Semantic Approach in Image Change Detection

International audienceChange detection is a main issue in various domains, and especially for remote sensing purposes. Indeed, plethora of geospatial images are available and can be used to update geographical databases. In this paper, we propose a classification-based method to detect changes between a database and a more recent image. It is based both on an efficient training point selection and a hierarchical decision process. This allows to take into account the intrinsic heterogeneity of the objects and themes composing a database while limiting false detection rates. The reliability of the designed framework method is first assessed on simulated data, and then successfully applied on very high resolution satellite images and two land-cover databases

Oceanic response to Pliensbachian and Toarcian magmatic events: Implications from an organic-rich basinal succession in the NW Tethys

The Bächental bituminous marls (Bächentaler Bitumenmergel) belonging to the Sachrang Member of the Lower Jurassic Middle Allgäu Formation were investigated using a multidisciplinary approach to determine environmental controls on the formation of organic-rich deposits in a semi-restricted basin of the NW Tethys during the Early Jurassic. The marls are subdivided into three units on the basis of mineralogical composition, source-rock parameters, redox conditions, salinity variations, and diagenetic processes. Redox proxies (e.g., pristane/phytane ratio; aryl isoprenoids; bioturbation; ternary plot of iron, total organic carbon, and sulphur) indicate varying suboxic to euxinic conditions during deposition of the Bächental section. Redox variations were mainly controlled by sea-level fluctuations with the tectonically complex bathymetry of the Bächental basin determining watermass exchange with the Tethys Ocean. Accordingly, strongest anoxia and highest total organic carbon content (up to 13%) occur in the middle part of the profile (upper tenuicostatum and lower falciferum zones), coincident with an increase in surface-water productivity during a period of relative sea-level lowstand that induced salinity stratification in a stagnant basin setting. This level corresponds to the time interval of the lower Toarcian oceanic anoxic event (T-OAE). However, the absence of the widely observed lower Toarcian negative carbon isotope excursion in the study section questions its unrestricted use as a global chemostratigraphic marker. Stratigraphic correlation of the thermally immature Bächental bituminous marls with the Posidonia Shale of SW Germany on the basis of C27/C29 sterane ratio profiles and ammonite data suggests that deposition of organic matter-rich sediments in isolated basins in the Alpine realm commenced earlier (late Pliensbachian margaritatus Zone) than in regionally proximal epicontinental seas (early Toarcian tenuicostatum Zone). The late Pliensbachian onset of reducing conditions in the Bächental basin coincided with an influx of volcaniclastic detritus that was possibly connected to complex rifting processes of the Alpine Tethys and with a globally observed eruption-induced extinction event. The level of maximum organic matter accumulation in the Bächental basin corresponds to the main eruptive phase of the Karoo-Ferrar large igneous province (LIP), confirming its massive impact on global climate and oceanic conditions during the Early Jurassic. The Bächental marl succession is thus a record of the complex interaction of global (i.e., LIP) and local (e.g., redox and salinity variations, basin morphology) factors that caused reducing conditions and organic matter enrichment in the Bächental basin. These developments resulted in highly inhomogeneous environmental conditions in semi-restricted basins of the NW Tethyan domain during late Pliensbachian and early Toarcian time

A Neural Network Model for Image Change Detection Based on Fuzzy Cognitive Maps

Abstract. This paper outlines a neural network model based on the Fuzzy Cognitive Maps (FCM) framework for solving the automatic image change detection problem. Each pixel in the reference image is assumed to be a node in the network. Each node has associated a fuzzy value, which determines the magnitude of the change. Each fuzzy value is updated by a trade-off between the influences received from the fuzzy values from other neurons and its own fuzzy value. Classical approaches in the literature have been designed assuming that the mutual influences between two nodes are symmetric. The main finding of this paper is the assumption that mutual influences could not be symmetric. This non symmetric relationship can be embedded by the FCM paradigm. The performance of the proposed method is illustrated by comparative analysis against some recent image change detection methods.