Within the framework of ESA's Earth Observation Program, the Medium Resolution Imaging Spectromet... more 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.
International Journal of Applied Earth Observation and Geoinformation, 1999
Within the framework of ESA's Earth Observation Program, the Medium Resolution Imaging Spectromet... more 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.
The Medium Resolution Imaging Spectrometer (MERIS) is one of the sensors carried by Envisat. MERI... more The Medium Resolution Imaging Spectrometer (MERIS) is one of the sensors carried by Envisat. MERIS is a fully programmable imaging spectrometer, however a standard 15-channel band set will be transmitted for each 300 m pixel (over land while over the ocean the pixels will be aggregated to 1200 m spatial resolution) covering visible and near-infrared wavelengths. Since MERIS is a multidisciplinary sensor providing data that can be input into ecosystem models at various scales, we studied MERIS's performance relative to the scale of observation using simulated datasets degraded to various spatial resolutions in the range of 6-300 m. Algorithms to simulate MERIS data using airborne imaging spectrometer datasets were presented, including a case study from DAIS (i.e. Digital Airborne Imaging Spectrometer) 79-channel imaging spectrometer data acquired on 8 July 1997 over the Le Peyne test site in southern France. For selected target endmembers garrigue, maquis, mixed oak forest, pine forest and bare agricultural eld, regions-of-interest (ROI) were de ned in the DAIS scene. For each of the endmembers, the vegetation index values in the corresponding ROI is calculated for the MERIS data at the spatial resolutions ranging from 6 to 300 m. We applied the NDVI, PVI, WDVI, SAVI, MSAVI, MSAVI2 and GEMI vegetation indices. Above-ground biomass (AGB) was estimated in the eld and derived from the DAIS image and the MERIS datasets (6-300 m spatial resolution). The vegetation indices are shown to be constant with the spatial scale of observation. The strongest correlation between the MERIS and DAIS NDVI is obtained when using a linear model with an oVset of 0.15 (r=0.31). A Pearson correlation matrix between AGB measured in the eld and each spectral band reveals a modest but signi cant ( p<0.05) correlation for most spectral bands. When mathematical functions are tted through the NDVI and biomass data, an exponential t shows ¶Present address:
is developed as one of the payload components of the ENVISAT-1. MERIS is a fully programmable ima... more is developed as one of the payload components of the ENVISAT-1. MERIS is a fully programmable imaging spectrometer, however 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 relative to the scale of observation using simulated data sets degraded to various resolutions in the range of 12m. to 300m. Algorithms to simulate MERIS data using airborne imaging spectrometer data sets are presented, including a case study from GERIS 63 channel data over a agricultural site in central Spain (the Almaden test site). Through a pixel purity analysis, end members are derived from the MERIS-type data and subsequently used as input to a spectral unmixing analysis yielding fraction of end member (abundance) images. The original data as well as the abundance images are spatially analyzed using variogram surfaces and mapping accuracy is modeled at various spatial scales. We observe differences between the sampling resolutions (i.e., pixel size) found to be optimal for the different ground cover types. I he optimal scale for observing different components of spectral mixtures varies depending on the type of mixture, however, the best possible resolutions in all cases of mixtures studied is below the envisaged 300 m. field of view for the MERIS sensor. The analysis of semivariogram surfaces demonstrates that the spatial distribution of the variance of the mixtures is invariant with scale, thus the observed mapping discrepancies are not related to the data processing but to the observations themselves.
In Azerbaijan oil mud volcanoes form on the surface as expressions of the vertical migration of o... more In Azerbaijan oil mud volcanoes form on the surface as expressions of the vertical migration of oil and gas as a result of gravitational loading of largely unconsolidated sediments in combination with structure control and stress regime. In general it is believed that mud volcano eruptions are triggered by earthquake activity since this can cause hydrate instability and explosive dissociation of the hydrocarbons can occur. Through typical geomorphologic mud volcano vents called gryphons and salses, mud volcanoes eject argillaceous material (breccia) and build up their topography. Optical satellite images (Advanced Spaceborne Thermal Emission and Reflection -ASTER) and ground truth data from 2000 to 2002, centred on onshore Azerbaijan, are analysed using Variable Multiple Endmember Spectral Mixture Analysis (VMESMA) in combination with Interferometric Synthetic Aperture Radar (InSAR) from six ERS-2 scenes from 1996 to 1999. ASTER and InSAR imagery are used to look for evidence of mineral alterations and precursory surface deformation related to mud volcanism. Preliminary field spectral data of 5 onshore mud volcano vents show typical mineral zonations present in the mud breccia fields. ASTER image analyses on Aktharma-Pashaly mud volcano shows Al-OH mineral zonation patterns over various mud volcano vents. Initial InSAR processing for Aktharma-Pashaly shows little correlation over this particular mud volcano, which makes it hard to assess data combinations of ASTER and InSAR. Fair correlation was found for Touragai, Great -and Lesser Kjanizadag mud volcanoes showing high to moderate correlation over a time period of 3 years.
Within the framework of ESA's Earth Observation Program, the Medium Resolution Imaging Spectromet... more 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.
International Journal of Applied Earth Observation and Geoinformation, 1999
Within the framework of ESA's Earth Observation Program, the Medium Resolution Imaging Spectromet... more 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.
The Medium Resolution Imaging Spectrometer (MERIS) is one of the sensors carried by Envisat. MERI... more The Medium Resolution Imaging Spectrometer (MERIS) is one of the sensors carried by Envisat. MERIS is a fully programmable imaging spectrometer, however a standard 15-channel band set will be transmitted for each 300 m pixel (over land while over the ocean the pixels will be aggregated to 1200 m spatial resolution) covering visible and near-infrared wavelengths. Since MERIS is a multidisciplinary sensor providing data that can be input into ecosystem models at various scales, we studied MERIS's performance relative to the scale of observation using simulated datasets degraded to various spatial resolutions in the range of 6-300 m. Algorithms to simulate MERIS data using airborne imaging spectrometer datasets were presented, including a case study from DAIS (i.e. Digital Airborne Imaging Spectrometer) 79-channel imaging spectrometer data acquired on 8 July 1997 over the Le Peyne test site in southern France. For selected target endmembers garrigue, maquis, mixed oak forest, pine forest and bare agricultural eld, regions-of-interest (ROI) were de ned in the DAIS scene. For each of the endmembers, the vegetation index values in the corresponding ROI is calculated for the MERIS data at the spatial resolutions ranging from 6 to 300 m. We applied the NDVI, PVI, WDVI, SAVI, MSAVI, MSAVI2 and GEMI vegetation indices. Above-ground biomass (AGB) was estimated in the eld and derived from the DAIS image and the MERIS datasets (6-300 m spatial resolution). The vegetation indices are shown to be constant with the spatial scale of observation. The strongest correlation between the MERIS and DAIS NDVI is obtained when using a linear model with an oVset of 0.15 (r=0.31). A Pearson correlation matrix between AGB measured in the eld and each spectral band reveals a modest but signi cant ( p<0.05) correlation for most spectral bands. When mathematical functions are tted through the NDVI and biomass data, an exponential t shows ¶Present address:
is developed as one of the payload components of the ENVISAT-1. MERIS is a fully programmable ima... more is developed as one of the payload components of the ENVISAT-1. MERIS is a fully programmable imaging spectrometer, however 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 relative to the scale of observation using simulated data sets degraded to various resolutions in the range of 12m. to 300m. Algorithms to simulate MERIS data using airborne imaging spectrometer data sets are presented, including a case study from GERIS 63 channel data over a agricultural site in central Spain (the Almaden test site). Through a pixel purity analysis, end members are derived from the MERIS-type data and subsequently used as input to a spectral unmixing analysis yielding fraction of end member (abundance) images. The original data as well as the abundance images are spatially analyzed using variogram surfaces and mapping accuracy is modeled at various spatial scales. We observe differences between the sampling resolutions (i.e., pixel size) found to be optimal for the different ground cover types. I he optimal scale for observing different components of spectral mixtures varies depending on the type of mixture, however, the best possible resolutions in all cases of mixtures studied is below the envisaged 300 m. field of view for the MERIS sensor. The analysis of semivariogram surfaces demonstrates that the spatial distribution of the variance of the mixtures is invariant with scale, thus the observed mapping discrepancies are not related to the data processing but to the observations themselves.
In Azerbaijan oil mud volcanoes form on the surface as expressions of the vertical migration of o... more In Azerbaijan oil mud volcanoes form on the surface as expressions of the vertical migration of oil and gas as a result of gravitational loading of largely unconsolidated sediments in combination with structure control and stress regime. In general it is believed that mud volcano eruptions are triggered by earthquake activity since this can cause hydrate instability and explosive dissociation of the hydrocarbons can occur. Through typical geomorphologic mud volcano vents called gryphons and salses, mud volcanoes eject argillaceous material (breccia) and build up their topography. Optical satellite images (Advanced Spaceborne Thermal Emission and Reflection -ASTER) and ground truth data from 2000 to 2002, centred on onshore Azerbaijan, are analysed using Variable Multiple Endmember Spectral Mixture Analysis (VMESMA) in combination with Interferometric Synthetic Aperture Radar (InSAR) from six ERS-2 scenes from 1996 to 1999. ASTER and InSAR imagery are used to look for evidence of mineral alterations and precursory surface deformation related to mud volcanism. Preliminary field spectral data of 5 onshore mud volcano vents show typical mineral zonations present in the mud breccia fields. ASTER image analyses on Aktharma-Pashaly mud volcano shows Al-OH mineral zonation patterns over various mud volcano vents. Initial InSAR processing for Aktharma-Pashaly shows little correlation over this particular mud volcano, which makes it hard to assess data combinations of ASTER and InSAR. Fair correlation was found for Touragai, Great -and Lesser Kjanizadag mud volcanoes showing high to moderate correlation over a time period of 3 years.
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