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Journals / International Journal of Environment and Geoinformatics / 2016 / Cilt: 3 - Sayı: 2

Landsat Images Classification and Change Analysis of Land Cover/Use in Istanbul

İsmail BÜYÜKSALİH
Pages
56–65
Publication Date
2016-08-02
DOI
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AI Summary & Key Takeaways

AI Insight
⚡ TL;DR(Too Long; Didn't Read)

When the obtained classification results are evaluated as a result of, the 1987 Landsat image overall accuracy of 79 % and a kappa value of 0.76, the 2007 Landsat image overall accuracy of 83.50% and kappa value of 0.81.

📌 3 Key Takeaways

🎯
Objective & Hypothesis:This paper describes the methodology and results of classifications of Landsat TM data of the Istanbul for the years 1987 and 2007.
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Key Findings & Data:When the obtained classification results are evaluated as a result of, the 1987 Landsat image overall accuracy of 79 % and a kappa value of 0.76, the 2007 Landsat image overall accuracy of 83.50% and kappa value of 0.81.
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Conclusion & Impact:The classifications have provided an economical and accurate way to quantify, map and analyze changes over time in land cover.
🔬Design:Research Article
📍Scope:2007 Verileri
⚙️Variables:: Remote sensing · Land cover/Land use · GIS

Abstract

This paper describes the methodology and results of classifications of Landsat TM data of the Istanbul for the years 1987 and 2007. Nine different land cover/use categories have been used, named built-up area, cropland, barren ground, grassland, scrub/brush, water, ever green, deciduous, cloud and others uses. When the obtained classification results are evaluated as a result of, the 1987 Landsat image overall accuracy of 79 % and a kappa value of 0.76, the 2007 Landsat image overall accuracy of 83.50% and kappa value of 0.81. Thus, Istanbul's change analysis was revealed that the 20-year period. The classifications have provided an economical and accurate way to quantify, map and analyze changes over time in land cover.

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Cite This Article

BÜYÜKSALİH, İ. (2016). Landsat Images Classification and Change Analysis of Land Cover/Use in Istanbul. International Journal of Environment and Geoinformatics, Cilt: 3 - Sayı: 2, 56–65. https://ajindex.com/articles/672650

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