Proceedings of the First International Workshop on the Analysis of Multi-temporal Remote Sensing Images : University of Trento, Italy, 13-14 September 2001 / editors, Lorenzo Bruzzone, Paul Smits.

Includes bibliographical references and index.

Print version record.

Foreword; Contents; Image Analysis and Algorithms; Digital change detection methods in natural ecosystem monitoring:A review; Automated and precise image registration procedures; Adaptive reduction of registration-noise effects in unsupervised change detection; Detection of pixel-level land-cover changes with multi-temporal imagery: Theory and examples with imagery of 1 meter and 1 kilometer spatial resolutions; Image thresholding for landslide detection by genetic programming; A multitemporal change-detection algorithm for the monitoring of burnt areas with SPOT-Vegetation data

Shape change detection by fuzzy measuresProposal of different approaches to spatio-temporal contextual classification of remote-sensing images; Fuzzy, neural and neuro-fuzzy classification of pre- and post-event SAR images for flood monitoring and disaster mitigation; Using linear regression for the automation of supervised classification in multitemporal images; An application-oriented change-detection technique; Multitemporal change detection for updates of topographic map data bases; Exploiting spatial and temporal information for extracting burned areas from time series of SPOT-VGT data

The use of SOM-encoded texture spectrum for change detectionThe use of Kohonen's neural nets for the detection of land-cover transitions; A hyperspectral toolkit for the analysis of multitemporal handheld spectroradiometer data; A temporal extension to traditional empirical orthogonal function analysis; An ace-based nonlinear extension to traditional empirical orthogonal function analysis; A bivariate extension to traditional empirical orthogonal function analysis

Encapsulation of dynamic information captured in long sequences of hyper-temporal image data in single temporal images -- examples, challenges and directions for developmentPerformance Assessment of Multi-Temporal SAR Image Filtering; Monitoring and Management of Natural Resources; Using temporal change of the land cover spectral signal to improve burnt area mapping; Land cover and soil loss multitemporal analysis: An application of geoindicators in the Pantanal wetlands (Brazil)

Natural resource in southern African drylands: Determining spatial availability and variability using ATSR2 time seriesMODIS 250m and 500m time series data for change detection and continuous representation of vegetation characteristics; Multitemporal phenological classification of Argentina; Monitoring natural disasters and 'hot spots' of land cover change with SPOTVEGETATION data to assess regions at risks; Multitemporal remotely sensed indices and a proposed integrated functional vegetation index (IFVI) to monitor holm-oak woods along a spatial gradient

The development of effective methodologies for the analysis of multi-temporal data is one of the most important and challenging issues that the remote sensing community will face in the next few years. The relevance and timeliness of this issue are directly related to the ever-increasing quantity of multi-temporal data provided by the numerous remote sensing satellites that orbit our planet. The synergistic use of multi-temporal remote sensing data and advanced analysis methodologies results in the possibility of solving complex problems related to the monitoring of the Earth's surface and atm.

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