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Dalmatia region in Croatia has dozens of registered active rockfall zones. Virtually whole area along main coastal road from city of Split to town of Omiš is a potential danger zone for inhabitants and community infrastructure. Almost every year, in periods after heavy rain and/or considerable low air temperature, many sudden rockfalls in this area are recorded. Stabilizing and managing the entire area without localising potential threats would require considerable funding, which private owners and local communities cannot afford, so more suitable method for forecasting and detecting potential rockfalls is needed. For this study a specific location named Luka in Duće area and a part of old town centre of Omiš are selected as pilot sites. Slope over Luka location is made of Eocene flysch, which is covered by a relatively thin and hard layer of breccia. Main component of flysch is marl, a rock material which is prone to weathering when submitted to atmospheric agents. As a result of weathering, surface formed of weaker marl is eroded with rain and the layer of harder breccia remains like “cantilever”. With time cracks start to form on the top of the cliff and parts of breccia start to fall off in large blocks. The cliffs over the town of Omiš are in the karstificated geological formation made mainly of limestone. Stabilizing the entire slopes in town area without localising potential threats would require considerable funding, which private owners and local community cannot afford, so a more cost-effective method to localise priorities should be found. One of them could be the proposed method that uses LiDAR technology. LiDAR (Light Detection and Ranging) is an optical remote sensing technology used in Terrestrial Laser Scanners. TLS is often used to perform periodical monitoring in large landslide and rockfall areas. In this study Optech ILRIS-3D with enhanced range was used at both pilot sites. First scan with ILRIS-3D was made in September 2011, however at that time a serial malfunction was noticed. After repairment in Canada, scanning started again in April 2012 and it was repeated five times in a 3-6 month intervals to this day. The first scan for both pilot sites was georeferenced and it will be used as a reference scan for comparison of all future periodical monitoring at this location. Comparison of the two scans was made by using IM Survey module of Polyworks software. As an example of comparison a large block removal was used to test the methodology of comparing sequential datasets (Fig. 1). On this figure the differences between two scans starting from 10 cm up to 4 m, from a 300 meters distant standpoint of the instrument, are clearly observed. With these results the morphology of the slope, block size and shape can be obtained very precisely and which can then be used in rockfall analysis. To detect smaller displacements of blocks (in the scale of millimetre to couple of centimetres) prior to its detachment, data should be acquired from standpoints closer to the cliff. However, this shortening of the range to the target raises the question of practical usage of this method for this and especially for even larger sites. Except for detecting unstable blocks at steep slopes, this temporal model of surveying can certainly be applied for observing erosion process in soft rock (similar to marl in this area) or as an additional tool for creating rockfall inventory for this area. That would be a long-term project (minimum 10 – 20 years with yearly periodical scanning), however the results of which could be used for the purpose of detailed hazard mapping of the wider area than this pilot sites, and for sure help us to better understand the process of rock fall in this region. In combination with previous methodologies, results obtained by a spectrometer could be used for better understanding some of triggering factors for rockfalls in these materials. In this project a non-destructive quantitative measurements of material reflectance were performed using portable field spectrometer TerraSpec 4 Hi-Res (ASD Inc., USA). All the measurements were made in the Geotechnical laboratory of the Faculty of Civil Engineering, Architecture and Geodesy. The measured wavelength region TerraSpec 4 ranges from 380 – 2500 nm which mean that covers a visible (400-700 nm) and near-infrared (700-2500 nm) regions. The first laboratory tests with spectrometer suggest the relative quantity of the carbonate mineral group can be detected (in this area it consists mostly of calcite) and also there is a high possibility that they could be correlated with other testing procedures (such as calcimetry of XRD analysis). Therefore, spectrometer as portable device, unlike previously mentioned, can find it application in very fast in-situ measurements of those properties.

The evaluation of the soil spatial variability using a fast, robust and cheap tool is one of the key steps towards the implementation of Precision Agriculture (PA) successfully. Soil organic carbon (OC), soil total nitrogen (TN) and soil moisture content (MC) are needed to be monitored for both agriculture and environmental applications. The literature has proven that visible and near infrared (vis-NIR) spectroscopy to be a quick, cheap and robust tool to acquire information about key soil properties simultaneously with relatively high accuracy. The on-line vis-NIR measurement accuracy depends largely on the quality of calibration models. In order to establish robust calibration models for OC, TN and MC valid for few selected European farms, several factors affecting model accuracy have been studied. Nonlinear calibration techniques, e.g. artificial neural network (ANN) combined with partial least squares regression (PLSR) has provided better calibration accuracy than the linear PLSR or principal component regression analysis (PCR) alone. It was also found that effects of sample concentration statistics, including the range or standard derivation and the number of samples used for model calibration are substantial, which should be taking into account carefully. Soil MC, texture and their interaction effects are other principle factors affecting the in situ and on-line vis-NIR measurement accuracy. This study confirmed that MC is the main negative effect, whereas soil clay content plays a positive role. The general calibration models developed for soil OC, TN and MC for farms in European were validated using a previously developed vis-NIR on-line measurement system equipped with a wider vis-NIR spectrophotometer (305 – 2200 nm) than the previous version. The validation results showed this wider range on-line vis-NIR system can acquire larger than 1500 data point per ha with a very good measurement accuracy for TN and OC and excellent accuracy for MC. The validation also showed that spiking few target field samples into the general calibration models is an effective and efficient approach for upgrading the implementation of the on-line vis-NIR sensor for measurement in new fields in the selected European farms.

International audience; The potential of the visible-near infrared (Vis-NIR; 400-2500 nm) laboratory spectroscopy for the estimation of soil properties has been previously demonstrated in the literature, and the Vis-NIR spatial spectroscopy is expected to provide direct estimates of these properties at the soil surface. The aim of this work was to examine whether Vis-NIR airborne spectroscopy could be used for mapping eight of the most common soil properties, including clay, sand, silt, calcium carbonate (CaCO3), free iron, cation-exchange capacity (CEC), organic carbon and pH, without mispredicting the local values of these properties and their spatial structures. Our study was based on 95 soil samples and a HyMap hyperspectral image available over 192 bare soil fields scattered within a 24.6 km(2) area. Predictions of soil properties from HyMap spectra were computed for the eight soil properties using partial least squares regression (PLSR). The results showed that 1) four out of the eight soil properties (CaCO3, iron, clay and CEC) were suitable for mapping using hyperspectral data, and both accurate local predictions and good representations of spatial structures were observed and 2) the application of prediction models using hyperspectral data over the study area provided statistical characterizations within soilscape variations and variograms that describe in details the short range soil variations. All results were consistent with the previous pedological knowledge of the studied region. This study opens up the possibility of more extensive use of hyperspectral data for digital soil mapping of these successfully predicted soil properties.

An investigation was carried out aiming at assessing the potential of vis-NIR reflectance spectroscopy, through comparison with the conventional X-ray powder diffraction (XRPD) technique, for the characterization of synthetic gleys, obtained in laboratory starting from Fe 0 and Fe 2+ under different conditions of initial pH (5.5, 7.0 and 8.5). XRPD analysis showed that in any case goethite formed, whereas magnetite and lepidocrocite developed in the less oxidised, and akaganéite and hematite in the more oxidised environments. Magnetite was found only starting from Fe 0, i.e. in the less oxidative condition, whereas sporadic hematite was detected just in Fe 2+ synthetic gleys at 8.5 pH. Vis-NIR reflectance spectroscopy fully confirmed XRPD results. The features of reflectance spectra allowed (i) to discriminate Fe 2+ from Fe 0 synthetic gleys; (ii) to detect goethite and akaganéite in the high-reflectance spectra of Fe 2+ synthetic gleys; (iii) to correlate the very poor reflectance of Fe 0 synthetic gley spectra to magnetite; and, (iv) to identify some goethite and lepidocrocite features in Fe 0 synthetic gleys spectra. The analysis of second-derivative spectra also addressed to goethite, lepidocrocite and magnetite in Fe 0 synthetic gleys; and (ii) goethite, akaganéite and - at pH 8.5 - hematite in Fe 2+ synthetic gleys. The results obtained appear to be as original as significant, introducing vis-NIR reflectance spectroscopy as an innovative and promising effective method for the characterization of the soil gley forms, and highly stimulating for further investigations.

Rapid, precise and quantitative assessment of soil quality is crucial for sustainable evaluation and monitoring of the effects of management on soil resource under agricultural systems and for the characterization and monitoring of land degradation processes. Over the past three decades, Visible (VIS) and near-infrared (NIR) spectroscopy have been shown to be an effective alternative to conventional laboratory analysis, and can provide time and cost effective approaches for the prediction of several soil properties related to soil quality indicators. For this study, VIS–NIR spectroscopic and chemometric analysis were employed for the assessment of soil quality indicators in three degraded areas (two survey sites depleted in organic carbon and one polluted by organic and inorganic compounds) located in Southern Italy (Apulia Region). The soil reflectance properties in the wavelengths range between 350-2500 nm were measured in three experimental sites(fields) selected for the project, before and after a recovery treatment by using compost (organic fertilizer). The objectives was to evaluate the efficiency of soil VIS–NIR spectra for prediction of selected soil indicators closely related to soil quality in Mediterranean areas, such as those investigated in this study, affected by land degradation processes (contamination and/or organic carbon impoverishment).

Visible to near-infrared spectroscopy has been applied for non-invasive assessment of meat freshness. The measurements were done at room temperature with non-frozen pork samples. The absorbance spectra of the main chromophores in meat including oxymyoglobin, water, fat, and protein were different enough to be identified spectrophotometrically. The decreasing trend in absorbance spectra of these components over time can be associated with freshness decay. We used two configurations, fiber-optic probes and integrating sphere, to study their efficiency in meat quality evaluation. In the integrated sphere configuration, the samples experienced an immediate smooth decrease of oxymyoglobin absorbance arising from loss of superficial freshness, while degradation kinetics of water, fat and protein absorbance were detected after about 2.5 hours. In the fiber-optic configuration capable for sensing up to 570-μm depth, the drop in oxymyoglobin absorbance started after 4.5 hours which would affect directly the color of sample associated with freshness.