Literature DB >> 28251451

Analysis of land cover/use changes using Landsat 5 TM data and indices.

Paria Ettehadi Osgouei1, Sinasi Kaya2.   

Abstract

Urban expansion and unprecedented rural to urban transition, along with a huge population growth, are major driving forces altering land cover/use in metropolitan areas. Many of the land cover classes such as farmlands, wetlands, forests, and bare soils have been transformed during the past years into human settlements. Identification of the city growth trends and the impact of it on the vegetation cover of an area is essential for a better understanding of the sustainability of urban development processes, both planned and unplanned. Analyzing the causes and consequences of land use dynamics helps local government, urban planners, and managers for the betterment of future plans and minimizing the negative effects.This study determined temporal changes in vegetation cover and built-up area in Istanbul (Turkey) using the normalized difference vegetation index (NDVI), soil-adjusted vegetation index (SAVI), and built-up area index (BUAI). The temporal data were based on Landsat 5 Thematic Mapper (TM) images acquired in June of 1984, 2002, 2007, 2009, and 2011. The NDVI was applied to all the Landsat images, and the resulting NDVI images were overlaid to generate an NDVI layer stack image. The same procedure was repeated using the SAVI and BUAI images. The layer stack images revealed those areas that had changed in terms of the different indices over the years. To determine temporal change trends, the values of 150 randomly selected control points were extracted from the same locations in the NDVI, SAVI, and BUAI layer stack images. The results obtained from these control points showed that vegetation cover decreased considerably because of a remarkable increase in the built-up area.

Entities:  

Keywords:  BUAI; Land cover/use change; Landsat TM; NDVI; SAVI

Mesh:

Year:  2017        PMID: 28251451     DOI: 10.1007/s10661-017-5818-5

Source DB:  PubMed          Journal:  Environ Monit Assess        ISSN: 0167-6369            Impact factor:   2.513


  5 in total

1.  NDVI indicated characteristics of vegetation cover change in China's metropolises over the last three decades.

Authors:  Jinyu Sun; Xuhui Wang; Anping Chen; Yuecun Ma; Mengdi Cui; Shilong Piao
Journal:  Environ Monit Assess       Date:  2010-09-21       Impact factor: 2.513

2.  Investigation on changes in complex vegetation coverage using multi-temporal landsat data of Western Black Sea region--a case study.

Authors:  Huseyin Oguz Coban; Ayhan Koc; Mehmet Eker
Journal:  J Environ Biol       Date:  2010 Jan-Mar

3.  Using NDVI to assess vegetative land cover change in central Puget Sound.

Authors:  Dana F Morawitz; Tina M Blewett; Alex Cohen; Marina Alberti
Journal:  Environ Monit Assess       Date:  2006-03-24       Impact factor: 2.513

4.  Use of remotely sensed data for analysis of land-use change in a highly urbanized district of mega city, Istanbul.

Authors:  Nebiye Musaoglu; Melike Gurel; Necla Ulugtekin; Aysegul Tanik; Dursun Zafer Seker
Journal:  J Environ Sci Health A Tox Hazard Subst Environ Eng       Date:  2006       Impact factor: 2.269

5.  [Impact of urbanization on vegetation phenology in major cities in Yangtze River Delta region].

Authors:  Gui-feng Han; Jian-hua Xu; Xing-zhong Yuan
Journal:  Ying Yong Sheng Tai Xue Bao       Date:  2008-08
  5 in total
  3 in total

1.  The acquisition of impervious surface area from LANDSAT 8 satellite sensor data using urban indices: a comparative analysis.

Authors:  Aliihsan Sekertekin; Saygin Abdikan; Aycan Murat Marangoz
Journal:  Environ Monit Assess       Date:  2018-06-07       Impact factor: 2.513

2.  Monitoring and assessment of urban growth patterns using spatio-temporal built-up area analysis.

Authors:  Maher Milad Aburas; Yuek Ming Ho; Mohammad Firuz Ramli; Zulfa Hanan Ash'aari
Journal:  Environ Monit Assess       Date:  2018-02-20       Impact factor: 2.513

3.  Monitoring spatio-temporal dynamics of urban and peri-urban land transitions using ensemble of remote sensing spectral indices-a case study of Chennai Metropolitan Area, India.

Authors:  Mathan M; Krishnaveni M
Journal:  Environ Monit Assess       Date:  2019-12-07       Impact factor: 2.513

  3 in total

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