Over the years, several satellite-based indicators have been developed for Fire Susceptibility Estimation (FSE) most of which are based on AVHRR data. Unfortunately, these indicators yield different results when applied to different ecosystems or geographic regions and this creates confusion concerning their effectiveness. This work aims at evaluating the performance of the existing AVHRR-based FSE methods. Such evaluation was performed in the Basilicata and Calabria Region by using NOAA-12,-14 summery imagery selected from a long time series acquired from 1995 to 1999. Fire susceptibility maps
obtained from the considered methods were compared to fire archives provided by the Italian National Forestry Service. The most satisfactory results were obtained from methods based on the cross analyses of NDVI (Normalized Difference Vegetation Index) with thermal channels.
The strict link between intra-annual vegetation dynamics (phenology) and Earth's climate makes phenological information fundamental to improve understanding and models of inter-annual variability in terrestrial carbon exchange and climate-biosphere interactions. In order to monitor phenology in a landscape characterized by heterogeneous features rapidly changing over the territory, we performed multitemporal classifications of NDVI-AVHRR data and interfaced them with Landsat-TM data and orography. The sample area is the Vulture basin (Southern Italy), where cultivated and densely vegetated areas coexist with urban and recently built industrial areas. These land cover patterns rapidly change over the territory at very small spatial scales; it is a complex zone very interesting for studying the use of remote sensing techniques in the integrated monitoring context. Clusters having homogeneous NDVI time behaviors were identified. In spite of its spatial resolution, AVHRR NDVI effectively picks up the characteristic phenology for different covers and altitudes. Moreover, some pixels having particular microclimate were clustered and their characterization was only possible by using orography and TM classification information. The comparison of two intra-annual classifications (1996 and 1998) showed that the proposed approach can be very useful for studying change in pattern of vegetation dynamics.
Land cover classification is one of the main applications of remotely sensed data and the capability of airborne hyperspectral data for such a purpose is known. The recent availability of high spatial resolution multispectral data, such as IKONOS and QuickBird, puts the question about advantages and disadvantages of these data in comparison with the hyperspectral ones. We evaluated the cost and accuracy of using IKONOS imagery to perform a land cover classification at high spatial resolution and compared them with results obtained from MIVIS airborne hyper-spectral scanner data (102 bands from VIS to TIR). The study was performed in a rural area (25 km2) of Basilicata region (Southern Italy) characterized by complex topography (altitude ranges from 600 to 1400m) and different land cover patterns (forests, lakes, cultivated areas, and small urban areas). Evaluations were made taking into account time-processing, feature extraction, accuracy for different classification levels, and costs as a function of the extension of the area to be classified. Quite high accuracies were obtained for the first classification level, whereas increasing the class number IKONOS was less accurate than MIVIS. Multispectral classification well identified the different forest species, but had some problems in distinguishing between gravel road and some plowed lands. The obtained results showed that IKONOS data are cost-effective for updating thematic maps to support planning and decision-making processes at local government scale.
Physical parameters related to Earth surface and atmosphere show different behaviors when observed at different space-time scales by using both remote sensing or traditional ground based techniques. The main aim of this project was to investigate the information content degradation which results moving from the use of observations obtained by direct-punctual (ground-based), higher spectral/spatial resolution (airborne sensors), higher time-resolution, low cost and low spatial resolution (satellites), in the context of the activities related to natural and environmental risks monitoring in protected natural areas. Several observational techniques have been contemporary used during two fields campaigns in the Pollino National Park (Southern Italy): a) from ground by direct measurements of near surface parameters (from - 70cm of depth up to 200cm of height) as well as by radiosonde and radiometric measurements of surface and atmospheric parameters; b) using hyperspectral (MIVIS) and photographic aerial observations; c) from LANDSAT-TM, NOAAA/AVHRR and ADEOS/AVIRIS satellite sounders. Campaign data have been integrated on a GIS (including high resolution cartographic layers) and long term evolutionary trends (up to 20 years) also considered after the analysis of available historical, LANDSAT and NOAA, satellite records. This paper will present the main achievements of the project with special emphasis on the trade-off between expected performances and economical sustainability of different environmental monitoring strategies in an operational context.
The main objective of this work has been to evaluate the potential of integration of satellite data and topographic factor, in order to achieve improved performance in forest fire danger estimation. Existing AVHRR-based fire danger estimation methods (a review is specifically made) aim at obtaining fire susceptibility classification exploiting, mainly, the temporal evolution of NDVI, and Surface Temperature (Ts). In this work fire danger estimation has been performed integrating satellite data with fuel type and topographic factors. In order to evaluate the reliability of the estimated indices, the time-space distribution of actual forest fires, provided by the Italian Forestry service, has been used. Preliminary results are very promising; they have shown that in the summer of 1996, a large number of forest fires occurred in the estimated higher danger areas.
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