scholarly journals AUTOMATIC EXTRACTION OF URBAN BUILT-UP AREA BASED ON OBJECT-ORIENTED METHOD AND REMOTE SENSING DATA

Author(s):  
L. Li ◽  
H. Zhou ◽  
Q. Wen ◽  
T. Chen ◽  
F. Guan ◽  
...  

Built-up area marks the use of city construction land in the different periods of the development, the accurate extraction is the key to the studies of the changes of urban expansion. This paper studies the technology of automatic extraction of urban built-up area based on object-oriented method and remote sensing data, and realizes the automatic extraction of the main built-up area of the city, which saves the manpower cost greatly. First, the extraction of construction land based on object-oriented method, the main technical steps include: (1) Multi-resolution segmentation; (2) Feature Construction and Selection; (3) Information Extraction of Construction Land Based on Rule Set, The characteristic parameters used in the rule set mainly include the mean of the red band (Mean R), Normalized Difference Vegetation Index (NDVI), Ratio of residential index (RRI), Blue band mean (Mean B), Through the combination of the above characteristic parameters, the construction site information can be extracted. Based on the degree of adaptability, distance and area of the object domain, the urban built-up area can be quickly and accurately defined from the construction land information without depending on other data and expert knowledge to achieve the automatic extraction of the urban built-up area. In this paper, Beijing city as an experimental area for the technical methods of the experiment, the results show that: the city built-up area to achieve automatic extraction, boundary accuracy of 2359.65 m to meet the requirements. The automatic extraction of urban built-up area has strong practicality and can be applied to the monitoring of the change of the main built-up area of city.

2013 ◽  
Vol 15 (2) ◽  
pp. 262 ◽  
Author(s):  
Mingming JIA ◽  
Dianwei LIU ◽  
Zongming WANG ◽  
Xuguang TANG ◽  
Zhangyu DONG

2021 ◽  
Vol 25 (6) ◽  
pp. 61-67
Author(s):  
I.V. Zen’kov ◽  
Trinh Le Hung ◽  
Yu.P. Yuronen ◽  
P.M. Kondrashov ◽  
A.A. Latyntsev ◽  
...  

A brief description of the industrial and logistics center operating in the city of Novorossiysk on the coast of the Tsemesskaya Bay in the Black Sea is presented. According to remote sensing data, the area of open pit mining of rock dumps dumped during the development of three marl deposits for use at four cement plants was determined. According to the results of satellite imagery and analytical calculations, downward trends in changes in the density of vegetation cover in territories with natural landscapes adjacent to the territory of industrial facilities located on the coast of the Tsemesskaya Bay were revealed.


Author(s):  
C. H. Hardy ◽  
A. L. Nel

The city of Johannesburg contains over 10 million trees and is often referred to as an urban forest. The intra-urban spatial variability of the levels of vegetation across Johannesburg’s residential regions has an influence on the urban heat island effect within the city. Residential areas with high levels of vegetation benefit from cooling due to evapo-transpirative processes and thus exhibit weaker heat island effects; while their impoverished counterparts are not so fortunate. The urban heat island effect describes a phenomenon where some urban areas exhibit temperatures that are warmer than that of surrounding areas. The factors influencing the urban heat island effect include the high density of people and buildings and low levels of vegetative cover within populated urban areas. This paper describes the remote sensing data sets and the processing techniques employed to study the heat island effect within Johannesburg. In particular we consider the use of multi-sensorial multi-temporal remote sensing data towards a predictive model, based on the analysis of influencing factors.


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