Next Article in Journal
Drivers of Productivity Trends in Cork Oak Woodlands over the Last 15 Years
Previous Article in Journal
Sentinel-2’s Potential for Sub-Pixel Landscape Feature Detection
Article Menu
Issue 6 (June) cover image

Export Article

Open AccessArticle
Remote Sens. 2016, 8(6), 489;

A New Neighboring Pixels Method for Reducing Aerosol Effects on the NDVI Images

State Key Laboratory of Earth Surface Processes and Resource Ecology, College of Resources Science and Technology, Beijing Normal University, Beijing 100875, China
State Key Laboratory of Resources and Environmental Information System, Institute of Geographical Sciences and Natural Resources Research, CAS, Beijing 100101, China
Author to whom correspondence should be addressed.
Academic Editors: Parth Sarathi Roy, Richard Müller and Prasad S. Thenkabail
Received: 22 March 2016 / Revised: 28 May 2016 / Accepted: 2 June 2016 / Published: 9 June 2016
Full-Text   |   PDF [19711 KB, uploaded 9 June 2016]   |  


A new algorithm was developed in this research to minimize aerosol effects on the normalized difference vegetation index (NDVI). Simulation results show that in red-NIR reflectance space, variations in red and NIR channels to aerosol optical depth (AOD) follow a specific pattern. Based on this rational, the apparent reflectance in these two bands of neighboring pixels were used to reduce aerosol effects on NDVI values of the central pixel. We call this method the neighboring pixels (NP) algorithm. Validation was performed over vegetated regions in the border area between China and Russia using Landsat 8 Operational Land Imager (OLI) imagery. Results reveal good agreement between the aerosol corrected NDVI using our algorithm and that derived from the Landsat 8 surface reflectance products. The accuracy is related to the gradient of NDVI variation. This algorithm can achieve high accuracy in homogeneous forest or cropland with the root mean square error (RMSE) being equal to 0.046 and 0.049, respectively. This algorithm can also be applied to atmospheric correction and does not require any information about atmospheric conditions. The use of the moving window analysis technique reduces errors caused by the spatial heterogeneity of aerosols. Detections of regions with homogeneous NDVI are the primary sources of biases. This new method is operational and can prove useful at different aerosol concentration levels. In the future, this approach may also be used to examine other indexes composed of bands attenuated by noises in remote sensing. View Full-Text
Keywords: AOD; aerosol corrected NDVI; neighboring pixels; Landsat 8 OLI AOD; aerosol corrected NDVI; neighboring pixels; Landsat 8 OLI

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).

Share & Cite This Article

MDPI and ACS Style

Wang, D.; Chen, Y.; Wang, M.; Quan, J.; Jiang, T. A New Neighboring Pixels Method for Reducing Aerosol Effects on the NDVI Images. Remote Sens. 2016, 8, 489.

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



[Return to top]
Remote Sens. EISSN 2072-4292 Published by MDPI AG, Basel, Switzerland RSS E-Mail Table of Contents Alert
Back to Top