network (AERONET) Version 3 Level 2.0 AOD data obtained from 2004–2014 for three sites located in the Beijing-Tianjin-Hebei (BTH) region. These are: Beijing, located over mixed bright urban surfaces, XiangHe located over suburban surfaces, and Xinglong located over hilly and vegetated surfaces. The AOD retrievals were also validated over different land-cover types defined by static monthly NDVI (Normalized Difference Vegetation Index) values obtained from the Terra-MODIS level-3 product (MOD13A3). These include non-vegetated surfaces (NVS, NDVI < 0.2), partially vegetated surfaces (PVS, 0.2 ≤ NDVI ≤ 0.3), moderately vegetated surfaces (MVS, 0.3 < NDVI < 0.5) and densely vegetated surfaces (DVS, NDVI ≥ 0.5). Results show that the DT, DB, and DTB-collocated retrievals achieve a high correlation coefficient of ~ 0.90–0.97, 0.89–0.95, and 0.86–0.95, respectively, with AERONET AOD. The DT C6 and C6.1 collocated retrievals were comparable at XiangHe and Xinglong, whereas at Beijing, the percentage of collocated retrievals within the expected error (↔EE) increased from 21.4% to 35.5%, the root mean square error (RMSE) decreased from 0.37 to 0.24, and the relative percent mean error (RPME) decreased from 49% to 27%. These results suggest significant relative improvement in the DT C6.1 product. The percentage of DB-collocated AOD retrievals ↔EE was greater than 70% at Beijing and Xinglong, whereas less than 66% was observed at XiangHe. Similar to DT AOD, DTB AOD retrievals performed well at XiangHe and Xinglong compared with Beijing. Regionally, DB C6 and C6.1-collocated retrievals performed better than DT and DTB in terms of good quality retrievals and relatively small errors. For diverse vegetated surfaces, DT-collocated retrievals reported small errors and good quality retrievals only for NVS and DVS, whereas larger errors were reported for PVS. MVS. DB contains good quality AOD retrievals over PVS, MVS, and DVS compared with NVS. DTB C6.1 collocated retrievals were better than C6 over NVS, PVS, and DVS. C6.1 is substantially improved overall, compared with C6 at local and regional scales, and over diverse vegetated surfaces.

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

2020 ◽  
Vol 13 (1) ◽  
pp. 1-11 ◽  
Author(s):  
Juan Huo ◽  
Daren Lu ◽  
Shu Duan ◽  
Yongheng Bi ◽  
Bo Liu
Keyword(s):  
Satellite Data ◽  
Cloud Base ◽  
Ka Band ◽  
Retrieval Accuracy ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Radar Measurements ◽  
The Mean ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Difference

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 are 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 are found to be underestimated by−1.10 ± 2.53 km on average and 49 % of CTH differences are within 1.0 km. The AHI CTHs are underestimated by −1.10 ± 2.27 km and 42 % are within 1.0 km. Both the MODIS and AHI CTH retrieval accuracy depends strongly on the cloud depth (CD). Large differences are mainly due to the retrieval of thin clouds of CD <1 km, especially when the cloud base height is higher than 4 km. For clouds with CD >1 km, the mean CTH difference decreases to -0.48±1.70 km for MODIS and to -0.76±1.63 km for AHI. It is found that MODIS CTHs with higher values (i.e. >6 km) show smaller discrepancy with radar CTH than those MODIS CTHs with lower values (i.e. <4 km). Statistical analysis illustrate that the CTH difference between the two satellite instruments is lower than the difference between the satellite instrument and the ground-based Ka-band radar. The monthly accuracy of both CTH retrieval algorithms is investigated and it is found that summer has the smallest retrieval difference.

scholarly journals Statistical Models in Estimating Air Temperature in a Mountainous Region of Greece

2017 ◽  
Vol 12 (3) ◽  
pp. 544-549 ◽  
Author(s):  
Stelios Maniatis ◽  
Kostas Chronopoulos ◽  
Aristidis Matsoukis ◽  
Athanasios Kamoutsis
Keyword(s):  
Air Temperature ◽  
Statistical Models ◽  
Mean Absolute Error ◽  
Absolute Error ◽  
Coefficient Of Determination ◽  
Multi Layer Perceptron ◽  
Simple Linear Regression ◽  
The Mean ◽  
Of Greece ◽  
Better Than

The current work focuses on the estimation of air temperature (T) conditions in two high altitude (alt) sites (1580 m), each one at different orientation (southeast and northwest) in the mountain (Mt) Aenos in the island of Cephalonia, Greece, by using two well-known statistical models, simple linear regression (SLR) and multi-layer perceptron ( MLP), one of the most commonly used artificial neural networks. More specifically, the estimation of mean, maximum and minimum T in high alt sites was based on the respective T data of two lower alt sites (1100 m), the first at southeast and the second at northwest orientations, and was carried out separately for each orientation. The performance of both SLR and MLP models was evaluated by the coefficient of determination (R2) and the Mean Absolute Error (MAE). Results showed that the examined models (SLR and MLP) provided very satisfactory results with regard to the estimation of mean, maximum and minimum T, regarding southeast orientation (R2 ranging from 0.96 to 0.98), with mean T estimation being relatively better, as confirmed by the lowest MAE (0.83). Regarding northwest orientation, T estimation was less accurate (lower R2 and higher MAE), compared to the respective estimation of southeast orientation, but, the results were considered adequate (R2 and MAE ranging from 0.88 to 0.92 and 1.00 to 1.40, respectively). In general, the estimations of the mean T were better than those of the extreme ones (minimum and maximum T). In addition, better results (higher R2 and lower, in general, MAE) were obtained when T estimations were based on T data derived from sites located at areas with similar surroundings, as in the case of dense and tall vegetation of the sites at southeast orientation, irrespective of applied method.

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