Papers by simone pascucci
The performance of empirical band ratio models were evaluated for the estimation of Coloured Diss... more The performance of empirical band ratio models were evaluated for the estimation of Coloured Dissolved Organic Matter (CDOM) using MODIS ocean colour sensor images and data collected on the North-Central Western Adriatic Sea (Mediterranean Sea). Relationships between in situ measurements (2013–2016) of CDOM absorption coefficients at 355 nm (a CDOM 355) with several MODIS satellite band ratios were evaluated on a test data set. The prediction capability of the different linear models was assessed on a validation data set. Based on some statistical diagnostic parameters (R 2 , APD and RMSE), the best MODIS band ratio performance in retrieving CDOM was obtained by a simple linear model of the transformed dependent variable using the remote sensing reflectance band ratio R rs (667)/R rs (488) as the only independent variable. The best-retrieved CDOM algorithm provides very good results for the complex coastal area along the North-Central Western Adriatic Sea where the Po River outflow is the main driving force in CDOM and nutrient circulation, which in winter mostly remains confined to a coastal boundary layer, whereas in summer it spreads to the open sea as well.
In this study the capabilities of seven multispectral and hyperspectral satellite imagers to esti... more In this study the capabilities of seven multispectral and hyperspectral satellite imagers to estimate soil variables (clay, sand, silt and organic carbon content) were investigated using data from soil spectral libraries. Four current (EO-1 ALI and Hyperion, Landsat 8 OLI, Sentinel-2 MSI) and three forthcoming (EnMAP, PRISMA and HyspIRI) satellite imagers were compared. To this aim, two soil spectra datasets that simulated each imager were obtained: (i) resampled spectra according to the specific spectral response and resolution of each satellite imager and (ii) resampled spectra with declared or actual noise (radiometric and atmospheric) added. Compared with those using full spectral resolution data, the accuracy of Partial Least Square Regression (PLSR) predictive models generally decreased when using resampled spectra. In the absence of noise, the performances of hyperspectral im-agers, in terms of Ratio of Performance to Interquartile Range (RPIQ), were generally significantly better than those of multispectral imagers. For instance the best RPIQ for sand estimation was obtained using EnMAP simulated data (2.56), whereas the outcomes gained using multispectral imagers varied from 1.56 and 2.28. The addition of noise to the simulated spectra brought about a decrease of statistical accuracy in all estimation models, especially for Hyperion data. Although the addition of noise reduced the performance differences between multispectral and hyperspectral imagers, the forthcoming hyperspectral imagers nonetheless provided the best RPIQ values for clay (2.16–2.33), sand (2.10–2.17), silt (2.77–2.85) and organic carbon (2.48–2.51) estimation. To better understand the impact of spectral resolution and signal to noise ratio (SNR) on the estimation of soil variables, PLSR models were applied to resampled and simulated spectra, iteratively increasing the band-width to: 10, 20, 40, 80 and 160 nm. Results showed that, for a bandwidth of 40 nm, i.e., a spectral resolution lower than that of current and forthcoming imagers, the estimation accuracy was very similar to that obtained with a higher spectral resolution. Forthcoming hyperspectral imagers will therefore improve the accuracy of soil variables estimation from bare soil imagery with respect to the results achievable by current hyperspectral and multispectral imagers, however this improvement is still too limited, to allow an accurate quantitative estimation of soil texture and SOC. This work provides useful indications about what could be expected, for the estimation of the most important soil variables , from the next generation of hyperspectral satellite imagers.
Process-based models can be usefully employed for the assessment of field and regional-scale impa... more Process-based models can be usefully employed for the assessment of field and regional-scale impact of drought on crop yields. However, in many instances, especially when they are used at the regional scale, it is necessary to identify the parameters and input variables that most influence the outputs and to assess how their influence varies when climatic and environmental conditions change. In this work, two different crop models, able to represent yield response to water, Aquacrop and SAFYE, were compared, with the aim to quantify their complexity and plasticity through Global Sensitivity Analysis (GSA), using Morris and EFAST (Extended Fourier Amplitude Sensitivity Test) techniques, for moderate to strong water limited climate scenarios. Although the rankings of the sensitivity indices was influenced by the scenarios used, the correlation among the rankings, higher for SAFYE than for Aquacrop, assessed by the top-down correlation coefficient (TDCC), revealed clear patterns. Parameters and input variables related to phenology and to water stress physiological processes were found to be the most influential for Aquacrop. For SAFYE, it was found that the water stress could be inferred indirectly from the processes regulating leaf growth, described in the original SAFY model. SAFYE has a lower complexity and plasticity than Aquacrop, making it more suitable to less data demanding regional scale applications, in case the only objective is the assessment of crop yield and no detailed information is sought on the mechanisms of the stress factors affecting its limitations.
—The ERMES agromonitoring system for rice cultiva-tions integrates EO data at different resolutio... more —The ERMES agromonitoring system for rice cultiva-tions 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 function-alities 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.
European Journal of Soil Science, 2014
A study was carried out to investigate the usefulness of multispectral and hyperspectral satellit... more A study was carried out to investigate the usefulness of multispectral and hyperspectral satellite information for the estimation of soil properties of agronomic importance such as soil texture and organic matter (SOM) in cultivated fields by comparing different estimation procedures. Images acquired from the Advanced Land Imager (ALI) and Hyperion sensors on board the EO-1 satellite were used, in combination with ground-sampling data from an agricultural field in central Italy, to evaluate the advantage of taking into account the spatial correlation between pixels. For this purpose, partial least squares regression (PLSR), ordinary least square (OLS) regression, regression with correlated errors (restricted maximum likelihood; REML) and ordinary kriging (OK) were compared through leave-one-out cross-validation. In order to predict soil variables by different models, the predictors of OLS and REML regressions were obtained from principal component analysis (PCA), PLSR and the minimum noise fraction (MNF) transformations of spectral data on bare soil or vegetation images. The PLSR did not provide satisfactory results in terms of root mean square error (RMSE) and ratio of performance to interquartile range (RPIQ) statistics, even with hyperspectral data, mainly because of the poor signal to noise ratio (SNR) of the Hyperion sensor. The estimation accuracy increased by using the MNF method in combination with a linear mixed effect model. A multivariate approach was sometimes better than univariate ordinary kriging (OK), demonstrating the value of including Hyperion bare soil or vegetation data in the estimation procedure. Hyperspectral data provided better results than multispectral data for clay, sand and especially for SOM estimation, highlighting the value of high-resolution spectral data for soil-related applications.
2009 Joint Urban Remote Sensing Event, 2009
This paper describes the suitability of airborne emissivity data to locate those materials notewo... more This paper describes the suitability of airborne emissivity data to locate those materials noteworthy in an urban context. Among them, the test cases of asphalt roads and asbestos cement roofs were analyzed to individuate those where a maintenance intervention is required. To this aim, we first identify and select using a segmentation procedure the roads' asphalt pavements and the asbestos
Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VII, 2007
Aim of this study is the identification of the hyperspectral scanner operational characteristics ... more Aim of this study is the identification of the hyperspectral scanner operational characteristics allowing for asbestos cement (AC) roofing sheets deterioration status assessment that is related to the asbestos fibers abundance. At this purpose we made laboratory measurements on AC samples with different deterioration status collected in two industrial areas in Italy. The asbestos occurrence in the AC samples was
2012 IEEE International Geoscience and Remote Sensing Symposium, 2012
In this paper we deal with the integrated use of time-series of SAR and MODIS images to derive th... more In this paper we deal with the integrated use of time-series of SAR and MODIS images to derive the temporal behavior, the abundance and the distribution of the floating macrophytes in the Winam Gulf (Kenyan portion of the Lake Victoria). The proliferation of invasive plants and aquatic weeds is of growing concern. Starting from 1989, Lake Victoria has been interested by the highest infestation of water hyacinth with significant socio-economic impact on riparian populations. The information provided by satellite can play an important role in supporting a decision system for the management of the water resources allowing also an easy and inexpensive way of monitoring the environment response to any action that might be undertaken to contrast its degradation. This paper aims at assessing the capability of medium/high resolution (Wideregion and Stripmap) COSMO-SkyMed ScanSAR time series imagery to support/supplement optical data, frequently affected by clouds, in the knowledge of temporal macrophytes growing cycles and sustain the monitor and management of the Lake Victoria waters.
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The integrated use of reflectances and thermography to study and diagnostic of transport infrastr... more The integrated use of reflectances and thermography to study and diagnostic of transport infrastructures has been applied on the Musumeci Bridge (Potenza, Italy) test site as a fast and non-destructive tool in the framework of the Integrated System for Transport Infrastructures surveillance and Monitoring by Electromagnetic Sensing (ISTIMES) project, funded by the European Commission in the frame of a joint Call "ICT and Security" of the Seventh Framework Programme, in order to extract appropriate information and make useful decisions [1].
ABSTRACT Rome Province with its 4 million inhabitants is one of the Italians areas with the large... more ABSTRACT Rome Province with its 4 million inhabitants is one of the Italians areas with the largest urban expansion, mainly concentrated around the capital city. The uncontrolled urbanization of the past has heavily marked the landscape, especially Rome countryside and coastline. However many zones have exceeded the anthropic pressurewithout serious consequence since the sensitivity towards environmental protection has grown in recent years. Rome Province Administration has devoted special attention to the improvement and protection of its naturalistic heritage by means of a series of administrative actions, cultural initiatives and projects for environmental education. In this perspective a three-year agreement was concluded with CNR LARA focused on the study of natural vegetation by means of MIVIS (Multispectral Infrared Visible Imaging Spectrometer) remotely sensed data. This study distinguished and mapped the most important natural forests, shrub and herbaceous formations, assessed the health conditions of the arboreal vegetation, identified the areas with little water supply, and measured some environmental parameters, like temperature and surface humidity. The results achieved highlight the large botanical and naturalistic assortment and the complexity of the study-area.
Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VII, 2007
In this paper the potential of the Hyperion spaceborne hyperspectral data in discriminating land ... more 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
IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing, 2014
Anomalous pixel responses often seriously affect remote sensing applications, especially in the t... more 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.
Remote Sensing for Environmental Monitoring, GIS Applications, and Geology VII, 2007
ABSTRACT Buried man-made structures, like archaeological handiworks, altering the natural trend o... more ABSTRACT Buried man-made structures, like archaeological handiworks, altering the natural trend of the soil surface can yield tonal anomalies on remotely sensed images. These anomalies differ in size and/or intensity according to either the environmental conditions at the time of acquisition or the spectral and spatial characteristics of the images. The research challenge is to identify the best wavelength to detect these anomalies. In this paper we have set up two new parameters for identifying and assessing the potential of anomaly detection: the Detection Index (DI), which counts the pixels related to the marks, and the Separation Index (SI), which relates the difference in brightness of the marks with respect to the background. These two indexes have been tested on MIVIS (Multispectral Visible Imaging Spectrometer) airborne hyperspectral data acquired on remains not yet excavated of a few archaeological sites. Results show that such indexes are an efficient, flexible and quick tool for assessing the image potential to detect buried structures. Moreover, when they are applied to hyperspectral data, they allows for identifying the spectral range more sensitive to the detection of the buried structures.
Remote Sensing of Environment, 2009
We analyze the capability of Hyperion spaceborne hyperspectral data for discriminating land cover... more We analyze the capability of Hyperion spaceborne hyperspectral data for discriminating land cover in a complex natural ecosystem according to the structure of the currently used European standard classification system (CORINE Land Cover 2000). For this purpose, we used Hyperion imagery acquired over Pollino National Park (Italy). Hyperion pre-processed data (30 m spatial resolution) were classified at the pixel level using common parametric supervised classification methods. The algorithms' performance and class level accuracy were compared with those obtained for the same area using airborne hyperspectral MIVIS data (7 m spatial resolution). Moreover, in selected test areas characterized by heterogeneous land cover (as mapped by MIVIS classification) a Linear Spectral Unmixing (LSU) technique was applied to Hyperion data to derive the abundance fractions of land cover endmembers. The accuracy of the LSU analysis was evaluated using the Residual Error parameter, by comparing Hyperion LSU results with land cover fractional abundances achieved from reference data (i.e., MIVIS and air-photo classification). The results show the potential of Hyperion spaceborne hyperspectral imagery in mapping land cover and vegetation diversity up to the 4th level of the CORINE legend, even at the sub-pixel level, within a fragmented ecosystem such as that of Pollino National Park. Moreover, we defined a criterion for evaluating the Hyperion accuracy in retrieving land cover abundances at the sub-pixel scale. Sub-pixel analysis allowed us to determine the optimal threshold to select the areas on which consistent fractional land cover monitoring can be achieved using the Hyperion sensor.
The application of integrated hyperspectral VNIR and thermal data for analyzing and monitoring th... more The application of integrated hyperspectral VNIR and thermal data for analyzing and monitoring the architectural and artistic heritage status is becoming a remarkable tool to be combined with other non-destructive techniques (e.g. GPR), and prior to destructive checking, in order to extract appropriate information and make useful decisions [1]. As the analysis of some kind of damages (e.g. water infiltrations)
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Papers by simone pascucci