GIS and 3D cadastre in land registration of the electrical networks

2015 ◽  
pp. 293-296
Author(s):  
E.C. Bobric ◽  
D. Irimia
Keyword(s):  
Electrical Networks ◽  
Land Registration ◽  
3D Cadastre

scholarly journals DOES COIMBRA NEED A 3D CADASTRE? PROTOTYPING A CROWDSOURCING APP AS A FIRST STEP TO FINDING OUT

2016 ◽  
Vol IV-2/W1 ◽  
pp. 55-62 ◽  
Author(s):  
C. Ellul ◽  
J. P. de Almeida ◽  
R. Romano
Keyword(s):  
General Public ◽  
Three Dimensional ◽  
Crowd Sourcing ◽  
Web Based ◽  
Property Ownership ◽  
Land Registration ◽  
3D Cadastre ◽  
Direct Feedback ◽  
Expensive Process

The Municipality of Coimbra in Portugal, and indeed the country as a whole, is currently undergoing a long-term land registration (cadastre creation) exercise, with approximately 50&amp;thinsp;% of the country having been surveyed, amounting to 1/3 of the total properties, by the end of 2013. The survey process is currently generating two-dimensional (2D) maps. However, as with many other countries, these maps have limitations when representing the real three-dimensional (3D) complexities of land and property ownership. Capturing 2D cadastre is an expensive process, and does not provide the required insight into the number of properties where the ownership situation is inadequately represented, as the survey does not include the internal building structure. Having information about the extent of the 2D/3D issue is, however, fundamental to making a decision as to whether to invest resources in even more expensive 3D survey. <br><br> Given that the 3D complexity inside buildings is only known to residents/occupants - thus making crowd sourcing perhaps the only economically feasible approach for its capture - this paper describes the development of a web-based App envisaged for use by the general public to flag different land and property ownership situations. The paper focuses on two aspects of the problem - firstly, identifying an appropriate, clear, set of diagrams depicting the various different ownership situations from which the user can then pick one, and secondly prototyping and user testing an App for multi-platform VGI data capture in absence of direct feedback from the final end users - i.e. the general public.

Designing a coherent land registration system for rural Portugal

2019 ◽  
Vol 2 (1) ◽  
Author(s):  
Tiago NUNES ◽  
Miguel COUTINHO
Keyword(s):  
Satellite Images ◽  
Field Research ◽  
Digital Native ◽  
Web Based ◽  
Registration System ◽  
Land Registration ◽  
Daily Rate ◽  
Property Owners ◽  
Property Identification

After almost a century of several attempts to establish a coherent land registration system across the whole country, in 2017 the Portuguese government decided to try a new, digital native approach to the problem. Thus, a web-based platform was created, where property owners from 10 pilot municipalities could manually identify their lands’ properties using a map based on satellite images. After the first month of submissions, it became clear that at the current daily rate, it would take years to achieve the goal of 100% rural property identification across just the 10 municipalities. Field research during the first month after launch enabled us to understand landowners’ relationships with their land, map their struggles with the platform, and prototype ways to improve the whole service. Understanding that these improvements would still not be enough to get to the necessary daily rate, we designed, tested and validated an algorithm that allows us to identify a rural property shape and location without coordinates. Today, we are able to help both Government and landowners identify a rural property location with the click of a button.

JUAL BELI TANAH YANG DILAKUKAN TANPA AKTA PPAT

2018 ◽  
Vol 4 (1) ◽  
pp. 89-107
Author(s):  
Cheri Bayuni Budjang
Keyword(s):  
Everyday Life ◽  
Government Regulation ◽  
Land Rights ◽  
The Other ◽  
Legal Certainty ◽  
Land Registration ◽  
The Future ◽  
The Right ◽  
Laws And Regulations

Buying and selling is a way to transfer land rights according to the provisions in Article 37 paragraph (1) of Government Regulation Number 24 of 1997 concerning Land Registration which must include the deed of the Land Deed Making Official to register the right of land rights (behind the name) to the Land Office to create legal certainty and minimize the risks that occur in the future. However, in everyday life there is still a lot of buying and selling land that is not based on the laws and regulations that apply, namely only by using receipts and trust in each other. This is certainly very detrimental to both parties in the transfer of rights (behind the name), especially if the other party is not known to exist like the Case in Decision Number 42 / Pdt.G / 2010 / PN.Mtp

Study of the operation of an artificial neural network that works in the electric network in order to prevent emergency conditions.

2020 ◽  
Vol 14 (1) ◽  
pp. 48-54
Author(s):  
D. Ostrenko ◽  
Keyword(s):  
Neural Networks ◽  
Learning Algorithm ◽  
Electricity Consumption ◽  
Electrical Energy ◽  
Energy System ◽  
Electrical Networks ◽  
Electric Networks ◽  
Electric Network ◽  
Time Dynamics ◽  
Emergency Situations

Emergency modes in electrical networks, arising for various reasons, lead to a break in the transmission of electrical energy on the way from the generating facility to the consumer. In most cases, such time breaks are unacceptable (the degree depends on the class of the consumer). Therefore, an effective solution is to both deal with the consequences, use emergency input of the reserve, and prevent these emergency situations by predicting events in the electric network. After analyzing the source [1], it was concluded that there are several methods for performing the forecast of emergency situations in electric networks. It can be: technical analysis, operational data processing (or online analytical processing), nonlinear regression methods. However, it is neural networks that have received the greatest application for solving these tasks. In this paper, we analyze existing neural networks used to predict processes in electrical systems, analyze the learning algorithm, and propose a new method for using neural networks to predict in electrical networks. Prognostication in electrical engineering plays a key role in shaping the balance of electricity in the grid, influencing the choice of mode parameters and estimated electrical loads. The balance of generation of electricity is the basis of technological stability of the energy system, its violation affects the quality of electricity (there are frequency and voltage jumps in the network), which reduces the efficiency of the equipment. Also, the correct forecast allows to ensure the optimal load distribution between the objects of the grid. According to the experience of [2], different methods are usually used for forecasting electricity consumption and building customer profiles, usually based on the analysis of the time dynamics of electricity consumption and its factors, the identification of statistical relationships between features and the construction of models.

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