scholarly journals A Merging Approach for Urban Boundary Correction Acquired By Remote Sensing Images

2014 ◽  
Vol XL-8 ◽  
pp. 1011-1015
Author(s):  
P. L. Zhang ◽  
W. Z. Shi ◽  
X. Y. Wu
Keyword(s):  
Remote Sensing ◽  
Urban Area ◽  
Social Economic ◽  
Demographic Data ◽  
Population Data ◽  
Scientific Basis ◽  
Spatial Form ◽  
Remote Sensing Images ◽  
Traditional Methods ◽  
Road Data

Since reform and opening up to outside world, ever-growing economy and development of urbanization of China have caused expansion of the urban land scale. It’s necessary to grasp the information about urban spatial form change, expansion situation and expanding regularity, in order to provide the scientific basis for urban management and planning. The traditional methods, like land supply cumulative method and remote sensing, to get the urban area, existed some defects. Their results always doesn’t accord with the reality, and can’t reflects the actual size of the urban area. Therefore, we propose a new method, making the best use of remote sensing, the population data, road data and other social economic statistic data. Because urban boundary not only expresses a geographical concept, also a social economic systems.It’s inaccurate to describe urban area with only geographic areas. We firstly use remote sensing images, demographic data, road data and other data to produce urban boundary respectively. Then we choose the weight value for each boundary, and in terms of a certain model the ultimate boundary can be obtained by a series of calculations of previous boundaries. To verify the validity of this method, we design a set of experiments and obtained the preliminary results. The results have shown that this method can extract the urban area well and conforms with both the broad and narrow sense. Compared with the traditional methods, it’s more real-time, objective and ornamental.

scholarly journals Understanding Urban Growth in Beijing-Tianjin-Hebei Region over the Past 100 Years Using Old Maps and Landsat Data

2021 ◽  
Vol 13 (16) ◽  
pp. 3264 ◽  
Author(s):  
Shuang Li ◽  
Zhongqiu Sun ◽  
Yafei Wang ◽  
Yuxia Wang
Keyword(s):  
Remote Sensing ◽  
Urban Area ◽  
Spatial Data ◽  
Urban Expansion ◽  
Remote Sensing Images ◽  
The Past ◽  
Old Maps ◽  
The World ◽  
The City

Studying urban expansion from a longer-term perspective is of great significance to obtain an in-depth understanding of the process of urbanization. Remote sensing data are mostly selected to investigate the long-term expansion of cities. In this study, we selected the world-class urban agglomeration of Beijing-Tianjin-Hebei (BTH) as the study area, and then discussed how to make full use of multi-source, multi-category, and multi-temporal spatial data (old maps and remote sensing images) to study long-term urbanization. Through this study, we addressed three questions: (1) How much has the urban area in BTH expanded in the past 100 years? (2) How did the urban area expand in the past century? (3) What factors or important historical events have changed the development of cities with different functions? By comprehensively using urban spatial data, such as old maps and remote sensing images, geo-referencing them, and extracting built-up area information, a long-term series of urban built-up areas in the BTH region can be obtained. Results show the following: (1) There was clear evidence of dramatic urban expansion in this area, and the total built-up area had increased by 55.585 times, from 126.181 km2 to 7013.832 km2. (2) Continuous outward expansion has always been the main trend, while the compactness of the built-up land within the city is constantly decreasing and the complexity of the city boundary is increasing. (3) Cities in BTH were mostly formed through the construction of city walls during the Ming and Qing dynasties, and the expansion process was mostly highly related to important political events, traffic development, and other factors. In summary, the BTH area, similarly to China and most regions of the world, has experienced rapid urbanization and the history of such ancient cities should be further preserved with the combined use of old maps.

Accurate Urban Area Detection in Remote Sensing Images

2015 ◽  
Vol 12 (9) ◽  
pp. 1948-1952 ◽  
Author(s):  
Hao Shi ◽  
Liang Chen ◽  
Fu-kun Bi ◽  
He Chen ◽  
Ying Yu
Keyword(s):  
Remote Sensing ◽  
Urban Area ◽  
Remote Sensing Images

Method of Remote Sensing Image Fine Classification Based on Geometric Features and SVM

2012 ◽  
Vol 500 ◽  
pp. 562-568 ◽  
Author(s):  
Xiao Dong Zhou ◽  
Chun Cheng Yang ◽  
Ni Na Meng
Keyword(s):  
Remote Sensing ◽  
Foreign Bodies ◽  
Deductive Reasoning ◽  
Morphological Characteristics ◽  
Remote Sensing Image ◽  
Svm Classifier ◽  
Geometric Features ◽  
Remote Sensing Images ◽  
Traditional Methods ◽  
Fine Classification

In order to overcome the phenomenon of foreign bodies in the same spectrum in remote sensing images, as needs of land-use surveys, traditional methods often can’t get good results. In this paper, an efficient method for dividing the classifying results of traditional methods into further items is proposed and studied. Our approach to remote sensing image fine classification is based on both geometric features and SVM. By making full use of geometric features in the structure of property characteristics, we produce rules of the morphological characteristics and distribution. With deductive reasoning, we further classify the classifying results of SVM classifier. Tests showed that the method can be better broken down into the waters of rivers, lakes, reservoirs and ponds.

scholarly journals CENSUS POPULATION DATA AND REMOTE SENSING IMAGES IN THE STUDY OF THE EVOLUTION OF THE SETTLEMENT OF CANABRAVA AND SURROUNDING AREAS, SALVADOR, BAHIA, BRAZIL, 1991 - 2010

2018 ◽  
Vol 6 (1) ◽  
Author(s):  
Eudoxio Antonio Batista Junior ◽  
Patrícia Lustosa Brito ◽  
Anderson Dias de Freitas
Keyword(s):  
Remote Sensing ◽  
Urban Sprawl ◽  
Census Data ◽  
Urban Expansion ◽  
Urban Infrastructure ◽  
Population Data ◽  
Remote Sensing Images ◽  
Census Tracts ◽  
Urban Services ◽  
Surrounding Areas

Urban sprawl in large Brazilian cities has intensified in recent decades, causing increased demand for urban infrastructure, urban services, and new areas for construction. The central goal of this article is to analyze the characteristics of urban expansion in the Canabrava community and its surroundings, in Salvador, Bahia, Brazil, using census data from 1991 and 2010 produced by the Brazilian Institute of Geography and Statistics (IBGE). One problem addressed was that the limits of the census tracts differed between the analyzed periods.  

scholarly journals A conceptual vulnerability and risk framework as outline to identify capabilities of remote sensing

2008 ◽  
Vol 8 (3) ◽  
pp. 409-420 ◽  
Author(s):  
H. Taubenböck ◽  
J. Post ◽  
A. Roth ◽  
K. Zosseder ◽  
G. Strunz ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Spatial Distribution ◽  
Urban Area ◽  
Natural Hazards ◽  
Social Economic ◽  
Population Distribution ◽  
Inductive Method ◽  
Small Scale ◽  
Conceptual Approach ◽  
Risk Framework

Abstract. This study aims at creating a holistic conceptual approach systematizing the interrelation of (natural) hazards, vulnerability and risk. A general hierarchical risk meta-framework presents potentially affected components of a given system, such as its physical, demographic, social, economic, political or ecological spheres, depending on the particular hazard. Based on this general meta-framework, measurable indicators are specified for the system "urban area" as an example. This framework is used as an outline to identify the capabilities of remote sensing to contribute to the assessment of risk. Various indicators contributing to the outline utilizing diverse remote sensing data and methods are presented. Examples such as built-up density, main infrastructure or population distribution identify the capabilities of remote sensing within the holistic perspective of the framework. It is shown how indexing enables a multilayer analysis of the complex and small-scale urban landscape to take different types of spatial indicators into account to simulate concurrence. The result is an assessment of the spatial distribution of risks within an urban area in the case of an earthquake and its secondary threats, using an inductive method. The results show the principal capabilities of remote sensing to contribute to the identification of physical and demographic aspects of vulnerability, as well as provide indicators for the spatial distribution of natural hazards. Aspects of social, economic or political indicators represent limitations of remote sensing for an assessment complying with the holistic risk framework.

Sign in / Sign up

Export Citation Format

Share Document