The accuracy of geostatistics for regional geomagnetic modeling in an archipelago setting

• Main Authors: Syirojudin, Muhamad, Haryono, Eko, Ahadi, Suaidi
• Format: Article PeerReviewed
• Language: English
• Published: Nature Research 2022
• Subjects: Geography and Environmental Sciences
• Online Access: https://repository.ugm.ac.id/282906/1/s41598-022-10362-1.pdf; https://repository.ugm.ac.id/282906/; https://api.mendeley.com/cross_publisher_access/v2/link_resolver?t=eyJlbmMiOiJBMjU2R0NNIiwiYWxnIjoiQTE5MktXIn0.I4ojzjkKudYatgUZ4_-VUx2eur7xmZKZeb-qmFM0VYAqVNvb58vVfA.Y2IKDiliAiD3_xxm.mdeTa83oNaBHbhznKFccWlOKS4OSw3D4WTO8T7bq47ofWDTgdFPL5SIFZC67CshX6mt6jkYJE3qbtddDI8oBoXqDl0Ty4AUeJAnBe62drgg-MQQ1kzopjo3nJd_2I1C_WSFy4eEPei2hY67qReNHM8uzWGIF67J4xLNSfKzNrRVv4cICQmkEKHVATiG_TovZRxZGNyncnckeQk-Wa8jloyazQSrwCmRjaVc2Rh6ZQTf3UG_RB7lm0GDc21HLjq0dwceFeRAruVedGEcLuWlLIwCqFBrYsjaRAgeAcwVeU0EO-tS4lH-lUp1Uf3VnDmCGbNt3QBm9K5wv7DajASFOmYBh3XhfxRcJrZnpNiZfgOVkOuo6XeUhcKIktQub88MIDolbMotQc2_Yt6L41QTW6N8qZa5MWcM8wvIYV6QIFK5RuIFCh931Bj5OHEAPknpyS6tY3uW5LtV1KR8l5K_ZCj79I8c.yFPTfiu0nonVIgtzL_VLUQ; https://www.scopus.com/inward/record.uri?eid=2-s2.0-85129715891&doi=10.1038%2fs41598-022-10362-1&partnerID=40&md5=f57891d12ed4e007b745f6692d152efb
• Institution: Universitas Gadjah Mada

Indonesia as an archipelago country relies on a limited number and clustered distributed repeat station networks. This paper explores the use of geostatistical modeling to overcome this data limitation. The model data set consisted of repeat station data from 1985 to 2015 epoch. The geostatistical methods utilized included ordinary kriging (OK), collocated cokriging (CC), and kriging with external drift (KED). The model generated using these geostatistical methods was then compared to spherical cap harmonic analyses (SCHA) and polynomial models. The geostatistical model was shown to perform better, with greater accuracy in declination, inclination, and total intensity, as indicated by the root mean square error (RMSE). We have demonstrated that the geostatistical method is a promising approach in the modeling of regional geomagnetic field, especially in areas with limited and clustered distributed data. © 2022, The Author(s).