This paper studies change detection of LWIR (Long Wave Infrared) hyperspectral imagery. Goal is to improve target acquisition and situation awareness in urban areas with respect to conventional techniques. Hyperspectral and conventional broadband high-spatial-resolution data were collected during the DUCAS trials in Zeebrugge, Belgium, in June 2011. LWIR data were acquired using the ITRES Thermal Airborne Spectrographic Imager TASI-600 that operates in the spectral range of 8.0-11.5 μm (32 band configuration). Broadband data were acquired using two aeroplanemounted FLIR SC7000 MWIR cameras. Acquisition of the images was around noon. To limit the number of false alarms due to atmospheric changes, the time interval between the images is less than 2 hours. Local co-registration adjustment was applied to compensate for misregistration errors in the order of a few pixels. The targets in the data that will be analysed in this paper are different kinds of vehicles. Change detection algorithms that were applied and evaluated are Euclidean distance, Mahalanobis distance, Chronochrome (CC), Covariance Equalisation (CE), and Hyperbolic Anomalous Change Detection (HACD). Based on Receiver Operating Characteristics (ROC) we conclude that LWIR hyperspectral has an advantage over MWIR broadband change detection. The best hyperspectral detector is HACD because it is most robust to noise. MWIR high spatial-resolution broadband results show that it helps to apply a false alarm reduction strategy based on spatial processing.
In this paper the potential of the Hyperion spaceborne hyperspectral data in discriminating land covers in complex
natural ecosystems was evaluated according to the hierarchical structure of the European standard legend (CORINE
Land Cover 2000). Furthermore, the ability of the Hyperion data in retrieving land cover information at sub-pixel level
was assessed by exploiting the vegetation classes' distribution as obtained by aerial-photos.
Four standard supervised classifiers have been compared in terms of algorithm performance and class accuracy by
applying statistical metric; the best results were achieved with the Minimum Distance (MD) classifier.
In those areas exhibiting mixed pixels at the Hyperion spatial resolution a Linear Spectral Unmixing technique was
applied for deriving abundance fractions of the endmembers (i.e. land covers) previously identified. Accuracy of the un-mixing
analysis was evaluated using a Residual Error index calculated by relating Hyperion fractional abundances and
reference aerial-photos.
Results show the capability of Hyperion data to map land covers and vegetation diversity even at sub-pixel level within a
complex natural landscape.
This work is aimed to atmospherically correct remote sensing data in the solar spectral domain (Visible and Near Infrared)
allowing the better assessment of the surface spectral material characteristics. This was obtained by the inversion of
the radiative transfer equation for at-sensor signal. In order to detect targets with peculiar spectral characteristics, the
atmospheric correction has to take into account the diffuse radiation that constitutes a significant component to the at
sensor radiance. The effect of this component (namely adjacency effect), which tends to mask the pixel seen by the sensor,
derives principally from the atmospheric scattering due to the aerosol loading in the scene. At this purpose an algorithm
based on 6S calculation was defined to derive the direct and diffuse component of the radiation required to determine the
contribution to the pixel reflectance related to the surrounding pixels. The developed algorithm allowed the assessment of
this environmental contribution besides the pixel reflectance. Such application, on airborne hyperspectral sensor MIVIS
(Multispectral Infrared and Visible Imaging Spectrometer) scenes, leads to obtain accurate pixel reflectance if compared
with ground measurements acquired within testing areas. This work shows how adjacency effect has a significant role in
the correction of remote sensing data, especially if acquired by an airborne hyperspectral sensor. The preliminary analysis
of the results have highlighted that the adjacency effect is not negligible, mainly when pixels in the scene are spectrally
heterogeneous.
The study, proposed within the framework of the cooperation with Kenyan Authorities, has been carried out on the
Kenyan part of the Lake Victoria. This lake is one of the largest freshwater bodies of the world where, over the last few
years, environmental challenges and human impact have perturbed the ecological balance. Pollution and sediments loads
from the tributaries rivers and antrophic sources caused a worrying increase of the turbidity level of the lake water.
Secchi transparency index has declined from 5 meters in the 1930s to less than one meter in the 1990s. With the aim of
providing an inexpensive way to gather information linked to the water clarity and quality, a method for remotely sensed
data interpretation, devoted to produce chl (chlorophyll), CDOM (coloured dissolved organic matter) and TSS (total
suspended solids) maps, has been assessed. At this purpose a bio-optical model, based on radiative transfer theory in
water bodies, has been refined. The method has been applied on an image acquired on January 2004 by
ENVISAT/MERIS sensor just a week after an in situ campaign took place. During the in situ campaign a data set for
model refinement and products validation has been collected. This data comprise surface radiometric quantity and
samples for laboratory analyses. The comparison between the obtained maps and the data provided by the laboratory
analysis showed a good correspondence, demonstrating the potentiality of remote observation in supporting the
management of the water resources.
Land cover classification is one of the main applications of remotely sensed data and the capability of airborne hyperspectral data for such a purpose is known. The recent availability of high spatial resolution multispectral data, such as IKONOS and QuickBird, puts the question about advantages and disadvantages of these data in comparison with the hyperspectral ones. We evaluated the cost and accuracy of using IKONOS imagery to perform a land cover classification at high spatial resolution and compared them with results obtained from MIVIS airborne hyper-spectral scanner data (102 bands from VIS to TIR). The study was performed in a rural area (25 km2) of Basilicata region (Southern Italy) characterized by complex topography (altitude ranges from 600 to 1400m) and different land cover patterns (forests, lakes, cultivated areas, and small urban areas). Evaluations were made taking into account time-processing, feature extraction, accuracy for different classification levels, and costs as a function of the extension of the area to be classified. Quite high accuracies were obtained for the first classification level, whereas increasing the class number IKONOS was less accurate than MIVIS. Multispectral classification well identified the different forest species, but had some problems in distinguishing between gravel road and some plowed lands. The obtained results showed that IKONOS data are cost-effective for updating thematic maps to support planning and decision-making processes at local government scale.
Physical parameters related to Earth surface and atmosphere show different behaviors when observed at different space-time scales by using both remote sensing or traditional ground based techniques. The main aim of this project was to investigate the information content degradation which results moving from the use of observations obtained by direct-punctual (ground-based), higher spectral/spatial resolution (airborne sensors), higher time-resolution, low cost and low spatial resolution (satellites), in the context of the activities related to natural and environmental risks monitoring in protected natural areas. Several observational techniques have been contemporary used during two fields campaigns in the Pollino National Park (Southern Italy): a) from ground by direct measurements of near surface parameters (from - 70cm of depth up to 200cm of height) as well as by radiosonde and radiometric measurements of surface and atmospheric parameters; b) using hyperspectral (MIVIS) and photographic aerial observations; c) from LANDSAT-TM, NOAAA/AVHRR and ADEOS/AVIRIS satellite sounders. Campaign data have been integrated on a GIS (including high resolution cartographic layers) and long term evolutionary trends (up to 20 years) also considered after the analysis of available historical, LANDSAT and NOAA, satellite records. This paper will present the main achievements of the project with special emphasis on the trade-off between expected performances and economical sustainability of different environmental monitoring strategies in an operational context.
In southern Italy the Basilicata Region authorities are strongly active in monitoring the regional environment for planning actions to undertake. To this aim the Basilicata Region has been promoting dedicated remote sensing activities. The criteria adopted in starting the initiatives are based on the use of the best available technologies and their integration with standard methodologies (satellite and airborne data integrated with ground measurements) devoted to the best planning and management of the territory. Airborne surveys were deployed mainly to derive the main land cover and vegetative units to allows the outset of detailed studies of physical-chemical characteristics of the natural (geologic outcrop and vegetative species discrimination) materials in the park zones highly protected. The resulting thematic map at 1:10.000 scale is, in comparison with the available ones, has a better detail whether in term of number of classes depicted or in term of classes distribution. The spectral resolution of the data has also evidenced the aptitude of the land cover maps to describe local ecosystem and to derive local biophysical important variables useful for management implications and to allow a correct parameterization of the surface variables useful to the modeling community.
In this work, a simple and robust technique, that allows for automatic identifying of surface materials by using Multispectral Infrared and Visible Imaging Spectrometer (MIVIS) radiances was applied in order to recognize rocky outcrops in the area of the Pollino National Park (southern Apennines, Italy). Tests were made over an area which is topographically complex and geologically characterized by ophiolite-bearing units (Ligurian units), Meso-Cenozoic shallow-water carbonates (Pollino Unit) and Plio-Quaternary sediments. Among ophiolitic rocks, serpentinite was chosen as a test-rock as it is present in isolated outcrops in the test-area, besides subtending important environmental problems because it contains asbestos. Geological information, coming from field observations or geological maps, was used as input and in order to verify the results of the MIVIS data processing.
Within the Pollino National Park environmental monitoring promoted by the Basilicata Region authorities (southern Italy), hyperspectral airborne data surveys were deployed to collect spectra images with higher spectral/spatial resolution. In order to define a standard atmospheric procedure to be applied to MIVIS data set, different radiative transfers code has been tested. Unfortunately generic correction procedures, like ATREM, widely applied to airborne hyperspectral data sets, could not be used for MIVIS data set because of the absence of the specific water absorption bands (0.94 and 1.14micrometers ) in its spectral region coverage. In this paper a technique to recover the right slope of the water absorption bands centered at 0.82micrometers , not measured by the MIVIS spectral resolution, is presented. The synthetic 0.84micrometers channel is spectrally recovered in place, by using the spectral behavior of each pixel. Channel simulations have been conducted on AVIRIS data sets resampled on the MIVIS NIR spectral channel curves and compared with the AVIRIS ones recorded at 0.84 micrometers . Data simulation has proved the efficiency of the method and the spectral coherence of the synthetic bands centred at 0.84(mu) +m. As a consequence the atmospheric correction code ATREM, with the help of appropriate contrivance to rescale the water vapour atmospheric amount, could be applied to the MIVIS data set by selecting, in the ATREM input file, only the water absorption band centred at 0.82micrometers .
The Straits of Messina was surveyed on September the 25th 1999, at 14:15 local time, by means of the 4 spectrometers of Multispectral Infrared Visible Imaging Spectrometer instrument, recording 102 channels from Visible to Thermal Infrared along four southwards oriented flight lines. The first flight line was recorded from an altitudes of 1500 m a.s.1. (nadir pixel size of 3 m), while the others have been acquired from an altitudes of 4000 m a.s.1. (nadir pixel size of 8 m). In the Straits of Messina the strong tidal currents as well as the morphological features determine the upwelling of deep waters to the photic layer. Traditional oceanographic surveys, based on period punctual sampling, are sometimes inadequate to deeply investigate the areas subjected to high variability altering in space and in time the distribution of abiotic and biotic parameters. The effect of tidal currents on the upwelling of the Straits of Messina was measured by using the MIVIS hyperspectral sensor and through the continuous survey of some tracer parameters from sailing vessel. The collected hyperspectral data sets, once calibrated to reflectance (by using atmospheric model and fields spectra collected during the campaign) and geometrically corrected, were used to develop preliminary local bio-optical algorithms derived from in situ (ground and sea) measurements and to obtain suitable mapping of the chlorophyll distribution and of the Sea Surface Temperature of the investigated area.
This presentation, taking its inspiration from various theoretical contributions suggested by various proposals, and going beyond the usual explanations and sometimes rash forecasts that the impact of a new technology has on physical space, wishes to underline the most important aspects of the introduction of a new method of studying urban installations, both ancient and modern, which is offered by urban telesurveys. To this end it is proposed, by means of an analysis of a sample area obtained from tele- surveying data provided by an aerial survey, using an advanced system of electronic pictures shot by MIVIS AA500000 of the CNR-Progetto LARA, to reveal and elaborate various findings and thus highlight a quantity and quality of extremely useful data.
KEYWORDS: Image processing, 3D modeling, Scanners, Global Positioning System, Spectrometers, 3D image processing, Raster graphics, Software development, Data modeling, Sensors
Study to develop a software methodology to geocode MIVIS hyperspectral images collected by the CNR LARA Project. Goal of the study is to integrate the airborne position and attitude system with the image data to obtain geocoded images at a medium-small scale (1:15000 - 1:10000).
On February 1994 a large area close to Trecate was affected by an oil blow-out from an AGIP rig located within the Ticino Regional Park. One month later an airborne survey has been carried out in the framework of the CNR Lara Project, by utilizing the Daedalus AA5000 MIVIS spectrometer with 102 channels from visible to thermal infrared. Different authors stress, for oil slicks discrimination, the utility of laser and microwaves based techniques, but the high spatial and spectral MIVIS resolutions can improve the detection of the relative coverage by spilled oil. This task has been performed by applying hyperspectral unmixing methods to the MIVIS calibrated data, obtaining an oil fractional image with respect to other chosen end-members. The analysis has shown a good agreement between the results of the unconstrained unmixing technique applied to MIVIS data and the ground truths, offering a tool useful to quantify in a synoptic overview the effects of oil spills over land, by relating the ppm of oil with the oil hyperspectral information gathered by MIVIS.
The availability of MIVIS hyperspectral data, deriving from an aerial survey recently performed over a test-site in Lake Garda, Italy, gave the possibility of a preliminary new insight in the field of specific applications of remote sensing to shallow water analysis. The spectroradiometers in the visible and in the thermal infrared were explored in particular, accessing to helpful information for the detection of bio-physical indicators of water quality, either related to the surface/sub-surface of waters or to the bottom of the lake, since the study area presents very shallow waters, never exceeding a 6-meter depth in any case. Primary interest was the detection of man-induced activities along the margins, like sewage effect and sedimentary structure in the bottom or algal bloom. Secondly, a correlation between absorbivity coefficients in the visible bands and bathimetric contour lines in the proximity of the marginal zone of the lake was accomplished, by means of two indicative spectroradiometric transects.
The Italian National Research Council (CNR) in the framework of its `Strategic Project for Climate and Environment in Southern Italy' established a new laboratory for airborne hyperspectral imaging devoted to environmental problems. Since the end of June 1994, the LARA (Laboratorio Aereo per Ricerche Ambientali -- Airborne Laboratory for Environmental Studies) Project is fully operative to provide hyperspectral data to the national and international scientific community by means of deployments of its CASA-212 aircraft carrying the Daedalus AA5000 MIVIS (multispectral infrared and visible imaging spectrometer) system. MIVIS is a modular instrument consisting of 102 spectral channels that use independent optical sensors simultaneously sampled and recorded onto a compact computer compatible magnetic tape medium with a data capacity of 10.2 Gbytes. To support the preprocessing and production pipeline of the large hyperspectral data sets CNR housed in Pomezia, a town close to Rome, a ground based computer system with a software designed to handle MIVIS data. The software (MIDAS-Multispectral Interactive Data Analysis System), besides the data production management, gives to users a powerful and highly extensible hyperspectral analysis system. The Pomezia's ground station is designed to maintain and check the MIVIS instrument performance through the evaluation of data quality (like spectral accuracy, signal to noise performance, signal variations, etc.), and to produce, archive, and diffuse MIVIS data in the form of geometrically and radiometrically corrected data sets on low cost and easy access CC media.
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