Using MODIS 250 m Imagery to Estimate Total Suspended Sediment

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INTERNATIONAL JOURNAL OF SYSTEMS APPLICATIONS, ENGINEERING & DEVELOPMENTIssue 1, Volume 3, 2009(a)(b)(c)0.180.160.14y = 0.0007e 47.755xR 2 = 0.59040.12R rs 645 (sr^-1)0.10.080.060.040.0200 0.02 0.04 0.06 0.08 0.1 0.12-0.02MODIS band 1 reflectanceFigure 3. Data used to develop a TSS algorithm for Mayaguez Bay; (a) Relationship between in situ R rs at 645 nm and TSS, (b)Two linear equations and (c) one exponential equations defining the relationship between in situ R rs at 645 nm and MODIS band1 reflectance.observations. Two linear equations were defined to establishthe relation between TSS (mg/l) and R rs at 645 nm (Fig. 3b)because of the presence of an extreme value. The highersquare correlation coefficient (R 2 =0.88; n=30; P
INTERNATIONAL JOURNAL OF SYSTEMS APPLICATIONS, ENGINEERING & DEVELOPMENTIssue 1, Volume 3, 2009Comparison between these validation results indicated thatequation 3 was able to better estimate TSS in lowerconcentrations, but during higher concentrations it tended tounderestimate this parameter. Although equation 1 showed ahigher RMSE, estimated values followed better the tendencyof observed values. The limitations of these algorithms canbe attributed to various factors: (i) limited data representativeof high TSS concentrations, (ii) MODIS band 1 is not capableof detecting TSS signal under low concentrations conditions,(iii) the atmospheric correction method is not appropriate, and(iv) the presence of sea-bottom effect in the signal. Anotherproblem that could be affecting the results is the mixing pixelphenomenon; which is a common and highly influenceproblem when trying to derive information from satelliteimagery [20]. In the case of TSS estimations, the mixingpixel occurs when variations in TSS concentrations or landand water areas are combined within the 250 m cover area of apixel. Occurrence of this phenomenon can be reduced byusing images with higher spatial resolution, but this alternativeis limited by current ocean color sensors.(b)D. Total Suspended Sediment ProductsEstimations of TSS were generated using the three developedalgorithms in order to spatially analyze results and compareefficiency of the equations. Figure 5 shows spatial variationsassociated to TSS concentration in Puerto Rico surroundingsareas and Mayagüez Bay for the dates used in the validationanalysis. The spatial variability observed in these productsappeared to respond by inshore processes showing higherconcentrations in areas closer to the shoreline which aretypical characteristics of coastal environments. In the case ofMayagüez Bay the majority of high values are concentrated inthe northern part of the bay where the Añasco River plume islocated. Comparison between all three different algorithmsdoes not indicate any significant difference between them; themain difference resides in algorithm 3 which range of valuesis considerably higher than the algorithm 1 and 2. Therefore,application of algorithm 3 resulted on sharper spatialvariations when comparing values in inshore and offshoreareas.(c)Figure 4. Validation results when applying (a) equation 1, (b)equation 2 and (c) equation 3.(a)40
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Using MODIS 250 m Imagery to Estimate Total Suspended Sediment

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