A review of the contributions of Alexander F.H. Goetz to imaging spectroscopy

All aspects of the science and engineering of imaging spectrometry have been advanced by the work of Dr. Alexander F.H. Goetz over the past 30 years. Dr. Goetz’s pioneering efforts were among the first to realize that it was feasible to obtain laboratory like spectra from space that would quantify earth materials based on biogeochemistry. He has made fundamental contributions to developing high spectral resolution field spectrometers and airborne imaging spectrometers, and to the image processing software and atmospheric correction software needed to analyze the data. These parallel developments in core technologies have made imaging spectroscopy available to a wide range of users of varying user expertise and disciplines, thus enabling the current state of rapid advances in the use of this data

A review of the contributions of Dr. Alexander F. H. Goetz to imaging spectroscopy

All aspects of the science and engineering of imaging spectrometry have been advanced by the work of Dr. Alexander F.H. Goetz over the past 30 years. Dr. Goetz¿s pioneering efforts were among the first to realize that it was feasible to obtain laboratory like spectra from space that would quantify earth materials based on biogeochemistry. He has made fundamental contributions to developing high spectral resolution field spectrometers and airborne imaging spectrometers, and to the image processing software and atmospheric correction software needed to analyze the data. These parallel developments in core technologies have made imaging spectroscopy available to a wide range of users of varying user expertise and disciplines, thus enabling the current state of rapid advances in the use of this dat

Hyperspectral Observations for Atmospheric Remote Sensing: Instrumentation, Atmospheric Correction, and Spectral Unmixing

Hyperspectral instruments expand the spectral dimension of remote sensing measurements by collecting data in hundreds of contiguous wavelength channels. Spectrally resolved measurements can be used to derive science products for a diverse range of fields such as atmospheric science, geology, oceanography, ecology, climate monitoring, and agricultural science, to name a few. The spectral information collected by hyperspectral instruments enables more accurate retrievals of physical properties and detection of temporal changes. These advantages have led to an increasing number of active and planned hyperspectral instruments. This thesis describes methods for attributing hyperspectral radiation observations to physical sources.We developed, validated and characterized improvements to a hyperspectral instrument, the Solar Spectral Irradiance Monitor (SSIM), built at the University of Colorado Boulder’s Laboratory for Atmospheric and Space Physics. Contributions include the characterization of the optics’ angular response, testing of an optics stabilizing platform and the development and testing of a spectrometer thermal control system. This instrument was then deployed on an aircraft for a field study with the National Ecological Observatory Network (NEON). SSIM measurements of upwelling and downwelling irradiance were used in conjunction with NEON’s Imaging Spectrometer to enable atmospheric correction of imagery collected below cloud layers.We developed a numerical spectral unmixing algorithm, Informed Non-Negative Matrix Factorization (INMF), to separate contributions to hyperspectral imagery from distinct physical sources such as surface reflectance, atmospheric absorption, molecular scattering, and aerosol scattering. INMF was tailored for hyperspectral applications by introducing algorithmic constraints based on the physics of radiative transfer. INMF was tested using imagery collected by the Hyperspectral Imager for the Coastal Ocean (HICO). To validate the method INMF results were compared to model-based atmospheric correction results. We demonstrate possible applications of INMF by presenting the retrieval of two physical properties, aerosol attributed radiance and seafloor depth. The retrievals were evaluated by comparing INMF output to independent retrievals of aerosol properties from the Moderate Resolution Imaging Spectroradiometer (MODIS) and in-situ seafloor depth measurements from the U.S. Coastal Relief Model. In these comparisons INMF shows promise for retrieving both physical properties, and may be improved with physics-based constraints on the seafloor and aerosol source spectra

Mediterranean Forest Species Mapping Using Hyperspectral Imagery

2011/2012Advances in hyperspectral technology provides scientists the opportunity to investigate problems that were difficult if not impossible to approach using multispectral data; among those, species composition which is a very important and dynamic forest parameter, linked with many environmental qualities that we want to map and monitor. This study addresses the problem of Mediterranean forest species mapping using satellite EO-1 Hyperion imagery (30m, 196 bands). Two pixel based techniques were evaluated, namely Spectral Angle Mapper (SAM) and Support Vector Machines (SVM), as well as an object oriented approach (GEOBIA). These techniques were applied in two study areas with different species composition and pattern complexity, namely Thasos and Taksiarchis. Extensive field work provided reference data for the accuracy assessment of the produced maps. Image preprocessing included several steps of data corrections and the Minimum Noise Fraction transformation, as means for data dimensionality reduction. In the case of Thasos, where two conifer species are present, SAM technique resulted in an overall accuracy (OA) of 3.9%, SVM technique yielded OA of 89.0% and GEOBIA achieved an OA of 85.3%. In the case of Taksiarchis, where more species are present – both conifers and broadleaved- the respective OA was 80.0%, 82.6% and 74.1%. All three methodologies implemented to investigate the value of hyperspectral imagery in Mediterranean forest species mapping, achieved very accurate results; in some cases equivalent to forest inventory maps. SAM was the straightest forward to implement, only depending on the training samples. Implementation SVM involved the specification of several parameters as well as the use of custom software and was more successful in the challenging landscape of Taksiarchis. GEOBIA adapted to scale through segmentation and extended the exercise of classification, allowing for knowledge based refinement. Lower accuracies could be attributed to the assessment method, as research on alternative assessment methods better adapted to the nature of object space is ongoing. Two typical Mediterranean forests were studied. In Thasos, two conifer species of the same genus, namely Pinus brutia and Pinus nigra, dominate a big part of the island. Both of them were accurately mapped by all methodologies. In Taksiarchis primarily stands of Quercus frainetto mix with stands of Fagus sylvatica and the aforementioned pines. The two pines were again mapped with high accuracy. However, there was a notable confusion between the two broadleaved species, indicating the need for further research, possibly taking advantage of species phenology. The outcome of the proposed methodologies could confidently meet the current needs for vegetation geographical data in regional to national scale, and demonstrate the value of hyperspectral imagery in Mediterranean forest species mapping.XXIII Ciclo198