Comparative Analysis of Four Models to Estimate Chlorophyll-a Concentration in Case-2 Waters Using MODerate Resolution Imaging Spectroradiometer (MODIS) Imagery

Abstract

Abstract:The occurrence and extent of intense harmful algal blooms (HABs) have increased in inland waters during recent decades. Standard monitor networks, based on infrequent sampling from a few fixed observation stations, are not providing enough information on the extent and intensity of the blooms. Remote sensing has great potential to provide the spatial and temporal coverage needed. Several sensors have been designed to study water properties (AVHRR, SeaBAM, and SeaWIFS), but most lack adequate spatial resolution for monitoring algal blooms in small and medium-sized lakes. Over the last decade, satellite data with 250-m spatial resolution have become available with MODIS. In the present study, three models inspired by published approaches (Kahru, Gitelson, and Floating Algae Index (FAI)) and a new approach named APPEL (APProach by ELimination) were adapted to the specific conditions of southern Quebec and used to estimate chlorophyll-a concentration (Chl-a) using MODIS data. Calibration and validation were provided from in situ Chl-a measured in four lakes over 9 years (2000)(2001)(2002)(2003)(2004)(2005)(2006)(2007)(2008) and concurrent MODIS imagery. MODIS bands 3 to 7, originally at 500-m spatial resolution, were downscaled to 250 m. The APPEL, FAI, and Kahru models yielded satisfactory results and enabled estimation of Chl-a for heavy blooming conditions (Chl-a > 50 mg•m −3 ), with coefficients of determination reaching 0.95, 0.94, and 0.93, respectively. The model inspired from Gitelson did not provide good estimations compared to the others (R 2 = 0.77).However, the performance of all models decreased when Chl-a was below 50 mg•m −3 . OPEN ACCESSRemote Sens. 2012, 4 2374

Performance Analysis of MODIS 500-m Spatial Resolution Products for Estimating Chlorophyll-a Concentrations in Oligo- to Meso-Trophic Waters Case Study: Itumbiara Reservoir, Brazil

“…Remote sensing techniques have been extensively used for monitoring chl-a in aquatic systems [4,[8][9][10]. The advantages of using remote sensing techniques to monitor chl-a are: (1) the geographical coverage of satellite images, which provide information about the entire aquatic system; (2) remote sensing, which allows us to obtain information from inaccessible places; and (3) historical satellite images, which allow the inference of water quality information from the past records [11].…”

“…Several methods for estimating chl-a concentration in different turbid waters (Case 2) with remote sensing have been investigated [4][5][6][7][8][9][10][11][12]. Many studies have suggested that remote spectroscopic measurements from the Moderate Resolution Imaging Spectroradiometer (MODIS) should be used to estimate chl-a concentrations in Case 2 waters through empirical and semi-empirical algorithms [4,15,16].…”

A Performance Review of Reflectance Based Algorithms for Predicting Phycocyanin Concentrations in Inland Waters

“…However, traditional monitoring methods consist of collection of field samples, laboratory analysis, and manual cell counts. These methods are time-consuming, labor intensive and costly [8]. Efficient alternative methods should be developed in order to improve the monitoring of CHABs and remote sensing has been proved as a valuable tool for this application [9].…”

An Adaptive Model to Monitor Chlorophyll-a in Inland Waters in Southern Quebec Using Downscaled MODIS Imagery

“…Performance of the AM was evaluated utilizing cross-validation using several statistical evaluation indices and a confusion matrix using an independent semi-quantitative database. We also used the same databases (continuous and ordinal) to compare performance of the AM to that of three other models originally developed to estimate Chl-a in inland waters (the Floating Algae Index (FAI), Kahru model, and APProach by ELimination (APPEL)) [13,22,24].…”