Evaluation of the damages caused by seismic events: First tests on supporting traditional multispectral classification with DSM

Seismic damages, as a roof entirely collapsed on the ground, are very difficult to be found using only multispectral classification algorithms. The availability of high resolution stereopairs from satellite disclose new possible fields of application to estimate changes and transformations of areas following catastrophic events. Combining both techniques it is obviously possible only when stereoscopic and multispectral images are available. In this case, as for all monitoring studies, it is necessary to compare the present situation to the pre-seismic one. The pre-seismic situation can be advantageously studied by classic photogrammetric techniques based on aerial frames, that are available in archives managed by photogrammetric companies and local government agencies. But it is also possible to extract the pre-seismic morphology from digital maps, containing the three-dimensional characteristics of the buildings. The present research tries to: a) improve the digital surface model extracted from Ikonos satellite images covering an area of central Italy (Foligno, Umbria), through a pre-treatment of images and a manual editing b) study the best DSM models to improve the detection of height difference, mainly in urban areas, and evaluate the results of the classification of land cover as further data to detect changes in building shape. DSM obtained by three-dimensional maps have been compared with DSM extracted directly from aerial stereo-pairs using different approaches. In the area under study a seismic event happened in September of the '97 causing relevant damages to different urbanized centres of the area

Applications of ISES for vegetation and land use

Remote sensing relative to applications involving vegetation cover and land use is reviewed to consider the potential benefits to the Earth Observing System (Eos) of a proposed Information Sciences Experiment System (ISES). The ISES concept has been proposed as an onboard experiment and computational resource to support advanced experiments and demonstrations in the information and earth sciences. Embedded in the concept is potential for relieving the data glut problem, enhancing capabilities to meet real-time needs of data users and in-situ researchers, and introducing emerging technology to Eos as the technology matures. These potential benefits are examined in the context of state-of-the-art research activities in image/data processing and management

Integrated surveying for the archaeological documentation of a neolithic site

It has been tested the applicability of integrated surveys (remote sensing, digital photogrammetry and terrestrial laser scanning (TLS)) in order to verify, through gradual and successive steps, how geomatic techniques can get 3D results with metric value combined with a quality content for an archaeological site. In particular, the data have been collected during the excavation campaign of Neolithic archaeological site in Taranto. The possibilities to scan articulated forms, in the presence of curve, concavity and convexity, and jutting parts rotate, characterized by alterations, through the acquisition of a dense points cloud makes the technique TLS needed in archaeology. Through the photogrammetric technique the laser data has been integrated concerning some details found on the site for which it has been required a higher degree of detail. The photogrammetric data has been acquired with the calibrated camera. The processing of the acquired data and their integration has been made possible to study an important archeological site, in its totality, from small scale (general site framework) to large scale (3D model with a high degree of detail) and to structure a multi-temporal database for simplified data management

3D building change detection using high resolution stereo images and a GIS database

In this paper, a workflow is proposed to detect 3D building changes in urban and sub-urban areas using high-resolution stereoscopic satellite images of different epochs and a GIS database. Semi-global matching (SGM) is used to derive Digital Surface Models (DSM) and subsequently normalised digital surface models (nDSM, the difference of a DSM and a digital elevation model (DEM)), from the stereo pairs at each epoch. Large differences between the two DSMs are assumed to represent height changes. In order to reduce the effect of matching errors, heights in the nDSM of at least one epoch must also lie above a certain threshold in order to be considered as candidates for building change. A GIS database is used to check the existence of buildings at epoch 1. As a result of geometric discrepancies during data acquisition caused by different view directions and illumination conditions, the outlines of existing buildings do not necessarily match even in non-changed areas. Consequently, in the change map, there are streaking-shaped structures along the building outlines which do not correspond to actual changes. To eliminate these effects morphologic filtering is applied. The mask we use operates as a threshold on the shape and size of detected new blobs and effectively removes small objects such as cars, small trees and salt and pepper noise. The results of the proposed algorithm using IKONOS and GeoEye images demonstrate its performance for detecting 3D building changes and to extract building boundaries.DAA

An Overview of Remote Sensing in Russian Forestry

The Russian Federation possesses vast forested areas, containing about 23% of the world's closed forests. A significant part of these forestlands is neither managed nor regularly monitored. This is due in part to the absence of developed infrastructure in the remote northern regions, which hampers the collection of data on forest inventory and monitoring in all areas by precise and expensive on-ground methods. As a result, the monitoring in all areas by precise and expensive on-ground methods. As a result, the former Soviet Union conducted intensive research on remote sensing during the last few decades, resulting in significant achievements. However, there has been a noticeable decline in remote sensing research and applications in the Russian forest sector from 1990-1998. Russia needs a new system of forest inventory and monitoring capable of providing reliable, practical information for sustainable forest management. Such a system should take into account current national demands on the Russian forest sector as well as the international obligations of the country. Remote sensing methods are an indispensable part of such a system. These methods will play a crucial role in critical applications such as ensuring the sustainability of forest management, protecting threatened forests, fulfilling the countrys Kyoto Protocol obligations, and others. This paper presents an overview of past and current remote sensing methods in the Russian forest sector, including both practical and scientific applications. Based on this overview, relevant applications of remote sensing methods in the Russian forest sector are discussed. This discussion considers current Russian economic conditions and the direction of political and social development of the country

A phase field model incorporating generic and specific prior knowledge applied to road network extraction from VHR satellite images.

We address the problem of updating road maps in dense urban areas by extracting the main road network from a very high resolution (VHR) satellite image. Our model of the region occupied by the road network in the image is innovative. It incorporates three different types of prior geometric knowledge: generic boundary smoothness constraints, equivalent to a standard active contour prior; knowledge of the geometric properties of road networks (i.e. that they occupy regions composed of long, low-curvature segments joined at junctions), equivalent to a higher-order active contour prior; and knowledge of the road network at an earlier date derived from GIS data, similar to other ‘shape priors’ in the literature. In addition, we represent the road network region as a ‘phase field’, which offers a number of important advantages over other region modelling frameworks. All three types of prior knowledge prove important for overcoming the complexity of geometric ‘noise’ in VHR images. Promising results and a comparison with several other techniques demonstrate the effectiveness of our approach

Automatic Road Extractions from High Resolution Satellite Imagery Using Road Intersection Model in Urban Areas

This paper proposes intersection model and strategy for road extraction from high resolution satellite images. Satellite images are rich in information. For Geographic Information System (GIS), many features require fast and reliable extraction of roads and intersections. They are also complex to analyze. Satellite image provides useful data that is extracted from satellite image of the urban area. Automatic extraction of the road intersections from the urban areas has been a challenging topic because the high resolution satellite images contain multiple layers that represent roads, buildings, and other high density objects. Our goals is to automatically separate the road layer from the other layers then extract the road intersections. Usually traditional image processing methods don't achieve satisfied performance in case of satellite images. This paper proposes a modified and a cost effective method for road extraction from high resolution satellites images. In order to find the precise road intersection of urban areas we have divided whole process into two sequential modules: first, extraction of road line using different Morphological direction filtering to automatically eliminate the other layers from road layer and finally, extraction of road intersections to determine the road orientation and interconnectivity. We applied this method to a set of randomly selected high resolution satellite image from urban and semi urban areas and the correctness of road network extraction reaches 95.71%, significantly higher than those of other existing road extraction methods