Registration of interferometric DEM by deep artificial neural networks using GPS control points coordinates as network target

Ahmed Serwa; Abdul Baser Qasimi; Vahid Isazade

Makale detayları

Registration of interferometric DEM by deep artificial neural networks using GPS control points coordinates as network target

Yazarlar:

Ahmed Serwa | Abdul Baser Qasimi | Vahid Isazade

Yayıncı:

Murat YAKAR

Ana Başlıklar:

Photogrammetry and Remote Sensing

Dergi:

International Journal of Engineering and Geosciences Vol.9 Issue 2, pp.292-301

Belge Tipi:

Makale

Yayın Tarihi:

7/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001323619

pISSN:

2548-0960

Anahtar kelimeler:

Özet:

 The interferometric Shuttle Radar Topography Mission SRTM satellites digital elevation model DEM is an important tool for studying topographic features on a medium-spacing scale. Data were collected and processed using the satellites orbital and navigation parameters with selected global GPS stations for verification. Distortion may be expressed by surveying measurements, such as position, distance, area, and shape. This study focuses on this distortion and proposes a new registration method to reduce its effect. Because of generality, the purpose shapes were excluded from this study. The proposed registration method depends on precise GPS control points that act as the ground truth for describing the considered surveying measurements. The processing was carried out using deep artificial neural networks DANN to produce a new registered DEM. A comparison was made between the original DEM and the new one, focusing on the selected surveying measurements. Another comparison was made between the GPS coordinates and SRTM polynomials to determine the potential of the proposed system. Some statistical investigations were applied to determine the level of significance of the distortion in each surveying measurement. The study shows that the distortion is highly significant; therefore, the proposed registration method is recommended to fix the distortion. An important finding is the enhancement in local coordinates scope.

 The interferometric Shuttle Radar Topography Mission SRTM satellites digital elevation model DEM is an important tool for studying topographic features on a medium-spacing scale. Data were collected and processed using the satellites orbital and navigation parameters with selected global GPS stations for verification. Distortion may be expressed by surveying measurements, such as position, distance, area, and shape. This study focuses on this distortion and proposes a new registration method to reduce its effect. Because of generality, the purpose shapes were excluded from this study. The proposed registration method depends on precise GPS control points that act as the ground truth for describing the considered surveying measurements. The processing was carried out using deep artificial neural networks DANN to produce a new registered DEM. A comparison was made between the original DEM and the new one, focusing on the selected surveying measurements. Another comparison was made between the GPS coordinates and SRTM polynomials to determine the potential of the proposed system. Some statistical investigations were applied to determine the level of significance of the distortion in each surveying measurement. The study shows that the distortion is highly significant; therefore, the proposed registration method is recommended to fix the distortion. An important finding is the enhancement in local coordinates scope.

 The interferometric Shuttle Radar Topography Mission SRTM satellites digital elevation model DEM is an important tool for studying topographic features on a medium-spacing scale. Data were collected and processed using the satellites orbital and navigation parameters with selected global GPS stations for verification. Distortion may be expressed by surveying measurements, such as position, distance, area, and shape. This study focuses on this distortion and proposes a new registration method to reduce its effect. Because of generality, the purpose shapes were excluded from this study. The proposed registration method depends on precise GPS control points that act as the ground truth for describing the considered surveying measurements. The processing was carried out using deep artificial neural networks DANN to produce a new registered DEM. A comparison was made between the original DEM and the new one, focusing on the selected surveying measurements. Another comparison was made between the GPS coordinates and SRTM polynomials to determine the potential of the proposed system. Some statistical investigations were applied to determine the level of significance of the distortion in each surveying measurement. The study shows that the distortion is highly significant; therefore, the proposed registration method is recommended to fix the distortion. An important finding is the enhancement in local coordinates scope.

 The interferometric Shuttle Radar Topography Mission SRTM satellites digital elevation model DEM is an important tool for studying topographic features on a medium-spacing scale. Data were collected and processed using the satellites orbital and navigation parameters with selected global GPS stations for verification. Distortion may be expressed by surveying measurements, such as position, distance, area, and shape. This study focuses on this distortion and proposes a new registration method to reduce its effect. Because of generality, the purpose shapes were excluded from this study. The proposed registration method depends on precise GPS control points that act as the ground truth for describing the considered surveying measurements. The processing was carried out using deep artificial neural networks DANN to produce a new registered DEM. A comparison was made between the original DEM and the new one, focusing on the selected surveying measurements. Another comparison was made between the GPS coordinates and SRTM polynomials to determine the potential of the proposed system. Some statistical investigations were applied to determine the level of significance of the distortion in each surveying measurement. The study shows that the distortion is highly significant; therefore, the proposed registration method is recommended to fix the distortion. An important finding is the enhancement in local coordinates scope.

Makale detayları

Registration of interferometric DEM by deep artificial neural networks using GPS control points coordinates as network target

Yazarlar:

Ahmed Serwa | Abdul Baser Qasimi | Vahid Isazade

Yayıncı:

Murat YAKAR

Ana Başlıklar:

Photogrammetry and Remote Sensing

Dergi:

International Journal of Engineering and Geosciences Vol.9 Issue 2, pp.292-301

Belge Tipi:

Makale

Yayın Tarihi:

7/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001323619

pISSN:

2548-0960

Remote sensing

DEM

Registration

Distortion

Sayı

Makale detayları

Registration of interferometric DEM by deep artificial neural networks using GPS control points coordinates as network target

Yazarlar: Ahmed Serwa | Abdul Baser Qasimi | Vahid Isazade

Yayıncı: Murat YAKAR

Ana Başlıklar: Photogrammetry and Remote Sensing

Dergi: International Journal of Engineering and Geosciences Vol.9 Issue 2, pp.292-301

Belge Tipi: Makale

Yayın Tarihi: 7/2024

Belge Dili: İngilizce

Document ID (Org No.): 2001323619

pISSN: 2548-0960

Remote sensing

DEM

Registration

Distortion

Sayı

Yazarlar:

Ahmed Serwa | Abdul Baser Qasimi | Vahid Isazade

Yayıncı:

Murat YAKAR

Ana Başlıklar:

Photogrammetry and Remote Sensing

Dergi:

International Journal of Engineering and Geosciences Vol.9 Issue 2, pp.292-301

Belge Tipi:

Makale

Yayın Tarihi:

7/2024

Belge Dili:

İngilizce

Document ID (Org No.):

2001323619

pISSN:

2548-0960