Geoid最新文献

{"title":"Identifikasi Sebaran Spasial Genangan Banjir Memanfaatkan Citra Sentinel-1 dan Google Earth Engine (Studi Kasus: Banjir Kalimantan Selatan)","authors":"Filsa Bioresita, M. Ngurawan, N. Hayati","doi":"10.12962/j24423998.v17i1.10383","DOIUrl":"https://doi.org/10.12962/j24423998.v17i1.10383","url":null,"abstract":"","PeriodicalId":30776,"journal":{"name":"Geoid","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"44380338","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analisis Perhitungan Volume Galian Tambang Terbuka (Open Pit Mining) Menggunakan Interpolasi Metode Gridding","authors":"Hafezs Satriani Ramadhan, A. Kurniawan, Mohammad Rohmaneo Darminto","doi":"10.12962/j24423998.v17i1.10369","DOIUrl":"https://doi.org/10.12962/j24423998.v17i1.10369","url":null,"abstract":"","PeriodicalId":30776,"journal":{"name":"Geoid","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42562471","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Perbandingan Metode Koreksi Atmosfer Dark Spectrum Fitting Dan Exponential Extrapolation Untuk Citra Satelit Landsat 8","authors":"Lalu Muhamad Jaelani, Gilang Amrullah Sayono","doi":"10.12962/j24423998.v17i1.8826","DOIUrl":"https://doi.org/10.12962/j24423998.v17i1.8826","url":null,"abstract":"","PeriodicalId":30776,"journal":{"name":"Geoid","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2022-01-10","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"49376704","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Hubungan Dual Polametric SAR Band – C dan Landsat 8 untuk Identifikasi Potensi Kekeringan","authors":"Hikmah Fajar Assidiq, Catur Aries Rokhmana","doi":"10.12962/J24423998.V16I2.8581","DOIUrl":"https://doi.org/10.12962/J24423998.V16I2.8581","url":null,"abstract":"Drought is a disastrous and complex disaster that can cause material and immaterial losses. The drought in Indonesia is categorized by several types including Agricultural Drought, Meteorological Drought, and Hydrological Drought. Agricultural drought is a condition where there is a decrease in water content in the soil. These conditions will have an impact on vegetation and / or land cover so preventive action is needed. Preventive action is carried out quickly, effectively and efficiently so that an approach with a dynamic pattern is needed. The dynamic pattern approach is done by a method that can be done any time. The use of Active Sensor remote sensing can perform monitoring at any time and dynamically. One of the satellites with radar sensors is Sentinel 1A. Sentinel 1A has a C band wave. Polarization in the Sentinel-1 image has a dual-pol form consisting of VV and VH or HH and HV. The Polarization combination has the potential to measure drought. The method that can be used is the Vegetation Radar Index. The radar vegetation index is developed from the NDVI algorithm. The RVI Drought Classification is made by maintaining the relationship between the NDVI Landsat 8 results and the RVI results. This study aims to examine the use of SAR data for drought identification with the relationship between Dual Polametric SAR Band C and Landsat 8. The results explain that NDVI has a coefficient of determination with an RVI of 0.2981 Kata kunci: kekeringan; RVI; Sentinel 1A Cara untuk sitasi: Assidiq, H.F., & Rokhmana, C.A. (2021). Hubungan Dual Polametric SAR Band – C dan Landsat 8 untuk Identifikasi Potensi Kekeringan. Geoid, 16(2), 248 258.","PeriodicalId":30776,"journal":{"name":"Geoid","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-04-09","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"46084158","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Deformasi Permukaan pada Manifestasi Gunung Lumpur di Wilayah Cekungan Jawa Timur dari Pengolahan Data SAR menggunakan Metode PS-InSAR","authors":"Bella Esti Ajeng Syahputri, Ira Mutiara Anjasmara, Amien Widodo","doi":"10.12962/J24423998.V16I2.7414","DOIUrl":"https://doi.org/10.12962/J24423998.V16I2.7414","url":null,"abstract":"Surface Deformation on Mud Mountain Manifestations in the East Java Basin from SAR Data Processing the PS-InSAR Method Abstract: This study presents the results of the Permanent Scatterer Interferometric SAR (PS-InSAR) processing technique, which aims to analyze the pattern and value of surface deformation due to mud volcano manifestations. Using the PS-InSAR method, the deformation identified from processing time-series data on the ALOS PALSAR 1 L-band SAR Image in 2007-2009 and C-band Sentinel 1A 2015-2019 can reach the accuracy of millimeters. The results also showed that the 2007-2009 data processing could not be used as deformation information. It is because the minimum number of images required for the PS-InSAR method was not fulfilled. The 2015-2019 data processing illustrates the deformation patterns and values on the mud volcano manifestation locations. The Sidoarjo Mud Volcano experience uplift with an average value of 5.46 mm/year. The Gununganyar Mud Volcano experienced average uplift of 1.71 mm/year and a subsidence of 7.08 mm/year. The majority of the Kalanganyar Mud Volcano experienced average subsidence of 0.99 mm/year. The Wringianom Mud Volcano experienced average subsidence of 3.37 mm/year, and the majority of Bujhel Tasek Bini and Pria Mud Volcano has average subsidence of 2.88 mm/year. This study's results can be useful for consideration in development activities or construction around the mud volcanoes manifestation in East Java Province.","PeriodicalId":30776,"journal":{"name":"Geoid","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45423496","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pendokumentasian Pilar Batas Daerah Kota Yogyakarta dan Kabupaten Sleman","authors":"M. I. Taftazani, Afradon Aditya Setyawan, Ananda Taufiq Akbar, Annisa Farida Hayuningsih, Dhany Yudi Prasteyo, W. Mayangsari","doi":"10.12962/J24423998.V16I2.8002","DOIUrl":"https://doi.org/10.12962/J24423998.V16I2.8002","url":null,"abstract":": The regional boundary between Yogyakarta City and Sleman Regency has been defined and confirmed in the Regulation of the Minister of Home Affairs No 72/2007, hereinafter referred to as Permendagri No 72/2007. This Permendagri regulates the regional boundaries of Yogyakarta City and Sleman Regency in terms of coordinating pillar points. Within the regional boundary between Yogyakarta City and Sleman Regency, 66 boundary pillars are consisting of three types of boundary pillars. The three types of pillars are the Main Boundary Reference Pillar (PABU), the Main Boundary Pillar (PBU), and the Boundary Pillar (PBA). Visual observations","PeriodicalId":30776,"journal":{"name":"Geoid","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"42647039","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analisis Variasi Temporal-Spasial Nilai Zenith Tropospheric Delay Menggunakan Data CORS di Provinsi Jawa Timur","authors":"Norma Aji Cemara Mannani, E. Handoko","doi":"10.12962/J24423998.V16I2.7420","DOIUrl":"https://doi.org/10.12962/J24423998.V16I2.7420","url":null,"abstract":"Global Navigation Satellite System (GNSS) are being developed as an atmospheric remote sensing system through the calculation of ZTD. The development of CORS station encourages research investigations about Zenith Tropospheric Delay (ZTD) with continuous data and good spatial resolution. This research studies about characteristics of spatial and temporal variation from ZWD in East Jawa. The case study in East Jawa Province Using 16 CORS Station. Meteorological data from four BMKG’s stations are used as comparison data. ZTD and ZWD value from CORS data are calculated using GIPSY 6.4 Software. ZWD values are gridded using the kriging method with the size of the grids is 0,25 x 0,25. ZWD value comparison from CORS and meteorology data have a strong correlation with coefficient value is 0,712. The mean ZWD trend is decreasing by about 1,628 mm/yr. Characteristics of spatial and temporal variations of the ZWD value influenced by monsoon Asia-Australian which cause dry and rainy seasons, global phenomena such as El Nino and La Nina, rainfall, local meteorological conditions such as temperature and humidity, weather, and topography of the stations. Kata kunci : CORS; GNSS; variasi; ZTD; ZWD Cara untuk sitasi: Mannani, N.A.C., & Handoko, E.Y. (2021). Analisis Variasi Temporal-Spasial Nilai Zenith Tropospheric Delay Menggunakan Data CORS di Provinsi Jawa Timur. Geoid, 16(2), 215 230.","PeriodicalId":30776,"journal":{"name":"Geoid","volume":"1 1","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-04-07","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"41944625","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Visualisasi Data Statistik Kabupaten Banyumas Menggunakan Peta Interaktif","authors":"Hanif Ilmawan, Purnama Budi Santosa","doi":"10.12962/J24423998.V16I2.7842","DOIUrl":"https://doi.org/10.12962/J24423998.V16I2.7842","url":null,"abstract":"Penyajian data statistik mengalami perkembangan seiring dengan kemajuan teknologi. Data statistik tidak hanya disajikan dalam bentuk tabel dan grafik saja, tetapi juga divisualisasikan menggunakan peta. Bahkan saat ini juga digunakan peta interaktif berbasis online untuk lebih memudahkan pengguna dalam mengakses dan mengeksplorasi data yang ada. Hal ini merupakan salah satu bentuk pelaksanaan dari Pasal 20 UU No. 16 Tahun 1997 yang mengatur bahwa penyelenggara kegiatan statistik wajib memberikan kesempatan yang sama kepada masyarakat untuk mengetahui dan memperoleh manfaat dari data statistik yang tersedia. Salah satu perangkat lunak yang dapat dimanfaatkan untuk melakukan visualisasi data statistik adalah StatPlanet Plus. Perangkat lunak ini bersifat free (versi offline dan non komersial). StatPlanet Plus mampu menghasilkan peta interaktif dengan menggunakan bahasa pemrograman Flash.  Penyajian data statisik menggunakan peta interaktif dapat membantu pengguna untuk memahami data dan mengungkap wawasan baru (Di Biase, 1990; Roberts, 2008). Peta interaktif juga berfungsi sebagai media komunikasi pemilik data dengan pengguna data (Roth, 2013). Hasil dari kegiatan ini adalah sebuah purwarupa peta interaktif untuk visualisasi data statistik Kabupaten Banyumas. Peta interaktif ini dapat menjadi alternatif bagi Badan Pusat Statistik Kabupaten Banyumas dalam melakukan publikasi data statistik, sehingga memudahkan masyarakat umum dalam mengakses data statistik. The development of technology affects the way people in presenting statistical data. Statistical data are not only presented in the form of table, chart, and diagram, but also visualized by using map. Moreover, interactive map is now used to make data access and exploration become far easier. This is an implementation of Law of the Republic of Indonesia Number 16 of 1997 which states that the conductor of statistical activities has to give a same opportunity for people to get benefits from available statistical data. One of softwares that can be used to visualize the statistical data is StatPlanet Plus. This software is free for offline and non commercial use. StatPlanet Plus can make an interactive map by using Flash script.Presenting statistical data using interactive map can help users to understand data and discover new insights (Di Biase, 1990; Roberts, 2008). Interactive map also used as a media for data owner to communicate with data users (Roth, 2013). The result of this study is a prototype of interactive map for visualizing the statistical data of Banyumas Regency. This interactive map is an alternative for Badan Pusat Statistik of Banyumas Regency to publish statistical data, so it will facilitate people to access the statistical data.","PeriodicalId":30776,"journal":{"name":"Geoid","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-02-24","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"48981275","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Analisis Pemodelan Arus Geostropik di Perairan Indonesia menggunakan Data Satelit Altimetri","authors":"Desi Suci Richasari, E. Handoko","doi":"10.12962/J24423998.V16I1.8564","DOIUrl":"https://doi.org/10.12962/J24423998.V16I1.8564","url":null,"abstract":"Studi ini bertujuan  untuk menentukan dan menganalisis arus geostropik terhadap indeks ENSO dan indeks musim. Lokasi studi ini terletak di sekitar lautan Indonesia dengan koordinat 20 ° N - 20 ° S dan 90 ° E - 150 ° E. Altimetri data satelit Jason Series sangat berguna sebagai penyedia data laut global, termasuk informasi tentang arus laut permukaan dan dinamika permukaan laut. Untuk menentukan arus geostropik, kami menggunakan algoritma geostropik dan metode analisis menggunakan koefisien korelasi hasil antara parameter penelitian dengan nilai indeks. Analisis temporal dan spasial menggunakan Matlab dan ArcMap untuk memvisualisasikan parameter yang diperoleh. Hasil penelitian ini menunjukkan bahwa korelasi antara anomali permukaan laut (SLA) dengan Multivariate ENSO Index (MEI) menunjukkan nilai negatif, menunjukkan bahwa SLA memiliki kondisi yang berlawanan dengan fenomena ENSO. El Nino yang kuat terjadi pada tahun 2015 dan La Nina terjadi pada tahun 2010. Perbedaan SLA tidak mempengaruhi arah arus geostropik tetapi mempengaruhi kecepatannya. Korelasi arus geotropik komponen zonal dengan AUSMI adalah 0,720 dan WNPMI adalah 0,446. Ini berarti bahwa arus geostropik memiliki arah yang sama dengan aliran angin musim. This research aims  to determine and analyze the geostrophic current towards the monsoon index and the ENSO index . The location of this research is around Indonesian seas with coordinates of 20 ° N - 20 ° S and 90 ° E - 150 ° E. Jason Series altimetry satellite data is very useful as a provider of data on global marine affairs, including information about sea surface and sea level currents. To determine the geostrophic current, we used the geostrophic algorithm and the method of analysis used the coefficient correlation of the results between the research parameters with the index. Temporal and spatial analysis using Matlab and ArcMap to visualize the parameters which is obtained. The results of this study indicate that  the corelation between Sea Level Anomalies (SLA) to the Multivariate ENSO Index (MEI) shows the negative value. It means that  SLA at Indonesian seas have opposite condition. The strong El Nino occurred in 2015 and La Nina occurred in 2010. The SLA difference does not affect the direction of geostrophic current but affect its velocity. The correlation of  zonal component geotrophic current to AUSMI 0,720 and WNPMI is 0,446. That means the geostrophic current have the same direction with the wind flow respectively at the moonson season.","PeriodicalId":30776,"journal":{"name":"Geoid","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"45453448","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

{"title":"Pemanfaatan GNSS pada Smartphone untuk Pembuatan Informasi Sebaran Covid-19 Berbasis Android (Studi Kasus: Kota Surabaya)","authors":"Anzhari Hibatul Akbar, M. N. Cahyadi","doi":"10.12962/J24423998.V16I1.8566","DOIUrl":"https://doi.org/10.12962/J24423998.V16I1.8566","url":null,"abstract":"Coronavirus disease 2019 (COVID-19) adalah penyakit pernapasan yang dapat menyebar dari orang ke orang. Pada tanggal 06 Juni 2020 di Surabaya tercatat terdapat 3906 kasus ODP, 3303 kasus PDP, 2918 kasus konfirmasi Covid-19, 766 orang sembuh, dan 282 orang meninggal. Sistem informasi geografis merupakan ilmu pengetahuan yang berbasis pada perangkat lunak komputer, yang digunakan untuk memberikan informasi bentuk digital dan analisis terhadap permukaan geografi bumi. GNSS merupakan metode penentuan posisi menggunakan satelit, yang mana sistem ini dapat digunakan banyak orang sekaligus, dibuat untuk mendapatkan posisi tiga dimensi. Dengan menggabungkan penentuan posisi pada GNSS smartphone dan data spasial sebaran kasus Covid-19 di Kota Surabaya, diharapkan dapat memberikan informasi tentang kondisi kesehatan masyarakat di lingkungan sekitar khususnya terkait Covid-19, dan juga mempermudah akses informasi karena berbasis aplikasi. \u0000Data yang digunakan adalah data sebaran Covid-19 pada 06 Juni 2020, data sebaran fasilitas kesehatan, dan fasilitas umum protokol kesehatan. Pembuatan aplikasi menggunakan flutter dan juga visual basic code sebagai editor. GNSS pada smartphone berfungsi untuk mengetahui nilai akurasi dengan aplikasi GPS Essentials dan untuk fitur-fitur pada aplikasi seperti penentuan lokasi pengguna, notifikasi sesuai lokasi pengguna, dan penentuan rute menuju suatu titik. \u0000Pada kelurahan dengan tingkat kasus Covid-19 tertinggi tidak selalu memiliki fasilitas umum protokol kesehatan yang sedikit tetapi yang banyak pun bisa menjadi kelurahan dengan tingkat kasus Covid-19 tertinggi. Untuk sebaran rumah sakit rujukan Covid-19 tidak ada yang berlokasi di kelurahan dengan tingkat kasus Covid-19 tertinggi. Suatu kelurahan yang memiliki kasus Covid-19 biasanya berada di dekat kelurahan yang tingkat kasusnya sama, satu tingkat di bawah atau di atas kelurahan tersebut. Berdasarkan hasil kuesioner, aplikasi yang dibuat mendapat tanggapan yang baik. Aplikasi yang dibuat dinamakan “Cegah Covid-19 Surabaya” saat ini mampu dijalankan di smartphone android pada versi Android 10, Pie, Oreo, Nougat, Marshmallow, dan Lollipop. \u0000====================================================================================================================== \u0000Coronavirus disease 2019 (COVID-19) is a respiratory disease that can spread from person to person. On June 6, 2020 in Surabaya there were 3906 ODP, 3303 PDP, 2918 Covid-19 confirmation, 766 people recovered, and 282 people died. Geographical information system is a science based on computer software, which is used to provide digital form information and analysis of the earth's geographic surface. GNSS is a method of positioning using satellites, which this system can be used by many people at once, made to get three-dimensional positions. By combining the positioning of GNSS smartphones and the spatial data for the distribution of the Covid-19 case in the city of Surabaya, it is expected to provide information abo","PeriodicalId":30776,"journal":{"name":"Geoid","volume":" ","pages":""},"PeriodicalIF":0.0,"publicationDate":"2021-01-21","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"43433351","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}