VARIABILITY OF SEA SURFACE TEMPERATURE (SST) AND CHLOROPHYLL-A (CHL-A) CONCENTRATIONS IN THE EASTERN INDIAN OCEAN DURING THE PERIOD 2002–2017

We analysed the variability of sea surface temperature (SST) and chlorophyll-a concentration (Chl-a) in the eastern Indian Ocean (EIO). We used monthly mean Chl-a and SST data with a 4-km spatial resolution derived from Level-3 Aqua Moderate-resolution Imaging Spectroradiometer (MODIS) distributed by the Asia-Pacific Data-Research Center (APDRC) for the period 2002–2017. Wavelet analysis shows the annual and interannual variability of SST and Chl-a concentration in the EIO. The annual variability of SST and Chl-a is influenced by monsoon systems. During a southeast monsoon, SST falls while Chl-a increases due to upwelling. The annual variability of SST and Chl-a is also influenced by the Indian Ocean Dipole (IOD). During positive phases of the IOD (2006, 2012 and 2015), there was more intense upwelling in the EIO caused by the negative anomaly of SST and the positive anomaly of Chl-a concentration

CHLOROPHYLL-A CONCENTRATIONS ESTIMATION FROM AQUA-MODIS AND VIIRS-NPP SATELLITE SENSORS IN SOUTH JAVA SEA WATERS

This study aimed to estimate the concentration of chlorophyll-a from satellite imagery of National Polar-Orbiting Operational Environmental Satellite System (NPOESS) Preparatory Project (NPP) in the south Java Sea waters and compare it to the concentrations of chlorophyll-a estimation result from the MODIS-Aqua satellite. NPP satellite had Visible/Infrared Imager Radiometer Suite (VIIRS) sensors which performance was same as Moderate Resolution Imaging Spectroradiometer (MODIS) sensor with a better spatial resolution. This study used daily satellite imagery of VIIRS-NPP for the period of September 2012 to August 2013. The algorithm that was used to estimate the concentration of chlorophyll-a was Ocean Color 3-band ratio (OC-3). The results showed that the spatial distribution pattern of chlorophyll-a concentration between VIIRS - NPP sensor and MODIS had the same pattern, but the estimation of chlorophyll-a concentration from the MODIS sensor was higher than VIIRS -NPP sensor. The concentration of chlorophyll-a showed that there were spatial and temporal variation in the south Java Sea waters. Generally, concentrations of chlorophyll-a was higher in East monsoon than West monsoon

KARAKTERISTIK DAN VARIABILITAS PARAMETER-PARAMETER OSEANOGRAFI LAUT JAWA HUBUNGANNYA DENGAN DISTRIBUSI HASIL TANGKAPAN IKAN

Penelitian kondisi oseanografi Laut Jawa telah dilakukan sejak 90 tahun yang lewat, sehingga data yang tersedia sudah cukup banyak. Studi ini bertujuan untuk menganalisis kembali data suhu dan salinitas yang diperoleh dari basis data world ocean data-2001 serta data deret waktu suhu permukaan laut dan konsentrasi klorofil-a hasil deteksi satelit dari basis data NASA. Analisis deret waktu dilakukan untuk melihat pengaruh musim dan iklim global terhadap lingkungan perairan dan sumber daya ikan di Laut Jawa. Hasil analisis menunjukkan bahwa variasi parameter-parameter oseanografi Laut Jawa dipengaruhi oleh angin muson dan iklim global ENSO dan variasi ini mempengaruhi distribusi ikan. This study based on remote sensing and in situ data, aimed to synthesize the effect of seasonal and interannual changes on the environment of Java Sea and its relationship with distribution of fish. Data of sea surface temperature, salinity, and chlorophyll-a data generated from Word Ocean Data- 2001 and NASA were used in the analysis. Time series analysis shows that variation of oceanographic parameters in Java Sea are affected by monsoon and ENSO and these variations affected on distribution of fish

STUDI PERUBAHAN TUTUPAN LAHAN MANGROVE BERBASIS OBJEK (OBIA) MENGGUNAKAN CITRA SATELIT DI PULAU DOMPAK PROVINSI KEPULAUAN RIAU

Berbagai ancaman pada hutan mangrove baik secara alamiah seperti perubahan iklim dan kegiatan manusia seperti penimbunan, alih fungsi lahan dan penebangan semakin meningkatkan kerentanan ekosistem itu sendiri. Pengindraan jauh merupakan metode yang sangat efektif untuk digunakan dalam kegiatan pemantauan mangrove karena dapat dilakukan secara berkala dan mampu menjangkau area yang luas. Penelitian ini bertujuan untuk menganalisis perubahan tutupan mangrove di Pulau Dompak Provinsi Kepulauan Riau. Metode yang digunakan berupa klasifikasi citra satelit berbasis objek (OBIA) dengan algoritma support vector machine (SVM). Data citra satelit yang digunakan adalah SPOT 4 Tahun 2007 dan Sentinel 2B Tahun 2018 dengan resolusi spasial 10 x 10 m. Survei lapang dilakukan pada bulan September-Oktober 2018 dengan metode sampling secara acak. Hasil klasifikasi OBIA dengan algoritma SVM menghasilkan tingkat akurasi sebesar 89%, nilai kappa 0,86 dengan skala segmentasi optimum yang diperoleh adalah skala 3. Berdasarkan analisis perubahan tutupan lahan terjadi adanya penurunan luasan hutan mangrove sebesar 34,19% atau sekitar 46,61 ha sejak Tahun 2007 hingga 2018.The threats on mangrove forest, either naturally such as climate change or human activities such as landfill, land-use change, and deforestation, can increase the vulnerability of this ecosystem itself. Remote sensing is an effective method to use as mangrove monitoring activity because it can be done periodically and can reach a large area. This research aims to analyse mangrove coverage changes in Dompak Island, Kepulauan Riau Province. The method that was used is satellite imagery classification based on object (OBIA) with support vector machine (SVM) algorithm. Satellite imagery data that was used are SPOT 4 in 2007 and Sentinel 2B in 2018 with spatial resolution of 10 x 10 m. Ground check was conducted on September-October 2018 using random sampling method. The classification results of OBIA with SVM algorithm showed 89% accuracy level, 0.86 kappa values with optimum segmentation value of 3. Based on coverage land analysis, there was degradation of 34.19% mangrove area, or about 46.61 ha, since 2007 to 2018

THE APPLICATION OF MULTICRITERIA EVALUATION MODEL USING FUZZY AHP TO DETERMINE THE LOCATION OF GROUPER CULTIVATION IN KEPULAUAN SERIBU

The development of grouper's cultivation in Kepulauan Seribu is growing rapidly but there were numerous problems with its cultivation such as limited suitable locations, negative environmental impacts, and land-use conflicts. Lack of information regarding the characteristics of water that suitable for aquaculture will lead to improper use of the location. To prevent this problem, this study aimed to identify and determine suitable locations for grouper's cultivation in Kepulauan Seribu by using the Fuzzy AHP multi-criteria evaluation model based on geographic information systems. The weighting parameter results showed that the distance to the resident is 37.28%, the water current is 26%, the distance to the market is 17.21%, the distance to the road is 11.33%, the distance to the pier is 5.34%, and water depth is 2.84% with a consistency ratio of 0.0337. The waters of Tidung island, Panggang island, Pramuka island, Karya island, Kelapa island, Kelapadua island, Kaliage island, and Pari island are ideal waters for grouper aquaculture activities because they have suitable water conditions and social infrastructure factors. The use of a multi-criteria evaluation model with Fuzzy AHP based on geographic information systems provided relevant analytical results in assigning a weighted score and determining the most dominant criteria that build around the importance of each parameter to other parameters in influencing the cultivation suitability class.Perkembangan budidaya ikan kerapu di Kepulauan Seribu berkembang pesat namun terdapat sejumlah kendala seperti terbatasnya lokasi yang sesuai, dampak negatif terhadap lingkungan, dan konflik penggunaan lahan. Kurangnya informasi terkait karakteristik perairan yang sesuai untuk budidaya akan menyebabkan pemanfaatan lokasi yang kurang tepat. Mencegah masalah tersebut penelitian ini bertujuan mengidentifikasi dan menentukan lokasi yang sesuai untuk budidaya ikan Kerapu di Kepulauan Seribu dengan menggunakan metode model evaluasi multikriteria Fuzzy AHP berbasis sistem informasi geografis. Hasil pembobotan parameter menunjukkan jarak ketempat penduduk (40,54%), jarak ke pasar (17%), jarak ke jalan (10,65%), arus perairan (27,06%), dan kedalaman perairan (4,75%) dengan konsistensi rasio sebesar 0,0228. Perairan Pulau Tidung, Pulau Panggang, Pulau Pramuka, Pulau Karya, Pulau Kelapa, Pulau Kelapadua, Pulau Kaliage, dan Pulau Pari merupakan perairan yang ideal bagi kegiatan budidaya ikan kerapu karena memiliki kondisi perairan dan faktor sosial infrastruktur yang sesuai. Pemanfaatan model evaluasi multikriteria dengan Fuzzy AHP berbasis sistem informasi geografis memberikan hasil analisis yang relevan dalam pemberian skor pembobotan dan dalam penentuan kriteria yang paling dominan berdasarkan tingkat kepentingan setiap parameter terhadap parameter lainnya dalam memengaruhi kelas kesesuaian budidaya

FISHING-VESSEL DETECTION USING SYNTHETIC APERTURE RADAR (SAR) SENTINEL-1 (CASE STUDY: JAVA SEA)

The synthetic aperture radar (SAR) instrument of Sentinel-1 is a remote sensing technology being developed to enable the detection of vessel distribution. The purpose of this research is to study fishing-vessel detection using SAR Sentinel-1 data. In this study, the constant false alarm rate method (CFAR) for Sentinel-1 data is used for the detection of fishing vessels in Indramayu sea waters. The data used to detect ships includes SAR Sentinel-1A images and vessel monitoring system (VMS) data acquired on 8 March and 20 March 2018. SAR Sentinel-1 imagery data is obtained through pre-processing and object identification using Sentinel Application Platform (SNAP) software. Overlay analysis is then used to enable discrimination of immovable and movable objects and validation of ships detected from SAR Sentinel-1 imagery is performed using VMS data. From overlay analysis, 46 ships were detected on 8 March 2018 and 39 ships on 20 March 2018. Of all the ship points detected using SAR Sentinel-1, 7.06% could be detected by VMS data while 92.94% could not. The number of ships detected by SAR Sentinel-1 is greater than those detected by VMS because not all ships use VMS devices.

VARIATION AND TREND OF SEA LEVEL DERIVED FROM ALTIMETRY SATELLITE AND TIDE GAUGE IN CILACAP AND BENOA COASTAL AREAS

Observation of sea levels continuously is very important in order to adapt the disasters in the coastal areas. Conventionally observations of sea level using tide gauge, but the number of tide gauge installed along the coast of Indonesia is still limited. Altimetry satellite data is one solution; therefore it is necessary to assess the potential and accuracy of altimetry satellite data to complement the sea level data from tide gauges. The study was conducted in the coastal waters of Cilacap and Bali by analysis data Envisat satellite altimetry for period 2003 to 2010 and data compiled from a variety of satellite altimetry from 2006 to 2014. Data tidal was used as a comparison of altimetry satellite data. The altimetry satellite data in Cilacap and Benoa waters more than 90% could be used to assess the variation and the sea level rise during the period 2003-2010. The rate of sea level rise both the data of tidal and satellite altimetry data indicates the same rate was 3.5 mm/year in Cilacap. in Benoa are 4.7 mm/year and 5.60 mm/year respectively

MAXIMUM ENTROPY MODEL FOR PREDICTION OF SMALL PELAGIC FISHING GROUNDS IN THE JAVA SEA

Optimalisasi penangkapan ikan pelagis kecil di Laut Jawa masih dapat ditingkatkan dengan pengembangan sistem informasi daerah penangkapan ikan. Penelitian ini bertujuan untuk memprediksi daerah penangkapan ikan pelagis kecil dengan menggunakan model Maximum Entropy (MaxEnt). Data yang digunakan dalam penelitian ini adalah data lingkungan berupa suhu permukaan laut (SPL) dan salinitas permukaan laut tahun 2018 di Laut Jawa yang diunduh dari Google Earth Engine melalui RStudio dan data posisi kapal penangkap ikan yang diunduh dari VIIRS Boat Detection (VBD). Model MaxEnt menunjukkan kinerja yang baik dengan nilai AUC 0,849. Kurva respons menunjukkan probabilitas tertinggi distribusi ikan berada pada SPL pada kisaran 27,0 – 31,0 oC, dan salinitas 32 – 34 psu. Peta prediksi daerah penangkapan ikan yang dihasilkan dengan pemodelan MaxEnt berupa peta kesesuaian habitat menunjukkan bahwa parameter salinitas berpengaruh sebesar 94,5% dan SPL sebesar 5,5%. Peta kesesuaian habitat ikan menunjukkan bahwa mayoritas koordinat kapal penangkapan berada pada nilai Habitat Suitability Index (HSI) 0,5 – 0,8. Daerah potensial penangkapan ikan pelagis kecil terkonsentrasi di wilayah tengah dan utara Laut Jawa mendekati perairan selatan Pulau Kalimantan.The optimization of small pelagic fishing in the Java Sea can still be improved by the development of fishing area information systems. This study aims to predict small pelagic fishing grounds using the Maximum Entropy (MaxEnt) model. The data used in this study are environmental data in the form of sea surface temperature (SST) and sea surface salinity year 2018 in the Java Sea downloaded from Google Earth Engine via RStudio and fishing vessel position data downloaded from VIIRS Boat Detection (VBD). The MaxEnt model showed good performance with an AUC value of 0.849. The response curve shows the highest probability of fish distribution being at SST in the range of 27.0 – 31.0 oC, and salinity of 32 – 34 psu. The predicted map of fishing areas produced by MaxEnt modeling in the form of a habitat suitability map showed that parameter salinity had an effect of 94.5% and SST of 5.5%. Peta fish habitat suitability shows that the majority of fishing vessel coordinates are at the Habitat Suitability Index (HSI) value of 0.5 – 0.8. Small pelagic fishing areas are concentrated in the central and northern regions of the Java Sea approaching the southern waters of Borneo Island

FISHING BOAT DISTRIBUTION ESTABLISHED BY COMPARING VMS AND VIIRS DATA AROUND THE ARU ISLANDS IN MALUKU INDONESIA

Marine protected areas (MPAs) and no take zones (NTZs) are essential for the preservation of marine ecosystems. However, these important areas can be severely harmed by illegal fishing. All vessels above 30 gross tons are required to use vessel monitoring systems (VMSs) that enable vessel tracking by sending geographic data to satellites in each specific time period. The Visible Infrared Radiometer Suite (VIIRS) is a sensor on the National Oceanic and Atmospheric Administration (NOAA)-20 satellite that can detect the light-emitting diode (LED) light used by fishing vessels from space during the night time. In this research, VMS and VIIRS fishery data were combined in order to identify fishing vessels that were detected by the VIIRS sensor of the NOAA-20 satellite. The research was focused on an area near the Aru Islands in the Arafura Sea in Indonesia. Data on LED light used by the fishing techniques of purse seine and bouke ami were obtained for the whole of 2018. The data were then processed using R software. An R package called LLFI (LED Light Fisheries Identifier) was created, containing several R-functions that calculate VMS vessel position during satellite overpass time and then combine the VMS and VIIRS data attributes, resulting in a dataset comprising vessels identified from the VIIRS dataset. Out of all the estimated VMS fishing vessel positions during the VIIRS satellite overpass, approximately 51% could be assigned to fishing vessels detected from the VIIRS dataset. For bouke ami, the identification rate was approximately 87%, while that for small purse seine was around 39%. Ultimately, the LLFI package created daily paths for each identified fishing vessel, displaying all its movements during the day of its’identification. These daily paths did not show any activity within MPA or NTZ. The LLFI package was successful in combining VMS and VIIRS data, estimating VMS vessel positions during the VIIRS satellite overpass, identifying a percentage of  the vessels, and creating a daily path for each identified vessel.

PEMETAAN GEOMORFOLOGI TERUMBU KARANG PULAU TUNDA MENGGUNAKAN KLASIFIKASI BERBASIS OBJEK

Pemetaan zona geomorfologi terumbu karang di Pulau Tunda ini belum pernah dilakukan khususnya menggunakan klasifikasi citra berbasis objek. Hasil pemetaan ini dapat digunakan sebagai dasar informasi perencanaan dan pengembangan suatu kawasan menuju pemanfaatan yang optimal seperti contoh pemanfaatan sebagai kawasan ekowisata bahari. Penelitian ini bertujuan untuk memetakan zona geomorfologi terumbu karang Pulau Tunda denganmenggunakan klasifikasi berbasis objek. Bahan analisis menggunakan citra multispektral Worldview-2 dengan akuisisi data tanggal 25 Agustus 2013 dan profil batimetri. Klasifikasi memakai algoritma segmentasi multiresolusi. Klasifikasi dibagi kedalam 2 level klasifikasi. Parameter klasifikasi level 1 menggunakan scale sebesar 200, shape 0.6 dan compactness 0.4. Segmentasi level 2 menggunakan scale 30, shape 0.6 dan compactness 0.4. Klasifikasi segmentasi objek ini mampu menghasilkan peta dengan tingkat akurasi yang tinggi pada setiap level. Akurasi klasifikasi level 1 adalah sebesar 97% dan level 2 sebesar 91%.</p