The MODIS 2.1-μm channel-correlation with visible reflectance for use in remote sensing of aerosol

Kaufman, Yoram J.; Wald, Andrew; Remer, L. A.; Gao, Bo‐Cai; Li, Rongrong; Flynn, Luke P.

doi:10.1109/36.628795

Cited by 764 publications

(446 citation statements)

References 33 publications

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“…The ENVI™ FLAASH (Fast Line of sight Atmospheric Analysis of Spectral Hypercubes) atmospheric correction module was applied to Landsat and HJ-1 images to derive the sea surface reflectance (R, unitless). FLAASH includes a method for aerosol estimation based on the dark pixel reflectance ratio method (Kaufman, Wald, Remer, Gao, Li, & Flynn, 1997), which has been successfully used in the atmospheric correction of multi-band or hyperspectral images over waters (e.g., Kutser, Pierson, Kallio, Reinart, & Sobek, 2004;Kutser, 2012;Tian, Lu, Chen, Yu, Xiao, Qiu, & Zhao, 2010;Moses, Gitelson, Perk, Gurlin, Rundquist, Leavitt, Barrow, & Brakhage, 2012;Zeng, Zhao, Tian, & Chen, 2013). The requirement of absolute accuracy of atmospheric correction in this study, however, is not critical because it is the relative height of the near-infrared band that is used for detecting and quantifying macroalgae.…”

Section: Satellite Datamentioning

confidence: 99%

Mapping macroalgal blooms in the Yellow Sea and East China Sea using HJ-1 and Landsat data: Application of a virtual baseline reflectance height technique

Xing

2016

Remote Sensing of Environment

139

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Several methods have been proposed in previous studies to map macroalgal blooms (MABs) in the Yellow Sea (YS) and East China Sea (ECS), yet some of the required spectral bands are not available on the new HJ-1 satellite sensors although they do provide optimal resolution and temporal coverage (30-m resolution with 2-day revisit frequency) for bloom mapping. In this study, an index of Virtual-Baseline Floating macroAlgae Height (VB-FAH) is proposed to use the green and red bands as the baseline to measure the height of the near-infrared (NIR) reflectance. Cross-sensor comparison with Landsat TM and ETM + data suggests that for several images evaluated here VB-FAH appears to be comparable to the previously proposed Floating Algae Index (FAI) even in the absence of a shortwave-infrared (SWIR) band. VB-FAH is applied to 30-m resolution TM and ETM + data for the YS during 1995-2006 and to HJ-1 data for the ECS during 2009-2014 to map MABs. Results show bloom history in the YS back to 1999 and early bloom occurrence in the ECS in winter and spring (e.g., February and March 2013). MABs are also found to extend to the ECS as far south as 26°N near Fujian Province and Taiwan, and as far east as the Kuroshio Current. These new findings provide important information for exploring the origins, causes, and consequences of MABs in the YS and ECS.

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Section: Satellite Datamentioning

confidence: 99%

Mapping macroalgal blooms in the Yellow Sea and East China Sea using HJ-1 and Landsat data: Application of a virtual baseline reflectance height technique

Xing

2016

Remote Sensing of Environment

139

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“…Based on the assumptions about the properties of the Earth's surface and the aerosol type expected over these surfaces, the MODIS Atmosphere team developed three algorithms for processing MODIS observations (Levy et al, 2013). Regions which appear visually dark from space, referred to as dark target (DT), include the algorithm assumptions for vegetated land surfaces (Kaufman et al, 1997a, b) and for remote ocean regions (Tanré et al, 1997). The third algorithm, called the deep blue (DB) algorithm, includes assumptions for surfaces which are visually bright from space and uses near-UV wavelengths (DB band near 410 nm).…”

Section: Modis Satellite Instrumentsmentioning

confidence: 99%

“…This comparative analysis does not aim to be a validation study of the MODIS sensor since many works during the long history of the MODIS sensor on the Terra and Aqua platforms have sought to improve its features (these include Kaufman et al, 1997a, b;Tanré et al, 1997;Remer et al, 2002Remer et al, , 2005Remer et al, , 2006Hsu, et al, 2004Hsu, et al, , 2006Hsu, et al, , 2013Levy et al, 2007Levy et al, , 2009Levy et al, , 2010Levy et al, , 2013Levy et al, , 2015Sayer et al, 2013Sayer et al, , 2014 https://darktarget.gsfc.nasa.gov/atbd/overview, last access: 9 April 2018). However, compared to other areas of the world, no studies have been reported in the Caribbean region and in Cuba in particular (Papadimas et al, 2009;Mishchenko et al, 2010;Kahn et al, 2011;Bennouna et al, 2011Bennouna et al, , 2013Witte et al, 2011;Gkikas et al, 2013Gkikas et al, , 2016Levy et al, 2015).…”

Section: Introductionmentioning

confidence: 99%

Comparison of aerosol optical depth from satellite (MODIS), sun photometer and broadband pyrheliometer ground-based observations in Cuba

Marrero¹,

Revilla

Parrado³

et al. 2018

Atmos. Meas. Tech.

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Abstract. In the present study, we report the first comparison between the aerosol optical depth (AOD) and Ångström exponent (AE) of the Moderate Resolution Imaging Spectroradiometer (MODIS) instruments on the Terra (AOD t ) and Aqua (AOD a ) satellites and those measured using a sun photometer (AOD SP ) at Camagüey, Cuba, for the period 2008 to 2014. The comparison of Terra and Aqua data includes AOD derived with both deep blue (DB) and dark target (DT) algorithms from MODIS Collection 6. Combined Terra and Aqua (AOD ta ) data were also considered. Assuming an interval of ±30 min around the overpass time and an area of 25 km around the sun photometer site, two coincidence criteria were considered: individual pairs of observations and both spatial and temporal mean values, which we call collocated daily means. The usual statistics (root mean square error, RMSE; mean absolute error, MAE; median bias, BIAS), together with linear regression analysis, are used for this comparison. Results show very similar values for both coincidence criteria: the DT algorithm generally displays better statistics and higher homogeneity than the DB algorithm in the behaviour of AOD t , AOD a , AOD ta compared to AOD SP . For collocated daily means, (a) RMSEs of 0.060 and 0.062 were obtained for Terra and Aqua with the DT algorithm and 0.084 and 0.065 for the DB algorithm, (b) MAE follows the same patterns, (c) BIAS for both Terra and Aqua presents positive and negative values but its absolute values are lower for the DT algorithm; (d) combined AOD ta data also give lower values of these three statistical indicators for the DT algorithm; (e) both algorithms present good correlations for comparing AOD t , AOD a , AOD ta vs. AOD SP , with a slight overestimation of satellite data compared to AOD SP , (f ). The DT algorithm yields better figures with slopes of 0.96 (Terra), 0.96 (Aqua) and 0.96 (Terra + Aqua) compared to the DB algorithm (1.07, 0.90, 0.99), which displays greater variability. Multi-annual monthly means of AOD ta establish a first climatology that is more comparable to that given by the sun photometer and their statistical evaluation reveals better agreement with AOD SP for the DT algorithm. Results of the AE comparison showed similar results to those reported in the literature concerning the two algorithms' capacity for retrieval. A comparison between broadband aerosol optical depth (BAOD), derived from broadband pyrheliometer observations at the Camagüey site and three other meteorological stations in Cuba, and AOD observations from MODIS on board Terra and Aqua show a poor correlation with slopes below 0.4 for both algorithms. Aqua (Terra) showed RMSE values of 0.073 (0.080) and 0.088 (0.087) for the DB and DT algorithms. As expected, RMSE values are higher than those from the MODIS-sun photometer comparison, but within the same order of magnitude. Results from the BAOD derived from solar radiation measurements demonstrate its reliability in describing climatological AOD series estimates.

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“…Based on the guidelines given in the FLAASH User's Guide (2008), the atmospheric model, which is based on the geographic location and the season of the year at the time of image acquisition, was chosen as 'Mid-Latitude Summer' for the 02 Jul, 14 Jul, 26 Sep, and 25 Oct images, and 'Sub-Arctic Summer' for the 19 Nov image. The aerosol retrieval method implemented in FLAASH is the approach suggested by Kaufman et al (1997), which involves selecting dark surface pixels in the image based on the at-sensor radiances at channels near 660 nm and 2100 nm. Since AISA does not have a spectral channel near 2100 nm, it was not possible to automatically retrieve aerosol properties from the image data using FLAASH.…”

Section: Flaash Atmospheric Correctionmentioning

confidence: 99%

Estimation of chlorophyll-a concentration in turbid productive waters using airborne hyperspectral data

et al. 2012

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The MODIS 2.1-μm channel-correlation with visible reflectance for use in remote sensing of aerosol

Abstract: For this reflectivity range the dust radiative effect at 2.2 m is small, and the surface reflectance in the blue and red channels can be retrieved.

Cited by 764 publications

References 33 publications

Mapping macroalgal blooms in the Yellow Sea and East China Sea using HJ-1 and Landsat data: Application of a virtual baseline reflectance height technique

Mapping macroalgal blooms in the Yellow Sea and East China Sea using HJ-1 and Landsat data: Application of a virtual baseline reflectance height technique

Comparison of aerosol optical depth from satellite (MODIS), sun photometer and broadband pyrheliometer ground-based observations in Cuba

Estimation of chlorophyll-a concentration in turbid productive waters using airborne hyperspectral data

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