The aim of this research is to assess a technique to retrieve actual evapotranspiration (ET) maps from remote sensing images by the combination of two different procedures. The first one, known as triangle method, computes the evapotranspiration fraction (EF) defined as the ratio LE/Rn, where Rn is the net radiation at the surface and LE is the latent heat flux. LE is directly proportional to ET. In order to retrieve LE, and consequently the surface evapotranspiration, a second procedure computes the net radiation of the investigated area. Therefore, by inversion, it is possible to obtain an estimate of the ET. The validation of these variables, net radiation and evapotranspiration derived from MODIS data, has been undertaken on the Capitanata area, Southern Italy, by comparison of model results with in-situ measurements provided by the Consorzio per la Bonifica della Capitanata di Foggia. © 2012 IEEE.

Rapid, precise and quantitative assessment of soil quality is crucial for sustainable evaluation andmonitoring of the effects of management on soil resource under agricultural systems and for thecharacterization 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 conventionallaboratory analysis, and can provide time and cost effective approaches for the prediction of several soilproperties related to soil quality indicators. For this study, VIS-NIR spectroscopic and chemometricanalysis were employed for the assessment of soil quality indicators in three degraded areas (two surveysites depleted in organic carbon and one polluted by organic and inorganic compounds) located inSouthern Italy (Apulia Region). The soil reflectance properties in the wavelengths range between350-2500 nm were measured in three experimental sites(fields) selected for the project, before and after arecovery treatment by using compost (organic fertilizer). The objectives was to evaluate the efficiency ofsoil VIS-NIR spectra for prediction of selected soil indicators closely related to soil quality inMediterranean areas, such as those investigated in this study, affected by land degradation processes(contamination and/or organic carbon impoverishment).

In this study, we report the adopted methodology which has allowed us to map surface water thermal anomalies and, consequently, to identify and locate coastal inflows in the Bari province coasts and Mar Piccolo sea (Taranto), the latter part of the National Priority List site identified by the National Program of Environmental Remediation and Restoration.

The availability of a nearly-continuous remotely-sensed chlorophyll 'a' maps (Chl a) from MODIS sensor, now longer than ten years, enables the assessment of multi-temporal trends for several locations around the world. In this paper the statistical method of the Support Vector Machine (SVM) has been applied to 5 years of MODIS data in order to generate Chl a maps. A Chl a multi-temporal analysis of Apulian region coastal zones in Southern Italy shows a positive trend in two test cases, confirming the increase of productivity in Southern Adriatic region found in the last years and demonstrating the simplicity and usefulness of this technique

In the last years, thermal images have made the detection of thermal anomalies possible. These images could represent an important tools to monitor legal or illegal outflows in coastal waters, especially in sites become contaminated and/or in sites with high naturalistic values. The objective of this study is to compare Landsat 8 Thermal Infrared Sensors (TIRS) band with TABI-320 processing both with a free and open source GIS and a remote sensing software finalized to the identification and mapping of water inflows along the coast and of submarine springs that reach the surface of Mar Piccolo sea of Taranto (Southern Italy). The approach with the TABI-320 sensors permitted detection of many other anomalies that cannot be seen with the Landsat 8 TIRS band with the same methodology, but the use of the last-one sensors is more suitable, simple and expeditious to map thermal values of the whole area. Methods, results, limits and potentialities of this approach are discussed.

Il telerilevamento è sempre più utilizzato nel monitoraggio ambientale e le immagini acquisite da sensori aviotrasportati rappresentano al giorno d'oggi uno strumento capace di utilizzare un numero elevato di bande spettrali a differenti risoluzioni geometriche al fine di discriminare i fenomeni che interessano il territorio investigato. In tale contesto, gli studi correlati all'impiego della spettroscopia Vis-NIR hanno evidenziato le potenzialità di quest'ultima, in termini di rapidità ed economicità, nella restituzione di informazioni inerenti i principali processi di degradazione del suolo (e.g. contaminazione, desertificazione, ecc.). Infatti, nel corso degli ultimi due decenni, l'uso della spettroscopia (Vis-NIR) nella scienza del suolo è stato ampiamente finalizzato allo studio della composizione del suolo e caratterizzazione delle sue principali proprietà. Le attività presentate in questo lavoro sono state finalizzate a sviluppare protocolli innovativi per il data fusiondi dati iperspettrali acquisiti su un'area interessata da processi di degradazione (contaminazione) mediante tecniche di proximal e remote sensing. Nello specifico, sono state acquisite immagini da remoto con sensore iperspettrale aviotrasportato (CASI-1500) nel range 380-1050 nm su di un'area contaminata da composti organici (policlorobifenili) ed inorganici (metalli pesanti), localizzata nel Sud Italia. Al contempo, sono state condotte indagini spettroradiometriche in situ su campioni di suolo prelevati dal sito di indagine, mediante spettroradiometro portatile (ASD FieldSpec Pro FR 4) nel range 350-2500 nm. L'elaborazione dei dati iperspettrali, attraverso sperimentazione di tecniche di data fusion, ha mirato allo sviluppo di specifici algoritmi in grado di correlare l'informazione relativa al contenuto di alcuni contaminanti alle firme spettrali dei suoli con il fine ultimo di produrre mappe di contaminazione.

Soil organic carbon (SOC) plays an important role in soil quality definition. In fact, soil organic matter (SOM) decline is one of the most relevant land degradation processes [1]. Therefore, an innovative methodology able to monitoring this soil property, collecting data more rapidly and economically, is needed. In this regard, remote sensing technique can open new scenarios of research. In particular, few studies have shown the capability to accurately determine SOC contents from airborne-hyperspectral sensors [2], [3], [4]. With this work we demonstrate that is possible to evaluate the Soil Organic Carbon in a test site in Apulia Region, Italy, through hyperspectral measurements by the airborne sensor CASI 1500, achieving very promising results.

Soil organic carbon (SOC) plays an important role in soil quality definition. In fact, soil organic matter (SOM) decline is one of the most relevant land degradation processes [1]. Therefore, an innovative methodology able to monitoring this soil property, collecting data more rapidly and economically, is needed. In this regard, remote sensing technique can open new scenarios of research. In particular, few studies have shown the capability to accurately determine SOC contents from airborne-hyperspectral sensors [2], [3], [4]. With this work we demonstrate that is possible to evaluate the Soil Organic Carbon in a test site in Apulia Region, Italy, through hyperspectral measurements by the airborne sensor CASI 1500, achieving very promising results.

This study aims to identify asbestos-containing materials (ACM) through the use of innovative technology such as aerial hyperspectral sensors. The development of operational methodologies and ad hoc processing were also applied for the purpose of this study. The activity was part of the ICT Living Labs DroMEP project carried out by Water Research Institute of the National Research Council (IRSA-CNR) and Servizi di Informazione Territoriale S.r.l. (SIT Srl). This was funded by the Apulia Region to support the growth and development of specialized SMEs in offering digital content and services. Uncontrolled abandoned wastes pose a threat to the human health and ecosystem. The presence of harmful or dangerous substances released without any control can become a dangerous source of pollution. Many areas of the Apulia region generally, in southern Italy, are subjected to this type of phenomena because most often, these areas are not easily accessible to Authorities for the control and management of the territory. Land monitoring and characterization operations would be carried out in a very long time and would require significant financial resources and considerable effort if done by conventional methods. The project activities include the testing and integration of several technologies already available, but not engineered for specific purposes. The work has been focused on the development of a methodology with a defined and high reliability capable of identifying the presence of ACM in various piles of rubbish abandoned in agro-ecosystems. The developed methodology analyses the spectral behaviour of ACM highlighting and emphasizing certain features through the use of a procedure based on an if-then-else control structure. It also allows the selection of the most effective features to combine that significantly reduces the number of false positives.

The increasing concentration of CO2 and other radiative activetrace gases in the atmosphere is causing tropospherictemperatures to rise. Changes in other climatic featuressuch as precipitation, cloudiness, humidity, and windinessare likely to follow changes in temperature. Such changescould have deep implications for hydrologic processes in generaland for water availability to sustain both rain-fed andirrigated agriculture, in particular.Evapotranspiration (ET) is the compound term describingthe physical processes of water transfer into the atmosphereby evaporation from soil and transpiration through vegetation;ET constitutes an important component of hydrologicalbalance particularly in semi-arid and sub-humid climates.Evapotranspiration is determined by various mathematicalmodels using climatic factors such as temperature, radiation,humidity, and wind speed, while its direct measurement isseldom available in experimental fields.A relatively new technology using on remote sensing to retrieveland surface parameters such as surface temperature,albedo and vegetation indices - which are indispensable to remotelysensed ET models - is adopted here to map regional,meso- and macro-scale patterns of ET at the earth's surfacein a globally consistent and economically feasible manner.The aim of our research is to assess a technique to retrieveET maps from remote sensing images by the combination oftwo different procedures. The first one, known as trianglemethod, computes the evapotranspiration fraction (EF) de-fined as the ratio LE/Rn, where Rn is the net radiation atthe surface and LE is the latent heat flux. LE is directly proportionalto ET. In order to retrieve LE, and consequentlythe surface evapotranspiration, a second procedure computesthe net radiation of the investigated area. Therefore, by inversion,it is possible to obtain an estimate of the ET.The validation of these variables, the net radiation and ofthe evapotranspiration derived from MODIS data, has beenundertaken on the Capitanata area, Southern Italy, by comparisonof model results with in-situ measurements providedby the Consorzio per la Bonifica della Capitanata di Foggia.

In this study, we report the adopted methodology used in GRASS, a free open-source GIS software, which has allowed us to map surface water thermal anomalies and, consequently, to identify and locate coastal inflows in the Mar Piccolo sea (Taranto) part of the National Priority List site identified by the National Program of Environmental Remediation and Restoration. An ongoing work, where to apply the same procedure, is being carried out on Bari province coast and effimeral streams.

L'utilizzo di dati telerilevati nell'ambito dell'agricoltura di precisione e dell'analisi di modelli idrologici ha assunto, negli ultimi anni, crescenteimportanza. In particolare, al fine di esaminare le condizioni della vegetazione da un punto di vista qualitativo e quantitativo, sono state sviluppate svariate metodologie che hanno portato alla formulazione di diversi indici di vegetazione. Tra di essi, l'indice di area fogliare (Leaf Area Index - LAI) rappresenta uno dei più importanti parametri per quantificare i processi fisici e biologici relativi alla copertura vegetale ed al consumo di acqua del suolo. In questo studio si presenta un confronto tra i modelli maggiormente adoperati per il calcolo del LAI applicati in un'area di studio localizzata nella zona della Capitanata (Sud Italia), nella quale sono state isolate ed analizzate, nella loro variabilità spazio-temporale, alcune classi distintive degli usi del suolo ivi predominanti. L'analisi si è concentrata sulla maniera in cui i modelli hanno risposto alla variabilità dell'uso del suolo, valutando l'idoneità di ogni dato modello nella caratterizzazione di ciascuna particolare area.In questo modo sono stati identificatigli algoritmi più adatti a ciascun tipo di zona nei casi in cui non si disponga di misure dirette raccolte in situ.

La conoscenza della quantità di carbonio organico nel suolo (SOM - Soil Organic Matter) puòessere di notevole aiuto nel pianificare le attività per la gestione sostenibile dei sistemi agricolifinalizzate sia all'aumento della produttività sia alla riduzione del rischio di degrado ambientale(processi di desertificazione). Negli ultimi anni pertanto, sono state messe a punto diversemetodologie per il monitoraggio di questo parametro. Tra queste la spettroscopia nel visibile evicino infrarosso, a scala di laboratorio, di campo e da remoto, si è rivelata uno strumentoparticolarmente efficace anche in relazione alle analisi chimiche tradizionali.In questo lavoro, tramite acquisizioni iperspettrali da aereo effettuate con il sensore CASI 1500, èstata valutata l'efficacia del telerilevamento nel monitoraggio del SOM. A tal fine due sorvoli hannopermesso di ottenere immagini pre e post trattamento di un sito degradato (con ridotto contenuto diSOM) in provincia di Taranto, arricchito in sostanza organica (spandimento di compost).Contestualmente ai sorvoli, sono state effettuate misure radiometriche al terreno e sono statiprelevati campioni di suolo successivamente analizzati in laboratorio per il contenuto in SOM.Dalla correlazione tra le analisi chimiche, la radiometria di campo e la classificazione delleimmagini è stata prodotta una mappa tematica che rappresenta la distribuzione della concentrazionedi SOM nel sito di indagine. I risultati preliminari sono incoraggianti e mostrano una rispostasignificativa dello metodologia utilizzata nel rilevare carbonio organico nel suolo, suggerendo chele tecniche di telerilevamento possono rappresentare uno strumento e adeguato per il monitoraggiodel SOM rapido ed efficace su scala locale.

The Leaf Area Index is an important vegetation biophysical parameter, defined as a ratio of leaf area to unit ground surface area (Watson, 1947). This index is related to several vegetation exchange processes, providing information on changes in productivity or climate impacts on ecosystems. In literature it is possible to find many algorithms to its retrieval (Viña, 2011; Ganguly, 2012). The choice of the model to use become thus crucial for any kind of application. The following research aims to compare different models of LAI, undergoing the following steps: first, through the USGS archive we selected a sample of images acquired by Landsat-8 satellite, from 2013 to 2016, with 30m of spatial resolution. Subsequently, we carried out a classification of soil based on different uses, which led to the identification of five land use classes. Then, images were preprocessed through Envi and Matlab softwares, in order to isolate a particular sub-region and apply correction of cloudiness and radiometric calibration. Therefore data processing consisted of vegetation indices calculation: NDVI (Normalized Difference Vegetation Index) (Rouse et Al., 1974), WDVI (Weighted Difference Vegetation Index) (Clevers, 1988), and EVI (Enhanced Vegetation Index) (Liu and Huete, 1995). Then, LAI algorithms were chosen and applied. Finally, multi-temporal statistical analysis was carried out to evaluate the most performing models for every land cover category, according to existing experimental data.

The monitoring of hydrological processes within the vadose zone is usually difficult, especially in the presence of compact rock subsoil. The possibility of recognizing the trend of the structural lineaments in fractured systems has important fallout in the understanding water infiltration processes, especially when the groundwater flow is strongly affected by the presence of faults and fractures that constitute the preferred ways of water fluxes.This study aims to detect fracture lineaments on fractured rock formations from CASI hyperspectral airborne VNIR images, with a size of 60 cm of the spatial resolution, and collected during November 2014. Lineaments detected with such high resolution have been compared with the fracture lineaments detected by a Landsat 8 image acquired at the same time of the CASI acquisition.The method has processed several remote sensed images at different spatial resolution, and it has produced the visualization of numerous lineament maps, as result of the vertical and sub-vertical fractures of the investigated area. The study has been applied to the fractured limestone outcrop of the Murgia region (Southern Italy). Here the rock formation hosts a deep groundwater, which supplies freshwater for drinking and irrigations purposes. The number of the fractures allowed a rough estimation of the vertical average hydraulic conductivity of the rock outcrop. This value was compared with field saturated rock hydraulic conductivity measurements derived from large ring infiltrometer tests carried out on the same rock outcrop.

In winter 2008-2009 Lake Occhito, a strategic multipleuses(irrigation and drinking supply) reservoir located inSouth Italy, was affected by an extraordinary Planktothrixrubescens bloom. P. rubescens is a filamentous potentiallytoxic cyanobacterium which has recently colonized manyenvironments in Europe and Italy. A number of studies iscurrently available on the use of remote sensing techniquesto monitor different fresh water cyanobacteria species, usingthe common biomarker pigment phycocyanin. By contrastno specific applications are available on the remote sensingmonitoring of P. rubescens, whose optical response ismarkedly influenced by the presence of the phycoerythrinaccessory pigment. In this paper we present a simple bandratio algorithm based on Water Leaving Reflectances fromMERIS data, atmospherically corrected using the AerosolOptical Thickness retrieved by MODIS data, to detect P.rubescens blooms. The high accuracy in AOT data, providedby MOD09 surface reflectance product, at 1km spatialresolution, allowed obtaining a good correlation (R2=0.75)between the WLR and the P. rubescens chlorophyll-aconcentrations measured in the field, through multiplestations fluorometric profiles. The combined use of MERISand MODIS data resulted thus in a very useful tool tomonitor such a phenomenon, even in areas where

Land degradation processes like organic matter impoverishment and contamination are growing increasingly allover the world due to a non-rational and often sustainable spread of human activities on the territory. Consequentlythe need to characterize and monitor degraded sites is becoming very important, with the aim to hinder such mainthreats, which could compromise drastically, soil quality.Visible and infrared spectroscopy is a well-known technique/tool to study soil properties. Vis-NIR spectralreflectance, in fact, can be used to characterize spatial and temporal variation in soil constituents (Brown et al.,2006; Viscarra Rossel et al., 2006), and potentially its surface structure (Chappell et al., 2006, 2007). It is a rapid,non-destructive, reproducible and cost-effective analytical method to analyse soil properties and therefore, it canbe a useful method to study land degradation phenomena.In this work, we present the results of proximal sensing investigations of three degraded sites (one affected byorganic and inorganic contamination and two affected by soil organic matter decline) situated southern Italyclose to Taranto city (in Apulia Region). A portable spectroradiometer (ASD-FieldSpec) was used to measure thereflectance properties in the spectral range between 350-2500 nm of the soil, in the selected sites, before and aftera recovery treatment by using compost (organic fertilizer). For each measurement point the soil was sampled inorder to perform chemical analyses to evaluate soil quality status.Three in-situ campaigns have been carried out (September 2012, June 2013, and September 2013), collectingabout 20 soil samples for each site and for each campaign.Chemical and spectral analyses have been focused on investigating soil organic carbon, carbonate content, textureand, in the case of polluted site, heavy metals and organic toxic compounds.Statistical analyses have been carried out to test a prediction model of different soil quality indicators based on thespectral signatures behaviour of each sample ranging.