Angelo Palombo

Experimental Approach to the Selection of the Components in the Minimum Noise Fraction

An experimental method to select the number of principal components in minimum noise fraction (MNF) is proposed to process images measured by imagery sensors onboard aircraft or satellites. The method is based on an experimental measurement by spectrometers in dark conditions from which noise structure can be estimated. To represent typical land conditions and atmospheric variability, a significative data set of synthetic noise-free images based on real Multispectral Infrared and Visible Imaging Spectrometer images is built. To this purpose, a subset of spectra is selected within some public libraries that well represent the simulated images. By coupling these synthetic images and estimated noise, the optimal number of components in MNF can be obtained. In order to have an objective (fully data driven) procedure, some criteria are proposed, and the results are validated to estimate the number of components without relying on ancillary data. The whole procedure is made computationally feasible by some simplifications that are introduced. A comparison with a state-of-the-art algorithm for estimating the optimal number of components is also made.

Transport infrastructure surveillance and monitoring by electromagnetic sensing: the ISTIMES project

The ISTIMES project, funded by the European Commission in the frame of a joint Call “ICT and Security” of the Seventh Framework Programme, is presented and preliminary research results are discussed. The main objective of the ISTIMES project is to design, assess and promote an Information and Communication Technologies (ICT)-based system, exploiting distributed and local sensors, for non-destructive electromagnetic monitoring of critical transport infrastructures. The integration of electromagnetic technologies with new ICT information and telecommunications systems enables remotely controlled monitoring and surveillance and real time data imaging of the critical transport infrastructures. The project exploits different non-invasive imaging technologies based on electromagnetic sensing (optic fiber sensors, Synthetic Aperture Radar satellite platform based, hyperspectral spectroscopy, Infrared thermography, Ground Penetrating Radar-, low-frequency geophysical techniques, Ground based systems for displacement monitoring). In this paper, we show the preliminary results arising from the GPR and infrared thermographic measurements carried out on the Musmeci bridge in Potenza, located in a highly seismic area of the Apennine chain (Southern Italy) and representing one of the test beds of the project.

Assessment of the abnormal growth of floating macrophytes in Winam Gulf (Kenya) by using MODIS imagery time series

Abstract The objective of this research study is to assess the capability of time-series of MODIS imagery to provide information suitable for enhancing the understanding of the temporal cycles shown by the abnormal growth of the floating macrophytes in order to support monitoring and management action of Lake Victoria water resources. The proliferation of invasive plants and aquatic weeds is of growing concern. Starting from 1989, Lake Victoria has been interested by the high infestation of water hyacinth with significant socio-economic impact on riparian populations. In this paper, we describe an approach based on the time-series of MODIS to derive the temporal behaviour, the abundance and distribution of the floating macrophytes in the Winam Gulf (Kenyan portion of the Lake Victoria) and its possible links to the concentrations of the main water constituencies. To this end, we consider the NDVI values computed from the MODIS imagery time-series from 2000 to 2009 to identify the floating macrophytes cover and an appropriate bio-optical model to retrieve, by means of an inverse procedure, the concentrations of chlorophyll a, coloured dissolved organic matter and total suspended solid. The maps of the floating vegetation based on the NDVI values allow us to assess the spatial and temporal dynamics of the weeds with high time resolution. A floating vegetation index (FVI) has been introduced for describing the weeds pollution level. The results of the analysis show a consistent temporal relation between the water constituent concentrations within the Winam Gulf and the FVI, especially in the proximity of the greatest proliferation of floating vegetation in the last 10 years that occurred between the second half of 2006 and the first half of 2007.The adopted approach will be useful to implement an automatic system for monitoring and predicting the floating macrophytes proliferation in Lake Victoria.

Downstream Services for Rice Crop Monitoring in Europe: From Regional to Local Scale

The ERMES agromonitoring system for rice cultivations integrates EO data at different resolutions, crop models, and user-provided in situ data in a unified system, which drives two operational downstream services for rice monitoring. The first is aimed at providing information concerning the behavior of the current season at regional/rice district scale, while the second is dedicated to provide farmers with field-scale data useful to support more efficient and environmentally friendly crop practices. In this contribution, we describe the main characteristics of the system, in terms of overall architecture, technological solutions adopted, characteristics of the developed products, and functionalities provided to end users. Peculiarities of the system reside in its ability to cope with the needs of different stakeholders within a common platform, and in a tight integration between EO data processing and information retrieval, crop modeling, in situ data collection, and information dissemination. The ERMES system has been operationally tested in three European rice-producing countries (Italy, Spain, and Greece) during growing seasons 2015 and 2016, providing a great amount of near-real-time information concerning rice crops. Highlights of significant results are provided, with particular focus on real-world applications of ERMES products and services. Although developed with focus on European rice cultivations, solutions implemented in the ERMES system can be, and are already being, adapted to other crops and/or areas of the world, thus making it a valuable testing bed for the development of advanced, integrated agricultural monitoring systems.

Reducing the Influence of Soil Moisture on the Estimation of Clay from Hyperspectral Data: A Case Study Using Simulated PRISMA Data

Soil moisture hampers the estimation of soil variables such as clay content from remote and proximal sensing data, reducing the strength of the relevant spectral absorption features. In the present study, two different strategies have been evaluated for their ability to minimize the influence of soil moisture on clay estimation by using soil spectra acquired in a laboratory and by simulating satellite hyperspectral data. Simulated satellite data were obtained according to the spectral characteristics of the forthcoming hyperspectral imager on board of the Italian PRISMA satellite mission. The soil datasets were split into four groups according to the water content. For each soil moisture level a prediction model was applied, using either spectral indices or partial least squares regression (PLSR). Prediction models were either specifically developed for the soil moisture level or calibrated using synthetically dry soil spectra, generated from wet soil data. Synthetically dry spectra were obtained using a new technique based on the effects caused by soil moisture on the optical spectrum from 400 to 2400 nm. The estimation of soil clay content, when using different prediction models according to soil moisture, was slightly more accurate as compared to the use of synthetically dry soil spectra, both employing clay indices and PLSR models. The results obtained in this study demonstrate that the a priori knowledge of the soil moisture class can reduce the error of clay estimation when using hyperspectral remote sensing data, such as those that will be provided by the PRISMA satellite mission in the near future.

An advanced tool of the CNR IMAA EO facilities: Overview of the TASI-600 hyperspectral thermal spectrometer

The paper shows the TASI-600 thermal hyperspectral sensor acquired by the Italian National Research Council — Institute of Methodologies for Environmental Analysis (CNR-IMAA) and describes some of the checks carried out during the commissioning phase. Furthermore, the first data acquired during the test-flight on hot spots of the volcanic island of Ischia (Central Italy) are shown. TASI-600 sensor has 32 spectral bands in the 8.0–11.5 mm spectral range, with a swath of 300 pixels and an IFOV of 1.2 mRad. The paper gives an overview of the principal TASI-600 characteristics, the CNR IMAA performance requirements and an overview of the technical innovation. Some of the outcomes of the tests performed in our laboratory in the Final Acceptance Test were focused to verify the linearity of the sensor up to higher temperatures (i.e. up to 500 K). Preliminary analysis of the in-flight and lab functional tests demonstrated that TASI-600 meets CNR IMAA requirements and as regard the radiometric accuracy it results higher than the requested.

A new joint application of non-invasive remote sensing techniques for structural health monitoring

This paper aims at analysing the potentialities of a new technological approach for the dynamic monitoring of civil infrastructures. The proposed approach is based on the joint use of a high-frequency thermal camera and a microwave radar interferometer to measure the oscillations due to traffic excitations of the Sihlhochstrasse Bridge, Switzerland, which was selected as test bed site in the ISTIMES project (EU—Seventh Framework Programme). The good quality of the results encourages the use of the proposed approach for the static and dynamic investigation of structures and infrastructures. Moreover, the remote sensing character of the two applied techniques makes them particularly suitable to study structures located in areas affected by natural hazard phenomena, and also to monitor cultural heritage buildings for which some conventional techniques are considered invasive. Obviously, their reliability needs further experiments and comparisons with standard contact sensors.

Suitability of CASI and ATM airborne remote sensing data for archaeological subsurface structure detection under different land cover: the Arpi case study (Italy)

In this paper multi-sensor airborne remote sensing has been applied to the Arpi archaeological area of southern Italy to assess its suitability for detecting and locating subsurface archaeological structures and to delineate subsurface remains beyond the current limits of ground geophysical data. To this aim, the capability of CASI and ATM reflectances in the VIS–NIR spectral range and the ATM apparent thermal inertia for subsurface archaeological prospection have been assessed at different sites of the Arpi archaeological area. First, linear spectral mixture analysis has been applied to CASI and ATM images to retrieve the dominant land cover for the selected subsurface structures, and then, the spectral bands most effective for the archaeological buried structure detection as a function of the land cover characteristics have been evaluated. The results reveal that multi/hyperspectral airborne remote sensing data can represent an effective and rapid tool to detect subsurface structures within different land cover contexts. Therefore, the proposed methodology can be used to perform a preliminary analysis of those areas where large cultural heritage assets occur by prioritizing and localizing the sites where to apply archaeological prospection.

Advanced Anomalous Pixel Correction Algorithms for Hyperspectral Thermal Infrared Data: The TASI-600 Case Study

Anomalous pixel responses often seriously affect remote sensing applications, especially in the thermal spectral range. In this paper, a new method to identify and correct anomalous pixel responses is presented. The method was specifically developed to handle with hyperspectral data and is based on the statistical analysis of a gray scale RX detector (RXD) image applied on the focal plane space rather than on the image space. An iterative thresholding method to correct anomalous pixels in automatic modality was tuned. Moreover, a band depth-based method to properly restore the lost information was applied. The band depth method serves to prevent the creation of new artifacts during the anomalous pixel correction that could affect applications such as anomaly or change detection and classification for thermal infrared (TIR) hyperspectral imagery. In this paper, we take into consideration hyperspectral TASI-600 data acquired during recent airborne campaigns in Europe. Evidences of the benefits on remote sensing applications such as classification and change detection algorithms in urban areas are shown.

Noninvasive Remote Sensing Techniques for Infrastructures Diagnostics

The present paper aims at analyzing the potentialities of noninvasive remote sensing techniques used for detecting the conservation status of infrastructures. The applied remote sensing techniques are ground-based microwave radar interferometer and InfraRed Thermography (IRT) to study a particular structure planned and made in the framework of the ISTIMES project (funded by the European Commission in the frame of a joint Call “ICT and Security” of the Seventh Framework Programme). To exploit the effectiveness of the high-resolution remote sensing techniques applied we will use the high-frequency thermal camera to measure the structures oscillations by high-frequency analysis and ground-based microwave radar interferometer to measure the dynamic displacement of several points belonging to a large structure. The paper describes the preliminary research results and discusses on the future applicability and techniques developments for integrating high-frequency time series data of the thermal imagery and ground-based microwave radar interferometer data.