Next Article in Journal
Characteristics of the Nonoccurrence of Tropical Cyclones in the Western North Pacific in August 2014
Next Article in Special Issue
Inversion of Nighttime PM2.5 Mass Concentration in Beijing Based on the VIIRS Day-Night Band
Previous Article in Journal
Inverse Modeling of Nitrogen Oxides Emissions from the 2010 Russian Wildfires by Using Satellite Measurements of Nitrogen Dioxide
Previous Article in Special Issue
Effect of the Aerosol Type Selection for the Retrieval of Shortwave Ground Net Radiation: Case Study Using Landsat 8 Data
Article Menu

Export Article

Open AccessArticle
Atmosphere 2016, 7(10), 134; doi:10.3390/atmos7100134

Retrieval of Aerosol Optical Depth over Arid Areas from MODIS Data

1
College of Global Change and Earth System Science, Beijing Normal University, Beijing 100875, China
2
Geomatics College, Shandong University of Science and Technology, Qingdao 266590, China
*
Author to whom correspondence should be addressed.
Academic Editors: Giovanni Pitari and Gabriele Curci
Received: 23 July 2016 / Revised: 5 October 2016 / Accepted: 12 October 2016 / Published: 16 October 2016
(This article belongs to the Special Issue Atmospheric Aerosols and Their Radiative Effects)
View Full-Text   |   Download PDF [18103 KB, uploaded 21 October 2016]   |  

Abstract

Moderate Resolution Imaging Spectroradiometer (MODIS) data have been widely applied for the remote sensing of aerosol optical depth (AOD) because the MODIS sensor features a short revisit period and a moderate spatial resolution. The Dense Dark Vegetation (DDV) method is the most popular retrieval method. However, the DDV method can only be used to retrieve the AOD with high precision when the surface reflectance in the visible spectrum is low, such as over dense vegetation or water. To obtain precise AOD values in areas with higher reflectance, such as arid areas, Land Surface Reflectance (LSR) must be estimated accurately. This paper proposes a method of estimating LSR for AOD retrieval over arid areas from long-term series of MODIS images. According to the atmospheric parameters (AOD and water vapor), the clearest image without clouds was selected from the long-term series of continuous MODIS images. Atmospheric correction was conducted based on similar ground-measured atmospheric parameters and was used to estimate the LSR and retrieve the AOD at adjacent times. To validate this method, aerosol inversion experiments were performed in northern Xinjiang, in which the inverted AOD was compared to ground-measured AOD and MODIS aerosol products (MOD04). The AOD retrieved using the new algorithm was highly consistent with the AOD derived from ground-based measurements, with a correlation coefficient of 0.84. Additionally, 82.22% of the points fell within the expected error defined by NASA. The precision of the retrieved AOD data was better than that of MOD04 AOD products over arid areas. View Full-Text
Keywords: arid areas; aerosol optical depth; MODIS; atmospheric correction arid areas; aerosol optical depth; MODIS; atmospheric correction
Figures

Figure 1

This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. (CC BY 4.0).

Scifeed alert for new publications

Never miss any articles matching your research from any publisher
  • Get alerts for new papers matching your research
  • Find out the new papers from selected authors
  • Updated daily for 49'000+ journals and 6000+ publishers
  • Define your Scifeed now

SciFeed Share & Cite This Article

MDPI and ACS Style

Tian, X.-P.; Sun, L. Retrieval of Aerosol Optical Depth over Arid Areas from MODIS Data. Atmosphere 2016, 7, 134.

Show more citation formats Show less citations formats

Note that from the first issue of 2016, MDPI journals use article numbers instead of page numbers. See further details here.

Related Articles

Article Metrics

Article Access Statistics

1

Comments

[Return to top]
Atmosphere EISSN 2073-4433 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top