Monitoring Change Detection of Vegetation Vulnerability Using Hotspots Analysis

Basheer Jasim; Oday Z. Jasim; Amjed N. AL-Hameedawi

doi:10.31436/iiumej.v25i2.3030

Authors

Basheer Jasim Technical Institute of Babylon, Al-Furat Al-Awsat Technical University, Iraq https://orcid.org/0000-0001-6768-1451
Oday Z. Jasim Civil Engineering Department https://orcid.org/0000-0003-4020-2953
Amjed N. AL-Hameedawi University of Technology - Iraq

DOI:

https://doi.org/10.31436/iiumej.v25i2.3030

Keywords:

Vegetation vulnerability, NDVI, Vegetation Cover, Change detection, Hotspot analysis

Abstract

Because of the ever-shifting nature of the weather conditions, which are made even more difficult by the dynamic relationship between the environment and the vegetation, one of the most important aspects is the vegetation. Landsat satellite imagery, TM sensor for 2002 and 2012, and OLI-TIRS sensor for 2022 were used for vegetation vulnerability. The Normalized Difference Vegetation Index (NDVI) method and hotspots analysis method were used for image classification, and the land cover map was obtained in three different years. The results of the analysis have shown that during 20 years, the extremely vulnerable zone has increased by 0.53%, the very vulnerable zone by 12.04%, and the moderately vulnerable zone has increased by 2.27% in terms of total area, also decreasing the non-significant zone by 5.74%, and the moderately safe zone decreased by 5.42%. The very safe zone decreased during this period by 2.94%. The extreme safe zone decreased by 0.73% in terms of total. Based on the assessment and validation of zone classification data, the overall accuracy value shows that the vegetation vulnerability accuracy for 2022 was equal to 90%. Also, the kappa coefficient for the classification vegetation vulnerability map was equal to 0.88. The research using Landsat data concluded that there had been a reduction in the amount of land covered by thick vegetation, which resulted in widespread drought conditions in some portions of the study region (Babylon Governorate). This research has shown that using satellite images and GIS spatial analysis is very effective in identifying and evaluating the trend of vegetation vulnerability in the Babylon Governorate. These data and techniques can be used for various analytical purposes.

ABSTRAK: Faktor perubahan cuaca yang mendadak, di mana hubungan dinamik antara alam sekitar dan tanaman menjadi lebih sukar, merupakan satu aspek penting bagi tumbuh-tumbuhan. Imej satelit Landsat, penderia TM 2002 dan 2012, dan penderia OLI-TIRS 2022 digunakan untuk tumbuh-tumbuhan yang terdedah. Kaedah Indeks Perubahan Ternormal Tumbuhan (NDVI) dan kaedah analisis kawasan khas digunakan bagi tujuan pengelasan imej, dan peta kawasan tanah berkaitan diperoleh dalam tiga tahun berbeza. Dapatan analisis menunjukkan selama 20 tahun, zon paling teruk terjejas telah bertambah sebanyak 0.53%, zon terjejas sebanyak 12.04%, zon sederhana terjejas bertambah kepada 2.27% berdasarkan total kawasan, juga pengurangan zon tidak penting 5.74%, zon sederhana selamat berkurang sebanyak 5.42%. Zon selamat telah berkurang selama tempoh ini sebanyak 2.94%. Zon paling selamat berkurang sebanyak 0.73% berdasarkan jumlah keseluruhan. Nilai ketepatan keseluruhan menunjukkan ketepatan tumbuh-tumbuhan terdedah pada 2022 bersamaan 90%, iaitu berdasarkan data klasifikasi zon pada ujian dan validasi. Juga, pekali kappa bagi klasifikasi peta tumbuh-tumbuhan terdedah bersamaan 0.88. Kesimpulan terhadap kajian menggunakan data Landsat ini adalah terdapat pengurangan pada bilangan tanah yang ditutupi oleh tumbuh-tumbuhan tebal, di mana menyebabkan keadaan kemarau yang berleluasa di sebahagian kawasan yang dikaji (Babylon Governorate). Kajian ini menunjukkan dengan menggunakan imej satelit dan analisis ruang GIS, ianya sangat berkesan dalam mengenal pasti dan menganalisa perkembangan tumbuh-tumbuhan yang terdedah di Babylon Governorate. Data dan teknik ini boleh digunakan untuk pelbagai tujuan analisis.

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