scholarly journals A NEW SPATIAL AND TEMPORAL FUSION MODEL

2016 ◽  
Vol III-7 ◽  
pp. 203-206
Author(s):  
Jing Wang ◽  
Bo Huang
Keyword(s):  
Temporal Resolution ◽  
Visual Analysis ◽  
High Temporal Resolution ◽  
Fusion Model ◽  
Data Set ◽  
Regression Error ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Temporal Model ◽  
Moderate Resolution Imaging Spectroradiometer

As Moderate Resolution Imaging Spectroradiometer (MODIS) and Enhanced Thematic Mapper Plus (ETM+) has a tradeoff between the high temporal resolution and high spatial resolution, this paper proposed a spatial and temporal model with auto-regression error correction (AREC) method to blend the two types of images in order to obtain the composed image with both high spatial and temporal resolution. Experiments and validation were conducted on a data set located in Shenzhen, China and compared with Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) in several objective indexes and visual analysis. It was found that AREC could effectively predict the land cover changes and the fusion results had better performances versus the ones of STARFM.

scholarly journals A NEW SPATIAL AND TEMPORAL FUSION MODEL

2016 ◽  
Vol III-7 ◽  
pp. 203-206
Author(s):  
Jing Wang ◽  
Bo Huang
Keyword(s):  
Temporal Resolution ◽  
Visual Analysis ◽  
High Temporal Resolution ◽  
Fusion Model ◽  
Data Set ◽  
Regression Error ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Temporal Model ◽  
Moderate Resolution Imaging Spectroradiometer

As Moderate Resolution Imaging Spectroradiometer (MODIS) and Enhanced Thematic Mapper Plus (ETM+) has a tradeoff between the high temporal resolution and high spatial resolution, this paper proposed a spatial and temporal model with auto-regression error correction (AREC) method to blend the two types of images in order to obtain the composed image with both high spatial and temporal resolution. Experiments and validation were conducted on a data set located in Shenzhen, China and compared with Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) in several objective indexes and visual analysis. It was found that AREC could effectively predict the land cover changes and the fusion results had better performances versus the ones of STARFM.

scholarly journals Investigating the frequency and interannual variability in global above-cloud aerosol characteristics with CALIOP and OMI

2016 ◽  
Vol 16 (1) ◽  
pp. 47-69 ◽  
Author(s):  
R. Alfaro-Contreras ◽  
J. Zhang ◽  
J. R. Campbell ◽  
J. S. Reid
Keyword(s):  
Interannual Variability ◽  
Orthogonal Polarization ◽  
Cloud Detection ◽  
Ozone Monitoring Instrument ◽  
Data Set ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
First Time ◽  
Aerosol Index

Abstract. Seven and a half years (June 2006 to November 2013) of Cloud-Aerosol Lidar with Orthogonal Polarization (CALIOP) aerosol and cloud layer products are compared with collocated Ozone Monitoring Instrument (OMI) aerosol index (AI) data and Aqua Moderate Resolution Imaging Spectroradiometer (MODIS) cloud products in order to investigate variability in estimates of biannual and monthly above-cloud aerosol (ACA) events globally. The active- (CALIOP) and passive-based (OMI-MODIS) techniques have their advantages and caveats for ACA detection, and thus both are used to derive a thorough and robust comparison of daytime cloudy-sky ACA distribution and climatology. For the first time, baseline above-cloud aerosol optical depth (ACAOD) and AI thresholds are derived and examined (AI  =  1.0, ACAOD  =  0.015) for each sensor. Both OMI-MODIS and CALIOP-based daytime spatial distributions of ACA events show similar patterns during both study periods (December–May) and (June–November). Divergence exists in some regions, however, such as Southeast Asia during June through November, where daytime cloudy-sky ACA frequencies of up to 10 % are found from CALIOP yet are non-existent from the OMI-based method. Conversely, annual cloudy-sky ACA frequencies of 20–30 % are reported over northern Africa from the OMI-based method yet are largely undetected by the CALIOP-based method. Using a collocated OMI-MODIS-CALIOP data set, our study suggests that the cloudy-sky ACA frequency differences between the OMI-MODIS- and CALIOP-based methods are mostly due to differences in cloud detection capability between MODIS and CALIOP as well as QA flags used. An increasing interannual variability of  ∼  0.3–0.4 % per year (since 2009) in global monthly cloudy-sky ACA daytime frequency of occurrence is found using the OMI-MODIS-based method. Yet, CALIOP-based global daytime ACA frequencies exhibit a near-zero interannual variability. Further analysis suggests that the OMI-derived interannual variability in cloudy-sky ACA frequency may be affected by OMI row anomalies in later years. A few regions are found to have increasing slopes in interannual variability in cloudy-sky ACA frequency, including the Middle East and India. Regions with slightly negative slopes of the interannual variability in cloudy-sky ACA frequencies are found over South America and China, while remaining regions in the study show nearly zero change in ACA frequencies over time. The interannual variability in ACA frequency is not, however, statistically significant on both global and regional scales, given the relatively limited sample sizes. A longer data record of ACA events is needed in order to establish significant trends of ACA frequency regionally and globally.

scholarly journals Evaluation of the Simard et al. 2011 Global Canopy Height Map in Boreal Forests

2020 ◽  
Vol 12 (7) ◽  
pp. 1114
Author(s):  
Wei Yang ◽  
Akihiko Kondoh
Keyword(s):  
Boreal Forests ◽  
Forest Canopy ◽  
Spatial Separation ◽  
Canopy Height ◽  
Tree Cover ◽  
Data Sets ◽  
Data Set ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Light detection and ranging (LiDAR) provides a state-of-the-art technique for measuring forest canopy height. Nevertheless, it may miss some forests due to its spatial separation of individual spots. A number of efforts have been made to overcome the limitation of global LiDAR datasets to generate wall-to-wall canopy height products, among which a global satellite product produced by Simard et al. (2011) (henceforth, the Simard-map) has been the most widely applied. However, the accuracy of the Simard-map is uncertain in boreal forests, which play important roles in the terrestrial carbon cycle and are encountering more extensive climate changes than the global average. In this letter, we evaluated the Simard-map in boreal forests through a literature review of field canopy height. Our comparison shows that the Simard-map yielded a significant correlation with the field canopy height (R2 = 0.68 and p < 0.001). However, remarkable biases were observed with the root mean square error (RMSE), regression slope, and intercept of 6.88 m, 0.448, and 10.429, respectively. Interestingly, we found that the evaluation results showed an identical trend with a validation of moderate-resolution imaging spectroradiometer (MODIS) tree-cover product (MOD44B) in boreal forests, which was used as a crucial input data set for generating the Simard-map. That is, both the Simard-map and MOD44B yielded an overestimation (underestimation) in the lower (upper) tails of the scatterplots between the field and satellite data sets. This indicates that the MOD44B product is the likely source of error for the estimation biases of the Simard-map. Finally, a field calibration was performed to improve the Simard-map in boreal forests by compensating for the estimation biases and discarding non-forest areas, which provided a more reliable canopy height product for future applications.

scholarly journals The Collection 6 MODIS aerosol products over land and ocean

2013 ◽  
Vol 6 (11) ◽  
pp. 2989-3034 ◽  
Author(s):  
R. C. Levy ◽  
S. Mattoo ◽  
L. A. Munchak ◽  
L. A. Remer ◽  
A. M. Sayer ◽  
...  
Keyword(s):  
Arid Land ◽  
Data Set ◽  
Deep Blue ◽  
New Information ◽  
Spatial Coverage ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Land Surfaces ◽  
Cloud Mask

Abstract. The twin Moderate resolution Imaging Spectroradiometer (MODIS) sensors have been flying on Terra since 2000 and Aqua since 2002, creating an extensive data set of global Earth observations. Here, we introduce the Collection 6 (C6) algorithm to retrieve aerosol optical depth (AOD) and aerosol size parameters from MODIS-observed spectral reflectance. While not a major overhaul from the previous Collection 5 (C5) version, there are enough changes that there are significant impacts to the products and their interpretation. The C6 aerosol data set will be created from three separate retrieval algorithms that operate over different surface types. These are the two "Dark Target" (DT) algorithms for retrieving (1) over ocean (dark in visible and longer wavelengths) and (2) over vegetated/dark-soiled land (dark in the visible), plus the "Deep Blue" (DB) algorithm developed originally for retrieving (3) over desert/arid land (bright in the visible). Here, we focus on DT-ocean and DT-land (#1 and #2). We have updated assumptions for central wavelengths, Rayleigh optical depths and gas (H2O, O3, CO2, etc.) absorption corrections, while relaxing the solar zenith angle limit (up to ≤ 84°) to increase poleward coverage. For DT-land, we have updated the cloud mask to allow heavy smoke retrievals, fine-tuned the assignments for aerosol type as function of season/location, corrected bugs in the Quality Assurance (QA) logic, and added diagnostic parameters such topographic altitude. For DT-ocean, improvements include a revised cloud mask for thin-cirrus detection, inclusion of wind speed dependence on the surface reflectance, updates to logic of QA Confidence flag (QAC) assignment, and additions of important diagnostic information. At the same time, we quantified how "upstream" changes to instrument calibration, land/sea masking and cloud masking will also impact the statistics of global AOD, and affect Terra and Aqua differently. For Aqua, all changes will result in reduced global AOD (by 0.02) over ocean and increased AOD (by 0.02) over land, along with changes in spatial coverage. We compared preliminary data to surface-based sun photometer data, and show that C6 should improve upon C5. C6 will include a merged DT/DB product over semi-arid land surfaces for reduced-gap coverage and better visualization, and new information about clouds in the aerosol field. Responding to the needs of the air quality community, in addition to the standard 10 km product, C6 will include a global (DT-land and DT-ocean) aerosol product at 3 km resolution.

scholarly journals Evaluation of JAXA Himawari-8-AHI Level-3 Aerosol Products over Eastern China

Atmosphere ◽  
2019 ◽  
Vol 10 (4) ◽  
pp. 215 ◽  
Author(s):  
Ding Li ◽  
Kai Qin ◽  
Lixin Wu ◽  
Jian Xu ◽  
Husi Letu ◽  
...  
Keyword(s):  
Eastern China ◽  
Retrieval Algorithm ◽  
High Temporal Resolution ◽  
Aerosol Model ◽  
Significant Difference ◽  
Moderate Resolution ◽  
Level 3 ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Land Surfaces

A novel geostationary satellite, the H8/AHI (Himawari-8/Advanced Himawari Imager), greatly improved the scan times per day covering East Asia, and the operational products have been stably provided for a period of time. Currently, atmospheric aerosol pollution is a major concern in China. H8/AHI aerosol products with a high temporal resolution are helpful for real-time monitoring of subtle aerosol variation. However, the H8/AHI aerosol optical thickness (AOT) product has been updated three times since its launch, and the evaluation of this dataset is currently rare. In order to validate its accuracy, this study compared the H8/AHI Level-3 (L3) hourly AOT products of all versions with measurements obtained from eleven sunphotometer sites located in eastern China from 2015 to 2018. Moderate Resolution Imaging Spectroradiometer (MODIS) Collection 6 AOT products from the same period were also used for inter-comparison. Although the H8/AHI AOT retrievals in version 010 show a moderate agreement with ground-based observations (correlation coefficient (R): 0.66–0.85), and the time series analysis shows that it can effectively monitor hourly variation, it suffers from an obvious underestimation of 0.3 compared to ground-based and MODIS observations. After the retrieval algorithm updated the predefined aerosol model, the overall underestimation of AHI AOTs was solved (version 010 slope: 0.43–0.62, version 030 slope: 0.75–1.02), and the AOTs in version 030 show a high agreement with observations from ten sites (R: 0.73–0.91). In addition, the surface reflectance dataset derived from the minimum reflectivity model in version 010 is inaccurate in parts of eastern China, for both “bright” and “dark” land surfaces, which leads to the overestimation of the AOT values under low aerosol loads at the Beijing and Xianghe sites. After the update of the surface dataset in version 030, this phenomenon was alleviated, resulting in no significant difference in scatterplots under different surface conditions. The AOTs of H8/AHI version 030 show a significant improvement compared to the previous two versions, but the spatial distribution of AHI is still different from MODIS AOT products due to the differences in sensors and algorithms. Therefore, although the evaluation in this study demonstrates the effectiveness of H8/AHI AOT products for aerosol monitoring at fine temporal resolutions, the performance of H8/AHI AOT products needs further study by considering more conditions.

scholarly journals Technical note: a new day- and night-time Meteosat Second Generation Cirrus Detection Algorithm MeCiDA

2007 ◽  
Vol 7 (4) ◽  
pp. 10933-10969
Author(s):  
W. Krebs ◽  
H. Mannstein ◽  
L. Bugliaro ◽  
B. Mayer
Keyword(s):  
Second Generation ◽  
Detection Efficiency ◽  
Detection Algorithm ◽  
Technical Note ◽  
High Temporal Resolution ◽  
Night Time ◽  
Ice Clouds ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. A new cirrus detection algorithm for the Spinning Enhanced Visible and Infra-Red Imager (SEVIRI) aboard the geostationary Meteosat Second Generation (MSG), MeCiDA, is presented. The algorithm uses the seven infrared channels of SEVIRI and thus provides a consistent scheme for cirrus detection at day and night. MeCiDA combines morphological and multi-spectral threshold tests and detects optically thick and thin ice clouds. The thresholds were determined by a comprehensive theoretical study using radiative transfer simulations for various atmospheric situations as well as by manually evaluating actual satellite observations. The retrieved cirrus masks have been validated by comparison with the Moderate Resolution Imaging Spectroradiometer (MODIS) Cirrus Reflection Flag. To study possible seasonal variations in the performance of the algorithm, one scene per month of the year 2004 was randomly selected and compared with the standard MODIS cirrus product. 81% of the pixels were classified identically by both algorithms. On average, MeCiDA detected 60% of the MODIS cirrus. A lower detection efficiency is to be expected for MeCiDA, as the spatial resolution of MODIS is considerably better and as we used only the thermal infrared channels in contrast to the MODIS algorithm which uses infrared and visible radiances. The advantage of MeCiDA compared to retrievals for polar orbiting instruments or previous geostationary satellites is that it allows to derive quantitative data every 15 min, 24 h a day. This high temporal resolution allows the study of diurnal variations and life cycle aspects. MeCiDA is fast enough for near real-time applications.

scholarly journals Volcanic SO2 by UV-TIR satellite retrievals: validation by using ground-based network at Mt. Etna

2015 ◽  
Vol 57 ◽  
Author(s):  
Claudia Spinetti ◽  
Giuseppe Giovanni Salerno ◽  
Tommaso Catalbiano ◽  
Elisa Carboni ◽  
Lieven Clarisse ◽  
...  
Keyword(s):  
Monitoring Network ◽  
Automatic Measurement ◽  
Data Set ◽  
Measurement Monitoring ◽  
Hyper Spectral ◽  
Paroxysmal Event ◽  
Mt Etna ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

<div class="page" title="Page 1"><div class="layoutArea"><div class="column"><p><span>Mt. Etna volcano in Italy is one of the most active degassing volcanoes worldwide, emitting a mean of 1.7 Mt/year of Sulphur Dioxide (SO</span><span>2</span><span>) in quiescent periods. In this work, SO</span><span>2 </span><span>measurements retrieved by Moderate Resolution Imaging Spectroradiometer (MODIS), hyper-spectral Infrared Atmospheric Sounding Interferometer (IASI) and the second Global Ozone Monitoring Experiment (GOME-2) data are compared with the ground-based data from the FLux Automatic MEasurement monitoring network (FLAME). Among the eighteen lava fountain episodes occurring at Mt. Etna in 2011, the 10 April paroxysmal event has been selected as a case-study for the simultaneous observation of the SO</span><span>2 </span><span>cloud by satellite and ground-based sensors. For each data-set two retrieval techniques were adopted and the measurements of SO</span><span>2 </span><span>mass and flux with their respective uncertainty were obtained. With respect to the FLAME SO</span><span>2 </span><span>mass of 4.5 Gg, MODIS, IASI and GOME-2 differ by about 10%, 15% and 30%, respectively. The SO</span><span>2 </span><span>flux correlation coefficient between MODIS and FLAME is 0.84. All the retrievals within the respective errors are in agreement with the ground-based measurements supporting the validity of these space measurements. </span></p></div></div></div>

scholarly journals Influence of Straw Burning on Urban Air Pollutant Concentrations in Northeast China

2019 ◽  
Vol 16 (8) ◽  
pp. 1379 ◽  
Author(s):  
Zhenzhen Wang ◽  
Jianjun Zhao ◽  
Jiawen Xu ◽  
Mingrui Jia ◽  
Han Li ◽  
...  
Keyword(s):  
Northeast China ◽  
Arable Land ◽  
Pollution Index ◽  
Air Pollutant ◽  
Thermal Anomalies ◽  
Pollutant Concentrations ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Straw Burning ◽  
Moderate Resolution Imaging Spectroradiometer

Northeast China is China’s primary grain production base. A large amount of crop straw is incinerated every spring and autumn, which greatly impacts air quality. To study the degree of influence of straw burning on urban pollutant concentrations, this study used The Moderate-Resolution Imaging Spectroradiometer/Terra Thermal Anomalies & Fire Daily L3 Global 1 km V006 (MOD14A1) and The Moderate-Resolution Imaging Spectroradiometer/Aqua Thermal Anomalies and Fire Daily L3 Global 1 km V006 (MYD14A1) data from 2015 to 2017 to extract fire spot data on arable land burning and to study the spatial distribution characteristics of straw burning on urban pollutant concentrations, temporal variation characteristics and impact thresholds. The results show that straw burning in Northeast China is concentrated in spring and autumn; the seasonal spatial distributions of PM2.5, PM10 andAir Quality Index (AQI) in 41 cities or regions in Northeast China correspond to the seasonal variation of fire spots; and pollutants appear in the peak periods of fire spots. In areas where the concentration coefficient of rice or corn is greater than 1, the number of fire spots has a strong correlation with the urban pollution index. The correlation coefficient R between the number of burned fire spots and the pollutant concentration has a certain relationship with the urban distribution. Cities are aggregated in geospatial space with different R values.

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