Articles
<![CDATA[Pemodelan Spasial Genangan Akibat Kenaikan Muka Air Laut di Pesisir Selatan Kabupaten Tulungagung Jawa Timur ]]>
<![CDATA[Zainul Hidayah]]>;
<![CDATA[Sastra Ardi Agamis Ilhami]]>;
<![CDATA[Abdurrahman As-Syakur]]>;
<![CDATA[Dwi Budi Wiyanto]]>;
<![CDATA[Harish Wirayuhanto]]>
<![CDATA[ Jurnal Kelautan Nasional Vol 18, No 1 (2023): APRIL ]]>
Publisher : <![CDATA[Pusat Riset Kelautan ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.15578/jkn.v18i1.10796
<![CDATA[Kenaikan muka air laut menjadi fenomena alam yang tidak dapat dihindari sebagai dampak dari pemanasan global dan perubahan iklim. Akumulasi kenaikan muka air laut, air pasang dan penurunan muka air tanah menjadi penyebab terjadinya banjir rob. Penelitian ini bertujuan untuk mengaplikasikan pemodelan spasial Sistem Informasi Geografis (SIG) menggunakan trend kenaikan muka air laut untuk mengetahui luas genangan serta mengidentifikasi dampak yang terjadi akibat banjir rob terhadap tutupan lahan di kawasan pesisir selatan Kabupaten Tulungagung Jawa Timur. Data pasang surut yang diambil mulai tahun 2014 hingga tahun 2020 diolah menggunakan metode Least Square untuk mengetahui nilai harmonik pasang surut. Kecenderungan terjadinya Sea Level Rise (SLR) diketahui dengan menganalisis anomali tinggi permukaan laut dari data hasil pengukuran satelit altimetri yang berasal dari National Oceanic and Atmospheric Administration (NOAA) dengan cakupan data dari tahun 1992 hingga tahun 2021 untuk perairan regional Indonesia. Pemodelan spasial menggunakan SIG dilakukan untuk mengetahui luas genangan dan tutupan lahan yang terdampak. Hasil analisis menunjukkan kenaikan muka air laut rata-rata sebesar 4,3 ± 0,4 mm/tahun maka diprediksi terjadi kenaikan MSL di perairan pesisir Tulungagung dari 1,999 meter pada tahun 2020 menjadi 2,7735 meter pada tahun 2200. Luas tutupan lahan pesisir yang tergenang pada akhir pemodelan diperkirakan mencapai 139,13 Ha. Kenaikan muka air laut diperkirakan membawa dampak terhadap lingkungan pesiisr di lokasi studi, karena akan menimbulkan banjir rob yang menggenahi pesisir pantai, pemukiman sawah dan tambak.]]>
<![CDATA[Spatio-Temporal Annual Changes of Mangrove Vegetation Coverages in Porong Estuary Based on Sentinel-2 Imagery ]]>
<![CDATA[Herlambang Aulia Rachman]]>;
<![CDATA[Abd Rahman As-Syakur]]>
<![CDATA[ Rekayasa Vol 16, No 1: April 2023 ]]>
Publisher : <![CDATA[Universitas Trunojoyo Madura ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.21107/rekayasa.v16i1.18882
<![CDATA[Mangrove is a typical coastal ecosystem with high productivity and has a number of ecosystem services. However this ecosystem is vulnerable particularly in urban areas due to land use change and illegal logging. Sidoarjo is one of the most developed urban area in the East Java Province, with mangrove ecpsystem scattered along the Porong estuary. This estuary is also the location of mudflow from the famous Lapindo mud disaster since 2006. This study aims to analyze the changes of mangrove coverages around the Porong estuary using satellite imagery data. Fractional Vegetation Coverage (Fv) was used to quantify the changes of mangrove vegetation coverage of Mangrove Forest from 2015 – 2021. The results show that there is a change in mangrove coverages in the area of study. The high change from lo vegetation coverage (LVC) to Full Vegetation Covarege (FCV) as found in the mouth of Porong River. This condition maybe caused by sedimentation process due to mudflow from volcanic disasters. ]]>
<![CDATA[BIOMASS ESTIMATION MODEL AND CARBON DIOXIDE SEQUESTRATION FOR MANGROVE FOREST USING SENTINEL-2 IN BENOA BAY, BALI ]]>
<![CDATA[A. A. Md. Ananda Putra Suardana]]>;
<![CDATA[Nanin Anggraini]]>;
<![CDATA[Kholifatul Aziz]]>;
<![CDATA[Muhammad Rizki Nandika]]>;
<![CDATA[Azura Ulfa]]>;
<![CDATA[Agung Dwi Wijaya]]>;
<![CDATA[Abd. Rahman As-syakur]]>;
<![CDATA[Gathot Winarso]]>;
<![CDATA[Wiji Prasetio]]>;
<![CDATA[Ratih Dewanti]]>
<![CDATA[ International Journal of Remote Sensing and Earth Sciences (IJReSES) Vol 19, No.1 (2022) ]]>
Publisher : <![CDATA[Ikatan Geografi Indonesia ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.30536/j.ijreses.2022.v19.a3797
<![CDATA[Remote sensing technology can be used to find out the potential of mangrove forests information. One of the potentials is to be able to absorb three times more CO2 than other forests. CO2 absorbed during the photosynthesis process, produces organic compounds that are stored in the mangrove forest biomass. Utilization of remote sensing technology is able to detect mangrove forest biomass using the density level of the vegetation index. This study focuses on determining the best AGB model based on the vegetation index and the ability of mangrove forests to absorb CO2. This research was conducted in Benoa Bay, Bali Province, Indonesia. The satellite image used is Sentinel-2. Classification of mangroves and non-mangroves using a multivariate random forest algorithm. Furthermore, the mangrove forest biomass model using a semi-empirical approach, while the estimation of CO2 sequestration using allometric equations. Mean Absolute Error (MAE) is used to evaluate the validation of the model results. The classification results showed that the detected area of Benoa Bay mangrove forest reached 1134 ha (OA: 0.98, kappa: 0.95). The best AGB estimation result is the DVI-based AGB model (MAE: 23,525) with a value range of 0 to 468.38 Mg/ha. DVI-based AGB derivatives are BGB with a value range of 0 to 79.425 Mg/ha, TAB with a value range of 0 to 547.8 Mg/ha, TCS with a value range of 0 to 257.47 Mg/ha, and ACS with a value range of 0 to 944.912 Mg/ha.]]>
<![CDATA[Distribusi Spasial Salinitas Laut Dari Citra Satelit Aquarius Di Samudera Hindia dan Hubungannya Dengan IOD ]]>
<![CDATA[I Putu Ranu Fajar Maharta]]>;
<![CDATA[Abd. Rahman As-syakur]]>
<![CDATA[ Journal of Marine and Aquatic Sciences Vol 9 No 1 (2023) ]]>
Publisher : <![CDATA[Fakultas Kelautan dan Perikanan Universitas Udayana ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.24843/jmas.2023.v09.i01.p11
<![CDATA[In the Indian Ocean there is a climatological oscillation phenomenon known as the India Ocean Dipole (IOD). IOD is a phenomenon that occurs due to the interaction between the atmosphere and the sea and is indicated by the presence of sea surface temperature anomalies in the western and eastern Indian Ocean. The IOD phenomenon can affect several physical-chemical parameters, one of which is salinity. To obtain salinity data, Aquarius satellite imagery is used, considering that it is very difficult to collect data in-situ. This study aims to conclude the pattern of distribution of the average salinity in the Indian Ocean every month, the rental pattern of the IOD correlation to the salinity in the Indian Ocean, and investigate the salinity anomaly that occurs during positive IOD cases in August 2012 and negative IOD cases in August 2012. June 2013. Salinity in the Indian Ocean differs between the west and east, and changes every month following the seasons that occur in the tropics. The Indian Ocean Dipole (IOD) is very influential on the distribution of salinity in the Indian Ocean because it has a fairly high correlation in almost the entire Indian Ocean. IOD causes salinity anomalies throughout the Indian Ocean, especially in the central part, when positive IOD, the salinity in the middle of the Indian Ocean will decrease, while when negative IOD, the salinity will increase.]]>
<![CDATA[CARBON STOCKS ESTIMATION ON URBAN VEGETATION USING UAV-SfM PHOTOGRAMMETRY METHOD ]]>
<![CDATA[Agus Sukma Yogiswara]]>;
<![CDATA[Takahiro Osawa]]>;
<![CDATA[I Wayan Nuarsa]]>;
<![CDATA[Abd. Rahman As-syakur]]>
<![CDATA[ ECOTROPHIC : Jurnal Ilmu Lingkungan (Journal of Environmental Science) Vol 17 No 1 (2023) ]]>
Publisher : <![CDATA[Master Program of Environmental Science, Postgraduate Program of Udayana University ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.24843/EJES.2023.v17.i01.p04
<![CDATA[Global warming and biodiversity loss are critical issues, and forest retention and reforestation programs are crucial in mitigating climate change. However, discussions around these programs often exclude the role of urban vegetation in carbon sequestration. Preserving urban vegetation, such as trees, can also significantly reduce carbon emissions. Urban vegetation can be found in two main locations: Urban Green Open Spaces (UGS) and Road Landscapes (RL). In Denpasar Bali, Glodokan Tiang or Polyalthia longifolia trees are planted at those locations. Data management and carbon stock calculation mechanisms are required to demonstrate the contribution of urban vegetation in terms of carbon sequestration. The technology of Unmanned Aerial Vehicle (UAV) can be used as an alternative to efficiently calculate the estimated carbon stock. The calculation uses the Diameter Breast High (DBH) value approach using the canopy area and Canopy Height Model (CHM) obtained from UAV data processing using the Sfm method. UAV estimates show that the highest Above Ground Biomass (AGB) value at Bajra Sandhi Renon Field is 201.59 kg with a stored carbon content of 94.75 kg, while on I Gusti Ngurah Rai Bypass has the highest AGB value of 215.04 kg with a stored carbon content of 101.07 kg. These results have been validated by field observations, where the results of the regression analysis at the location of Bajra Sandhi Renon and I Gusti Ngurah Rai, show that between field observation data and estimation data with UAV there is no significant difference. While the results of the t-test: Paired Two Sample for Means at the Bajra Sandhi Renon Field and the Bypass I Gusti Ngurah Rai have a value above the significance level which proves that there is no significant difference between the carbon stock value from field observations and the carbon stock from the UAV approach. Keywords: Carbon Stock; Above Ground Biomass; Urban Vegetation; UAV-Sfm]]>
<![CDATA[APLIKASI SISTEM INFORMASI GEOGRAFI BERBASIS DATA RASTER UNTUK PENGKELASAN KEMAMPUAN LAHAN DI PROVINSI BALI DENGAN METODE NILAI PIKSEL PEMBEDA (Application of Geographic Information System (GIS) Based Raster Data to Classify Land Capability in Bali) ]]>
<![CDATA[I Wayan Sandi Adnyana]]>;
<![CDATA[Abd. Rahman As-syakur]]>
<![CDATA[ Jurnal Manusia dan Lingkungan Vol 19, No 1 (2012): Maret ]]>
Publisher : <![CDATA[Pusat Studi Lingkungan Hidup Universitas Gadjah Mada ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.22146/jml.18448
<![CDATA[ASBTRAKPenggunaan teknologi seperti SIG sangat baik untuk mengelompokkan data keruangan lahan berdasarkan faktor potensi dan penghambat penggunaannya. Dengan mengimprovisasi metode tumpang susun diharapkan mampu mempercepat proses studi tentang pengkelasan kemampuan lahan. Tujuan penelitian ini adalah pengaplikasian SIG berbasis data raster untuk memetakan kelas kemampuan lahan di Provinsi Bali dengan menggunakan metode ”nilai piksel pembeda”. Hasil penelitian menunjukkan bahwa penggunaan SIG dapat memperlihatkan sebaran kelas kemampuan lahan yang heterogen dan kompleks sehingga memperjelas informasi lahan pada satuan unit lahan yang sempit. Selain itu penggunaan metode ini juga membantu mempercepat proses tumpang susun dan query data. Kelas kemampuan lahan di Provinsi Bali dapat dikelompokkan menjadi 8 kelas, dari kelas I sampai kelas VIII. Sebaran kelas kemampuan lahannya didominasi oleh lahan dengan kelas VI, VII dan VIII yaitu seluas 50,7% dari luas Provinsi Bali. Kabupaten Buleleng, Jembrana, dan Karangasem berturut-turut merupakan daerah-daerah terluas yang memiliki kemampuan lahan kelas VIII. Daerah-daerah tersebut harus lebih instensif dalam menjaga lahan-lahan berkelas VIII agar tidak beralih fungsi dari lahan hutan menjadi lahan non hutan.ABSTRACTThe use of technologies such as GIS are very good for spatial data classifying based on potential and inhibiting use factors. With improvise an overlay method expected to accelerate study process about land capability classifying. The purpose of this research is the application of GIS based raster data to mapping land capability class in Bali Province by using "differentiator pixel value". The results showed that the use of GIS can show the heterogeneous and complex distribution of land capability classes and can clarify the land information on a narrow land unit. Furthermore, the uses of this method also help to accelerate the overlay and query data process. The distribution of land capability class is dominated by land with class VI, VII and VIII, which is covering 50.7% of the Bali Province. Districts that have a biggest land capability class VII is Buleleng, Jembrana, and Karangasem, respectively. Therefore, these districts should be more intensive to keeping the lands class VIII for not switching function from forest into non-forest land.]]>
<![CDATA[Pemanfaatan Citra Satelit Aqua-MODIS untuk Pemantauan Dinamika Spasio-Temporal Produktivitas Primer Bersih di Perairan Laut Jawa ]]>
<![CDATA[Alfandy Putra Anugrah]]>;
<![CDATA[Zainul Hidayah]]>;
<![CDATA[Abdurrahman As-Syakur]]>;
<![CDATA[Herlambang Aulia Rachman]]>
<![CDATA[ Jurnal Kelautan Tropis Vol 26, No 3 (2023): JURNAL KELAUTAN TROPIS ]]>
Publisher : <![CDATA[Universitas Diponegoro ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.14710/jkt.v26i3.18222
<![CDATA[The Java Sea is an area with the highest rate of exploitation of fishery resources in Indonesia. As much as 32% of the total national fishery production or 2.2 million tons has come from catches in the Java Sea, even though the area of these waters only covers 7% of the total area of national waters. Fisheries productivity is related to the net primary productivity value resulting from the activity of phytoplankton or chlorophyll-a. Net primary productivity (NPP) is influenced by the presence of nutrients, light, chlorophyll-a, Photosynthetically Available Radiation (PAR) and sea surface temperature (SST). The purpose of this research is to analyze the distribution value of net primary productivity in the Java Sea by utilizing Aqua-MODIS satellite imagery using the Vertically Generalized Production Model (VGPM) method with a range of 2017-2021. The results showed that the waters of the Java Sea have quite high fertility and are classified as Eutrophic because the general monthly average from 2017-2021 has an NPP value of >750 mgC/m2/day. The value of primary productivity follows the seasonal pattern, will be high in the east moonson season and decrease in the west monsoon season. Laut Jawa merupakan wilayah dengan laju eksploitasi sumberdaya perikanan tertinggi di Indonesia. Sebanyak 32% dari total produksi perikanan nasional atau sebesar 2,2 juta ton berasal dari hasil tangkapan di Laut Jawa meskipun luas wilayah perairan ini hanya mencakup 7% dari total luas wilayah perairan nasional. Produktivitas perikanan tangkap berhubungan dengan nilai produktivitas primer bersih hasil dari aktivitas fitoplankton atau klorofil-a. Produktivitas primer bersih di suatu perairan dipengaruhi oleh adanya unsur hara, cahaya, klorofil-a, Photosynthetically Available Radiation (PAR) dan suhu permukaan laut (SPL). Tujuan dari penelitian ini adalah untuk menganalisis nilai distribusi produktivitas primer bersih di Laut Jawa dengan memanfaatkan citra satelit Aqua-MODIS menggunakan metode Vertically Generalized Production Model (VGPM) dengan rentang tahun 2017-2021. Hasil penelitian menunjukkan bahwa perairan Laut Jawa memiliki kesuburan yang cukup tinggi dan tergolong Eutrofik karena rata-rata bulanan secara umum mulai dari tahun 2017-2021 memiliki nilai NPP >750 mgC/m2/hari. Nilai produktivitas primer mengikuti pola musim, akan tinggi pada musim timur (kemarau) dan menurun pada musim barat (penghujan).]]>
<![CDATA[Studi Perubahan Garis Pantai di Teluk Penyu, Cilacap, Jawa Tengah Menggunakan Citra Sentinel-1 dan Sentinel-2 ]]>
<![CDATA[Azhar Muhammad Hanisa]]>;
<![CDATA[Abd. Rahman As-syakur]]>;
<![CDATA[I Wayan Gede Astawa Karang]]>
<![CDATA[ Journal of Marine Research and Technology Vol 7 No 1 (2024): FEBRUARI 2024 ]]>
Publisher : <![CDATA[Department of Marine Sciences, Faculty of Marine and Fisheries, Universitas Udayana ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.24843/JMRT.2024.v07.i01.p02
<![CDATA[The coastline is defined as the location where water and land contact at any given time. Coastline change is considered as one of the most dynamic processes in coastal areas and is an indication of coastal accretion and erosion. The process of accretion and erosion can cause beach conditions to become unbalanced and even damaged. Cilacap Regency has a coastline of approximately 80 km which is directly adjacent to the Indian Ocean. The coast of Cilacap experienced changes in coastline which tended to be high from 1999-2008. For this reason, research has been carried out regarding coastline changes in Penyu Bay using remote sensing. The data used are Sentinel-1 and Sentinel-2 satellite images for 2016 and 2021. The analysis of shoreline changes uses the Digital Shoreline Analysis System (DSAS). The results of an analysis of shoreline changes in Penyu Bay from 2016 to 2021 show an average accretion of 1,278.49 m2 at Sentinel-1. While Sentinel-2 shows an average accretion of 2,917.68 m2. The average rate of line change per year on Sentinel-1 is 1 m/year with an indication of accretion and Sentinel-2 is 1,11 m/year with an indication of erosion. Accuracy test with Root Mean Square Error shows that Sentinel-1 is 36.80 m and Sentinel-2 is 15.43 m. Sentinel-1 has an accuracy value (CE90) of 55.84 m in class 2 with a scale of 1:100,000, while Sentinel-2 is 23.41 m in class 2 with a scale of 1:50,000.]]>
<![CDATA[Analysis of The Heavy Metal Content (Cd and Zn) in Water, Sediment, Roots, and Leafs of Sonnetaria sp. in Badung River Estuary Area ]]>
<![CDATA[Gayatri, Ni Nyoman Puspa]]>;
<![CDATA[Zulfa, Rozifatul]]>;
<![CDATA[Parwayoni, Ni Made Susun]]>;
<![CDATA[As-syakur, Abd. Rahman]]>;
<![CDATA[Wijana, I Made Sara]]>
<![CDATA[ Bumi Lestari Journal of Environment Vol 24 No 2 (2024) ]]>
Publisher : <![CDATA[Environmental Research Center (PPLH) of Udayana University ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.24843//blje.2024.v24.i02.p03
<![CDATA[The estuary area of the Tukad Badung river has the potential to experience heavy metal pollution because of its location for various domestic and industrial wastes also has dense shipping activities around it. This study aims to identify the heavy metal content of Cd and Zn in water, sediment, root, and leaf samples of Sonnetaria sp. that grows in the area. The results obtained from the analysis of the heavy metal content of Cd and Zn in water samples were 0.006 mg/L and 0.014 mg/L. The results of the analysis of heavy metal content of Cd and Zn in sediment samples were 0.406 mg/kg and 15.462 mg/kg, respectively. This shows that water and sediment samples are still below the applicable quality standards. The Bioaccumulation Factor (BCF) value shows that the roots and leaves of Sonnetaria sp. can accumulate heavy metal Cd by 0.034483 and 0.041872 and accumulate heavy metal Zn by 0.011059 and 0.016751. The calculation of Translocation Factor (TF) of Cd metal of 1.214286 and Zn of 1.51462 shows that Sonnetaria sp. belongs to the category of phytoextraction (TF>1). Based on the Igeo index, the estuary area of the Tukad Badung river is classified as unpolluted to moderately polluted by heavy metals Cd (Igeo: 0.436517) and not contaminated with Zn metals (Igeo: -2.76359).]]>
<![CDATA[Estimasi Biaya dan Manfaat Ekonomi Sampah di Kota Denpasar (Studi Kasus di: TPS 3R Sekar Tanjung Desa Sanur Kauh, TPS 3R Kesiman, dan TPS 3R Bung Tomo ]]>
<![CDATA[Premananda, I Wayan Hari]]>;
<![CDATA[Wijana, I Made Sara]]>;
<![CDATA[As-syakur, Abd. Rahman]]>;
<![CDATA[Sudarma, I Made]]>;
<![CDATA[Indriyanti, Komang Dessica]]>;
<![CDATA[Dewi, I Gusti Ayu Istri Pradnyandari]]>;
<![CDATA[Andiani, Anak Agung Eka]]>;
<![CDATA[Novanda, I Gede Agus]]>;
<![CDATA[Premananda, Made Goura]]>;
<![CDATA[Primajana, Dewa Jati]]>
<![CDATA[ Bumi Lestari Journal of Environment Vol 24 No 1 (2024) ]]>
Publisher : <![CDATA[Environmental Research Center (PPLH) of Udayana University ]]>
Show Abstract
|
Download Original
|
Original Source
|
Check in Google Scholar
|
DOI: 10.24843/blje.2024.v24.i01.p04
<![CDATA[Timbulan sampah yang masih belum dapat ditangani menjadi permasalahan di Kota Denpasar. Menurut Arfani dan Lestari (2021) kendala utama dari pengelolaan sampah adalah mengenai pendanaan untuk sarana dan prasarana. Untuk mengurangi beban yang timbul dari biaya pengelolaan sampah, pemerintah harus merencanakan pengelolaan yang efektif. Objek penelitian ini adalah timbulan sampah di Kota Denpasar di TPS 3 R Sekar Tanjung, TPS 3 R Kesiman Kertalangu, dan TPS 3 R Bung Tomo. Metode yang digunakan dalam penelitian ini yaitu metode deskriptif, yaitu dengan menghitung kapasitas pengelolaan sampah di TPS 3 R dan membandingkan antara biaya dengan manfaat pengelolaan sampah di TPS 3 R. Berdasarkan hasil penelitian ini dapat disimpulkan yaitu: Pengelolaan sampah pada TPS 3R Kesiman Kertalangu memiliki tingkat efisiensi yang paling tinggi yaitu 82,7%. Hal tersebut sejalan dengan jumlah mesin dan peralatan yang digunakan. TPS 3R Kesiman Kertalangu menggunakan total 9 mesin dan peralatan pada tahap pengolahan. Jumlah tersebut merupakan yang terbanyak diantara TPS 3R lainnya. Dari tiga lokasi penelitian, satu lokasi yaitu TPS 3 R Bung Tomo belum melakukan kegiatan pemilahan dari sumbernya, sedangkan dua lokasi lainnya telah melakukan kegiatan pemilahan dari sumbernya. Pada tiga TPS 3 R di Kota Denpasar, dua diantaranya memiliki B/C Ratio >1 yaitu TPS 3 R Sekar Tanjung dan TPS 3 R Kesiman Kertalangu yang mengindikasikan kegiatan pengelolaan sampah layak secara ekonomi dan TPS 3 R Bung Tomo memiliki B/C Ratio <1 yang mengindikasikan kegiatan pengelolaan sampah belum layak secara ekonomi.]]>
