Application of Remote Sensing Technology, GIS and AHP-TOPSIS Model to Quantify Urban Landscape Vulnerability to Land Use Transformation

2017 ◽  
pp. 31-40 ◽  
Author(s):  
Alok Bhushan Mukherjee ◽  
Akhouri Pramod Krishna ◽  
Nilanchal Patel
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Urban Landscape ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Land Use Transformation ◽  
Topsis Model

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.

scholarly journals Assessment of Land Use and Vegetative Cover in Kano Metropolis (from 1975-2015) Employing GIS and Remote Sensing Technology

2020 ◽  
Vol 27 (2) ◽  
pp. 1-7
Author(s):  
M. Haruna ◽  
M.K. Ibrahim ◽  
U.M. Shaibu
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Agricultural Land ◽  
Landsat 8 ◽  
Vegetative Cover ◽  
Gis And Remote Sensing ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Agricultural Planning ◽  
Bare Land

This study applied GIS and remote sensing technology to assess agricultural land use and vegetative cover in Kano Metropolis. It specifically examined the intensity of land use for agricultural and non agricultural purpose from 1975 – 2015. Images (1975, 1995 and 2015), landsat MSS/TM, landsat 8, scene of path 188 and 052 were downloaded for the study. Bonds for these imported scenes were processed using ENVI 5.0 version. The result indicated five classified features-settlement, farmland, water body, vegetation and bare land. The finding revealed an increase in settlement, vegetation and bare land between 1995 and 2015, however, farmland decreased in 2015. Indicatively, higher percentage of land use for non agricultural purposes was observed in recent time. Conclusively, there is need to accord surveying the rightful place and priority in agricultural planning and development if Nigeria is to be self food sufficient. Keywords: Geographic Information System, Agriculture, Remote sensing, Land use, Land cover

The Quantitative Evaluation of Ecological Assets in Sanjiang Plain Based on Remote Sensing Technology

2013 ◽  
Vol 316-317 ◽  
pp. 245-249
Author(s):  
Fan Ying Meng ◽  
Zheng Hong Miao
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Quantitative Measurement ◽  
Sanjiang Plain ◽  
Land Use Type ◽  
Remote Sensing Technology ◽  
Sensing Technology ◽  
Land Use Types ◽  
Landsat 7 ◽  
Ecological Assets

on the basis of the measurement of ecological parameters by using remote sensing technology, combined with ecological method and Landsat–7 ETM +, we made a quantitative measurement of ecological assets of Sanjiang Plain in 2010, got the spatial distribution of ecological assets. The results show that: the value of ecological assets in Sanjiang Plain was 2.35 × 1012 yuan. The value was generally higher in the southern and lower in the northern parts of the study area. Baoqing has the highest sum value and Youyi has the lowest value than other areas. Forestlands have higher value of ecological assets than other land use types. Land use type may be the mainly reason for the spatial difference of ecological assets in Sanjiang Plain.

scholarly journals Perbandingan Quadratic Discriminant Analysis dan Support Vector Machine untuk Klasifikasi Tutupan Lahan di DKI Jakarta

2020 ◽  
Vol 9 (1) ◽  
pp. 12-20
Author(s):  
Kamaluddin Junianto Dimas ◽  
Rahma Anisa ◽  
Itasia Dina Sulvianti
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Support Vector Machine ◽  
Discriminant Analysis ◽  
Land Cover ◽  
Training Data ◽  
Support Vector ◽  
Quadratic Discriminant Analysis ◽  
Remote Sensing Technology ◽  
Sensing Technology

DKI Jakarta is a center of government as well as economy and business of Indonesia, thus development projects in Jakarta continue every year. Therefore, monitoring for land use has to be improved in accordance to DKI Jakarta Spatial Planning. The attempt needs to be supported by continuous data availability regarding land cover condition in Jakarta. The aforementioned data collecting process become easier due to remote sensing technology development. Remote sensing technology can be utilized for analyzing the size of land use area by using classification analysis. It has been found that the level of accuracy depends on the type of classification method and number of training data. This research evaluated the level of overall accuracy, sensitivity, and specificity of Quadratic Discriminant Analysis (QDA) and Support Vector Machine (SVM) along with number of data training used in classifying Jakarta land cover in 2017. The results showed that in both methods, the variance of all the aforementioned criteria were getting smaller along with the increasing number of training data. QDA and SVM had similar performance based on overall accuracy and specificity. However, SVM was better than QDA on sensitivity.

Sign in / Sign up

Export Citation Format

Share Document