Height Model Integration using ALOS PALSAR, X SAR, SRTM C, AND ICESAT/GLAS

Atriyon Julzarika (2015) Height Model Integration using ALOS PALSAR, X SAR, SRTM C, AND ICESAT/GLAS. International Journal of Remote Sensing and Earth Sciences, 12 (2). pp. 107-116. ISSN 0216-6739

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Abstract

The scarcity of height models is one of the important issues in Indonesia. ALOS PALSAR, X SAR, SRTM C, and ICESAT/GLAS are free available global height models. Four data can be integrated the height models. Integration takes advantage of each characteristic data. The spatial resolution uses ALOS PALSAR. ICESAT/GLAS has a minimal height error because it is DTM. SAR has advantages of minimal error in the highland and need a low pass filter on the lowland. DSM uses X SAR and DEM from ALOS PALSAR. Characteristics and penetration of vegetation objects can be seen from the wavelength type of SAR data. This research aims to make height model integration in order to get the vertical accuracy better than vertical accuracy of global height models and minimum height error. The study area is located in Karo Regency. The first process is to crop the height models into Karo Regency, geoid undulation correction using EGM 2008. The next step is to detect pits and spires by using radius value 1000 m and depth +1.96σ (+5 m) with uncertainty 95,45%. Then generate HEM and height model integration. To know the accuracy of this height model, 100 reference points measured using GNSS, altimeter, and similar point observed on the height model integration are selected. The accuracy test covers RMSE, accuracy (z), and height difference test. The result of this study shows that the height model integration has a vertical accuracy in 1.14 m. This height model integration can be used for mapping scale 1: 10.0000.

Item Type: Article
Uncontrolled Keywords: integration, height model, SAR data, scale 1:10.000
Subjects: Taksonomi LAPAN > Teknologi Penginderaan Jauh > Penelitian, Pengkajian, dan Pengembangan > Pemanfaatan Penginderaan Jauh > Pengolahan Data > Klasifikasi
Divisions: LAPAN > Deputi Penginderaan Jauh > Pusat Pemanfaatan Penginderaan jauh
Depositing User: Administrator Repository
Date Deposited: 03 Sep 2021 00:36
Last Modified: 20 Jul 2022 07:51
URI: https://karya.brin.go.id/id/eprint/10985

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