scholarly journals Revisited Estimation of Moderate Resolution Sargassum Fractional Coverage Using Decametric Satellite Data (S2-MSI)

2021 ◽  
Vol 13 (24) ◽  
pp. 5106
Author(s):  
Jacques Descloitres ◽  
Audrey Minghelli ◽  
François Steinmetz ◽  
Cristèle Chevalier ◽  
Malik Chami ◽  
...  
Keyword(s):  
Physiological State ◽  
Remote Sensing Data ◽  
Coefficient Of Determination ◽  
Fractional Coverage ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Difference ◽  
Terra Modis ◽  
Sentinel 2

Since 2011, massive stranding of the brown algae Sargassum has regularly affected the coastal waters of the West Caribbean, Brazil and West Africa, leading to significant environmental and socio-economic impacts. The AFAI algal index (Alternative Floating Algae Index) is often used with remote sensing data in order to estimate the Sargassum coverage, and more precisely the AFAI deviation, which consists of the difference between AFAI and AFAI of the Sargassum-free background. In this study, the AFAI deviation is computed using NASA’s 1 km Terra/MODIS (Moderate-Resolution Imaging Spectroradiometer) and ESA/Copernicus’s 20 m Sentinel-2/MSI (Multi Spectral Instrument) for the same sites and at the same time. Both MODIS and MSI AFAI deviations are compared to confirm the relevance of AFAI deviation technique for two very different spatial resolutions. A high coefficient of determination was found, thus confirming a satisfactory downsampling from 20 m (MSI) to 1 km (MODIS). Then, AFAI deviations are used to estimate the fractional coverage of Sargassum (noted FC). A new linear relationship between the MODIS AFAI deviation and FC is established using the dense Sargassum aggregations observed by MSI data. The AFAI deviation is proportional to FC with a factor of proportionality close to 0.08. Finally, it is shown that the factor is dependent on the Sargassum spectral reflectance, submersion or physiological state.

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 Pendugaan Kejadian Pemutihan Karang Berdasarkan Analisis Suhu Permukaan Laut (SPL) Tahun 2015-2016 di Perairan Bali

2017 ◽  
Vol 4 (2) ◽  
pp. 286
Author(s):  
Jajang Nuryana ◽  
I Gede Hendrawan ◽  
Widiastuti Karim
Keyword(s):  
Coral Bleaching ◽  
Hot Spot ◽  
Satellite Image ◽  
Distribution Patterns ◽  
Triangle Center ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
The Difference ◽  
Level 2

National Ocean Atmospheric Administrations (NOAA) by the program coral reef Watch (CRW) has developed a method to estimate the potential of coral bleaching using Sea Surface Temperature (SST). The products are hot spot (HS) and degree heating week (DHW). HS is the SST 1°C (SSTL?1) above normal and DHW is the length of HS inhabits a place. The CRW product do not provided detail informations because it has a lower resolution. It is need a satellite image with a higher resolution to provide better informations. One of the satellite images that can be used is Moderate Resolution Imaging Spectroradiometer (MODIS) with a spatial resolution of 1 km. The purpose of this study was to know HS and DHW distribution patterns and status of coral bleaching in Bali waters seen from the analysis of HS and DHW. MODIS data is used daily, then do mosaicing process to get a weekly SPL (8 daily) and the monthly SST. Monthly SPL normally used to get maximum montly mean (MMM). HS obtained from the difference between 8 daily weekly SST and SST normal (MMM).).Location bleaching based on data Coral Triangle Center (CTC) and coralwatch.org.  SST results revealed difference of SPL in 2015 and 2016 amounted to 1.48°C. Highest DHW in Bali Hai, Nusa Penida is 10 465° C-weeks in April 2016. Based on the value HS and DHW coral reefs in Bali waters threatened bleaching level Alert 1 and Alert level 2.

scholarly journals Evaluation of the Multi-Angle Implementation of Atmospheric Correction (MAIAC) Aerosol Algorithm for Himawari-8 Data

2019 ◽  
Vol 11 (23) ◽  
pp. 2771 ◽  
Author(s):  
Lu She ◽  
Hankui Zhang ◽  
Weile Wang ◽  
Yujie Wang ◽  
Yun Shi
Keyword(s):  
Mean Squared Error ◽  
Atmospheric Correction ◽  
Remote Sensing Data ◽  
Japan Meteorological Agency ◽  
Absolute Bias ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Highly Correlated ◽  
New Generation

Himawari-8, operated by the Japan Meteorological Agency (JMA), is a new generation geostationary satellite that provides remote sensing data to retrieve atmospheric aerosol optical depth (AOD) at high spatial (1 km) and high temporal (10 min) resolutions. The Geostationary- National Aeronautics and Space Administration (NASA) Earth exchange (GeoNEX) project recently adapted the multiangle implementation of atmospheric correction (MAIAC) algorithm, originally developed for joint retrieval of AOD and surface anisotropic reflectance with the moderate resolution imaging spectroradiometer (MODIS) data, to generate Earth monitoring products from the latest geostationary satellites including Himawari-8. This study evaluated the GeoNEX Himawari-8 ~1 km MAIAC AOD retrieved over all the aerosol robotic network (AERONET) sites between 6°N–30°N and 91°E–127°E. The corresponding JMA Himawari-8 AOD products were also evaluated for comparison. We only used cloud-free and the best quality satellite AOD retrievals and compiled a total of 16,532 MAIAC-AERONET and 21,737 JMA-AERONET contemporaneous pairs of AOD values for 2017. Statistical analyses showed that both MAIAC and JMA data are highly correlated with AERONET AOD, with the correlation coefficient (R) of ~0.77, and the root mean squared error (RMSE) of ~0.16. The absolute bias of MAIAC AOD (0.02 overestimation) appears smaller than that of the JMA AOD (0.05 underestimation). In comparison with the JMA data, the time series of MAIAC AOD were more consistent with AERONET AOD values and better capture the diurnal variations of the latter. The dependence of MAIAC AOD bias on scattering angles is also discussed.

scholarly journals Satellite-based radiative forcing by light-absorbing particles in snow across the Northern Hemisphere

2020 ◽  
Author(s):  
Jiecan Cui ◽  
Tenglong Shi ◽  
Yue Zhou ◽  
Dongyou Wu ◽  
Xin Wang ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Northern Hemisphere ◽  
Radiative Forcing ◽  
Remote Sensing Data ◽  
The Arctic ◽  
Snow Albedo ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Earth’S Climate

Abstract. Snow is the most reflective natural surface on Earth and consequently plays an important role in Earth’s climate. Light-absorbing particles (LAPs) deposited on the snow surface can effectively decrease snow albedo, resulting in positive radiative forcing. In this study, we used remote sensing data from NASA’s Moderate Resolution Imaging Spectroradiometer (MODIS) and the Snow, Ice, and Aerosol Radiative (SNICAR) model to quantify the reduction in snow albedo due to LAPs, before validating and correcting the data against in situ observations. We then incorporated these corrected albedo reduction data in the Santa Barbara DISORT Atmospheric Radiative Transfer (SBDART) model to estimate Northern Hemisphere radiative forcing in January and February for the period 2003–2018. Our analysis reveals an average corrected reduction in snow albedo of ~0.0246, with instantaneous radiative forcing and daily radiative forcing values of ~5.87 and ~1.69 W m−2, respectively. We also observed significant spatial variations in corrected snow albedo reduction, instantaneous radiative forcing and daily radiative forcing throughout the Northern Hemisphere, with the lowest respective values (~0.0123, ~1.09 W m−2, and ~0.29 W m−2) occurring in the Arctic and the highest (~0.1669, ~36.02 W m−2, and ~10.60 W m−2) in northeastern China. From MODIS retrievals, we determined that the LAP content of snow accounts for 57.6 % and 37.2 % of the spatial variability in Northern Hemisphere albedo reduction and radiative forcing, respectively. We also compared retrieved radiative forcing values with those of earlier studies, including local-scale observations, remote-sensing retrievals, and model-based estimates. Ultimately, estimates of radiative forcing based on satellite-retrieved data are shown to represent true conditions on both regional and global scales.

High Efficiency of Solar Cell Model Based on Two Types of Nanoparticles

2020 ◽  
Vol 13 (1) ◽  
pp. 87-92
Keyword(s):  
Solar Cell ◽  
High Efficiency ◽  
Cell Model ◽  
Deep Blue ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Terra Modis ◽  
Level 2

Climatology of aerosols, their trends and classification based on the long-term Moderate Resolution Imaging Spectroradiometer (MODIS) measurements (from February 2000 to July 2015) of aerosol optical depths at 550 nm (τ550) and Angstrom exponent (α470-660) using the wavelengths of 470 and 660nm in Nairobi, Skukuza and Ilorin AERONET stations were analyzed in this work. The level-2 collection-6 Deep Blue (L2 C006 DB) of the parameters listed above from the aqua- (MYD04) and terra- (MOD04) MODIS of the study area were statistically analyzed using SPSS. To be able to understand the temporal variation in the characteristics of aerosols in the three stations and during each season separately, MODIS measurements of τ, retrieved for the study area, were compared with AERONET τ. Overall, aqua-MODIS τ corroborate the AERONET measurements well in Nairobi and Ilorin stations with underestimation of 29.80 % and overestimation of 2.90 % respectively, whereas Skukuza station has terra-MODIS τ as the best representation of the AERONET measurements with underestimation of 1.90 %. ....

scholarly journals Evaluation of VIIRS, GOCI, and MODIS Collection 6 AOD retrievals against ground sunphotometer observations over East Asia

2016 ◽  
Vol 16 (3) ◽  
pp. 1255-1269 ◽  
Author(s):  
Q. Xiao ◽  
H. Zhang ◽  
M. Choi ◽  
S. Li ◽  
S. Kondragunta ◽  
...  
Keyword(s):  
Air Quality ◽  
East Asia ◽  
Infrared Imaging ◽  
Environmental Data ◽  
Urban Centers ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Terra Modis

Abstract. Persistent high aerosol loadings together with extremely high population densities have raised serious air quality and public health concerns in many urban centers in East Asia. However, ground-based air quality monitoring is relatively limited in this area. Recently, satellite-retrieved Aerosol Optical Depth (AOD) at high resolution has become a powerful tool to characterize aerosol patterns in space and time. Using ground AOD observations from the Aerosol Robotic Network (AERONET) and the Distributed Regional Aerosol Gridded Observation Networks (DRAGON)-Asia Campaign, as well as from handheld sunphotometers, we evaluated emerging aerosol products from the Visible Infrared Imaging Radiometer Suite (VIIRS) aboard the Suomi National Polar-orbiting Partnership (S-NPP), the Geostationary Ocean Color Imager (GOCI) aboard the Communication, Ocean, and Meteorology Satellite (COMS), and Terra and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) (Collection 6) in East Asia in 2012 and 2013. In the case study in Beijing, when compared with AOD observations from handheld sunphotometers, 51 % of VIIRS Environmental Data Record (EDR) AOD, 37 % of GOCI AOD, 33 % of VIIRS Intermediate Product (IP) AOD, 26 % of Terra MODIS C6 3 km AOD, and 16 % of Aqua MODIS C6 3 km AOD fell within the reference expected error (EE) envelope (±0.05 ± 0.15 AOD). Comparing against AERONET AOD over the Japan–South Korea region, 64 % of EDR, 37 % of IP, 61 % of GOCI, 39 % of Terra MODIS, and 56 % of Aqua MODIS C6 3 km AOD fell within the EE. In general, satellite aerosol products performed better in tracking the day-to-day variability than tracking the spatial variability at high resolutions. The VIIRS EDR and GOCI products provided the most accurate AOD retrievals, while VIIRS IP and MODIS C6 3 km products had positive biases.

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 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 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.

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