2,133 research outputs found
Monitoring land use changes using geo-information : possibilities, methods and adapted techniques
Monitoring land use with geographical databases is widely used in decision-making. This report presents the possibilities, methods and adapted techniques using geo-information in monitoring land use changes. The municipality of Soest was chosen as study area and three national land use databases, viz. Top10Vector, CBS land use statistics and LGN, were used. The restrictions of geo-information for monitoring land use changes are indicated. New methods and adapted techniques improve the monitoring result considerably. Providers of geo-information, however, should coordinate on update frequencies, semantic content and spatial resolution to allow better possibilities of monitoring land use by combining data sets
Modeling Complex Object Changes in Satellite Image Time-Series: Approach based on CSP and Spatiotemporal Graph
This paper proposes a method for automatically monitoring and analyzing the
evolution of complex geographic objects. The objects are modeled as a
spatiotemporal graph, which separates filiation relations, spatial relations,
and spatiotemporal relations, and is analyzed by detecting frequent sub-graphs
using constraint satisfaction problems (CSP). The process is divided into four
steps: first, the identification of complex objects in each satellite image;
second, the construction of a spatiotemporal graph to model the spatiotemporal
changes of the complex objects; third, the creation of sub-graphs to be
detected in the base spatiotemporal graph; and fourth, the analysis of the
spatiotemporal graph by detecting the sub-graphs and solving a constraint
network to determine relevant sub-graphs. The final step is further broken down
into two sub-steps: (i) the modeling of the constraint network with defined
variables and constraints, and (ii) the solving of the constraint network to
find relevant sub-graphs in the spatiotemporal graph. Experiments were
conducted using real-world satellite images representing several cities in
Saudi Arabia, and the results demonstrate the effectiveness of the proposed
approach
Segmentation of optical remote sensing images for detecting homogeneous regions in space and time.
With the amount of multitemporal and multiresolution images growing exponentially, the number of image segmentation applications is recently increasing and, simultaneously, new challenges arise. Hence, there is a need to explore new segmentation concepts and techniques that make use of the temporal dimension. This paper describes a spatio-temporal segmentation that adapts the traditional region growing technique to detect homogeneous regions in space and time in optical remote sensing images. Tests were conducted by considering the Dynamic Time Warping measure as the homogeneity criterion. Study cases on high temporal resolution for sequences of MODIS and Landsat-8 OLI vegetation indices products provided satisfactory outputs and demonstrated the potential of the spatio-temporal segmentation method.Também publicado na Revista Brasileira de Cartografia, v. 70, n. 5, p. 1779-1801, 2018. Special Issue XIX Brazilian Syposium on GeoInformatics, 2018. DOI: 10.14393/rbcv70n5-45227
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