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.

Clicks: 383
ID: 73983
2019
Article Quality & Performance Metrics
Overall Quality
Not rated
Combines reader engagement with the AI quality analysis. This article has not been analysed, so there is no overall score — reader engagement is measured and shown alongside.
AI Quality Assessment
Not analyzed
Readership in this journal
Steady

Ranked #22 of 221 articles by views in Environmental monitoring and assessment

Most read Least read

Bar heights use a square-root scale. Only the 120 most-read articles are drawn; the journal has 221 in total.

Mint this article as an NFT
Not yet minted

Create a permanent, verifiable on-chain record of this article on the Scimatic Network. The NFT is held in your Journament account, and you can withdraw it to your own wallet at any time.

5 SUSD one-off · no wallet required
Sign in to mint
Abstract
Land-use/land-cover change is the most vulnerable factor in any developing urban environment. Increased infrastructure and population density tend to alter the land features which in turn will have an impact on climate change and will increase the impervious layer. Study of trends in land-use/land-cover change is required for analyzing the possible ways of managing the natural system. In this study, the spatial and temporal changes of the urban and peri-urban landscape of the Chennai Metropolitan Area (CMA), Tamil Nadu, India, were analyzed using satellite images. Imageries from Landsat 5 (TM) and Landsat 8 (OLI/TIRS) sensors were taken for the years 1988, 1997, 2006, and 2017. Ensembles of remote sensing spectral indices (NDVI, MNDWI, NDBI, and NDBaI) were calculated for the land-use/land-cover classification. The confusion matrix was used for assessing the accuracy for the year 2017. The overall accuracy of the LULC classification obtained was 91.76% with the kappa coefficient of 0.84. The results show that during the period of February 1988 to February 2017, the agriculture/fallow land, barren/semi-barren, vegetation, and water bodies/wetlands have decreased by 53.62%, 1.45%, 58.99%, and 30.59%, respectively. This decrease has contributed to an increase of 173.83% in built-up area. About 26,881 ha of agriculture/fallow land, 10,482 ha of vegetation land, and 2454 ha of water bodies/wetlands were converted to built-up and other land-use over the period. This essentially meant that CMA has changed from predominantly an agricultural area (42.21%) in 1988 to built-up area (48.72%) in 2017.
Reference Key
m2019monitoringenvironmental Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors M, Mathan;M, Krishnaveni;
Journal Environmental monitoring and assessment
Year 2019
DOI
10.1007/s10661-019-7986-y
URL
Keywords
remote sensing gis cma land-use/land-cover spectral indices urban sprawl

Citations

No citations found. To add a citation, contact the admin at info@scimatic.org

Comments

No comments yet. Be the first to comment on this article.