scholarly journals Evaluation of Data Quality and Drought Monitoring Capability of FY-3A MERSI Data

2010 ◽  
Vol 2010 ◽  
pp. 1-10 ◽  
Author(s):  
Daxiang Xiang ◽  
Liangming Liu ◽  
Qiao Wang ◽  
Na Yang ◽  
Tao Han
Keyword(s):  
Data Quality ◽  
Three Dimensional ◽  
Drought Monitoring ◽  
Monitoring Model ◽  
Time Period ◽  
Medium Resolution ◽  
Moderate Resolution ◽  
Basic Parameters ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Evaluation Of Data

FY-3A is the second Chinese Polar Orbital Meteorological Satellite with global, three-dimensional, quantitative, and multispectral capabilities. Its missions include monitoring global disasters and environment changes. This study describes some basic parameters and major technical indicators of the FY-3A and evaluates data quality and drought monitoring capability of the Medium-Resolution Imager (MERSI) onboard the FY-3A. Data obtained with the MERSI was compared with that of the MODerate-resolution Imaging Spectroradiometer (MODIS), imaged at the same time period and geographic zone. In addition, the Temperature/Vegetation Drought Index (TVDI), a highly accurate and stable monitoring model, was used to monitor drought condition with MERSI and MODIS sensors. It is found in the study that the relative accuracy of data, obtained with these two devices, was consistent with the acceptable overall accuracy of 93.8. Furthermore, spatial resolution of MERSI is superior as compared to that of MODIS. Therefore, FY-3A MERSI can serve a reliable and new data source for drought monitoring.

scholarly journals 250-m Aerosol Retrieval from FY-3 Satellite in Guangzhou

2021 ◽  
Vol 13 (5) ◽  
pp. 920
Author(s):  
Zhongting Wang ◽  
Ruru Deng ◽  
Pengfei Ma ◽  
Yuhuan Zhang ◽  
Yeheng Liang ◽  
...  
Keyword(s):  
Mixing Model ◽  
Blue Band ◽  
Aerosol Retrieval ◽  
Aerosol Distribution ◽  
Medium Resolution ◽  
Fine Spatial Resolution ◽  
Yearly Average ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Aerosol distribution with fine spatial resolution is crucial for atmospheric environmental management. This paper proposes an improved algorithm of aerosol retrieval from 250-m Medium Resolution Spectral Image (MERSI) data of Chinese FY-3 satellites. A mixing model of soil and vegetation was used to calculate the parameters of the algorithm from moderate-resolution imaging spectroradiometer (MODIS) reflectance products in 500-m resolution. The mixing model was used to determine surface reflectance in blue band, and the 250-m aerosol optical depth (AOD) was retrieved through removing surface contributions from MERSI data over Guangzhou. The algorithm was used to monitor two pollution episodes in Guangzhou in 2015, and the results displayed an AOD spatial distribution with 250-m resolution. Compared with the yearly average of MODIS aerosol products in 2015, the 250-m resolution AOD derived from the MERSI data exhibited great potential for identifying air pollution sources. Daily AODs derived from MERSI data were compared with ground results from CE318 measurements. The results revealed a correlation coefficient between the AODs from MERSI and those from the ground measurements of approximately 0.85, and approximately 68% results were within expected error range of ±(0.05 + 15%τ).

scholarly journals Assessment of the calibration performance of satellite visible channels using cloud targets: application to Meteosat-8/9 and MTSAT-1R

2010 ◽  
Vol 10 (5) ◽  
pp. 12629-12664 ◽  
Author(s):  
S.-H. Ham ◽  
B. J. Sohn
Keyword(s):  
Three Dimensional ◽  
Radiative Transfer Model ◽  
Transfer Model ◽  
Perfect Agreement ◽  
Convective Clouds ◽  
Calibration Methods ◽  
Matching Technique ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. To examine the calibration performance of the Meteosat-8/9 Spinning Enhanced Visible Infra-Red Imager (SEVIRI) 0.640-μm and the Multi-functional Transport Satellite (MTSAT)-1R 0.724-μm channels, three calibration methods were employed. First, a ray-matching technique was used to compare Meteosat-8/9 and MTSAT-1R visible channel reflectances with the well-calibrated Moderate Resolution Imaging Spectroradiometer (MODIS) 0.646-μm channel reflectances. Spectral differences of the response function between the two channels of interest were taken into account for the comparison. Second, collocated MODIS cloud products were used as inputs to a radiative transfer model to calculate Meteosat-8/9 and MTSAT-1R visible channel reflectances. In the simulation, the three-dimensional radiative effect of clouds was taken into account and was subtracted from the simulated reflectance to remove the simulation bias caused by the plane-parallel assumption. Third, an independent method used the typical optical properties of deep convective clouds (DCCs) to simulate reflectances of selected DCC targets. Although the three methods were not in perfect agreement, the results suggest that calibration accuracies were within 5–10% for the Meteosat-8 0.640-μm channel, 4–9% for the Meteosat-9 0.640-μm channel, and up to 20% for the MTSAT-1R 0.724-μm channel. The results further suggest that the solar channel calibration scheme combining the three methods in this paper can be used as a tool to monitor the calibration performance of visible sensors that are particularly not equipped with an onboard calibration system.

scholarly journals Analysis of global three-dimensional aerosol structure with spectral radiance matching

2019 ◽  
Vol 12 (12) ◽  
pp. 6541-6556 ◽  
Author(s):  
Dong Liu ◽  
Sijie Chen ◽  
Chonghui Cheng ◽  
Howard W. Barker ◽  
Changzhe Dong ◽  
...  
Keyword(s):  
Three Dimensional ◽  
Satellite Observation ◽  
Eastern Coast ◽  
Spectral Radiance ◽  
Ground Track ◽  
Vertical Distributions ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Ground Based Lidar ◽  
Relative Errors

Abstract. A method is assessed which expands aerosol vertical profiles inferred from nadir-pointing lidars to cross-track locations next to nadir columns. This is achieved via matching of passive radiances at off-nadir locations with their counterparts that are collocated with lidar data. This spectral radiance matching (SRM) method is tested using profiles inferred from Cloud-Aerosol Lidar and Infrared Pathfinder Satellite Observation (CALIPSO) lidar observations and collocated Moderate Resolution Imaging Spectroradiometer (MODIS) passive imagery for the periods 10–25 April and 14–29 September 2015. CALIPSO profiles are expanded out to 100 km on both sides of the daytime ground track. Reliability of constructed profiles that are removed from the ground track by number of kilometers are tested by requiring the algorithm to reconstruct profiles using only profiles that are removed from it along track by more than the number of kilometers. When sufficient numbers of pixels and columns are available, the SRM method can correctly match ∼75 % and ∼68 % of aerosol vertical structure at distances of 30 and 100 km from the ground track, respectively. The construction algorithm is applied to the eastern coast of Asia during spring 2015. Vertical distributions of different aerosol subtypes indicate that the region was dominated by dust and polluted dust transported from the continent. It is shown that atmospheric profiles and aerosol optical depth (AOD) inferred from ground-based measurements agree with those constructed by the SRM method. For profiles, the relative errors between those measured by ground-based lidar and those constructed in the surrounding area are similar to the relative errors between the ground-based station and CALIPSO overpass at the closest distance. For AOD, the measurements from the ground-based network agree with those inferred from constructed aerosol structure better than direct observations from CALIPSO and close to those inferred from MODIS radiances.

scholarly journals Exploring VIIRS Continuity with MODIS in an Expedited Capability for Monitoring Drought-Related Vegetation Conditions

2021 ◽  
Vol 13 (6) ◽  
pp. 1210
Author(s):  
Trenton D. Benedict ◽  
Jesslyn F. Brown ◽  
Stephen P. Boyte ◽  
Daniel M. Howard ◽  
Brian A. Fuchs ◽  
...  
Keyword(s):  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Infrared Imaging ◽  
Geometric Mean ◽  
Drought Monitoring ◽  
Zero Bias ◽  
Modis Ndvi ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Common Application

Vegetation has been effectively monitored using remote sensing time-series vegetation index (VI) data for several decades. Drought monitoring has been a common application with algorithms tuned to capturing anomalous temporal and spatial vegetation patterns. Drought stress models, such as the Vegetation Drought Response Index (VegDRI), often use VIs like the Normalized Difference Vegetation Index (NDVI). The EROS expedited Moderate Resolution Imaging Spectroradiometer (eMODIS)-based, 7-day NDVI composites are integral to the VegDRI. As MODIS satellite platforms (Terra and Aqua) approach mission end, the Visible Infrared Imaging Radiometer Suite (VIIRS) presents an alternate NDVI source, with daily collection, similar band passes, and moderate spatial resolution. This study provides a statistical comparison between EROS expedited VIIRS (eVIIRS) 375-m and eMODIS 250-m and tests the suitability of replacing MODIS NDVI with VIIRS NDVI for drought monitoring and vegetation anomaly detection. For continuity with MODIS NDVI, we calculated a geometric mean regression adjustment algorithm using 375-m resolution for an eMODIS-like NDVI (eVIIRS’) eVIIRS’ = 0.9887 × eVIIRS − 0.0398. The resulting statistical comparisons (eVIIRS’ vs. eMODIS NDVI) showed correlations consistently greater than 0.84 throughout the three years studied. The eVIIRS’ VegDRI results characterized similar drought patterns and hotspots to the eMODIS-based VegDRI, with near zero bias.

scholarly journals Can We Use Satellite-Based FAPAR to Detect Drought?

Sensors ◽  
2019 ◽  
Vol 19 (17) ◽  
pp. 3662 ◽  
Author(s):  
Jian Peng ◽  
Jan-Peter Muller ◽  
Simon Blessing ◽  
Ralf Giering ◽  
Olaf Danne ◽  
...  
Keyword(s):  
Quality Assurance ◽  
Drought Index ◽  
Agricultural Drought ◽  
Drought Monitoring ◽  
Climate Variables ◽  
The Public ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Absorbed Photosynthetically Active Radiation

Drought in Australia has widespread impacts on agriculture and ecosystems. Satellite-based Fraction of Absorbed Photosynthetically Active Radiation (FAPAR) has great potential to monitor and assess drought impacts on vegetation greenness and health. Various FAPAR products based on satellite observations have been generated and made available to the public. However, differences remain among these datasets due to different retrieval methodologies and assumptions. The Quality Assurance for Essential Climate Variables (QA4ECV) project recently developed a quality assurance framework to provide understandable and traceable quality information for Essential Climate Variables (ECVs). The QA4ECV FAPAR is one of these ECVs. The aim of this study is to investigate the capability of QA4ECV FAPAR for drought monitoring in Australia. Through spatial and temporal comparison and correlation analysis with widely used Moderate Resolution Imaging Spectroradiometer (MODIS), Satellite Pour l’Observation de la Terre (SPOT)/PROBA-V FAPAR generated by Copernicus Global Land Service (CGLS), and the Standardized Precipitation Evapotranspiration Index (SPEI) drought index, as well as the European Space Agency’s Climate Change Initiative (ESA CCI) soil moisture, the study shows that the QA4ECV FAPAR can support agricultural drought monitoring and assessment in Australia. The traceable and reliable uncertainties associated with the QA4ECV FAPAR provide valuable information for applications that use the QA4ECV FAPAR dataset in the future.

scholarly journals Impact of data quality and surface-to-column representativeness on the PM<sub>2.5</sub>/satellite AOD relationship for the Continental United States

2013 ◽  
Vol 13 (12) ◽  
pp. 31635-31671 ◽  
Author(s):  
T. D. Toth ◽  
J. Zhang ◽  
J. R. Campbell ◽  
E. J. Hyer ◽  
J. S. Reid ◽  
...  
Keyword(s):  
United States ◽  
Data Quality ◽  
Dry Mass ◽  
Orthogonal Polarization ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Total Column ◽  
Particle Mass Concentration

Abstract. Satellite-derived aerosol optical depth (AOD) observations have been used to estimate particulate matter less than 2.5 μm (PM2.5). However, such a relationship could be affected by the representativeness of satellite-derived AOD to surface aerosol particle mass concentration and satellite AOD data quality. Using purely measurement-based methods, we have explored the impacts of data quality and representativeness on the AOD inferred PM2.5/AOD relationship for the Continental United States (CONUS). This is done through temporally and spatially collocated datasets of PM2.5 and AOD retrievals from Aqua/Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Multi-angle Imaging Spectroradiometer (MISR), and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). These analyses show that improving data quality of satellite AOD, such as done with data assimilation-grade retrievals, increases their correlation with PM2.5. However, overall correlation is relatively low across the CONUS. Also, integrated extinction observed within the 500 m above groud level (a.g.l.), as measured by CALIOP, is not well representative of the total column AOD. Surface aerosol in the Eastern CONUS is better correlated than in the Western CONUS. The best correlation values are found for estimated dry mass CALIOP extinction at 200–300 m a.g.l. and PM2.5, but additional work is needed to address the ability of using actively sensed AOD as a proxy for PM2.5 concentrations.

scholarly journals Impact of data quality and surface-to-column representativeness on the PM<sub>2.5</sub> / satellite AOD relationship for the contiguous United States

2014 ◽  
Vol 14 (12) ◽  
pp. 6049-6062 ◽  
Author(s):  
T. D. Toth ◽  
J. Zhang ◽  
J. R. Campbell ◽  
E. J. Hyer ◽  
J. S. Reid ◽  
...  
Keyword(s):  
United States ◽  
Data Quality ◽  
Ground Level ◽  
Dry Mass ◽  
Orthogonal Polarization ◽  
Data Sets ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Total Column

Abstract. Satellite-derived aerosol optical depth (AOD) observations have been used to estimate particulate matter smaller than 2.5 μm (PM2.5). However, such a relationship could be affected by the representativeness of satellite-derived AOD to surface aerosol particle mass concentration and satellite AOD data quality. Using purely measurement-based methods, we have explored the impacts of data quality and representativeness on the AOD-inferred PM2.5 / AOD relationship for the contiguous United States (CONUS). This is done through temporally and spatially collocated data sets of PM2.5 and AOD retrievals from Aqua/Terra Moderate Resolution Imaging Spectroradiometer (MODIS), Multi-angle Imaging Spectroradiometer (MISR), and Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP). These analyses show that improving data quality of satellite AOD, such as done with data assimilation-grade retrievals, increases their correlation with PM2.5. However, overall correlation is relatively low across the CONUS. Also, integrated extinction observed within 500 m above ground level (a.g.l.), as measured by CALIOP, is not well representative of the total column AOD. Surface aerosol in the eastern CONUS is better correlated with total column AOD than in the western CONUS. The best correlation values are found for estimated dry mass CALIOP extinction at 200–300 m a.g.l. and PM2.5, but additional work is needed to address the ability of using actively sensed AOD as a proxy for PM2.5 concentrations.

Using Temperature Vegetation Drought Index for Monitoring Drought Based on Remote Sensing Data

2011 ◽  
Vol 356-360 ◽  
pp. 2854-2859
Author(s):  
Lin Sheng Huang ◽  
Qing Song Guan ◽  
Yan Sheng Dong ◽  
Dong Yan Zhang ◽  
Wen Jiang Huang ◽  
...  
Keyword(s):  
Drought Index ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Remote Sensing Data ◽  
Feature Space ◽  
Drought Monitoring ◽  
Arcgis Engine ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Drought is one of the major natural disasters in China, it has extremely affected national food security. In this study, Normalized Difference Vegetation Index (NDVI) and surface temperature (Ts) were calculated by using 8-day composite Moderate-Resolution Imaging Spectroradiometer (MODIS) reflectance product data MOD09A1 and MOD11A2, then NDVI-Ts feature space was obtained and dry edge and wet edge equation was fit. According to coefficients of dry edge and wet edge equation, Temperature Vegetation Drought Index (TVDI) will be calculated and refer it as a drought monitoring indicator. In addition, drought monitoring and classification of Shandong province (China) was completed by TVDI from February to May,2011. Furthermore, the drought classification diagram was made and the drought area in each period was counted. The results showed revealed that: NDVI-Ts feature was roughly a triangular shape in the two-dimensional plane, and drought conditions could be better monitored through TVDI. Finally, the desktop demonstration system of drought monitoring was designed and some general functions were realized based on ArcGis Engine.

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