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

Error processes in the integration of digital cartographic data in geographic information systems.

Errors within a Geographic Information System (GIS) arise from several factors. In the first instance receiving data from a variety of different sources results in a degree of incompatibility between such information. Secondly, the very processes used to acquire the information into the GIS may in fact degrade the quality of the data. If geometric overlay (the very raison d'etre of many GISs) is to be performed, such inconsistencies need to be carefully examined and dealt with. A variety of techniques exist for the user to eliminate such problems, but all of these tend to rely on the geometry of the information, rather than on its meaning or nature. This thesis explores the introduction of error into GISs and the consequences this has for any subsequent data analysis. Techniques for error removal at the overlay stage are also examined and improved solutions are offered. Furthermore, the thesis also looks at the role of the data model and the potential detrimental effects this can have, in forcing the data to be organised into a pre-defined structure

Unmanned Aerial Systems for Wildland and Forest Fires

Wildfires represent an important natural risk causing economic losses, human death and important environmental damage. In recent years, we witness an increase in fire intensity and frequency. Research has been conducted towards the development of dedicated solutions for wildland and forest fire assistance and fighting. Systems were proposed for the remote detection and tracking of fires. These systems have shown improvements in the area of efficient data collection and fire characterization within small scale environments. However, wildfires cover large areas making some of the proposed ground-based systems unsuitable for optimal coverage. To tackle this limitation, Unmanned Aerial Systems (UAS) were proposed. UAS have proven to be useful due to their maneuverability, allowing for the implementation of remote sensing, allocation strategies and task planning. They can provide a low-cost alternative for the prevention, detection and real-time support of firefighting. In this paper we review previous work related to the use of UAS in wildfires. Onboard sensor instruments, fire perception algorithms and coordination strategies are considered. In addition, we present some of the recent frameworks proposing the use of both aerial vehicles and Unmanned Ground Vehicles (UV) for a more efficient wildland firefighting strategy at a larger scale.Comment: A recent published version of this paper is available at: https://doi.org/10.3390/drones501001

Classification and boundary vagueness in mapping presettlement forest types

Presettlement forest types were mapped as fuzzy sets from point data representing trees contained in General Land Office survey notes (circa 1850) for Chippewa County, Michigan. The resulting representation agreed with a polygon map of the same forest types at 66 % of the locations (represented as grid cells) in the county. Boundary vagueness was defined in relation to the slope of a linear function fitted to the negative relation between entropy of forest types and distance to polygon boundaries. The similarity between forest type compositions (i.e. classification ambiguity) was shown to account for 55 % of the variation in boundary vagueness

Modeling and improving Spatial Data Infrastructure (SDI)

Spatial Data Infrastructure (SDI) development is widely known to be a challenging process owing to its complex and dynamic nature. Although great effort has been made to conceptually explain the complexity and dynamics of SDIs, few studies thus far have actually modeled these complexities. In fact, better modeling of SDI complexities will lead to more reliable plans for its development. A state-of-the-art simulation model of SDI development, hereafter referred to as SMSDI, was created by using the system dynamics (SD) technique. The SMSDI enables policy-makers to test various investment scenarios in different aspects of SDI and helps them to determine the optimum policy for further development of an SDI. This thesis begins with adaption of the SMSDI to a new case study in Tanzania by using the community of participant concept, and further development of the model is performed by using fuzzy logic. It is argued that the techniques and models proposed in this part of the study enable SDI planning to be conducted in a more reliable manner, which facilitates receiving the support of stakeholders for the development of SDI.Developing a collaborative platform such as SDI would highlight the differences among stakeholders including the heterogeneous data they produce and share. This makes the reuse of spatial data difficult mainly because the shared data need to be integrated with other datasets and used in applications that differ from those originally produced for. The integration of authoritative data and Volunteered Geographic Information (VGI), which has a lower level structure and production standards, is a new, challenging area. The second part of this study focuses on proposing techniques to improve the matching and integration of spatial datasets. It is shown that the proposed solutions, which are based on pattern recognition and ontology, can considerably improve the integration of spatial data in SDIs and enable the reuse or multipurpose usage of available data resources

Urban scene description for a multi scale classication of high resolution imagery case of Cape Town urban Scene

Includes abstract.Includes bibliographical references.In this paper, a multi level contextual classification approach of the City of Cape Town, South Africa is presented. The methodology developed to identify the different objects using the multi level contextual technique comprised three important phases

A multivariate morphometric analysis of diagnostic traits in southern Italy and Sicily pubescent oaks

Species identification within the species complex of Q. pubescens is a well-known taxonomic challenge among European botanists. Some of the specific pubescent oak binomials currently accepted in various European floras and checklistswere originally described in Sicily and southern Calabria. As a consequence, several species belonging to the pubescent oaks group (Q. pubescens, Q. amplifolia, Q. congesta, Q. dalechampii, Q. leptobalana and Q. virgiliana) are reported in the taxonomic and phytosociological literature. To verify whether it was possible to associate a diverse set of morphological characters with each of these different taxa, thirteen natural populations of pubescent oak from Sicily and southern Calabria were sampled. A total of 391 trees, 3,887 leaves and 1,047 fruits were collected. Overall, 28 morphological characters of oak leaves and fruits were statistically analysed using univariate and multivariate procedures. The results showed that neither the groups of morphological diversity identified by cluster analysis, nor those obtained by our expert identification through the use of analytical keys, matched with the current taxonomical frameworks as proposed by the most recent floras and checklists. Nearly all of the morphological characters considered displayed a more or less continuous trend of variation, both within and among populations. In the light of these findings it seems unlikely that more than one biological species of pubescent oak occurs in Sicily and southern Calabria

Assessing contextual descriptive features for plot-based classification of urban areas

A methodology for mapping urban land-use types integrating information from multiple data sources (high spatial resolution imagery, LiDAR data, and cadastral plots) is presented. A large set of complementary descriptive features that allow distinguishing different urban structures (historical, urban, residential, and industrial) is extracted and, after a selection process, a plot-based image classification approach applied, facilitating to directly relate the classification results and the urban descriptive parameters computed to the existent land-use/land-cover units in geospatial databases. The descriptive features are extracted by considering different hierarchical scale levels with semantic meaning in urban environments: buildings, plots, and urban blocks. Plots are characterised by means of image-based (spectral and textural), three-dimensional, and geometrical features. In addition, two groups of contextual features are defined: internal and external. Internal contextual features describe the main land cover types inside the plot (buildings and vegetation). External contextual features describe each object in terms of the properties of the urban block to which it belongs. After the evaluation in an heterogeneous Mediterranean urban area, the land-use classification accuracy values obtained show that the complementary descriptive features proposed improve the characterisation of urban typologies. A progressive introduction of the different groups of descriptive features in the classification tests show how the subsequent addition of internal and external contextual features have a positive effect by increasing the final accuracy of the urban classes considered in this study. © 2012 Elsevier B.V.The authors appreciate the financial support provided by the Spanish Ministry of Science and Innovation and FEDER in the framework of the projects CGL2009-14220 and CGL2010-19591/BTE, and the support of the Spanish Instituto Geografico Nacional (IGN).Hermosilla, T.; Ruiz Fernández, LÁ.; Recio Recio, JA.; Cambra López, M. (2012). Assessing contextual descriptive features for plot-based classification of urban areas. Landscape and Urban Planning. 106(1):124-137. doi:10.1016/j.landurbplan.2012.02.008S124137106