Francesca Despini

Analysis of temperature maps of waterbodies obtained from ASTER TIR images

Thermal water pollution is a highly relevant issue to which increasing attention is being paid. Satellite remote sensing represents a useful tool for the mointoring and study of the temperatures of waterbodies. The purpose of this work is to define a methodology for the analysis of the surface temperature maps of coastal waterbodies and watercourses from satellite images for quality assessment and for regulatory purposes. Three different procedures are developed in order to study the temperature field of waterbodies, to extract the temperature profile at a fixed distance from the coastline and to analyse the cross sections of the watercourses as prescribed by the law. Extraction and analysis of surface temperature patterns are undertaken using image segmentation techniques. This work also represents a first test of the advantages given by the Sharpening Water Thermal Imagery (SWTI) algorithm, which improves the spatial resolution of Advanced Space-borne Thermal Emission and Reflection Radiometer (ASTER) images from 90 to 30 m. The developed procedures and the SWTI algorithm are applied to ASTER images acquired on the lagoon of Venice and on the delta of the Po River. Statistical parameters and temperature profile are extracted in order to verify compliance with legal limits. The use of the developed procedures enables the individuation and quantification of thermal anomalies such as industrial discharges both in the sea and in watercourses.

Applications of Terra MODIS data for Iraq marshland monitoring

Since the 1970s, the Iraq Marshlands have been damaged significantly, but recently (May 2003-March 2004), more than 20% of the original marshland area has been re-flooded. The goal of the work is to observe the evolution of the marshes in terms of extension and to evaluate the success of wetland restoration on the base of multispectral and multitemporal MODIS images collected in 2007-2008. MODIS (MODerate resolution Imaging Spectroradiometer) has a viewing swath width of 2,330 km and views the entire surface of the Earth every one to two days. Its detectors measure 36 spectral bands between 0.405 and 14.385 μm, and it acquires data at three spatial resolutions -- 250m, 500m, and 1,000m. These data with their low spatial resolution but high time frequency are suitable for regional-scale time-series studies. The satellite data have been corrected for atmospheric effects using an IDL (Interactive Data Language) procedure based on MODTRAN and 6S radiative transfer codes. These radiative transfer codes require, in input, atmospheric vertical profiles, aerosol optical thickness(AOT) and columnar water vapour content (WV). Vertical profiles are obtained from the nearest meteorological station or by climatological data set. AOT and WV are retrieved either from the MODIS MODATML2 atmospheric product, or from the AERONET (Aerosol robotic network). Then different classifications (Pixel- and Object-Oriented) have been tested, compared and discussed to evaluate the best approach to apply on regional-scale time-series studies.

Improvement of the spatial resolution of MODIS coastal waters thermal mapping

Thermal mapping is an highly relevant tool for the assessment of the quality of coastal waters. Remote sensing is an useful technique for monitoring large surfaces in near real time, nevertheless, spatial resolution represents an important limiting factor. In this work it the spatial improvement, from 1km to 250m, of MODIS thermal imagery on coastal water obtained with the SWTI (SharpeningWater Thermal Imagery) is shown. This algorithm is applied, for the first time, to MODIS images acquired on the lagoon of Venice and on the delta of the Po River. The performances of SWTI are evaluated taking as a reference a couple of ASTER images acquired simultaneously to the MODIS images and on the same areas. Moreover, the water temperatures obtained with a simple bilinear interpolation of the MODIS images is also considered. Several statistical parameters, as bias and root mean square difference, are used to quantify the the difference between ASTER and MODIS/SWTI water temperatures along coastlines. In all the the cases these differences are lower than 1K.

Attempt of identification of wet areas with ASTER images for archeological studies

Satellite images are a tool increasingly used in environmental monitoring and in recent years have become also strongly used in the field of archaeology. In this study it was conducted an experimental analysis on the identification of wetlands from satellite images in order to identify sites of interest from the archaeological point of view because probable sites of ancient settlements. The studied area is the Plan de la Limagne which is located in North-East of the French city of Clermont-Ferrand. For wet areas identification were used two ASTER satellite images and pre-existing carthography. Different indexes have been used to identify wet areas. First of all, it was used the NDVI (Normalized Difference Vegetation Index) to discriminate bare soils. Secondly, through the Tasseled Cap transform, other indexes were obtained, such as the Greeness Index, the Brightness Index (SBI – Soil Brightnes Index) and the Wetness Index. Then it has been used the ATI index (Apparent Thermal Inertia) that provides information on the thermal inertia of soils. Through these indexes, visual inspection and the study of spectral signatures, it has been tried not only to identify wetlands within the images, but also to find repeatable processes for the detection of these areas. Some “anomalous” areas, that are probably wet areas, have been identified with this procedure. The identification of wet areas has been carried out in a raw way, this is surely a first approximation analysis. Certainly the in situ analysis would provide the possibility of a better evaluation, in fact field measurements could be used to calibrate the model and then find an effective and repeatable procedure for identifying wetlands.

SPOT5 imagery for soil salinity assessment in Iraq

Soil salinization is a form of topsoil degradation due to the formation of soluble salts at deleterious levels. This phenomenon can seriously compromise vegetation health and agricultural productivity, and represents a worldwide environmental problem. Remote sensing is a very useful tool for soil salinization monitoring and assessment. In this work we show some results of a study aimed to define a methodology for soil salinity assessment in Iraq based on SPOT 5 imagery. This methodology allows the identification of salinized soils primarily on bare soils. Subsequently some soil salinity assessment can be done on vegetated soils. On bare soil the identification of salt is based on spectral analysis, using the Minimum Noise Fraction transformation and several indexes found in literature. In case of densely vegetated soils the methodology for the discrimination of salinized soils has been integrated with the results obtained from the classification of vegetation coverage.