Multispectral Infrared And Visible Imaging Spectrometer Data Research Articles

Chlorophyll concentration mapping with MIVIS data to assess crown discoloration in the Ticino Park oak forest

Airborne hyperspectral remote observations, characterized by high spatial and spectral resolution, allow the estimation of quantitative vegetation variables useful in forest condition assessment. In this research, total chlorophyll (a + b) concentration (C ab), a biochemical variable describing crown discoloration rate, was mapped to assess oak (Quercus robur L.) condition in the Ticino Regional Park. A simulation experiment was conducted to evaluate the error in C ab estimation due to ecological variables (i.e. canopy leaf area index and understorey characteristics) and to sun-sensor configurations when optical indices are used. Canopy reflectance was simulated by means of the PROSPECT leaf radiative transfer model (Jacquemoud and Baret 1990) coupled with the SAILH canopy radiative transfer model, a variation of the SAIL (Scattering by Arbitrarily Inclined Leaves) model modified to include the hot spot effect (Verhoef 1984, Kuusk 1991). The vegetation was modelled as a two layer medium with oak canopy as the top layer and the understorey as the bottom layer. Simulations were performed for varying leaf C ab and canopy Leaf Area Index (LAI) of the top layer, θl (mean leaf inclination angle) and LAI of the bottom layer (LAIu) and sun-sensor geometry. Optical indices were calculated and used in C ab retrieval. Simulations demonstrated that errors in C ab estimation were negligible when MTCI (MERIS Terrestrial Chlorophyll Index) was used, thus indicating that MTCI was the most reliable index in mapping C ab in this forest environment. Empirical models based on optical indices were developed to map C ab from Multispectral Infrared and Visible Imaging Spectrometer (MIVIS) images acquired by an airborne survey on the Park forested area. A regression analysis between C ab concentration measured in leaves sampled in field and optical indices computed from hyperspectral MIVIS data was conducted. The MTCI index showed the highest performances and was therefore used to map C ab concentration of the Ticino Park oak forest. The C ab map was then used to assess crown discoloration level.

Aerial remote sensing hyperspectral techniques for rocky outcrops mapping

In this work the MIVIS (Multispectral Infrared and Visible Imaging Spectrometer) hyperspectral data, acquired during aerial campaigns made in 1998 over the Pollino National Park in the framework of the «Progetto Pollino», have been used to set up a supervised technique devoted to identify the presence of selected rocky outcrops. Tests have been performed over an extended area characterised by a complex orography. Within this area, serpentinite was chosen as a test-rock because it is present in isolated outcrops, distributed all over the test-area, besides subtending important problems of environmental nature as it contains asbestos. Geological information, coming from field observations or geological maps, was used to trigger the algorithms and as ground truth for its validation. Two spectral analysis techniques, SAM (Spectral Angle Mapper) and LSU (Linear Spectral Unmixing), have been applied and their results n combined to automatically identify serpentinite outcrops and, in some cases, to mark its boundaries. The approach used in this work is characterised by simplicity (no atmosphere and illumination corrections were performed on MIVIS data), robustness (material of interest is identified for certainty) and intrinsic exportability (the method proposed can be applied on different geographic areas and, in theory, to identify any kind of material because no datum about atmospheric and illumination conditions is required).

Estimation of leaf and canopy water content in poplar plantations by means of hyperspectral indices and inverse modeling

This study investigates the applicability of empirical and radiative transfer models to estimate water content at leaf and landscape level. The main goal is to evaluate and compare the accuracy of these two approaches for estimating leaf water content by means of laboratory reflectance/transmittance measurements and for mapping leaf and canopy water content by using airborne Multispectral Infrared and Visible Imaging Spectrometer (MIVIS) data acquired over intensive poplar plantations (Ticino, Italy). At leaf level, we tested the performance of different spectral indices to estimate leaf equivalent water thickness (EWT) and leaf gravimetric water content (GWC) by using inverse ordinary least squares (OLS) regression, and reduced major axis (RMA) regression. The analysis showed that leaf reflectance is related to changes in EWT rather than GWC, with best results obtained by using RMA regression by exploiting the spectral index related to the continuum removed area of the 1200 nm water absorption feature with an explained variance of 61% and prediction error of 6.6%. Moreover, we inverted the PROSPECT leaf radiative transfer model to estimate leaf EWT and GWC and compared the results with those obtained by means of empirical models. The inversion of this model showed that leaf EWT can be successfully estimated with no prior information with mean relative errors of 14% and determination coefficient of 0.65. Inversion of the PROSPECT model showed some difficulties in the simultaneous estimation of leaf EWT and dry matter content, which led to large errors in GWC estimation. At landscape level with MIVIS data, we tested the performance of different spectral indices to estimate canopy water per unit ground area (EWT canopy). We found a relative error of 20% using a continuum removed spectral index around 1200 nm. Furthermore, we used a model simulation to evaluate the possibility of applying empirical models based on appositely developed MIVIS double ratios to estimate mean leaf EWT at landscape level ( EWT ― ). It is shown that combined indices (double ratios) yielded significant results in estimating leaf EWT at landscape level by using MIVIS data (with errors around 2.6%), indicating their potential in reducing the effects of LAI on the recorded signal. The accuracy of the empirical estimation of EWT canopy and EWT ― was finally compared with that obtained from inversion of the PROSPECT + SAILH canopy reflectance model to evaluate the potential of both methods for practical applications. A relative error of 27% was found for EWT canopy and an overestimation of leaf EWT ― with relative errors around 19%. Results arising from this remote sensing application support the robustness of hyperspectral regression indices for estimating water content at both leaf and landscape level, with lower relative errors compared to those obtained from inversion of leaf and 1D canopy radiative transfer models.

Characterization and Mapping of Fuel Types for the Mediterranean Ecosystems of Pollino National Park in Southern Italy by Using Hyperspectral MIVIS Data

Abstract The characterization and mapping of fuel types is one of the most important factors that should be taken into consideration for wildland fire prevention and prefire planning. This research aims to investigate the usefulness of hyperspectral data to recognize and map fuel types in order to ascertain how well remote sensing data can provide an exhaustive classification of fuel properties. For this purpose airborne hyperspectral Multispectral Infrared and Visible Imaging Spectrometer (MIVIS) data acquired in November 1998 have been analyzed for a test area of 60 km2 selected inside Pollino National Park in the south of Italy. Fieldwork fuel-type recognitions, performed at the same time as remote sensing data acquisition, were used as a ground-truth dataset to assess the results obtained for the considered test area. The method comprised the following three steps: 1) adaptation of Prometheus fuel types for obtaining a standardization system useful for remotely sensed classification of fuel types and properties in the considered Mediterranean ecosystems; 2) model construction for the spectral characterization and mapping of fuel types based on a maximum likelihood (ML) classification algorithm; and 3) accuracy assessment for the performance evaluation based on the comparison of MIVIS-based results with ground truth. Results from our analysis showed that the use of remotely sensed data at high spatial and spectral resolution provided a valuable characterization and mapping of fuel types being that the achieved classification accuracy was higher than 90%.

Will ASTER see the Etna SO 2 plume?

The aim of this paper is to show the feasibility of evaluating the sulphur dioxide (SO 2 ) flux emitted by Mt Etna volcano, using remotely sensed data of Advanced Spaceborne Thermal Emission and Reflection radiometer (ASTER) in the thermal infrared (TIR). ASTER is one of the instruments on board the first Earth Observation System (EOS) satellite launched on 18 December 1999. To simulate the ASTER data, Multispectral Infrared and Visible Imaging Spectrometer (MIVIS) images, acquired during the 'Sicily '97' campaign, were used. The SO 2 column abundance maps shown in this paper have been obtained by means of a simple algorithm based on the split-window technique. The parameters of the algorithm were computed using Moderate Resolution Atmospheric Radiance and Transmittance Model (MODTRAN) simulations performed with atmospheric profiles acquired during MIVIS flights. The mean SO 2 flux on 12 and 16 June 1997, obtained using the ASTER simulated images, results in 42 and 33 kg s m 1 respectively; these values are in good agreement with the results obtained by the inversion procedure used by Teggi et al . (1999) applied to the MIVIS data and with the Correlation Spectrometer (COSPEC) measurements performed during the campaign by other teams.

Estimation of SO2 abundance in the eruption plume of Mt. Etna using two MIVIS thermal infrared channels: a case study from the Sicily-1997 Campaign

In this paper, an algorithm is developed based on the split-window technique, to estimate the SO2 abundance in the plume of Mt. Etna volcano using the multispectral infrared and visible imaging spectrometer (MIVIS). The MIVIS data were remotely sensed in the thermal infrared (TIR) during the Sicily-1997 Campaign. In this study, the MODTRAN 3.5 code has been used to simulate the radiance at the sensor; the radiative transfer model was input along with the data of radio-sounding performed simultaneously with the MIVIS flight using a mobile radio-theodolite. From the SO2 map, derived from the MIVIS image, the SO2 flux along the axis of the plume was computed knowing the wind speed at the plume altitude. The SO2 flux is variable along the plume axis. The average SO2 flux (about 45 kg s–1 on 12 June and about 30 kg s–1 on 16 June) emitted from the vents is compared with the correlation spectrometer (COSPEC) measurements carried out by other teams (from the ground and from a light aircraft flying under the plume) during the MIVIS flight. Finally, by means of this algorithm it should be easier, with respect to the previously described procedure to monitor the SO2 flux of a specific volcano such as Mt. Etna.