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Optimizing bathymetric position index (BPI) calculation: An analysis of parameters and recommendations for the selection of their optimal values

The present research paper addresses a critical gap in existing literature concerning the absence of a standardized methodology for parameter selection in the computation of the Bathymetric Position Index (BPI) values. The BPI is a measure of where a georeferenced location, with a defined depth, is relative to the neighbouring seascape, and it plays a significant role in characterizing benthic terrain for modelling and classification. Arguably, the two most important parameters when calculating the BPI are the size and the shape of the neighbourhood of analysis. With regards to the radius parameter, which defines the size of the neighbourhood, the optimal radius value for calculating the BPI must be carefully chosen, considering both the size of the target morphology and the scale factor, which is equal to the radius in map units multiplied by the cell size. It is recommended that the optimal radius value should closely match the size of the target morphology. Tests were performed using an annular neighbourhood shape and they have revealed that the outer radius is the most influential factor in the BPI calculation. Further experimentations and comparisons between circular and annular shapes have indicated that the use of different shapes has no significant impact on the results. The study has found no substantial correlation between the BPI values and other examined terrain variables, such as depth, slope, and curvature. This lack of correlation may be attributed to the BPI values accounting for the specific neighbourhood size, while for the studied variables the default window size was used, which is a considerably smaller scale than the ones used in most BPI calculations. In conclusion, this research highlights the importance of parameter selection in BPI calculations and provides valuable insights into the optimal radius choice and the negligible impact of neighbourhood shape. The findings also shed light on the unique nature of BPI values and their relationship with other geospatial variables.

Ketersediaan
201551.136Perpustakaan BIG (Eksternal Harddisk)Tersedia
Informasi Detail
Judul Seri
Applied Computing and Geoscience - Open Access
No. Panggil
551.136
Penerbit
Amsterdam : Elsevier.,
Deskripsi Fisik
15 hlm PDF, 24.262 KB
Bahasa
Inggris
ISBN/ISSN
2590-1974
Klasifikasi
551.136
Tipe Isi
text
Tipe Media
-
Tipe Pembawa
-
Edisi
Vol.23, September 2024
Subjek
Annulus shape
Local neighbourhood parameters
Morphological variables influence
Bathymetric Position Index (BPI)
Optimal radius values
Geospatial analysis
Info Detail Spesifik
-
Pernyataan Tanggungjawab
Versi lain/terkait

Tidak tersedia versi lain

Lampiran Berkas
  • Optimizing bathymetric position index (BPI) calculation: An analysis of parameters and recommendations for the selection of their optimal values
    The present research paper addresses a critical gap in existing literature concerning the absence of a standardized methodology for parameter selection in the computation of the Bathymetric Position Index (BPI) values. The BPI is a measure of where a georeferenced location, with a defined depth, is relative to the neighbouring seascape, and it plays a significant role in characterizing benthic terrain for modelling and classification. Arguably, the two most important parameters when calculating the BPI are the size and the shape of the neighbourhood of analysis. With regards to the radius parameter, which defines the size of the neighbourhood, the optimal radius value for calculating the BPI must be carefully chosen, considering both the size of the target morphology and the scale factor, which is equal to the radius in map units multiplied by the cell size. It is recommended that the optimal radius value should closely match the size of the target morphology. Tests were performed using an annular neighbourhood shape and they have revealed that the outer radius is the most influential factor in the BPI calculation. Further experimentations and comparisons between circular and annular shapes have indicated that the use of different shapes has no significant impact on the results. The study has found no substantial correlation between the BPI values and other examined terrain variables, such as depth, slope, and curvature. This lack of correlation may be attributed to the BPI values accounting for the specific neighbourhood size, while for the studied variables the default window size was used, which is a considerably smaller scale than the ones used in most BPI calculations. In conclusion, this research highlights the importance of parameter selection in BPI calculations and provides valuable insights into the optimal radius choice and the negligible impact of neighbourhood shape. The findings also shed light on the unique nature of BPI values and their relationship with other geospatial variables.
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