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All Journal Agromet Jurnal Ilmu dan Teknologi Kelautan Tropis Indonesian Journal of Geography Journal of Marine and Aquatic Sciences Jurnal Ilmu Lingkungan Geoplanning : Journal of Geomatics and Planning Journal of Degraded and Mining Lands Management Forum Geografi Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital International Journal of Remote Sensing and Earth Sciences (IJReSES) Jurnal Penginderaan Jauh dan Pengolahan Data Citra Digital The International Journal of Remote Sensing and Earth Sciences (IJReSES)
Dony Kushardono
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Aerospace Engineering Agriculture, Biological Sciences & Forestry Biochemistry, Genetics & Molecular Biology Computer Science & IT Control & Systems Engineering Decision Sciences, Operations Research & Management Earth & Planetary Sciences Electrical & Electronics Engineering Environmental Science Library & Information Science

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Journal : Forum Geografi

 1 
Object Segmentation on UAV Photo Data to Support the Provision of Rural Area Spatial Information Sari, Nurwita Mustika; Kushardono, Dony
Forum Geografi Vol 29, No 1 (2015): Forum Geografi
Publisher : Forum Geografi

Show Abstract | Download Original | Original Source | Check in Google Scholar

Abstract

The use of Unmanned Aerial Vehicle (UAV) to take aerial photographs is increasing in recent years. Photo data taken by UAV become one of reliable detailed-scale  remote sensing data sources. The capability to obtain cloud-free images and the flexibility of time are some of the advantages of UAV photo data compared to satellite images with optical sensor. Displayed area at the data shows the objects clearly. Rural area has certain characteristics in its land cover namely ricefield. To delineate the area correctly there is an object-based image analysis methods (OBIA) that could be applied. In this  study, proposed a novel method to  execute the separation of objects that exist in the data with segmentation method. The result shows an effective segmentation method to separate different objects in rural areas recorded on UAV image data. The accuracy obtained is 90.47% after optimization process. This segmentation can be a valid basis to support the provision of spatial information in rural area.
The Relationship between the Mixed Pixel Spectral Value of Landsat 8 OLI Data and LAPAN Surveillance Aircraft (LSA) Aerial-Photo Data Sari, Nurwita Mustika; Chulafak, Galdita Aruba; Zylshal, Zylshal; Kushardono, Dony
Forum Geografi Vol 31, No 1 (2017): July 2017
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v31i1.3500

Abstract

Medium resolution satellite data such as Landsat is very potential for mixed pixel (mixel) to occur. Indonesian land use diverse especially urban areas makes high potential mixel in the first Landsat pixel size of 30 meters x 30 meters on the actual condition. Aircraft multispectral aerial photo data LAPAN Surveillance Aircraft (LSA) with a spatial resolution reached 58 cm can display objects in more detail in these sizes. The purpose of this research is to study mixel on Landsat data with multispectral data LSA as a complement Landsat data. The method proposed in this study is a visual interpretation with GEOBIA method for classification of land cover, and then test the validity of the sample to be used in research, and the use of such vegetation index NDVI to see the connection between vegetation index data of vegetation index LSA with Landsat data. The results showed that the regression equation obtained by regression between NDVI of Landsat data and NDVI of  LSA with a significance of less than 0.05 is y = 0.732x - 0102 with a value of R2 = 0.887. Through these results we can conclude that the NDVI values on both the data related to one another.
Object Segmentation on UAV Photo Data to Support the Provision of Rural Area Spatial Information Sari, Nurwita Mustika; Kushardono, Dony
Forum Geografi Vol 29, No 1 (2015): July 2015
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v29i1.792

Abstract

The use of Unmanned Aerial Vehicle (UAV) to take aerial photographs is increasing in recent years. Photo data taken by UAV become one of reliable detailed-scale  remote sensing data sources. The capability to obtain cloud-free images and the flexibility of time are some of the advantages of UAV photo data compared to satellite images with optical sensor. Displayed area at the data shows the objects clearly. Rural area has certain characteristics in its land cover namely ricefield. To delineate the area correctly there is an object-based image analysis methods (OBIA) that could be applied. In this  study, proposed a novel method to  execute the separation of objects that exist in the data with segmentation method. The result shows an effective segmentation method to separate different objects in rural areas recorded on UAV image data. The accuracy obtained is 90.47% after optimization process. This segmentation can be a valid basis to support the provision of spatial information in rural area.
Object Segmentation on UAV Photo Data to Support the Provision of Rural Area Spatial Information Nurwita Mustika Sari; Dony Kushardono
Forum Geografi Vol 29, No 1 (2015): July 2015
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v29i1.792

Abstract

The use of Unmanned Aerial Vehicle (UAV) to take aerial photographs is increasing in recent years. Photo data taken by UAV become one of reliable detailed-scale  remote sensing data sources. The capability to obtain cloud-free images and the flexibility of time are some of the advantages of UAV photo data compared to satellite images with optical sensor. Displayed area at the data shows the objects clearly. Rural area has certain characteristics in its land cover namely ricefield. To delineate the area correctly there is an object-based image analysis methods (OBIA) that could be applied. In this  study, proposed a novel method to  execute the separation of objects that exist in the data with segmentation method. The result shows an effective segmentation method to separate different objects in rural areas recorded on UAV image data. The accuracy obtained is 90.47% after optimization process. This segmentation can be a valid basis to support the provision of spatial information in rural area.
The Relationship between the Mixed Pixel Spectral Value of Landsat 8 OLI Data and LAPAN Surveillance Aircraft (LSA) Aerial-Photo Data Nurwita Mustika Sari; Galdita Aruba Chulafak; Zylshal Zylshal; Dony Kushardono
Forum Geografi Vol 31, No 1 (2017): July 2017
Publisher : Universitas Muhammadiyah Surakarta

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.23917/forgeo.v31i1.3500

Abstract

Medium resolution satellite data such as Landsat is very potential for mixed pixel (mixel) to occur. Indonesian land use diverse especially urban areas makes high potential mixel in the first Landsat pixel size of 30 meters x 30 meters on the actual condition. Aircraft multispectral aerial photo data LAPAN Surveillance Aircraft (LSA) with a spatial resolution reached 58 cm can display objects in more detail in these sizes. The purpose of this research is to study mixel on Landsat data with multispectral data LSA as a complement Landsat data. The method proposed in this study is a visual interpretation with GEOBIA method for classification of land cover, and then test the validity of the sample to be used in research, and the use of such vegetation index NDVI to see the connection between vegetation index data of vegetation index LSA with Landsat data. The results showed that the regression equation obtained by regression between NDVI of Landsat data and NDVI of  LSA with a significance of less than 0.05 is y = 0.732x - 0102 with a value of R2 = 0.887. Through these results we can conclude that the NDVI values on both the data related to one another.
Co-Authors Adhi Harmoko Saputro Agus Hidayat Anisa Rarasati Anugrah Indah Lestari Anugrah Indah Lestari Bisman Nababan Chulafak, Galdita Aruba Chulafak, Galdita Aruba Dede Dirgahayu Dimyati, Ratih Dewanti Dirgahayu Domiri, Dede Dominggus Samuel Helberth Lothar Matheus Koreri Awak Dwi Purwanto, Anang Erna Sri Adiningsih Esthi K Dewi Fitriani, Sarah Putri Galdita Aruba Chulafak Galdita Aruba Chulafak Hawis H Madduppa Ilyas, Turissa Pragunanti Jalu Tejo Nugroho Jalu Tejo Nugroho Jonson Lumban Gaol Jonson Lumban-Gaol Kustiyo Kustiyo, Kustiyo LILIK BUDIPRASETYO Linda Yunita Made Parsa MASITA DWI MANDINI MANESSA, MASITA DWI MANDINI Mukhoriyah Mukhoriyah, Mukhoriyah Nandika, M. Rizki nFN Zylshal Nurwita Mustika Sari Nurwita Mustika Sari Nurwita Mustika Sari Nurwita Mustika Sari Nurwita Mustika Sari, Nurwita Mustika Rachmad Wirawan Rokhmatuloh, Rokhmatuloh Sarah Putri Fitriani Sartono Marpaung, Sartono Sri Harini Teguh Prayogo Udhi C Nugroho Yati, Emi Zylshal Zylshal Zylshal Zylshal Zylshal Zylshal Zylshal Zylshal, Zylshal Zylshal, Zylshal