Geo-Information Technology and Its Applications

Geo-information technology has been playing an ever more important role in environmental monitoring, land resource quantification and mapping, geo-disaster damage and risk assessment, urban planning and smart city development. This book focuses on the fundamental and applied research in these domains, aiming to promote exchanges and communications, share the research outcomes of scientists worldwide and to put these achievements better social use. This Special Issue collects fourteen high-quality research papers and is expected to provide a useful reference and technical support for graduate students, scientists, civil engineers and experts of governments to valorize scientific research

An index based road feature extraction from LANDSAT-8 OLI images

Road feature extraction from the remote sensing images is an arduous task and has a significant role in various applications of urban planning, updating the maps, traffic management, etc. In this paper, a new band combination (B652) to form a road index (RI) from OLI multispectral bands based on the spectral reflectance of asphalt, is presented for road feature extraction. The B652 is converted to road index by normalization. The morphological operators (top-hat or bottom-hat) uses on RI to enhance the roads. To sharpen the edges and for better discrimination of features, shock square filter (SSF), is proposed. Then, an iterative adaptive threshold (IAT) based online search with variational min-max and Markov random fields (MRF) model are used on the SSF image to segment the roads and non-roads. The roads are extracting by using the rules based on the connected component analysis. IAT and MRF model segmentation methods prove the proposed index (RI) able to extract road features productively. The proposed methodology is a combination of saturation based adaptive thresholding and morphology (SATM), and saturation based MRF (SMRF), applied to OLI images of several urban cities of India, producing the satisfactory results. The experimental results with the quantitative analysis presented in the paper

Remote Sensing

This dual conception of remote sensing brought us to the idea of preparing two different books; in addition to the first book which displays recent advances in remote sensing applications, this book is devoted to new techniques for data processing, sensors and platforms. We do not intend this book to cover all aspects of remote sensing techniques and platforms, since it would be an impossible task for a single volume. Instead, we have collected a number of high-quality, original and representative contributions in those areas

Satellite and UAV Platforms, Remote Sensing for Geographic Information Systems

The present book contains ten articles illustrating the different possible uses of UAVs and satellite remotely sensed data integration in Geographical Information Systems to model and predict changes in both the natural and the human environment. It illustrates the powerful instruments given by modern geo-statistical methods, modeling, and visualization techniques. These methods are applied to Arctic, tropical and mid-latitude environments, agriculture, forest, wetlands, and aquatic environments, as well as further engineering-related problems. The present Special Issue gives a balanced view of the present state of the field of geoinformatics

Spatial Permeability Model at the European Union Land Border

In the frame of the ISFEREA action, the JRC IPSC carried out an analysis of the permeability of the EU Eastern land border to a specific class of illegal migration flows. This analysis is based on a preliminary version of a spatial quantitative model of the "green border" permeability. This model was built on the assumption that the flow of illegal migrants is function of the geographical permeability of the border and crossing points, the efficacy to control them by the Authorities, and also function of the driving force defined by people's willingness to cross (push and pull factors). The spatial model developed by the JRC attempts to represent in deep only the first part of this equation, while the modularity of the proposed model may allows further development for a more comprehensive explanation the illegal migration phenomena. With the present release the model uses as input more than 20 spatial datasets ranging from satellite remotely-sensed data, land use land cover, digital terrain model, weather and environmental conditions, presence of population, infrastructures, and physical obstacles, and presence of border control points. The model is focused on the geographic permeability related to a standard adult person having illegal behavior and deciding to cross the green border by foot. The basic criteria implemented in the current release are built around three concepts: the rapidity of walking allowed by the terrain and the weather conditions (walk), the possibility to hide by the physical environment (hide), and the probability to be stopped by a border police agent (secure). The geographic permeability is conceptualized as function inverse of the friction surface calculated using fuzzy multi-criteria methodology with a spatial resolution of 1 kilometer. Friction statistics are related to specific spatial contexts around the border lines (from 1 to 50 km) aggregated at the national and sub-national level between different countries. The model confirms the two major entry routes into Europe: the Ukrainian border and the Turkish section of the Greek border. The model shows also the high sensitivity of the potential corridor of Norway but the high number of border points at this boundary seems to be sufficient to protect this entry point. The report concludes that, in spite of limitations linked to data collection and availability, the permeability maps which resulted from this study show the high potential of such a model for the analysis of potential and actual migration flows and related policy planning. This tool could provide an opportunity to test different “what-if” scenarios about the driving forces of illegal migratory flows at the external EU land border, to prioritize investments of Member States in border management infrastructures at EU level, and to develop policy advice for relevant internal and external EU policies. This modeling tool can help estimate the impact on permeability of concrete measures, such as changes in the number of border points or number of border guards and in their level of equipment at these particular points. The flexibility of the model also allows for the input of additional data like typology of border points, in order to improve the results. Finally, the development of a more comprehensive model would require the co-operation of and contribution from relevant authorities of the EU Member States as well as FRONTEX.JRC.G.2-Global security and crisis managemen

Automatic road network extraction from high resolution satellite imagery using spectral classification methods

Road networks play an important role in a number of geospatial applications, such as cartographic, infrastructure planning and traffic routing software. Automatic and semi-automatic road network extraction techniques have significantly increased the extraction rate of road networks. Automated processes still yield some erroneous and incomplete results and costly human intervention is still required to evaluate results and correct errors. With the aim of improving the accuracy of road extraction systems, three objectives are defined in this thesis: Firstly, the study seeks to develop a flexible semi-automated road extraction system, capable of extracting roads from QuickBird satellite imagery. The second objective is to integrate a variety of algorithms within the road network extraction system. The benefits of using each of these algorithms within the proposed road extraction system, is illustrated. Finally, a fully automated system is proposed by incorporating a number of the algorithms investigated throughout the thesis. CopyrightDissertation (MSc)--University of Pretoria, 2010.Computer Scienceunrestricte

A Global Human Settlement Layer from optical high resolution imagery - Concept and first results

A general framework for processing of high and very-high resolution imagery for creating a Global Human Settlement Layer (GHSL) is presented together with a discussion on the results of the first operational test of the production workflow. The test involved the mapping of 24.3 millions of square kilometres of the Earth surface spread over four continents, corresponding to an estimated population of 1.3 billion of people in 2010. The resolution of the input image data ranges from 0.5 to 10 meters, collected by a heterogeneous set of platforms including satellite SPOT (2 and 5), CBERS-2B, RapidEye (2 and 4), WorldView (1 and 2), GeoEye-1, QuickBird-2, Ikonos-2, and airborne sensors. Several imaging modes were tested including panchromatic, multispectral and pan-sharpened images. A new fully automatic image information extraction, generalization and mosaic workflow is presented that is based on multiscale textural and morphological image features extraction. New image feature compression and optimization are introduced, together with new learning and classification techniques allowing for the processing of HR/VHR image data using low-resolution thematic layers as reference. A new systematic approach for quality control and validation allowing global spatial and thematic consistency checking is proposed and applied. The quality of the results are discussed by sensor, by band, by resolution, and eco-regions. Critical points, lessons learned and next steps are highlighted.JRC.G.2-Global security and crisis managemen