Interactive Correlation Environment (ICE) — A Statistical Web Tool for Data Collinearity Analysis

Abstract

Web tools for statistical investigation with an interactive and friendly interface enable users without programming knowledge to conduct their analyses. We develop an Interactive Correlation Environment (ICE) in an open access platform to perform spectral collinearity analysis for biogeochemical activity retrieval. We evaluate its performance on different browsers and applied it to retrieve chlorophyll-a (chl-a) concentration in a tropical reservoir. The use of ICE to retrieve water chl-a concentration got a Root Mean Square Error (RMSE) lower than 7% for seasonal datasets, enhancing ICE's ability to adapt it within season. An RMSE of 17% was found for the mixed dataset with a large range of chl-a concentrations. We conclude that the use of ICE is recommended, due to its quick response, easily manipulation, high accuracy, and empirical adaptation to seasonal variability. Its use is enhanced by the development of hyperspectral sensors, which allow the identification of several biogeochemical components, such as chl-a, phycocyanin (PC), soil salinity, soil types, leaf nitrogen, and leaf chl-a concentration.

Improving Inland Water Quality Monitoring through Remote Sensing Techniques

“…Therefore, for each period, we analyzed the correlation among the spectral bands and chl-a concentration. We also evaluated the use of band ratios through the web tool, Interactive Correlation Environment (ICE), available at www.dsr.inpe.br/hidrosfera/ice [37]. This web tool builds a two-dimensional correlation plot of the radiometric measurement (i.e., surface reflectance from the MOD09GA) and its relation to the interesting biogeochemical component (i.e., chl-a).…”

“…The importance of using band ratios lies in the fact that the specular reflection from water under wavy conditions gets suppressed by the ratio architecture of this type of algorithm, which cancels out the specular reflection from the two bands used in the ratio [47]. To analyze all possible band ratios, we used the ICE [37] to generate two-dimensional correlation plots of the R 2 between chl-a concentration and band ratio values. ICE was previous described in Section 2.4.1, and more information can be found in [37].…”

“…To analyze all possible band ratios, we used the ICE [37] to generate two-dimensional correlation plots of the R 2 between chl-a concentration and band ratio values. ICE was previous described in Section 2.4.1, and more information can be found in [37]. Figure 6 shows the plots for the four seasons analyzed using the calibration dataset.…”

Evaluation of the suitability of MODIS, OLCI and OLI for mapping the distribution of total suspended matter in the Barra Bonita Reservoir (Tietê River, Brazil)

“…Furthermore, new regional models were created using correlation tools (correlogram plot and ICE tool - Ogashawara et al, 2014). The MODIS models (simple models (either Band 1 or Band 2), spectral difference (Band 1 -Band 2) and band ratio (Band 1/Band 2)) tested by Cui et al (2010) showed that a single-band model (Band 1) can better retrieve TSM concentrations.…”

Bio-Optical Modeling in a Tropical Hypersaline Lagoon Environment

“…The development of these empirical algorithms was conducted by calculating the correlation among different band ratios and the concentrations of chl-a and turbidity values. To perform this analysis, we used a web tool named Interactive Correlation Environment (ICE) described by [48] and available at [49]. This web tool builds a two-dimensional correlation plot of the HICO's R rs and its relation to the interested limnological parameter (i.e., chl-a or turbidity).…”