Accession Number:
AD1096679
Title:
Evaluation of Terra Modis C6 and C6.1 Aerosol Products Against Beijing, Xianghe, and Xinglong Aeronet Sites in China During 2004 2014
Corporate Author:
NAVAL RESEARCH LAB WASHINGTON DC WASHINGTON United States
Report Date:
2019-02-27
Abstract:
In this study, Terra-MODIS Moderate Resolution Imaging Spectroradiometer Collections 6 and 6.1 C6 and C6.1 aerosol optical depth AOD retrievals with the recommended high-quality flag QF 3 were retrieved from Dark-Target DT, Deep-Blue DB and merged DT and DB DTB level-2 AOD products for verification against Aerosol Robotic Network AERONET Version 3 Level 2.0 AOD data obtained from 2004-2014 for three sites located in the Beijing-Tianjin-Hebei BTH region. These are Beijing, located over mixed bright urban surfaces, XiangHe located over suburban surfaces, and Xinglong located over hilly and vegetated surfaces. The AOD retrievals were also validated over different land-cover types defined by static monthly NDVI Normalized Difference Vegetation Index values obtained from the Terra-MODIS level-3 product MOD13A3. These include non-vegetated surfaces NVS, NDVI 0.2, partially vegetated surfaces PVS, 0.2 NDVI 0.3, moderately vegetated surfaces MVS, 0.3 NDVI 0.5 and densely vegetated surfaces DVS, NDVI 0.5. Results show that the DT, DB, and DTB-collocated retrievals achieve a high correlation coefficient of 0.90-0.97, 0.89-0.95, and 0.86-0.95, respectively, with AERONET AOD. The DT C6 and C6.1 collocated retrievals were comparable at XiangHe and Xinglong, whereas at Beijing, the percentage of collocated retrievals within the expected error EE increased from 21.4 to 35.5 , the root mean square error RMSE decreased from 0.37 to 0.24, and the relative percent mean error RPME decreased from 49 to 27 . These results suggest significant relative improvement in the DT C6.1 product. The percentage of DB-collocated AOD retrievals EE was greater than 70 at Beijing and Xinglong, whereas less than 66 was observed at XiangHe. Similar to DT AOD, DTB AOD retrievals performed well at XiangHe and Xinglong compared with Beijing.
Descriptive Note:
Journal Article - Open Access
Supplementary Note:
Remote Sensing , 11, 5, 01 Jan 0001, 01 Jan 0001, [ 1 ] Nanjing Univ Informat Sci and Technol, Sch Marine Sci, Nanjing 210044, Jiangsu, Peoples R China[ 2 ] East China Univ Technol, Key Lab Digital Land and Resources, Nanchang 330013, Jiangxi, Peoples R China[ 3 ] COMSATS Univ Islamabad, Dept Meteorol, Earth and Atmospher Remote Sensing Lab EARL, Islamabad 45550, Pakistan[ 4 ] Univ Sussex, Sch Global Studies, Dept Geog, Brighton BN1 9RH, E Sussex, England[ 5 ] China Univ Geosci, Sch Earth Sci, Dept Geog, Wuhan 430074, Hubei, Peoples R China[ 6 ] New Mexico State Univ, Dept Entomol Plant Pathol and Weed Sci, Las Cruces, NM 88003 USA[ 7 ] Nanjing Univ Informat Sci and Technol, Sch Atmospher Sci, Nanjing 210044, Jiangsu, Peoples R China[ 8 ] Naval Res Lab, Monterey, CA 93943 USA[ 9 ] CNR, Inst Methodol Environm Anal, I-85050 Tito, PZ, Italy[ 10 ] Univ Maryland Baltimore Cty, Joint Ctr Earth Syst Technol, Baltimore, MD 21221 USA
Pages:
0016
Distribution Statement:
Approved For Public Release;
File Size:
3.00MB
