The distribution of phytoplankton chlorophyll concentration in Lake Garda (Italy) was estimated using Landsat ThematicMapper (TM) data acquired at two diOEerent times, February 1992 and March 1993. To investigate the waterleaving radiance adequately, the contribution of the atmospheric path radiance reaching the sensor should be removed. In this work a completely image-based atmospheric correction method was applied by means of an inversion technique based on a simpli. ed radiative transfer code (RTC). A semi-empirical approach of relating atmospherically corrected TM spectral re ectances to in situ measurements through regression analysis was used. Limnological parameters were measured near to the TM images dates; some of the in situ measurements were used to de. ne algorithms relating chlorophyll concentration measurements to water surface re ectance and the others too were used to validate the results of the predictive model. The models developed, which performed better (r2 5 0.818) when concentrations were higher than >3.0mgmÕ 3 , were used to map chlorophyll concentration throughout the lake. Spatial distribution maps of chlorophyll concentration and concentration changes were produced with contour intervals of 1mgm-3
Determination of chlorophyll concentration changes in Lake Garda using an image-based radiative transfer code for Landsat TM images
Brivio PA;C Giardino;
2001
Abstract
The distribution of phytoplankton chlorophyll concentration in Lake Garda (Italy) was estimated using Landsat ThematicMapper (TM) data acquired at two diOEerent times, February 1992 and March 1993. To investigate the waterleaving radiance adequately, the contribution of the atmospheric path radiance reaching the sensor should be removed. In this work a completely image-based atmospheric correction method was applied by means of an inversion technique based on a simpli. ed radiative transfer code (RTC). A semi-empirical approach of relating atmospherically corrected TM spectral re ectances to in situ measurements through regression analysis was used. Limnological parameters were measured near to the TM images dates; some of the in situ measurements were used to de. ne algorithms relating chlorophyll concentration measurements to water surface re ectance and the others too were used to validate the results of the predictive model. The models developed, which performed better (r2 5 0.818) when concentrations were higher than >3.0mgmÕ 3 , were used to map chlorophyll concentration throughout the lake. Spatial distribution maps of chlorophyll concentration and concentration changes were produced with contour intervals of 1mgm-3I documenti in IRIS sono protetti da copyright e tutti i diritti sono riservati, salvo diversa indicazione.