Review on RS technologies for seagrass mapping in tropical region
Seagrass ecosystems can be mapped using RS because this technique is versatile and accurate. The availability of seagrass information is very important for the sustainable management of seagrass ecosystems. The use of RS technology to map seagrass has become the focus of many researches worldwide by...
| Main Authors: | , , |
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| Format: | Article |
| Language: | English |
| Published: |
Penerbit Universiti Kebangsaan Malaysia
2022
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| Online Access: | http://journalarticle.ukm.my/19263/1/2.pdf |
| _version_ | 1796933033142517760 |
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| author | Wiwin Ambarwulan, Ratna Sari Dewi, Widiatmaka, |
| author_facet | Wiwin Ambarwulan, Ratna Sari Dewi, Widiatmaka, |
| author_sort | Wiwin Ambarwulan, |
| collection | UKM |
| description | Seagrass ecosystems can be mapped using RS because this technique is versatile and accurate. The availability of seagrass information is very important for the sustainable management of seagrass ecosystems. The use of RS technology to map seagrass has become the focus of many researches worldwide by using various types of platforms, sensors and various algorithms for satellite imagery processing. In literature, there have been many review papers related to seagrass, however, a comprehensive review on various aspects of seagrass is limited. The objective of this review paper was to fill the gap by highlighting the existing RS technology, seagrass biophysical property and image processing analysis. Review results indicated that RS technology is a powerful tool for accelerating seagrass mapping and for monitoring the condition of seagrass ecosystems at regional scale due to the availability of long-archived RS data and their free-access. In literature, the empirical approaches still dominated seagrass mapping methodology compared to the semi-analytic and analytic approaches. A clear conclusion from this review is that the development in sensor technology and data processing algorithm is still ongoing and has driven RS capabilities to map seagrass more rapidly, accurately and less expensive. Future research on seagrass mapping could be focused on a more automated classification by applying machine-learning to handle a large amount of data to improve accuracy and to discover robust methods for image pre-processing that is suitable for tropical shallow waters such as those in Indonesia. |
| first_indexed | 2024-03-06T04:40:58Z |
| format | Article |
| id | ukm.eprints-19263 |
| institution | Universiti Kebangsaan Malaysia |
| language | English |
| last_indexed | 2024-03-06T04:40:58Z |
| publishDate | 2022 |
| publisher | Penerbit Universiti Kebangsaan Malaysia |
| record_format | dspace |
| spelling | ukm.eprints-192632022-08-08T04:34:38Z http://journalarticle.ukm.my/19263/ Review on RS technologies for seagrass mapping in tropical region Wiwin Ambarwulan, Ratna Sari Dewi, Widiatmaka, Seagrass ecosystems can be mapped using RS because this technique is versatile and accurate. The availability of seagrass information is very important for the sustainable management of seagrass ecosystems. The use of RS technology to map seagrass has become the focus of many researches worldwide by using various types of platforms, sensors and various algorithms for satellite imagery processing. In literature, there have been many review papers related to seagrass, however, a comprehensive review on various aspects of seagrass is limited. The objective of this review paper was to fill the gap by highlighting the existing RS technology, seagrass biophysical property and image processing analysis. Review results indicated that RS technology is a powerful tool for accelerating seagrass mapping and for monitoring the condition of seagrass ecosystems at regional scale due to the availability of long-archived RS data and their free-access. In literature, the empirical approaches still dominated seagrass mapping methodology compared to the semi-analytic and analytic approaches. A clear conclusion from this review is that the development in sensor technology and data processing algorithm is still ongoing and has driven RS capabilities to map seagrass more rapidly, accurately and less expensive. Future research on seagrass mapping could be focused on a more automated classification by applying machine-learning to handle a large amount of data to improve accuracy and to discover robust methods for image pre-processing that is suitable for tropical shallow waters such as those in Indonesia. Penerbit Universiti Kebangsaan Malaysia 2022-04 Article PeerReviewed application/pdf en http://journalarticle.ukm.my/19263/1/2.pdf Wiwin Ambarwulan, and Ratna Sari Dewi, and Widiatmaka, (2022) Review on RS technologies for seagrass mapping in tropical region. Sains Malaysiana, 51 (4). pp. 959-976. ISSN 0126-6039 https://www.ukm.my/jsm/malay_journals/jilid51bil4_2022/KandunganJilid51Bil4_2022.html |
| spellingShingle | Wiwin Ambarwulan, Ratna Sari Dewi, Widiatmaka, Review on RS technologies for seagrass mapping in tropical region |
| title | Review on RS technologies for seagrass mapping in tropical region |
| title_full | Review on RS technologies for seagrass mapping in tropical region |
| title_fullStr | Review on RS technologies for seagrass mapping in tropical region |
| title_full_unstemmed | Review on RS technologies for seagrass mapping in tropical region |
| title_short | Review on RS technologies for seagrass mapping in tropical region |
| title_sort | review on rs technologies for seagrass mapping in tropical region |
| url | http://journalarticle.ukm.my/19263/1/2.pdf |
| work_keys_str_mv | AT wiwinambarwulan reviewonrstechnologiesforseagrassmappingintropicalregion AT ratnasaridewi reviewonrstechnologiesforseagrassmappingintropicalregion AT widiatmaka reviewonrstechnologiesforseagrassmappingintropicalregion |