JOURNAL OF DEGRADED AND MINING LANDS MANAGEMENT ISSN: 2339-076X (p); 2502-2458 (e), Volume 6, Number 3 (April 2019):1719-1725 DOI:10.15243/jdmlm.2019.063.1719

Research Article

Land changes detection on using harmonic modelling method

Atriyon Julzarika1,2*, Nanin Anggraini1, Kayat3, Mutiaraning Pertiwi2 1 Indonesian National Institute of Aeronautics and Space (LAPAN), 2 Geodesy Geomatics Engineering, Universitas Gadjah Mada (UGM), Indonesia 3 Ministry of Environment and Forestry (KLHK), Indonesia *corresponding author: [email protected] Received 14 January 2019, Accepted 9 February 2019

Abstract: Rote Island is one of the islands in . 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. Keywords: big data engine, harmonic modelling, land changes, Rote Island To cite this article: Julzarika, A., Anggraini, N., Kayat, and Pertiwi, M. 2019. Land changes detection on Rote Island using harmonic modelling method. J. Degrade. Min. Land Manage. 6(3): 1719-1725, DOI: 10.15243/jdmlm. 2019.063.1719.

Introduction a lot of uniqueness when viewed from various aspects including geology, culture, ecology, and Remote sensing data has evolved from water resources. However, this uniqueness is not conventional to dynamic (Kumay, 2015). One yet comprehensively utilized and explored because example of this dynamic data is the big data engine. there are not many studies and researches Big data includes remote sensing optical and radar conducted in this area. The Integration System sensor data. Some examples of images contained in Development Activity Through a Multidisciplinary big data engines are Landsat, Sentinel, ALOS Approach to Natural Resource Mapping and the PALSAR, WorldView, Ikonos, GeoEye, Environment is expected to open up insight into the QuickBird, MODIS, and others. In addition to the uniqueness and provide preliminary data for big data engine, there are also various thematic further management (Julzarika et al., 2018). information and algorithm making according to Natural Resources and the environment on Rote user application needs. The big data engine is also Island experienced insignificant changes. facilitated in the initial processing, extraction of Generally, changes are caused by steppe and geobiophysical information, to the presentation of savanna environments. In addition, it is also caused spatial information. This big data engine is by vertical deformation or the appointment of Rote dynamic and fast in its processing that depends on Island due to geological activity with the the internet and cloud data. One of the uses of this Australian plate degraded, both in quantity and big data engine is in the field of inland water quality. Geographical position and topographic resources, especially lakes. Rote Island is one of shape cause Rote Island have very diverse the outermost regions in Indonesia. This island has www.jdmlm.ub.ac.id 1719

Land changes detection on Rote Island using harmonic modeling method biodiversity. Likewise, the geological structure of Material and Methods Rote Island causes a variety of natural formations that are very interesting and have quite high This study uses data from the big data engine in the tourism potential. Among the uniqueness found on form of Landsat. Big data Engine is a platform for Rote Island are a number of lakes scattered petabyte-scale scientific analysis and visualization throughout the Rote Island region, from the west to of geospatial datasets, both for the public interest the east. Some lakes on Rote Island have a unique, and for business and government users. Big Data very high salinity content making some of these Engine stores satellite imageries, manages it and lakes as dead sea lakes (Nikodemus et al., 2004). makes it available for the first time for global scale The condition of the saltwater lake also allows the data mining. Public data archives cover the images development of various unique animal and plant of the historical earth that has existed for more than species, thus increasing the overall biological forty years, and new images are collected every richness of Rote Island (Zitierung et al., 2012). day. Big data Engine also provides Application Rote Island have dead sea lake areas. This Program Interface (APIs) in JavaScript and Python, area has more than 15 saltwater lakes. The as well as other tools, to enable analysis of large saltwater lakes are like Lake Oemasapoka, datasets (GEE, 2018). Oeinalaen, and others. This area also has higher Landsat is a satellite owned by the United vertical deformation which causes the potential to States of Geological Survey (USGS) which has a form a new salty lake around the "Mulut Seribu" mission to survey geological and natural resource area. Vertical deformation factor is one of the mapping (USGS, 2018). Currently, Landsat has causes of land changes in this region. This area also entered the eighth generation. In the big data has a variety of endemic flora and fauna and still engine, there are Landsat 1, Landsat 2, Landsat 3, lacks research exploration in this area (Julzarika et Landsat 4, Landsat 5, Landsat 7, and Landsat 8 al., 2018). images. Landsat images began in 1972 and still Land changes as a consequence of increased continue today (Trisakti et al., 2016). demand for space have various forms. One way to Geographically, Rote Island is located at 10° eliminate land changes due to environmental 25'- 11° 00' South Latitude and 121° 49'- 123° 26' degradation (Pratisto and Danoedoro, 2008). It is East Longitude (Rote Ndao District, 2018). Rote is necessary to build and grow awareness and concern one of the islands in East Nusa Tenggara which has from the elements of the government, society and unique geological and biodiversity characteristics. the business world so that they can participate in This geographical position causes Rote Island to be tackling the problem of environmental degradation the southernmost island of the Republic of in accordance with their respective capacities and Indonesia. Rote Island itself consists of at least 94 capabilities (Buma et al., 2018) ; (Tang, et al., large and small islands that are included in the area 2016). These factors affect the land changes on of Rote Ndao , see figure 1 (Rote Ndao Rote Island. The grassland ecosystem on Rote Regency, 2018). Island is very vulnerable and affects environmental variables both in terms of geophysical-chemical, biological, socio-economic and cultural aspects as well as aspects of public health. Grassland ecosystems that have their own peculiarity from other regions in Indonesia and in the world because this grassland ecosystem is formed in dry climatic conditions with a hilly and wavy topography (Karimi and Bastiaanssen, 2015). Common causes of land changes are found in various cases in the world. Economic development can be seen simply from the increased purchasing power of the people (Suroso and Susanto, 2006; François et al., 2016). This increase in purchasing Figure 1. Rote Island power was responded by increasing facilities, infrastructure, as well as things needed by the The method used in this study is the Harmonic community (Priasty, 2014). The land changes Modeling method. The Geomatics approach is used discussed in this study are land changes on Rote to land changes detection. Geomatics approach is Island. This study aims to detect land changes with used to its processing in big data engine. Harmonic harmonic modelling using multitemporal Landsat modelling method is the main method on its images from big data engine. processing.

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Land changes detection on Rote Island using harmonic modeling method

Data in the form of satellite images is obtained by composite value, n is the cycle length, and m is the the big data engine. Big data engine in this paper is polynomial sequence and is equal to the number of Google Earth Engine (GEE). The data used is harmonics in the approximation. Timestamp when Landsat images. Landsat data began from 1972- Landsat images are stored as milliseconds since the present. Then all of the Landsat data is focused on beginning of time (January 1, 1970) and converted Rote Island. All Landsat data is processed to to ephemeris day. Value of 365,242,181 days of monitor changes on Rote Island. The method used ephemeris per tropical year is used as the duration is harmonic modelling. The results obtained from of the annual cycle. Regression models with one to this big data engine are land changes on Rote four harmonics (i.e. the first sequence to the fourth Island. Field validation needs to be done to sequence of the Fourier series) are tested to determine the accuracy of information on land determine the shape of the model that gives the best changes on Rote Island. The flow chart of this match to the data without introducing false research can be seen in Figure 2. oscillations recorded by Hermance (2007) and Bradley et al. (2007). This harmonic process is only used for evaluation of harmonic regression models, and not as additional data.

… (2) where: DOY : Day of the Year GB : the beginning of image acquisition with certain assumptions GE : the end of image acquisition with certain assumptions t : the relative time (less dimension) at the time of acquisition n : the total number of harmonics j : the number of harmonic terms a0, bj, : are harmonic coefficients that are cj calculated using the standard

• a small f is used rather than F ∗ only to distinguish the DOY function from the function of the normalization time t; Figure 2. Research flowchart • modM means modulo M operation, which makes sense for areas where GB is larger than GE (for Land changes can be extracted using harmonic example, in the Southern Hemisphere); M = 365 in modelling methods. Harmonic modelling is a our case because 365 is the longest time interval method in big data engine to detect the land between two different days in a year. changes. This method is Ordinary least squares (OLS) Regression (Julzarika, 2018). OLS regression is used to adjust separate Fourier series Results and Discussion (eCognition, 2016). A Fourier series form based on that presented in (Artis et al., 2007) used in the Landsat images on Rote Island used are already analysis. Each time series of data is estimated as corrected in geometry and radiometry. The trigonometric polynomials, geometry of Landsat images is more stable between images because the sensor is fixed. Radiometric from big data (Landsat) is in Surface Reflectance (SR). ....(1) The next process is making thematic maps. It Where coefficients a0, b1, ..., bn are specified in is created vegetation index maps from formula (2). Parameter t is the timestamp multitemporal and multi data from Landsat in big Journal of Degraded and Mining Lands Management 1721

Land changes detection on Rote Island using harmonic modeling method data engine. This vegetation index map is created is used because representing water, land, and by the Normalized Difference Vegetation Index dynamic land mathematically. (NDVI) method. This aims to determine changes in Checking water and land boundaries need to vegetation and non-vegetation in the study area. be done first. Then the land changes checking is This condition will facilitate the harmonic carried out in areas that have varying NDVI values. modelling process so that it can know the area that If the NDVI value does not vary, the objects in the is undergoing change. The harmonic modelling field are relatively fixed, whereas if the NDVI used in this big data (Landsat) is degree 1, see value changes drastically then the region Figure 3. This Harmonic modelling use equation 1 experiences drastic land changes. Every NDVI that and equation 2. Harmonic modelling is useful in experiences a change in value on temporal data is the detection of land changes from multi-temporal then fitted with a value. The geometry of this stable and multi data. Degree 1 from harmonic modelling Landsat images will affect the fitted NDVI.

Figure 3. Harmonic modelling using Landsat multitemporal in land area

Checking is done simply by checking the land near been made geometric and radiometric corrections. the edge of Rote Island and the water near the edge Harmonic modelling uses degrees 1. The fixed of Rote Island. The boundary remains in the NDVI boundary of the lake and sea lies in black (image). value (harmonic modelling) close to 0. In this big The land is separated with water firmly according data (Landsat), the island fixed boundary is more to the red colour chart. suitable to use level 1 harmonic modelling. This If we see a detail of the land changes images, can be proven by land and water graphs used in it can be seen that there are some fundamental harmonic modelling of lake boundary changes. Such changes such as the addition of new determination. land and there have been low vegetation (light This land graph aims to find out that the green), changes in vegetation height (dark green), location of the point is on land. This is marked from changes in vegetation to settlements (purple), and a graph pattern based on harmonic modelling white-beige on the newly raised land see Figure 5. degrees 1. These restrictions will be separated on Land changes on Rote Island grow the graph for land and water. The fixed boundary significantly; generally occur in the steppe and of the island lies in black (image). The land is savanna regions. Settlement growth did not separated with water firmly according to the red increase significantly. In addition, it is also colour chart. indicated that there is an addition of new land due The land is separated with water firmly to vertical deformation, especially on Coastal Rote, according to the red colour chart. Other checks are see Figure 5 in a very light green colour. Overall also needed on the water graph, namely the the land changes dominate the coastal and savanna location of the point in the water adjacent to the of Rote Island, see Figure 6. Land changes on Rote land, see figure 4. In this water graph analysis also Island generally consist of vertical deformation on uses big data (Landsat) in 1972-2018. The data has its movement and horizontal on the savanna.

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Land changes detection on Rote Island using harmonic modeling method

Figure 4. Harmonic modelling using Landsat multitemporal in water area

Figure 1. Vertical deformation on Coastal Rote

Figure 6. The sample area of land changes using harmonic modelling

Accuracy tests are of two types namely horizontal conducted in August 2018. Geostatically, the test accuracy and vertical accuracy (Julzarika and sample met tolerance. Locations that are not Dewi, 2018). In this study using horizontal suitable occur in the savanna area when the survey accuracy test. Accuracy testing is done by was very dry. This savanna is generally in the form comparing the results of land changes with of syncline and anti-syncline, see Figure 7. conditions in the field. The field survey was

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Land changes detection on Rote Island using harmonic modeling method

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 Figure 7. Savanna as the main cause of land Professional version 5.0.6.2. Definiens AG. changes on Rote Island München, Germany. François, J.P., Andrew, C. and Alan, N.G. 2016. High- resolution mapping of global surface water and its The method of testing accuracy is to compare the long-term changes. Nature 540: 418–422. results of land changes from the big data engine GEE. 2018. Google Earth Engine. Google. The United with field data. This accuracy test uses a States of America. confidence level of 95% (1,96σ). The land changes Hermance, J.F. 2007. Stabilizing high-order, non- accuracy result is 95%. The results of land changes classical harmonic analysis of NDVI data for generally occur in the Savanna area. This accuracy average annual models by damping model test is processed in the big data engine. This roughness. International Journal of Remote Sensing method can be used for rapid mapping of land 28(12): 2801-2819, doi:10.1080/ changes monitoring. 01431160600967128. Julzarika, A., Laksono, D.P., Subehi, L., Dewi, E.K., Kayat, Sofiyuddin, H.A. and Nugraha, M.F.I. 2018. Conclusion Comprehensive integration system of saltwater environment on Rote Island using a Land changes on Rote Island can be detected using multidisciplinary approach. Journal of Degraded multitemporal Landsat images from big data and Mining Lands Management 6(1): 1553-1567, engine. The land changes use harmonic modelling doi: 10.15243/jdmlm. 2018.061.1553. method in Geomatics approach. In this paper, we Julzarika, A. 2018. Mining land identification in Wetar Island using remote sensing data. Journal of use Google Earth Engine for its big data engine. Degraded and Mining Lands Management 6(1): The land changes dominate the coastal and savanna 1513-1518, doi: 10.15243/jdmlm. 2018.061.1513. of Rote Island. Land changes on Rote land Julzarika, A. and Dewi, E.K. 2018. ALOS PALSAR generally consist of vertical deformation on its DTM vertical accuracy test for DGNSS-Altimeter movement and horizontal on the savanna. In combination measurements. Jurnal of addition, there were also changes in savanna and Penginderaan Jauh dan Pengolahan Data Citra steppe in the dry and rainy seasons. Multitemporal Digital 15(1): 11-24, doi:10.30536/ Landsat data can be used for land changes. The j.pjpdcd.2018.v15.a2804 land changes accuracy result is 95% in 1,96σ. This Karimi, P. and Bastiaanssen, W.G. 2015. Spatial evapotranspiration, rainfall and land use data in method can be used for rapid mapping of land water accounting—Part 1: Review of the accuracy of changes monitoring. the remote sensing data. Hydrology and Earth System Sciences19: 507–532. Kumay, D.U. 2015. Remote sensing platforms and Acknowledgement sensor. NBKRIST Vidyanagar. India. The authors wish to thank Ministry of Research, Nikodemus, P.N., Susanto, S. and Sudira, P. 2004. Water Technology, and Higher Education, Universitas Gadjah resource prediction on a small island: a case study on Mada, LAPAN, LIPI, Ministry for Public Works and Rote Island, East Nusa Tenggara. Jurnal Manusia Public Housing, Ministry of Environment and Forestry, dan Lingkungan 11(2):55-63 (in Indonesian). Ministry for Marine and Fisheries, local government, Pratisto, A. and Danoedoro, P. 2008. The impact of land and local residents in supporting this research project. use changes against flood discharge and flood hazard Atriyon Julzarika is the main contributor to this paper. (case study in Gesing Watershed, Purworejo, based on Landsat TM and ASTER VNIR image. Proceedings of the Annual Scientific Meeting of the References Indonesian Remote Sensing Society (PIT-MAPIN), Bandung. Artis, M., Clavel, J.G., Hoffmann, M. and Nachane, D. Priasty, E.W. 2014. Analysis of the impact of changes in 2007. Harmonic Regression Models: A Comparative land use of watersheds in North Bengkulu Regency. Review with Applications. Institute for Empirical Jurnal of Bengkulu Mandiri 4 January 2014 (in

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