Automated delineation of smallholder farm fields is difficult because of their small size, irregular shape and the use of mixed-cropping systems. Edges between smallholder plots are often indistinct in satellite imagery and contours have to be identified by considering the transition of the complex textural patterns of the fields. We introduce a strategy to delineate field boundaries using a fully convolutional network in combination with a globalization and grouping algorithm to produce a hierarchical segmentation of the fields. We carry out an experimental analysis in a study area in Kofa, Nigeria, using a WorldView-3 image, comparing several state-of-the-art contour detection algorithms. The proposed strategy outperforms state-of-the-art computer vision methods and shows promising results by automatically delineating field boundaries with an accuracy close to human level photo-interpretation.

Innumerable forest fire spread models exist for taking a decision, but far less focus is on the real causative factors which initiate/ignite fire in an area. It has been observed that the majority of the forest fires in India are initiated due to anthropogenic factors. In this study, we develop a geo-information system approach for management of forest fire in Mudumalai Wildlife Sanctuary, Tamil Nadu, India, with the objective to develop a forest fire likelihood model, integrating GIS and knowledge-based approach for predicting fire-sensitive initiation areas considering major causative and anti-causative factors. Amongst the various causative factors investigated, it was found that wildlife-dependent factor (antler collection and poaching) contributed significantly to fire occurrence followed by management-dependent factors (uncontrolled tourism and grazing), with much less influence of demographic factors. Similarly, anti-causative factor (stationing of anti-poaching/ fire camps) was considered as quite significant.The likelihood model so developed, envisaging various factors and flammability, accounted for different scenarios as a result of pair-wise comparison on an ordinal scale in a knowledge matrix. The inferential statistics computed indicated the robustness of the model and its insensitivity to moderate changes. It makes it possible for this forest fire likelihood model to predict and prevent a forest fire in an effective and scientific manner because it can assume forest fire likelihood in real time and present in proper time.

Trajectories of people contain a vast amount of information on users' interests and popularity of locations. To obtain this information, the places visited by the owner of the device on such a trajectory need to be recognized. However, the location information on a point of interest (POI) in a database is normally limited to an address and a coordinate pair, rather than a polygon describing its boundaries. A region of interest can be used to intersect trajectories to match trajectories with objects of interest. In the absence of expensive and often not publicly available detailed spatial data like cadastral data, we need to approximate this ROI. In this paper, we present several approaches to approximate the size and shape of ROIs, by integrating data from multiple public sources, a validation technique, and a validation of these approaches against the cadastral data of the city of Enschede, The Netherlands.

Many spatial phenomena exhibit vagueness. Representation of such phenomena requires vague objects. In previous work, we provided definitions for vague objects: vague points, vague lines, and vague regions. Each of these objects is presented as a fuzzy set in ℝ2that satisfies well-defined properties. In this paper, we propose a number of geometric measures for vague objects, using the concept of mass distribution. The membership function of a vague object can be seen as a mass distribution. According to this view, a crisp object is a body with constant density, and a vague object is a body of varying density. We provide mathematical definitions for length of a vague line, area of a vague region, centroid of a vague object, as well as a measure for the vagueness of an object. The length of a vague line and the area of a vague region are indeed the mass of the vague line and of the vague region, respectively. Both metrics give an average of the values of the corresponding crisp metric on the α-cuts of the vague object. The centroid of a vague object is its centre of mass associated with a membership degree. The last metric functions as a measure of the degree of vagueness for a vague object.

Vagueness is often present in spatial phenomena. Representing and analysing vague spatial phenomena requires vague objects and operators, whereas current GIS and spatial databases can only handle crisp objects. This paper provides mathematical definitions for vague object types and operators. The object types that we propose are a set of simple types, a set of general types, and vague partitions. The simple types represent identifiable objects of a simple structure, i.e. not divisible into components. They are vague points, vague lines, and vague regions. The general types represent classes of simple type objects. They are vague multipoint, vague multiline, and vague multiregion. General types assure closure under set operators. Simple and general types are defined as fuzzy sets in ℝ2 satisfying specific properties that are expressed in terms of topological notions. These properties assure that set membership values change mostly gradually, allowing stepwise jumps. The type vague partition is a collection of vague multiregions that might intersect each other only at their transition boundaries. It allows for a soft classification of space. All types allow for both a finite and an infinite number of transition levels. They include crisp objects as special cases. We consider a standard set of operators on crisp objects and define them for vague objects. We provide definitions for operators returning spatial types. They are regularized fuzzy set operators: union, intersection, and difference; two operators from topology: boundary and frontier; and two operators on vague partitions: overlay and fusion. Other spatial operators, topological predicates and metric operators, are introduced giving their intuition and example definitions. All these operators include crisp operators as special cases. Types and operators provided in this paper form a model for a spatial data system that can handle vague information. The paper is illustrated with an application of vague objects in coastal erosion.

We introduce the language LOTOS/TM for the formal specification of a network of cooperating agents with a shared data repository and private local data. LOTOS/TM is the orthogonal integration of the process-algebraic protocol specification language LOTOS and the functional, object-oriented database specification language TM. The specified world consists of a number of interacting LOTOS processes — describing the cooperating agents — and a special LOTOS process representing the shared data repository, which is modeled as a TM database. The data repository's functionality is made available to the other, cooperating processes through one or more external database gates. Interaction at such a gate corresponds to a method invocation in the database. In addition to shared persistent data, the TM language is used to specify the data encapsulated locally within processes, and the transient data communicated over gates. Some features of LOTOS/TM are inherently suitable for describing cooperation, such as combinators for synchronization on specific methods. These features are illustrated by examples showing navigation events on a shared graph structure that resembles a hypertext. Emphasis in the examples is placed on coordination aspects of the scenario. LOTOS/TM serves as a formalism for a more user-friendly specification language by the name of CoCoA that is currently under construction.

The relational data model is based on sets of tuples, i.e. it does not allow duplicate tuples an a relation. Many database languages and systems do require multi-set semantics though, either because of functional requirements or because of the high costs of duplicate removal in database operations. Several proposals have been presented that discuss multi-set semantics. As these proposals tend to be either rather practical, lacking the formal background, or rather formal, lacking the connection to database practice, the gap between theory and practice has not been spanned yet. This paper proposes a complete extended relational algebra with multi-set semantics, having a clear formal background and a close connection to the standard relational algebra. It includes constructs that extend the algebra to a complete sequential database manipulation language that can either be used as a formal background to other multi-set languages like SQL, or as a database manipulation language on its own. The practical usability of the latter option has been demonstrated in the PRISMA/DB database project, where a variant of the language has been used as the primary database language.>