A comparative accuracy of Google Earth height with MyGeoid, EGM96 and MSL

Rusli, Noradila; Pa’suya, Muhammad Faiz; Talib, Noorfatekah

doi:10.1088/1755-1315/37/1/012003

Cited by 6 publications

(5 citation statements)

References 2 publications

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“…Since the elevation data supplied by Google Earth still does not have the required accuracy [79][80][81][82][83], the elevation of the GCPs was estimated using a procedure that took advantages of Timex images properties. As seen in Section 1.2, the high-frequency swash oscillation on the beach is average out on Timex, therefore these images have been extensively used to identify the shoreline as land-water interface.…”

Section: Methods 2-remote Acquisition Of Gcpsmentioning

confidence: 99%

Operational Use of Surfcam Online Streaming Images for Coastal Morphodynamic Studies

2019

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Coastal video monitoring has been proven to be a valuable shore-based remote-sensing technique to study coastal processes, as it offers the possibility of high-frequency, continuous and autonomous observations of the coastal area. However, the installation of a video systems infrastructure requires economical and technical efforts, along with being often limited by logistical constraints. This study presents methodological approaches to exploit “surfcam” internet streamed images for quantitative scientific studies. Two different methodologies to collect the required ground control points (GCPs), both during fieldwork and using web tools freely available are presented, in order to establish a rigorous geometric connection between terrestrial and image spaces. The application of an image projector tool allowed the estimation of the unknown camera parameters necessary to georectify the online streamed images. Three photogrammetric procedures are shown, distinct both in the design of the computational steps and in number of GCPs available to solve the spatial resection system. Results showed the feasibility of the methodologies to generate accurate rectified planar images, with the best horizontal projection accuracy of 1.3 m compatible with that required for a quantitative analysis of coastal processes. The presented methodologies can turn “surfcam” infrastructures and any online streaming beach cam, into fully remote shore-based observational systems, fostering the use of these freely available images for the study of nearshore morphodynamics.

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Section: Methods 2-remote Acquisition Of Gcpsmentioning

confidence: 99%

Operational Use of Surfcam Online Streaming Images for Coastal Morphodynamic Studies

2019

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“…Peta lokasi penelitian dan persebaran titik sampel penelitian Analisis data dilakukan dengan melakukan memperbaiki hasil digitasi dari Survei Lapangan dengan GPS menggunakan Sistem Informasi Geografis (Bachtiar et al, 2014;Abidin, 2021;Bharata et al, 2021). Karakteristik Jalur Trekking di analisis menggunakan Digital Elevation Height dari perangkat lunak Google Earth Pro (Rusli & Majid, 2012;Rusli et al, 2014;Tîrlă et al, 2014;Rusli et al, 2016;El-Ashmawy, 2016;Wang et al, 2017;Kurniawan et al, 2020;Bharata et al, 2021;Yanti et al, 2022) dan QGIS (Lestariani et al, 2018;Yanti et al, 2022;Bharata et al, 2022) untuk mengisi atribut data berupa Beda Tinggi, Jarak Miring, Kelerengan, Relief, dan Waktu Tempuh (Lailissaum et al, 2013;Bachtiar et al, 2014;Yudhi et al, 2018;Bharata et al, 2021;Yanti et al, 2022). Sumber data ketinggian yang terdapat dari Google Earth Pro memiliki sumber data yang tidak diketahui, namun memiliki akurasi yang cukup tinggi (Rusli dkk, 2014;El-Ashmawy, 2016;Wang dkk, 2017).…”

Section: Metodeunclassified

“…Berkenaan dengan Karakteristik kelima Jalur Trekking tersebut dalam penelitian ini diukur melalui Survei Lapangan dengan GPS untuk mendapatkan data Jalur beserta waktu keberangkatan dan sampainya. Selanjutnya dilakukan pengolahan data melalui Sistem Informasi Geografis dengan Google Earth Pro untuk melihat Profil Jalur yang menampilkan Digital Elevation Height dengan mengaktifkan fitur Medan (Terrain) (Rusli & Majid, 2012;Rusli et al, 2014;Tîrlă et al, 2014;Rusli et al, 2016;El-Ashmawy, 2016;Wang et al, 2017;Kurniawan et al, 2020;Bharata et al, 2021;Yanti et al, 2022) dan memasukan Atribut data pada QGIS (Lailissaum et al, 2013;Bachtiar et al, 2014;Yudhi et al, 2018;Bharata et al, 2021;Yanti et al, 2022). Karakteristik Jalur yang di deskripsikan meliputi Beda Tinggi, Jarak Miring, Kelerengan, Relief, dan Waktu Tempuh (Lailissaum et al, 2013;Bachtiar et al, 2014;Yudhi et al, 2018;Bharata et al, 2021;Yanti et al, 2022).…”

Section: Hasil Dan Pembahasanunclassified

Karakteristik Jalur Trekking Sebagai Potensi Landskap Wisata Alam di Desa Panji Anom

Bharata,

Wesnawa,

Astawa

2023

JJPG

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Penelitian ini dilaksanakan di Jalur Trekking yang dirintis di kawasan Wisata Alam Panorama Puncak Landep, Desa Panji Anom yang memiliki Potensi Daya Tarik Wisata pemandangan alam di Bali Utara. Tujuan penelitian ini adalah: (1) untuk mendeskripsikan Karakteristik Jalur Trekking yang ada di kawasan Wisata Alam Panorama Puncak Landep, dan (2) untuk mendeskripsikan Potensi Landskap yang ada di sepanjang setiap Jalur Trekking yang ada di kawasan Wisata Alam Panorama Puncak Landep. Penelitian dirancang sebagai penelitian deskriptif dengan pendekatan keruangan. Data diperoleh melalui survei lapangan dengan Mobile GPS, dan Observasi Lapangan. Hasil penelitian menunjukkan bahwa: (1) karakteristik Jalur Trekking yang terdapat di kawasan Wisata Alam Panorama Puncak Landep dapat dikelompokkan menjadi tiga, yaitu Titik Potensi Tinggi (Beda Tinggi = Rata-Rata 64 meter, Jarak Miring = Rata-Rata 405 meter, Kelerengan = Rata-Rata 15,8% – 17,3%, Relief = Miring Sedang, Waktu Tempuh = Rata-Rata ± 20 Menit), Titik Potensi Sedang (Beda Tinggi = Rata-Rata 79 meter, Jarak Miring = Rata-Rata 586 meter, Kelerengan = Rata-Rata 15% – 22%, Relief = Miring Sedang – Miring Terjal, Waktu Tempuh = Rata-Rata ± 28 Menit), Titik Potensi Rendah (Beda Tinggi = Rata-Rata 103 meter, Jarak Miring = Rata-Rata 897 meter, Kelerengan = Rata-Rata 11,8% – 21,6%, Relief = Miring Sedang – Miring Terjal, Waktu Tempuh = Rata-Rata ± 40 Menit), (2) Potensi Landskap yang terdapat pada masing-masing Jalur Trekking di kawasan Wisata Alam Panorama Puncak Landep dapat dikategorikan menjadi tiga, yaitu potensi tinggi dengan bentuk, vegetasi, dan warna sebagai factor dominan; potensi sedang dengan bentuk, vegetasi, dan warna sebagai faktor dominan; potensi rendah dengan bentuk, pemandangan, kelangkaan dan modifikasi struktural sebagai faktor dominan.

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“…Historical data on rainfall near Ketapang averages 2892 mm per year [27], while the annual temperature averages 27.3 • C (from 1982 to 2012). The study area has a range of elevation above mean sea level from 10 to 24 m [28].…”

Section: Study Sitementioning

confidence: 99%

Land Cover and Land Use Change Decreases Net Ecosystem Production in Tropical Peatlands of West Kalimantan, Indonesia

Basuki

Kauffman

Peterson

et al. 2021

Forests

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Deforested and converted tropical peat swamp forests are susceptible to fires and are a major source of greenhouse gas (GHG) emissions. However, information on the influence of land-use change (LUC) on the carbon dynamics in these disturbed peat forests is limited. This study aimed to quantify soil respiration (heterotrophic and autotrophic), net primary production (NPP), and net ecosystem production (NEP) in peat swamp forests, partially logged forests, early seral grasslands (deforested peat), and smallholder-oil palm estates (converted peat). Peat swamp forests (PSF) showed similar soil respiration with logged forests (LPSF) and oil palm (OP) estates (37.7 Mg CO2 ha−1 yr−1, 40.7 Mg CO2 ha−1 yr−1, and 38.7 Mg CO2 ha−1 yr−1, respectively), but higher than early seral (ES) grassland sites (30.7 Mg CO2 ha−1 yr−1). NPP of intact peat forests (13.2 Mg C ha−1 yr−1) was significantly greater than LPSF (11.1 Mg C ha−1 yr−1), ES (10.8 Mg C ha−1 yr−1), and OP (3.7 Mg C ha−1 yr−1). Peat swamp forests and seral grasslands were net carbon sinks (10.8 Mg CO2 ha−1 yr−1 and 9.1 CO2 ha−1 yr−1, respectively). In contrast, logged forests and oil palm estates were net carbon sources; they had negative mean Net Ecosystem Production (NEP) values (−0.1 Mg CO2 ha−1 yr−1 and −25.1 Mg CO2 ha−1 yr−1, respectively). The shift from carbon sinks to sources associated with land-use change was principally due to a decreased Net Primary Production (NPP) rather than increased soil respiration. Conservation of the remaining peat swamp forests and rehabilitation of deforested peatlands are crucial in GHG emission reduction programs.

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A comparative accuracy of Google Earth height with MyGeoid, EGM96 and MSL

Cited by 6 publications

References 2 publications

Operational Use of Surfcam Online Streaming Images for Coastal Morphodynamic Studies

Operational Use of Surfcam Online Streaming Images for Coastal Morphodynamic Studies

Karakteristik Jalur Trekking Sebagai Potensi Landskap Wisata Alam di Desa Panji Anom

Land Cover and Land Use Change Decreases Net Ecosystem Production in Tropical Peatlands of West Kalimantan, Indonesia

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