Quality Control Relevance on Acquisition of Large Scale Geospatial Data to Urban Territorial Management

Filho, A. G. G.; Borba, Philipe; Silva, V. H. S.; Cerdeira, A. L.; Póz, Aluir Porfírio Dal

doi:10.1109/lagirs48042.2020.9165682

Cited by 3 publications

(2 citation statements)

References 5 publications

Supporting

Mentioning

Contrasting

Unclassified

Order By: Relevance

“…Di dalam EXIF terdapat informasi berupa pengaturan kamera, lingkungan pengambilan gambar, gambar itu sendiri serta informasi hak cipta dan informasi geografis [28]. Informasi gegorafis seperti longitude, latitude dan altitude dapat ditambahkan ke dalam file gambar [29]. Informasi-informasi tersebut disimpan dalam EXIF Header [27].…”

Section: A Geotaggingunclassified

Peningkatan Akurasi Penanganan Pengaduan Pelayanan Publik Berbasis Lokasi Pelapor Menggunakan Geolokasi

Nugroho

Basid

2022

eltikom

View full text Add to dashboard Cite

Era new normal mengharuskan segala aktivitas bersifat daring, sehingga masyarakat lebih banyak menggunakan pelayanan public. Salah satunya adalah berupa pengaduan dari masyarakat. Banyaknya pengaduan yang masuk, menyebabkan operator harus memisahkan laporan pengaduan yang benar dengan laporan pengaduan yang merupakan perbuatan jahil. Dasar pikiran pemisahan adalah kesesuaian lokasi pelapor dengan lokasi kejadian. Namun, beberapa aplikasi sering memberikan laporan berupa lokasi yang tidak akurat. Sehingga diperlukan strategi khusus, dengan memanfaatkan teknologi untuk mengetahui lokasi kejadian dengan akurat. Salah satu cara meningkatkan akurasi adalah dengan menerapkan kombinasi kombinasi teknik geotagging dan geofencing. Teknik geotagging untuk mengetahui informasi lokasi secara lengkap dan metode geofencing untuk menentukan apakah lokasi termasuk dalam lingkup sebuah wilayah. Penerapan kombinasi kedua teknik ini memberikan akurasi sebesar 96%.

show abstract

Section: A Geotaggingunclassified

Peningkatan Akurasi Penanganan Pengaduan Pelayanan Publik Berbasis Lokasi Pelapor Menggunakan Geolokasi

Nugroho

Basid

2022

eltikom

View full text Add to dashboard Cite

show abstract

“…Figure 4 presents the architectural design of the reporting system for the improvement and development of regional infrastructure. Users can submit pictures (taken directly using their built-in mobile camera or selected from the phone's gallery) through the system on their Android mobile devices [21]. After that, the process of obtaining the coordinates utilizes the user's mobile GPS [22].…”

Section: Proposed Modelmentioning

confidence: 99%

Smart-geofencing for system of reporting inadequate regional infrastructure using crossing and winding number

Basid

Nugroho

2022

IJEECS

View full text Add to dashboard Cite

Infrastructure is a <span>major factor in increasing regional productivity and become the center of economic growth. problems arise when infrastructure improvements are only centered on downtown areas. One of the ways to develop regional infrastructure is with media reporting inadequate infrastructure. The use of smartphone technology and geofencing techniques are considered to be helpful in reporting media. Increasingly sophisticated built-in features in smartphones are undeniable proof of the technology’s highly impressive advancement. Mobile applications utilizing location-based services (LBS) assisted by a global positioning systems (GPS) sensor are rapidly becoming popular. One of its most-favorited features is geofencing. The volunteered-geographic-information (VGI)-based reporting system for regional infrastructure damage uses this feature to obtain the data input directly from the users. In this current research, the author uses two methods in geofencing, including crossing number (CN) and winding number (WN). Several previous studies suggest that the combination of these methods might result in faster computation, compared to the raycasting method. By using winding and crossing number methods, 98% of increased accuracy can be obtained, while a prior method could only obtain 96%. An improvement in the system’s speed is also expected.</span>

show abstract

Deep Learning Multimodal Fusion for Road Network Extraction: Context and Contour Improvement

Filho

Shimabukuro

Póz

2023

IEEE Geosci. Remote Sensing Lett.

View full text Add to dashboard Cite

Quality Control Relevance on Acquisition of Large Scale Geospatial Data to Urban Territorial Management

Cited by 3 publications

References 5 publications

Peningkatan Akurasi Penanganan Pengaduan Pelayanan Publik Berbasis Lokasi Pelapor Menggunakan Geolokasi

Peningkatan Akurasi Penanganan Pengaduan Pelayanan Publik Berbasis Lokasi Pelapor Menggunakan Geolokasi

Smart-geofencing for system of reporting inadequate regional infrastructure using crossing and winding number

Deep Learning Multimodal Fusion for Road Network Extraction: Context and Contour Improvement

Contact Info

Product

Resources

About