scholarly journals An Algorithm of Automatic Administrative Region Index Map Generation for National-level Map Production

2019 ◽  
Vol 2 ◽  
pp. 1-4
Author(s):  
Ruolei Wang ◽  
Jianjun Liu ◽  
Zhao Li ◽  
Jun Zhang
Keyword(s):  
National Level ◽  
Production Lines ◽  
Recognition Error ◽  
Multi Scale ◽  
Administrative Region ◽  
Database Construction ◽  
Map Generation ◽  
Error Accumulation ◽  
Dynamic Updating ◽  
Information Database

<p><strong>Abstract.</strong> Since the project of dynamic updating of national fundamental geographic information database was launched, National Geomatics Center of China has published the newest version of multi-scale databases, derived databases and subdivision maps once a year. As one of the derived cartographic databases, administrative region index database allows users to find maps covering their regions of interest quickly by input the name or number of the relevant map. Due to the boundaries or attributes of some administrative regions may often change, updating of administrative region index database is necessary. To improve efficiency and quality in the national-level map production and database construction, an algorithm of administrative region index map automatic generalization has been proposed in this paper to replace the traditional manual production lines, which are time-consuming and uncontrollable in quality. The method goes in depth with handling coordinate recognition error accumulation and residue lines caused by the clip.</p>

Research on Database and Mining-Map Automatic Generation System of Metal Mine Production Information

2013 ◽  
Vol 321-324 ◽  
pp. 2587-2595
Author(s):  
Xin Rui Liu ◽  
Peng Chen ◽  
Yong Sheng Chen ◽  
Qun He ◽  
Hong Bin Ma
Keyword(s):  
Automatic Generation ◽  
Three Dimension ◽  
Production Lines ◽  
Whole Process ◽  
Metal Mine ◽  
Mine Production ◽  
Automatic Mapping ◽  
Mining Design ◽  
Information Database ◽  
Object Oriented Database

According to the intensive analysis of metal mine production information database and data characteristics, object-oriented database is primarily discussed to establish for metal mine production information with UML technique. Then the subsequent design idea and approach is presented on mine three-view drawing of metal mine production information system, taking the requests and rules of mapping in metal mine into account and applying the techniques of ObjectARX, to realize three dimension information visualization and automatic mapping of metal mine production information and mining design. In the whole process we cohered with experiences from engineering to do interactive improvement and develop simple and convenient system operation interfaces according with working habits of direct labor on production lines,which owns strong application significance and wonderful popularization value among metal mines at present.

scholarly journals Analysis of human exposure to landslides with a GIS multiscale approach

2022 ◽  
Author(s):  
S. Modugno ◽  
S. C. M. Johnson ◽  
P. Borrelli ◽  
E. Alam ◽  
N. Bezak ◽  
...  
Keyword(s):  
Human Exposure ◽  
Local Level ◽  
Explanatory Power ◽  
National Level ◽  
Landslide Hazard ◽  
Landslide Risk ◽  
Multiscale Approach ◽  
Landslide Occurrence ◽  
Multi Scale ◽  
Overview Analysis

AbstractDecision-making plays a key role in reducing landslide risk and preventing natural disasters. Land management, recovery of degraded lands, urban planning, and environmental protection in general are fundamental for mitigating landslide hazard and risk. Here, we present a GIS-based multi-scale approach to highlight where and when a country is affected by a high probability of landslide occurrence. In the first step, a landslide human exposure equation is developed considering the landslide susceptibility triggered by rain as hazard, and the population density as exposed factor. The output, from this overview analysis, is a global GIS layer expressing the number of potentially affected people by month, where the monthly rain is used to weight the landslide hazard. As following step, Logistic Regression (LR) analysis was implemented at a national and local level. The Receiver Operating Characteristic indicator is used to understand the goodness of a LR model. The LR models are defined by a dependent variable, presence–absence of landslide points, versus a set of independent environmental variables. The results demonstrate the relevance of a multi-scale approach, at national level the biophysical variables are able to detect landslide hotspot areas, while at sub-regional level geomorphological aspects, like land cover, topographic wetness, and local climatic condition have greater explanatory power.

A Multi-Scale Study of US Drought Awareness

2020 ◽  
Author(s):  
Jonghun Kam
Keyword(s):  
Big Data ◽  
Public Awareness ◽  
National Level ◽  
Spatiotemporal Analysis ◽  
Economic Losses ◽  
Social Response ◽  
Us States ◽  
Multi Scale

&lt;p&gt;Big data have meaningful, but hidden, information about our society's behavior and response to influential events. Particularly, water-related disasters, such as drought and flood, cause rapid increase in public awareness/interest when they already happen. Despite the improved prediction skill, lack of timely social response to these disasters exacerbates economic losses and fatalities.&amp;#160;&lt;/p&gt;&lt;p&gt;In this presentation, I will introduce the utility of Google Trends data in monitoring and understanding the dynamic patterns of social response to drought at the state and national level. The first part of this presentation will show a case study of the dynamics of Californian awareness during the 2011&amp;#8211;17 California Drought. The second part of this seminar will show a spatiotemporal analysis of US national drought awareness among the 49 US states. In closing, I will discuss the role of big data in transforming our society to a water-related disaster-ready environment.&lt;/p&gt;

scholarly journals The Project to Complete the Regional Topographic Geodatabase in Lombardy, Italy

2021 ◽  
Vol 4 ◽  
pp. 1-8
Author(s):  
Piera Belotti ◽  
Fabio Conzi ◽  
Chiara Dell’Orto ◽  
Maurizio Federici ◽  
Luigi Fregonese ◽  
...  
Keyword(s):  
Quality Assessment ◽  
National Level ◽  
National Guidelines ◽  
Urban And Regional Planning ◽  
Lombardy Region ◽  
Multi Scale ◽  
Assessment Validation ◽  
World Economic ◽  
Temporary Association ◽  
Gis Environment

Abstract. The Regional Topographic Geodatabase (DBTR) was officially defined in 2005 as the multi-scale (1:1,000 – 1:2,000 – 1:5,000 – 1:10,000) cartographic reference for urban and regional planning in Lombardy Region. The DBTR had been previously introduced at national level to take over traditional numerical topographic maps adopted for urban planning, with the aim to provide a base map to be implemented either at regional level (Regional Geoportal) and by local administrations. The DBTR is structured by following some national guidelines that define either the content and the topological structure, that makes simple its implementation in GIS environment. The construction of the entire DBTR has historically gone through different phases, with the consistent support of the regional subsidiary policy. But when the effects of the world economic crisis in 2008 became tangible in the budget of public administrations, the growth of the project faced an important break. In 2017 the administration of Lombardy Region has promoted and financed a new project finalized to the completion of the DBTR. A temporary association of mapping companies won the tender and completed the project by summer 2020, despite of the difficulties related to the COVID-19 pandemic. A team led by Politecnico di Milano was appointed for the quality assessment. The proposed paper would like to present this project and the operational solutions applied for the production of the new subsections of the DBTR, as well as its quality assessment/validation.

scholarly journals DESIGN AND ESTABLISHMENT OF QUALITY MODEL OF FUNDAMENTAL GEOGRAPHIC INFORMATION DATABASE

2018 ◽  
Vol XLII-3 ◽  
pp. 1249-1252 ◽  
Author(s):  
W. Ma ◽  
J. Zhang ◽  
Y. Zhao ◽  
P. Zhang ◽  
Y. Dang ◽  
...  
Keyword(s):  
Quality Control ◽  
Quality Evaluation ◽  
Development Stage ◽  
Geographic Information ◽  
Database Management System ◽  
Quality Model ◽  
Model Framework ◽  
Data Set ◽  
Database Construction ◽  
Information Database

In order to make the quality evaluation for the Fundamental Geographic Information Databases(FGIDB) more comprehensive, objective and accurate, this paper studies and establishes a quality model of FGIDB, which formed by the standardization of database construction and quality control, the conformity of data set quality and the functionality of database management system, and also designs the overall principles, contents and methods of the quality evaluation for FGIDB, providing the basis and reference for carry out quality control and quality evaluation for FGIDB. This paper designs the quality elements, evaluation items and properties of the Fundamental Geographic Information Database gradually based on the quality model framework. Connected organically, these quality elements and evaluation items constitute the quality model of the Fundamental Geographic Information Database. This model is the foundation for the quality demand stipulation and quality evaluation of the Fundamental Geographic Information Database, and is of great significance on the quality assurance in the design and development stage, the demand formulation in the testing evaluation stage, and the standard system construction for quality evaluation technology of the Fundamental Geographic Information Database.

scholarly journals CscGAN: Conditional Scale-Consistent Generation Network for Multi-Level Remote Sensing Image to Map Translation

2021 ◽  
Vol 13 (10) ◽  
pp. 1936
Author(s):  
Yuanyuan Liu ◽  
Wenbin Wang ◽  
Fang Fang ◽  
Lin Zhou ◽  
Chenxing Sun ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Feature Learning ◽  
Limited Capacity ◽  
Multi Scale ◽  
Multiple Datasets ◽  
Map Generation ◽  
Generation Network ◽  
Multi Level ◽  
Different Levels ◽  
Loss Level

Automatic remote sensing (RS) image to map translation is a crucial technology for intelligent tile map generation. Although existing methods based on a generative network (GAN) generated unannotated maps at a single level, they have limited capacity in handling multi-resolution map generation at different levels. To address the problem, we proposed a novel conditional scale-consistent generation network (CscGAN) to simultaneously generate multi-level tile maps from multi-scale RS images, using only a single and unified model. Specifically, the CscGAN first uses the level labels and map annotations as prior conditions to guide hierarchical feature learning with different scales. Then, a multi-scale discriminator and two multi-scale generators are introduced to describe both high-resolution and low-resolution representations, aiming to improve the similarity of generated maps and thus produce high-quality multi-level tile maps. Meanwhile, a level classifier is designed for further exploring the characteristics of tile maps at different levels. Moreover, the CscGAN is optimized by jointly multi-scale adversarial loss, level classification loss, and scale-consistent loss in an end-to-end manner. Extensive experiments on multiple datasets and study areas demonstrate that the CscGAN outperforms the state-of-the-art methods in multi-level map translation, with great robustness and efficiency.

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