Within the framework of ESA's Earth Observation Program, the Medium Resolution Imaging Spectrometer (MERIS) is being developed as one of the payload components of the ENVISAT-1. Although MERIS is a fully programmable imaging spectrometer, a standard 15 channel band set will be transmitted for each 300 m pixel (over land) covering the visible and near-infrared wavelength range. Since MERIS is a multidisciplinary sensor providing data that can be input into ecosystem models at various scales, we studied MERIS' performance for mineral mapping relative to the scale of observation using simulated data sets degraded to various resolutions in the range of 10 m to 300 m. Algorithms to simulate MERIS data using airborne imaging spectrometer data sets are presented using data from HyMAP acquired on 2 June 1999 over the Tabernas area of southern Spain (Almeria province). A spectral library of mineral spectra was examined to identify potential mappable mineral suites at the MERIS spectral resolution and band setting. A total of 74 (out of 160) minerals have absorption features in the MERIS wavelengths; most of them represent ore (or related) minerals not likely to be 'seen' by the sensor given it's FOV. The study thus focused on goethite and hematite mapping. The HyMAP data was used to simulate MERIS data at various resolutions. Mineral maps were produced using the cross correlogram spectral mapping (CCSM) approach. The results were evaluated against the mineral maps produced using the original HyMAP data using the (1) misclassification, (2) RMS value of the CCSM and (3) the optimal sampling size derived from local variance estimates. (1) and (2) show that accuracy decreases rapidly with larger FOV, possibly due to increased spectral mixing. The optimal sampling sizes calculated for hematite and goethite reflect this. Values were to be 20-30 m for goethite and <10 m for hematite.
|Number of pages||9|
|Journal||International Journal of Applied Earth Observation and Geoinformation|
|Publication status||Published - 1999|
- imaging spectrometry
- remote sensing