Land changes detection on Rote Island using harmonic modelling method


  • Atriyon Julzarika Indonesian National Institute of Aeronautics and Space (LAPAN)
  • Nanin Anggraini
  • K Kayat Ministry for Environment and Forestry
  • Mutiaraning Pertiwi Geodesy Geomatics Engineering, Universitas Gadjah Mada (UGM)



big data engine, harmonic modelling, land changes, Rote Island


Rote Island is one of the islands in East Nusa Tenggara. In this island, land changes occur significantly. This land changes can be detected by Landsat images. These images are obtained from the big data engine. The big data engine used is the Google Earth Engine. This study aimed to detect land changes with harmonic modelling using multitemporal Landsat images from the big data engine. Harmonic modelling is used in monitoring changes in Normalized Difference Vegetation Index values in a multitemporal manner from Landsat images. Processing is done using the Geomatics approach. Land changes on Rote Island generally occur on coastal and savanna. Land changes on land generally have vertical deformation on its movement and horizontal on the savanna. The land changes accuracy result is 95% in 1,96σ. This method can be used for rapid mapping of land changes monitoring.

Author Biography

Atriyon Julzarika, Indonesian National Institute of Aeronautics and Space (LAPAN)

Remote Sensing Applications Center, LAPAN


Artis, M., Clavel, J.G., Hoffmann, M. and Nachane, D. 2007. Harmonic Regression Models: A Comparative Review with Applications. Institute for Empirical Research in Economics University of Zurich. Working Paper Series ISSN 1424-0459.

Bradley, B.A., Jacob, R.W., Hermance, J.F. and Mustard, J.F. 2007. A curve fitting procedure to derive inter-annual phenologies from time series of noisy satellite NDVI data. Remote Sensing of Environment 106(2): 137-145, doi: 10.1016/ j.rse. 2006.08.002.

Buma W.G., Lee, L.I. and Seo, J.Y. 2018. Recent Surface water extent of Lake Chad from multispectral sensors and GRACE. Sensors (Basel) 18(7): 2082, doi:10.3390/s18072082.

eCognition, 2016. Reference Book: Definiens Professional version Definiens AG. München, Germany.

François, J.P., Andrew, C. and Alan, N.G. 2016. High-resolution mapping of global surface water and its long-term changes. Nature 540: 418–422.

GEE. 2018. Google Earth Engine. Google. The United States of America.

Hermance, J.F. 2007. Stabilizing high-order, non-classical harmonic analysis of NDVI data for average annual models by damping model roughness. International Journal of Remote Sensing 28(12): 2801-2819, 10.1080/01431160600967128.

Julzarika, A., Laksono, D.P., Subehi, L., Dewi, E.K., Kayat, Sofiyuddin, H.A. and Nugraha, M.F.I. 2018. Comprehensive integration system of saltwater environment on Rote Island using a multidisciplinary approach. Journal of Degraded and Mining Lands Management 6(1): 1553-1567, DOI: 10.15243/jdmlm. 2018.061.1553.

Julzarika, A. 2018. Mining land identification in Wetar Island using remote sensing data. Journal of Degraded and Mining Lands Management 6(1): 1513-1518, DOI: 10.15243/jdmlm. 2018.061.1513.

Julzarika, A. and Dewi, E.K. 2018. ALOS PALSAR DTM vertical accuracy test for DGNSS-Altimeter combination measurements. Jurnal of Penginderaan Jauh dan Pengolahan Data Citra Digital 15(1): 11-24,

Karimi, P. and Bastiaanssen, W.G. 2015. Spatial evapotranspiration, rainfall and land use data in water accounting—Part 1: Review of the accuracy of the remote sensing data. Hydrology and Earth System Sciences19: 507–532.

Kumay, D.U. 2015. Remote sensing platforms and sensor. NBKRIST Vidyanagar. India.

Nikodemus, P.N., Susanto, S. and Sudira, P. 2004. Water resource prediction on a small island: a case study on Rote Island, East Nusa Tenggara. Jurnal Manusia dan Lingkungan 11(2):55-63 (in Indonesian).

Pratisto, A. and Danoedoro, P. 2008. The impact of land use changes against flood discharge and flood hazard (case study in Gesing Watershed, Purworejo, based on Landsat TM and ASTER VNIR image. Proceedings of the Annual Scientific Meeting of the Indonesian Remote Sensing Society (PIT-MAPIN), Bandung.

Priasty, E.W. 2014. Analysis of the impact of changes in land use of watersheds in North Bengkulu Regency. Jurnal of Bengkulu Mandiri 4 January 2014 (in Indonesian).

Rote Ndao Regency, 2018. Rote Ndao Regency Official Website. Retrieved June 9, 2018, from Rote Ndao Regency (in Indonesian).

Suroso and Susanto H.A. 2006. Effect of changes in land use against the flood discharge of the Banjaran River basin. Jurnal Teknik Sipil 3(2):75-80 (in Indonesian).

Tang, G., Long, D. and Hong, Y. 2016. Systematic anomalies over inland water bodies of High Mountain Asia in TRMM precipitation estimates: No longer a problem for the GPM era?IEEE Geoscience and Remote Sensing Letters 13: 1762–1766.

Trisakti, B., Julzarika, A. and Dewi, E.K. 2016. Utilization of Standards for the Use of Remote Sensing Data for Monitoring Land Changes. Report activities on remote sensing applications centre, LAPAN, Jakarta (in Indonesian).

United States of Geological Survey (USGS). 2018. Landsat Mission. USGS. Retrieved on July 2018. Amerika Serikat.

Zitierung, E., Wright, C. and Lewis, B. 2012. On the edge of crisis: contending perspectives on development, tourism, and community participation on Rote Island, Indonesia. ASEAS-Österreichische Zeitschrift Für Südostasienwissenschaften 5(1): 102–127.








How to Cite

Julzarika, A., Anggraini, N., Kayat, K., & Pertiwi, M. (2019). Land changes detection on Rote Island using harmonic modelling method. Journal of Degraded and Mining Lands Management, 6(3), 1719–1725.



Research Article