scholarly journals Accuracy assessment of moderate resolution image spectroradiometer products for dust storms in semiarid environment

2011 ◽  
Vol 8 (2) ◽  
pp. 373-380 ◽  
Author(s):  
J. Amanollahi ◽  
S. Kaboodvandpour ◽  
A. M. Abdullah ◽  
M. F. Ramli
Keyword(s):  
Accuracy Assessment ◽  
Dust Storms ◽  
Semiarid Environment ◽  
Resolution Image ◽  
Moderate Resolution ◽  
Moderate Resolution Image Spectroradiometer

scholarly journals Evaluating the Spatial Representativeness of the MODerate Resolution Image Spectroradiometer Albedo Product (MCD43) at AmeriFlux Sites

2019 ◽  
Vol 11 (5) ◽  
pp. 547 ◽  
Author(s):  
Hongmin Zhou ◽  
Shunlin Liang ◽  
Tao He ◽  
Jindi Wang ◽  
Yanchen Bo ◽  
...  
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Land Cover ◽  
Spatial Scale ◽  
Surface Heterogeneity ◽  
Mixed Forests ◽  
Land Cover Types ◽  
Resolution Image ◽  
Moderate Resolution ◽  
Moderate Resolution Image Spectroradiometer

Land surface albedo is a key parameter in regulating surface radiation budgets. The gridded remote sensing albedo product often represents information concerning an area larger than the nominal spatial resolution because of the large viewing angles of the observations. It is essential to quantify the spatial representativeness of remote sensing products to better guide the sampling strategy in field experiments and match products from different sources. This study quantifies the spatial representativeness of the MODerate Resolution Image Spectroradiometer (MODIS) (collection V006) 500 m daily albedo product (MCD43A3) using the high-resolution product as intermediate data for different land cover types. A total of 1820 paired high-resolution Landsat Thematic Mapper (TM) and coarse-resolution (MODIS) albedo data from five land cover types were used. The TM albedo data was used as the spatial-complete high resolution data to evaluate the spatial representativeness of the MODIS albedo product. Semivarioagrams were estimated from 30 m Landsat data at different spatial scales. Surface heterogeneity was evaluated with sill value and relative coefficient of variation. The 30 m Landsat albedo data was aggregated to 450 m–1800 m using two different methods and compared with MODIS albedo product. The spatial representativeness of MODIS albedo product was determined according to the surface heterogeneity and the consistency of MODIS data and the aggregated TM value. Results indicated that for evergreen broadleaf forests, deciduous broadleaf forests, open shrub lands, woody savannas and grasslands, the MODIS 500 m daily albedo product represents a spatial scale of approximately 630 m. For mixed forests and croplands, the representative spatial scale was approximately 690 m. The difference obtained was primarily because of the complexity of the landscape structure. For mixed forests and croplands, the structure of the landscape was relatively complex due to the presence of different forest and plant types in the pixel area, whereas the other landscape structures were considerably simpler.

scholarly journals Dynamics of Muddy Rain of 15 June 2018 in Nepal

Atmosphere ◽  
2020 ◽  
Vol 11 (5) ◽  
pp. 529
Author(s):  
Ashok Kumar Pokharel ◽  
Tianli Xu ◽  
Xiaobo Liu ◽  
Binod Dawadi
Keyword(s):  
Dust Emission ◽  
Dust Storms ◽  
Strong Wind ◽  
Hysplit Model ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Upper Level ◽  
Terra Satellite ◽  
Negative Buoyancy

It has been revealed from the Modern-Era Retrospective analysis for Research and Applications MERRA analyses, Moderate Resolution Imaging Spectroradiometer MODIS/Terra satellite imageries, Naval Aerosol Analysis and Prediction System NAAPS model outputs, Cloud –Aerosol Lidar and Infrared Pathfinder Satellite Observations CALIPSO imageries, Hybrid Single Particle Lagrangian Integrated Trajectory HYSPLIT model trajectories, atmospheric soundings, and observational records of dust emission that there were multiple dust storms in the far western parts of India from 12 to 15 June 2018 due to thunderstorms. This led to the lifting of the dust from the surface. The entry of dust into the upper air was caused by the generation of a significant amount of turbulent kinetic energy as a function of strong wind shear generated by the negative buoyancy of the cooled air aloft and the convective buoyancy in the lower planetary boundary layer. Elevated dust reached a significant vertical height and was advected towards the northern/northwestern/northeastern parts of India. In the meantime, this dust was carried by northwesterly winds associated with the jets in the upper level, which advected dust towards the skies over Nepal where rainfall was occurring at that time. Consequently, this led to the muddy rain in Nepal.

scholarly journals Quality Assessment of PROBA-V LAI, fAPAR and fCOVER Collection 300 m Products of Copernicus Global Land Service

2020 ◽  
Vol 12 (6) ◽  
pp. 1017 ◽  
Author(s):  
Beatriz Fuster ◽  
Jorge Sánchez-Zapero ◽  
Fernando Camacho ◽  
Vicente García-Santos ◽  
Aleixandre Verger ◽  
...  
Keyword(s):  
Quality Assessment ◽  
Accuracy Assessment ◽  
Observation System ◽  
Good Precision ◽  
Area Index ◽  
Global Land ◽  
Moderate Resolution ◽  
Earth Observation System ◽  
Temporal Profiles ◽  
Absorbed Photosynthetically Active Radiation

The Copernicus Global Land Service (CGLS) provides global time series of leaf area index (LAI), fraction of absorbed photosynthetically active radiation (fAPAR) and fraction of vegetation cover (fCOVER) data at a resolution of 300 m and a frequency of 10 days. We performed a quality assessment and validation of Version 1 Collection 300 m products that were consistent with the guidelines of the Land Product Validation (LPV) subgroup of the Committee on Earth Observation System (CEOS) Working Group on Calibration and Validation (WGCV). The spatiotemporal patterns of Collection 300 m V1 LAI, fAPAR and fCOVER products are consistent with CGLS Collection 1 km V1, Collection 1 km V2 and Moderate Resolution Imagery Spectroradiometer Collection 6 (MODIS C6) products. The Collection 300 m V1 products have good precision and smooth temporal profiles, and the interannual variations are consistent with similar satellite products. The accuracy assessment using ground measurements mainly over crops shows an overall root mean square deviation of 1.01 (44.3%) for LAI, 0.12 (22.2%) for fAPAR and 0.21 (42.6%) for fCOVER, with positive mean biases of 0.36 (15.5%), 0.05 (10.3%) and 0.16 (32.2%), respectively. The products meet the CGLS user accuracy requirements in 69.1%, 62.5% and 29.7% of the cases for LAI, fAPAR and fCOVER, respectively. The CGLS will continue the production of Collection 300 m V1 LAI, fAPAR and fCOVER beyond the end of the PROBA-V mission by using Sentinel-3 OLCI as input data.

scholarly journals Validation and Accuracy Assessment of MODIS C6.1 Aerosol Products over the Heavy Aerosol Loading Area

Atmosphere ◽  
2019 ◽  
Vol 10 (9) ◽  
pp. 548 ◽  
Author(s):  
Xinpeng Tian ◽  
Zhiqiang Gao
Keyword(s):  
Urban Areas ◽  
Vegetation Index ◽  
Normalized Difference Vegetation Index ◽  
Accuracy Assessment ◽  
Aerosol Loading ◽  
Deep Blue ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Terra Modis ◽  
Reflecting Surface

The aim of this study is to evaluate the accuracy of MODerate resolution Imaging Spectroradiometer (MODIS) aerosol optical depth (AOD) products over heavy aerosol loading areas. For this analysis, the Terra-MODIS Collection 6.1 (C6.1) Dark Target (DT), Deep Blue (DB) and the combined DT/DB AOD products for the years 2000–2016 are used. These products are validated using AErosol RObotic NETwork (AERONET) data from twenty-three ground sites situated in high aerosol loading areas and with available measurements at least 500 days. The results show that the numbers of collections (N) of DB and DT/DB retrievals were much higher than that of DT, which was mainly caused by unavailable retrieval of DT in bright reflecting surface and heavy pollution conditions. The percentage falling within the expected error (PWE) of the DT retrievals (45.6%) is lower than that for the DB (53.4%) and DT/DB (53.1%) retrievals. The DB retrievals have 5.3% less average overestimation, and 25.7% higher match ratio than DT/DB retrievals. It is found that the current merged aerosol algorithm will miss some cases if it is determined only on the basis of normalized difference vegetation index. As the AOD increases, the value of PWE of the three products decreases significantly; the undervaluation is suppressed, and the overestimation is aggravated. The retrieval accuracy shows distinct seasonality: the PWE is largest in autumn or winter, and smallest in summer. The most severe overestimation and underestimation occurred in the summer. Moreover, the DT, DB and DT/DB products over different land cover types still exhibit obvious deviations. In urban areas, the PWE of DB product (52.6%) is higher than for the DT/DB (46.3%) and DT (25.2%) products. The DT retrievals perform poorly over the barren or sparsely vegetated area (N = 52). However, the performance of three products is similar over vegetated area. On the whole, the DB product performs better than the DT product over the heavy aerosol loading area.

scholarly journals MODIS Sensor Capability to Burned Area Mapping—Assessment of Performance and Improvements Provided by the Latest Standard Products in Boreal Regions

Sensors ◽  
2020 ◽  
Vol 20 (18) ◽  
pp. 5423
Author(s):  
José A. Moreno-Ruiz ◽  
José R. García-Lázaro ◽  
Manuel Arbelo ◽  
Manuel Cantón-Garbín
Keyword(s):  
Accuracy Assessment ◽  
Fire Service ◽  
Global Scale ◽  
Burned Area ◽  
Commission Error ◽  
Positional Accuracy ◽  
Wildfire Management ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Moderate Resolution Imaging Spectroradiometer

This paper presents an accuracy assessment of the main global scale Burned Area (BA) products, derived from daily images of the Moderate-Resolution Imaging Spectroradiometer (MODIS) Fire_CCI 5.1 and MCD64A1 C6, as well as the previous versions of both products (Fire_CCI 4.1 and MCD45A1 C5). The exercise was conducted on the boreal region of Alaska during the period 2000–2017. All the BA polygons registered by the Alaska Fire Service were used as reference data. Both new versions doubled the annual BA estimate compared to the previous versions (66% for Fire_CCI 5.1 versus 35% for v4.1, and 63% for MCD64A1 C6 versus 28% for C5), reducing the omission error (OE) by almost one half (39% versus 67% for Fire_CCI and 48% versus 74% for MCD) and slightly increasing the commission error (CE) (7.5% versus 7% for Fire_CCI and 18% versus 7% for MCD). The Fire_CCI 5.1 product (CE = 7.5%, OE = 39%) presented the best results in terms of positional accuracy with respect to MCD64A1 C6 (CE = 18%, OE = 48%). These results suggest that Fire_CCI 5.1 could be suitable for those users who employ BA standard products in geoinformatics analysis techniques for wildfire management, especially in Boreal regions. The Pareto boundary analysis, performed on an annual basis, showed that there is still a potential theoretical capacity to improve the MODIS sensor-based BA algorithms.

scholarly journals Long-term aerosol optical depth datasets over China retrieved from satellite data

2011 ◽  
Vol 4 (6) ◽  
pp. 6643-6678 ◽  
Author(s):  
Y. Xue ◽  
H. Xu ◽  
Y. Li ◽  
L. Yang ◽  
L. Mei ◽  
...  
Keyword(s):  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Dust Storms ◽  
The Tibetan Plateau ◽  
Hysplit Model ◽  
The North ◽  
Moderate Resolution ◽  
Dust Weather ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Nine years of daily aerosol optical depth (AOD) measurements have been derived from the Moderate Resolution Imaging Spectroradiometer (MODIS) data using the Synergetic Retrieval of Aerosol Properties (SRAP) method over China for the period from August 2002 to August 2011, comprising AODs at 470, 550, and 660 nm. Then, the variation over China over the nine years was determined from the derived AOD data. Preliminary daily results show the agreement between the Aerosol Robotic Network (AERONET) AOD data and the derived AOD data. From 1219 daily collocations, representing mutually cloud-free conditions, we find that more than 54% of SRAP-MODIS retrieved AOD values comparing with AERONET-observed values within an expected error envelop of 20%. From 222 monthly averaged collocations, representing mutually cloud-free conditions, we find that more than 63% of SRAP-MODIS retrieved AOD values comparing with AERONET-observed values within an expected error envelop of 15% and more than 70% within an expected error envelop of 20%. In addition, the long-term SRAP AOD dataset has been implemented in analysing case studies involving dust storms, haze and the characteristics of AOD variation over China over the past nine years. It was found that areas in China with high AOD values generally appear in the Inner Mongolia, the North China Plain, Tarim Basin, the Sichuan Basin, the Tibetan Plateau and the middle and lower reaches of the Yangtze River and area with low AOD values generally appear in the Fujian Province, the Yungui Plateau, and northeast plain. The seasonal averaged AOD results indicate that AOD values generally reach their maximum in spring and their minimum in winter. The yearly mean and monthly mean SRAP AOD were also used to study the spatial and temporal aerosol distributions over China. The results indicate that the AOD over China exhibited no obvious change. Monthly averaged AOD in August in Beijing experienced one decreasing processes from 2006 to 2010, especially after 2007. The monthly mean AOD decreased from 0.46 in 2007 to 0.29 in 2010. SRAP AODs were used to study one haze case and dust case. Combining AOD data from the SRAP AOD dataset and HYSPLIT model can forecast the transport of haze. SRAP AOD data are also sensitive enough to reflect the occurrence and intensity of dust weather. Thus, the SRAP AOD dataset can be used to precisely reflect the spatial distribution, concentration distribution and transmission path of dust.

scholarly journals Air Temperature Modelling Depended on Remote Sensing Techniques

2020 ◽  
Vol 38 (3A) ◽  
pp. 352-360
Author(s):  
Zainab T. Mohammed ◽  
Riyad H. Al-Anbari ◽  
Oday Z. Jasim
Keyword(s):  
Air Temperature ◽  
Land Surface ◽  
Accuracy Assessment ◽  
Day Length ◽  
Temperature Estimation ◽  
Digital Elevation ◽  
Moderate Resolution ◽  
Moderate Resolution Imaging Spectroradiometer ◽  
Remote Sensing Techniques ◽  
Elevation Model

Air temperature (T air) near the land surface is a fundamental descriptor of physical environmental conditions and one of the most widely used climatic variables in global change studies. In this study, the researcher trying to suggest a model for estimating air temperature in summer season for any region through integrating of Iraqi Agrometeorological network daily (T air) with the moderate resolution imaging spectroradiometer (MODIS) land surface temperature (LST), Duration Day Length (DDL) and Digital Elevation Model (DEM). In this model, using satellite images for the study area and data of air temperature for four weather stations located in Babylon governorate from 1- June to 30- September on year 2017 for modeling and accuracy assessment air temperature estimation. The standard error of this model is 1.72887° C, and the correlation equal to 0.69698.

scholarly journals DUST STORM DETECTION USING MODIS DATA OVER THE MIDDLE EAST

2019 ◽  
Vol XLII-4/W18 ◽  
pp. 1147-1151
Author(s):  
A. Zandkarimi ◽  
P. Fatehi
Keyword(s):  
Remote Sensing ◽  
Middle East ◽  
Dust Storm ◽  
Dust Storms ◽  
Time Data ◽  
Sensing Technology ◽  
Moderate Resolution ◽  
Resolution Imaging ◽  
Data Source ◽  
Moderate Resolution Imaging Spectroradiometer

Abstract. Dust storms are one of the common phenomena in the arid and semi-arid regions which cause many economic and environmental losses also affect human health. Therefore, it is necessary to be able to detect dust storms. Several methods exist for dust monitoring, such as Ground-based measurements, satellite remote sensing, video surveillance, wireless sensors. Remote sensing technology provides wide coverage, high spectral and temporal resolutions, even near real-time data, which can offer a valuable data source for dust storm monitoring. We used an algorithm based on Moderate Resolution Imaging Spectroradiometer (MODIS) images for detecting dust storm over the Middle East. The proposed algorithm uses the brightness temperature using multi-bands. The performance of the algorithm was evaluated using the ground-based observations of synoptic stations. The results showed that by applying the algorithm, the dust area can be clearly separated, especially in the regions that cloud is mixed with dust and achieved overall accuracy was ~78%.

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