Novel Approach to Estimate Diffuse Attenuation Coefficients for QuickBird Satellite Images: A Case Study at Kish Island, the Persian Gulf

Diffuse attenuation coefficient (k d) is a critical parameter for benthic habitat mapping using remotely sensed data. This research attempted to develop a new approach to estimate k d in blue and green bands of QuickBird satellite image based on the integration of Lyzenga’s method and updated NASA-k...

Ausführliche Beschreibung

Gespeichert in:
Bibliographische Detailangaben
Veröffentlicht in:Journal of the Indian Society of Remote Sensing 2013-12, Vol.41 (4), p.797-806
Hauptverfasser: Kabiri, Keivan, Pradhan, Biswajeet, Shafri, Helmi Zulhaidi Mohd, Mansor, Shattri Bin, Samimi-Namin, Kaveh
Format: Artikel
Sprache:eng
Schlagworte:
Online-Zugang:Volltext
Tags: Tag hinzufügen
Keine Tags, Fügen Sie den ersten Tag hinzu!
Beschreibung
Zusammenfassung:Diffuse attenuation coefficient (k d) is a critical parameter for benthic habitat mapping using remotely sensed data. This research attempted to develop a new approach to estimate k d in blue and green bands of QuickBird satellite image based on the integration of Lyzenga’s method and updated NASA-k d ⁴⁹⁰ algorithm. To do this, the Lyzenga’s method was utilized to determine the ratio of k d in different bands of QuickBird satellite image. Additionally, NASA-k d ⁴⁹⁰ algorithm was applied to determine k d ⁴⁹⁰ by using remotely sensed reflectance values of blue (R ᵣₛ ᴮˡᵘᵉ) and green (R ᵣₛ ᴳʳᵉᵉⁿ) bands in each pixel of QuickBird satellite image. Since the aforementioned algorithm has been developed for other types of sensors, an approach using weighted mean value of parameters for SeaWiFS, MERIS, VIIRS, and OCTS sensors were employed to estimate parameter values for QuickBird image. After determining the k d ⁴⁹⁰ values as k d for blue band, the k d values for green and red bands were subsequently obtained by using Lyzenga’s method. Then, Mumby and Edwards’ method was employed as evidence to evaluate the accuracy of the results achieved from newly developed approach. Eventually, the maximum likelihood classifier was implemented during pre and post correction steps to examine the capability of the proposed approach. The final results proved to be consistent in the areas deeper than 2 m between estimated k d values using the proposed approach and the results obtained from Mumby and Edwards’ method. On the other hand, the values estimated for extremely shallow areas seem to be overestimated. Furthermore, results demonstrated an increment of ~16 % in the overall accuracy of the classification.
ISSN:0255-660X
0974-3006
DOI:10.1007/s12524-013-0293-0