scholarly journals ESTIMATION OF NATURAL GREEN IN URBAN AREAS USING REMOTE SENSING TECHNOLOGY : Annual change of forest and field in Kyoto city

2002 ◽  
Vol 67 (552) ◽  
pp. 77-84 ◽  
Author(s):  
Keigo KOIZUMI ◽  
Naoki TAKAGI
Keyword(s):  
Remote Sensing ◽  
Urban Areas ◽  
Annual Change ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Kyoto City

scholarly journals STUDY OF DUST POLLUTION DETECTING ABILITY IN URBAN AREAS BY REMOTE SENSING TECHNOLOGY TO SUPPORT AIR ENVIRONMENT OBSERVATION

2012 ◽  
Vol 15 (4) ◽  
pp. 33-47
Author(s):  
Van Thi Tran ◽  
Binh Thi Trinh ◽  
Bao Duong Xuan Ha
Keyword(s):  
Remote Sensing ◽  
Satellite Imagery ◽  
Urban Areas ◽  
Satellite Image ◽  
Regression Function ◽  
Statistical Correlation ◽  
Step Test ◽  
Residential Areas ◽  
Remote Sensing Technology ◽  
Sensing Technology

This paper presents the approach towards application of remote sensing technology to monitor the air environemnt. Specific inital research is findings PM10 dust from SPOT 5 satellite image. The calculation based on reflectance value on remote sensing satellite images. The main method is to calculate statistical correlation regression between the PM10 concentration from ground station observations and reflectance value on each image band and the main components of satellite imagery in 2003 to find the best regression function, applied then to images 2011 where its radiance value was relatively normalized under atmospheric, geometric, environmental conditions of image 2003. The results showed the best correlation in nonlinear regression case. Spatial distribution of PM10 concentrations > 200μg/m3 found on most main roads, industrial parks and residential areas. This study is a first step test, but the results have demonstrated that satellite imagery can be used as a useful, effective tool, to monitor air environment in cities.

Time Series Analysis of Land Cover Using Remote Sensing Technology

2020 ◽  
Vol 17 (2) ◽  
pp. 902-910
Author(s):  
Ahmad Taufiq Hosni ◽  
Suharto Teriman ◽  
Nor Aizam Adnan ◽  
Muhamad Asri Abdullah Kamar
Keyword(s):  
Remote Sensing ◽  
Land Cover ◽  
Urban Areas ◽  
Management Plan ◽  
Urban Environments ◽  
Lulc Changes ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Development Area ◽  
Landsat Satellite

The observation of land use/land cover (LULC) is essential as it allows humans to investigate the alteration of land which occurs over a period of time. This is to allow mankind to have a proper management of the earth resources and well planned development. One way to observe LULC is by using remote sensing technology since it provides continuous data monitoring of the earth’s surface. This study is carried out at Bandar Meru Raya, Ipoh, Perak and aimed to quantify the LULC changes, especially in urban areas which occurred within two decades from 1995 to 2005 and from 2005 to 2015. Maximum likelihood supervised classification was performed on three Landsat satellite imageries using ERDAS Imagine 2014 software. The images were classified into 4 general LULC categories namely forest, development area, green area, and water bodies. The results indicated that a considerable amount of forested area was decreasing by 183.12 hectares within the last 20 years while development area gained a total of 157.12 hectares. This LULC changes showed a serious loss of trees and this sort of change tends to affect the nature’s ecosystem. Therefore, by quantifying the loss of forest area will enable authorities to oversee and plan a better management of trees for future in urban environments. Such management plan is necessary in order to maintain the importance of trees towards nature and community.

Hyperspectral Remote Sensing Technology (HRST) program

1997 ◽  
Author(s):  
Tom Wilson ◽  
Rebecca Baugh ◽  
Ron Contillo ◽  
Tom Wilson ◽  
Rebecca Baugh ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Hyperspectral Remote Sensing ◽  
Remote Sensing Technology ◽  
Sensing Technology

Application of remote sensing technology to the relation of submarine pipelines and coastal morphology

1995 ◽  
Vol 32 (2) ◽  
pp. 77-83
Author(s):  
Y. Yüksel ◽  
D. Maktav ◽  
S. Kapdasli
Keyword(s):  
Remote Sensing ◽  
Sediment Transport ◽  
Surf Zone ◽  
Hydrodynamic Forces ◽  
Construction Site ◽  
Coastal Morphology ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Sea Bed

Submarine pipelines must be designed to resist wave and current induced hydrodynamic forces especially in and near the surf zone. They are buried as protection against forces in the surf zone, however this procedure is not always feasible particularly on a movable sea bed. For this reason the characteristics of the sediment transport on the construction site of beaches should be investigated. In this investigation, the application of the remote sensing method is introduced in order to determine and observe the coastal morphology, so that submarine pipelines may be protected against undesirable seabed movement.

Based on IDRISI Remote Sensing Images Land-Use Types of Supervised Classification Techniques

2013 ◽  
Vol 415 ◽  
pp. 305-308
Author(s):  
Kun Zhang ◽  
Hai Feng Wang ◽  
Zhuang Li
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Classification Techniques ◽  
Analysis And Evaluation ◽  
Remote Sensing Classification ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Remote Sensing Image Classification ◽  
Land Use Types ◽  
Area Distribution

With remote sensing technology and computer technology, remote sensing classification technology has been rapid progress. In the traditional classification of remote sensing technology, based on the combination of today's technology in the field of remote sensing image classification, some new developments and applications for land cover classification techniques to make more comprehensive elaboration. Using the minimum distance classifier extracts of the study area land use types. Ultimately extracted land use study area distribution image and make its analysis and evaluation.

Monitoring water quality using proximal remote sensing technology

2021 ◽  
pp. 149805
Author(s):  
Xiao Sun ◽  
Yunlin Zhang ◽  
Kun Shi ◽  
Yibo Zhang ◽  
Na Li ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Quality ◽  
Remote Sensing Technology ◽  
Sensing Technology
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