BATHYMETRIC EXTRACTION USING PLANETSCOPE IMAGERY (CASE STUDY: KEMUJAN ISLAND, CENTRAL JAVA)

Asih Sekar Sesama, Kuncoro Teguh Setiawan, Atriyon Julzarika

Abstract

Bathymetry refers to the depth of the seabed relative to the lowest water level. Depth information is essential for various studies of marine resource activities, for managing port facilities and facilities, supporting dredging operations, and predicting the flow of sediment from rivers into the sea. Bathymetric mapping using remote sensing offers a more flexible, efficient,and cost-effective method and covers a largearea. This study aims to determine the ability of Planet Scope imagery to estimate and map bathymetry and to as certain its accuracy using the Stumpf algorithm on the in-situ depth data. PlanetScope level 3B satellite imagery and tide-corrected survey dataare employed; satellite images are useful in high-precision bathymetry extraction.The bathymetric extraction method used the Stumpf algorithm. The research location was Kemujan Island, Karimunjawa Islands, Central Java. The selection of this region wasbased on its water characteristics, which have a reasonably high variation in depth. Based on the results of the data processing, it was found that the PlanetScope image data were able to estimate depths of up to 20 m. In the bathymetric results, the R2 accuracy value was 0.6952, the average RMSE value was 2.85 m,and the overall accuracy rate was 71.68%.

Keywords

marine resources activity, Stumpf algorithm, Karimun Jawa Island, remote sensing, water characteristics

Full Text:

PDF

References

Banko G., (1998), A Review of Assessing the Accuracy of Classifications of Remotely Sensed Data and of Methods Including Remote Sensing Data in Forest Inventory. INTERIM REPORT IR-98-081

Gabr B., Ahmed M. and Marmoush Y., (2020), PlanetScope and Landsat 8 Imageries for Bathymetry Mapping. Journal of Marine Science and Engineering 8, 143

Gao BC., Montes M.J., Li RR., Dierssen H.M. and Davis CO. (2007) An Atmospheric Correction Algorithm for Remote Sensing of Bright Coastal Waters Using MODIS Land and Ocean Channels in the Solar Spectral Region. IEEE Trans. Geosci. Remote Sens 45: 1835–1843

Jensen JR., (2007) Remote Sensing of the Environment: An Earth Resource Perspective, 2nd ed. Prentice Hall: Upper Saddle River, NJ, USA

Muzirafuti A., Barecca G., Crupi A., Faina G., Paltrinieri D., Lanza S. and Randazzo G., (2020), The Contribution of Multispectral Satellite Image to Shallow Water Bathymetry Mapping on the Coast of Misano Adriatico, Italy. Journal of Marine Science and Engineering 8, 126

Nurkhayati R, (2013), Pemetaan Batimetri Perairan Dangkal Menggunakan Citra Quickbird di Perairan Taman Nasional Karimunjawa, Kabupaten Jepara, Jawa Tengah (Bathymetry Mapping of Shallow Waters Using Quickbird Images in the Waters of Karimunjawa National Park, Jepara Regency, Central Java). Jurnal Bumi Indonesia 2(2)

Pe’eri S., Parrish C., Azuike C.., Alexander L., and Armstrong A., (2014), Satellite Remote Sensing as Reconnaissance Tool for Assessing Nautical Chart Adequacy and Completeness. Marine Geodesy 37: 293–314.

Pike S., Traganos D., Poursanidis D., et al, (2019), Leveraging Commercial High-Resolution Multispectral Satellite and Multibeam Sonar Data to Estimate Bathymetry: The Case Study of the Caribbean Sea. Remote Sens 11, 1830

Planet Lab Inc, (2020), Planet Imagery Product Spesification, Available via GOOGLE.https://assets.planet.com/docs/combined-imagery-product-spec-april-2019.pdf. Accessed 20 July 2020

Poursanidis D., Traganos D., Chrysoulakis N. and Reinartz P., (2019). Cubesats Allow High Spatiotemporal Estimates of Satellite-Derived Bathymetry. Remote Sens. 11, 1299

Said NM., Mahmud M.R and Hasan R.C., (2017), Satellite-Derived Bathymetry: Accuracy Assessment on Depths Derivation Algorithm for Shallow Water Area. The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-4/W5: 159-164

Siregar V.P and Selamat M.B., (2008), Interpolator Dalam Pembuatan Kontur Peta Batimetri (Interpolator in Bathymetric Map Contouring). E-Jurnal Ilmu dan Teknologi Kelautan Tropis 1(1): 39-47

Stumpf R. P., Holderied K. and Sinclair M., (2003), Determination of Water Depth with High-Resolution Satellite Imagery over Variable Bottom Types. Limnology Oceanography 48: 547-556

Sun F.D., Sun W.X., Chen J., Gong P. (2012) Comparison and improvement of methods for identifying waterbodies in remotely sensed imagery. Int. J. Remote Sens 33: 6854–6875

Suprayogi I., Trimaijon and Mahyudin, (2013), Model Prediksi Liku Kalibrasi Menggunakan Pendekatan Jaringan Saraf Tiruan (JST) (Studi Kasus: Sub AS Siak Hulu) (Calibration Twist Prediction Model Using Artificial Neural Network (ANN) Approach (Case Study: Sub AS Siak Hulu))

Waskito R and Wicaksono P., (2019) Aplikasi Citra WorldView-2 untuk Pemetaan Batimetri di Pulau Kemujan Taman Nasional Karimunjawa. (WorldView-2 Image Application for Bathymetry Mapping in Kemujan Island, Karimunjawa National Park) Jurnal Penginderaan Jauh Indonesia 1(1): 32-38

Refbacks

  • There are currently no refbacks.