Authors |
Beh, BC; Tan, KC; Jafri, MZM; Lim, HS |
Editors |
Neale, CMU; Maltese, A |
[=Group Author] |
SPIE |
Author Full Name |
Beh, Boon Chun; Tan, Kok Chooi; Jafri, Mohd. Zubir Mat; Lim, Hwee San |
Title |
Comparison of Different Discriminant Functions for Mangrove Species Analysis in Matang Mangrove Forest Reserve (MMFR), Perak Based on Statistical Approach |
Source |
REMOTE SENSING FOR AGRICULTURE, ECOSYSTEMS, AND HYDROLOGY XIX |
Series |
Proceedings of SPIE |
Language |
English |
Document Type |
Proceedings Paper |
Conference Title |
Conference on Remote Sensing for Agriculture, Ecosystems, and Hydrology |
Conference Date |
SEP 12-15, 2017 |
Conference Location |
Warsaw, POLAND |
Conference Sponsors |
SPIE |
Author Keywords |
Mangroves; discriminant; accuracy; Matang Mangrove Forest Reserve (MMFR) |
Keywords Plus |
HYPERSPECTRAL DATA; RIVER |
Abstract |
Mangroves are known as salt-tolerant evergreen forests, whereas its create land-ocean interface ecosystems. Besides, mangroves bring direct and indirect benefits to human activities and play a major role as significant habitat for sustaining biodiversity. However, mangrove ecosystem study based on the mangrove species are very crucial to get a better understanding of their characteristics and ways to separate among them. In this paper, discriminant functions obtained using statistical approach were used to generate the score range for six mangrove species (Rhizophora apiculata, Acrostichum aurem, Acrostichum speciosum, Acanthus ilicifolius, Ceriops tagal and Sonneratia ovata) in Matang Mangrove Forest Reserve (MMFR), Perak. With the computation of score range for each species, the fraction of the species can be determined using the proposed algorithm. The results indicate that by using 11 discriminant functions out of 16 are more effective to separate the mangrove species as the higher accuracy was obtained. Overall, the determination of leaf sample's species is chosen base on the highest fraction measured among the six mangrove species. The obtained accuracy for mangrove species using statistical approach is low since it is impossible to successfully separate all the mangrove species in leaf level using their inherent reflectance properties. However, the obtained accuracy results are satisfactory and able to discriminate the examined mangrove species at species scale. |
Author Address |
[Beh, Boon Chun] INTI Int Coll Penang, George Town 11900, Malaysia; [Tan, Kok Chooi; Jafri, Mohd. Zubir Mat; Lim, Hwee San] Univ Sains Malaysia, Sch Phys, George Town 11800, Malaysia |
Reprint Address |
Tan, KC (corresponding author), Univ Sains Malaysia, Sch Phys, George Town 11800, Malaysia. |
E-mail Address |
kctan@usm.my |
ResearcherID Number |
San Lim, Hwee/F-6580-2010 |
ORCID Number |
San Lim, Hwee/0000-0002-4835-8015 |
Funding Agency and Grant Number |
Universiti Sains MalaysiaUniversiti Sains Malaysia [304/PFIZIK/6313260] |
Funding Text |
Authors gratefully acknowledge the financial support from the Universiti Sains Malaysia short-term grant (grant no: 304/PFIZIK/6313260). Authors would like to thanks to Forestry of Perak, Malaysia for giving us the permission to collect our samples data in Matang Mangrove Forest Reserve. Besides, our sincere thanks go to the technical staffs, Mr. Yacob and Mr. Syah who greatly contribute and help in this project. Thanks are also extended to USM for support and encouragement. |
Publisher |
SPIE-INT SOC OPTICAL ENGINEERING |
Publisher City |
BELLINGHAM |
Publisher Address |
1000 20TH ST, PO BOX 10, BELLINGHAM, WA 98227-0010 USA |
ISSN |
0277-786X |
ISBN |
978-1-5106-1307-2; 978-1-5106-1306-5 |
29-Character Source Abbreviation |
PROC SPIE |
Year Published |
2017 |
Volume |
10421 |
Article Number |
104211U |
Digital Object Identifier (DOI) |
10.1117/12.2277821 |
Page Count |
10 |
Web of Science Category |
Remote Sensing |
Subject Category |
Remote Sensing |
Document Delivery Number |
BJ1BR |
Unique Article Identifier |
WOS:000417373000044
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