scholarly journals Spatio-temporal topological relationships between land parcels in cadastral database

Author(s):  
W. Song ◽  
F. Zhang

There are complex spatio-temporal relationships among cadastral entities. Cadastral spatio-temporal data model should not only describe the data structure of cadastral objects, but also express cadastral spatio-temporal relationships between cadastral objects. In the past, many experts and scholars have proposed a variety of cadastral spatio-temporal data models, but few of them concentrated on the representation of spatiotemporal relationships and few of them make systematic studies on spatiotemporal relationships between cadastral objects. The studies on spatio-temporal topological relationships are not abundant. In the paper, we initially review current approaches to the studies of spatio-temporal topological relationships, and argue that spatio-temporal topological relation is the combination of temporal topology on the time dimension and spatial topology on the spatial dimension. Subsequently, we discuss and develop an integrated representation of spatio-temporal topological relationships within a 3-dimensional temporal space. In the end, based on the semantics of spatiotemporal changes between land parcels, we conclude the possible spatio-temporal topological relations between land parcels, which provide the theoretical basis for creating, updating and maintaining of land parcels in the cadastral database.

Author(s):  
Cyril Tissot ◽  
Etienne Neethling ◽  
Mathias Rouan ◽  
Gérard Barbeau ◽  
Hervé Quénol ◽  
...  

This paper focuses on simulating environmental impacts on grapevine behavioral dynamics and vineyard management strategies. The methodology presented uses technology from geomatics object oriented databases and spatio-temporal data models. Our approach has two principle objectives, first, to simulate grapevine phenology and grape ripening under spatial and temporal environmental conditions and constraints and secondly, to simulate viticultural practices and adaptation strategies under various constraints (environmental, economical, socio-technical). The approach is based on a responsive agent-based structure where environmental conditions and constraints are considered as a set of forcing data (biophysical, socio-economic and regulatory data) that influences the modelled activities. The experiment was conducted in the regulated wine producing appellation Grand Cru “Quarts de Chaume”, situated in the middle Loire Valley, France. All of the methodology, from the implementation of the knowledge database to the analysis of the first simulation, is presented in this paper.


2021 ◽  
Vol 94 (3) ◽  
pp. 325-354
Author(s):  
Jerzy Parysek ◽  
Lidia Mierzejewska

The purpose of this study is to present a description of the course of the COVID-19 epidemic in Poland in the space-time dimension in the period from March 15th to August 8th 2020. The result of the conducted research is a presentation of the regional differentiation of the course of the epidemic in Poland, the comparison of the intensity of SARS-CoV-2 infections in particular voivodeships, the determination of the degree of similarity in the course of the pandemic development process in individual regions (voivodeships) of the country, and also the indication of the factors which could be taken into account when attempting to explain the interregional differences in the course of the epidemic. The conducted research shows, among other things, that: (1) in terms of time, the development of the epidemic was generally monotonic, however the increase in new infections was rather cyclical, (2) in the spatial dimension, the development of the epidemic was rather random, although the greatest number of infections was characteristic of the most populated regions of the country, (3) the level of infections in Poland was mainly positively influenced by: population density, working in industry, people beyond retirement, age as well as a poorly developed material base of inpatient care.


Author(s):  
Yu Jiang ◽  
Shenggeng Lin ◽  
Jinjian Ruan ◽  
Hong Qi

As the ocean data acquired by the Argo project is increasingly huge, how to use artificial intelligence to analyze it so as to discover the distribution and variation of ocean temperature with space and time becomes an important research topic in the world. In this article, a spatio-temporal dependence-based tensor fusion method is proposed, which can be used to determine and analyze the thermocline. In the time dimension, long short-term memory is used to predict the temperature of seawater; in the spatial dimension, the thermocline is found incrementally by using tensor analysis. Experiments on BOA Argo data from 2004 to 2016 show that the proposed method can accurately determine the boundary of the thermocline and predict the future trend of the thermocline.


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