Comparative Study on NDVI with RVI for Estimated Area and Class Distribution

  • I Made Yuliara Udayana University, Denpasar, Indonesia
  • Ni Nyoman Ratini Udayana University, Denpasar, Indonesia
  • I Gde Antha Kasmawan Udayana University, Denpasar, Indonesia
Keywords: class distribution, comparative study, estimated area, NDVI, RVI

Abstract

This study aims to determine the differences and comparison of the results of the estimated area, the distribution of clove vegetation using the Normalized Difference Vegetation Index (NDVI) and Ratio Vegetation Index (RVI) and to choose a vegetation index that is more suitable for clove vegetation analysis in Buleleng district, Bali. The method used is to compare statistically descriptive area and distribution class produced by the NDVI and RVI models with area data from the Forestry and Plantation Service (FPS), Buleleng regency, Bali in 2014, amounting to 7622.32 ha. The estimated area of ??clove vegetation by the NDVI model was 7852.68 ha and the RVI model was 7669.44 ha. There is an estimated difference in the area of ??clove vegetation of 183.24 ha and a difference in the broad class category of 2453.85 ha for the Rare class (NDVI > RVI) category, for the Medium class of 1611.45 ha (RVI > NDVI), and for the Dense class of 659.16 ha (RVI > NDVI). Comparison of the area with FPS data obtained 97.07% for the NDVI model and 99.39% for the RVI model. This shows that the RVI model vegetation index is more suitable for use in the estimation of the area and class of clove vegetation distribution in Buleleng regency, Bali.

Downloads

Download data is not yet available.

References

Adams, J. B., & Gillespie, A. R. (2006). Remote sensing of landscapes with spectral images: A physical modeling approach. Cambridge University Press.

Beeri, O., Phillips, R., Hendrickson, J., Frank, A. B., & Kronberg, S. (2007). Estimating forage quantity and quality using aerial hyperspectral imagery for northern mixed-grass prairie. Remote Sensing of Environment, 110(2), 216-225. https://doi.org/10.1016/j.rse.2007.02.027

Dinas Kehutanan dan Perkebunan Pemkab Buleleng. (2014). Laporan Triwulan Luas Areal dan Produksi Komoditas Perkebunan Kabupaten Buleleng Tahun 2014.

Dinas Kehutanan dan Perkebunan Pemkab Buleleng. (2015). Laporan Triwulan Luas Areal dan Produksi Komoditas Perkebunan Kabupaten Buleleng Tahun 2015.

Gao, G., & Wang, S. (2012, June). Compare Analysis of Vegetation Cover Change in Jianyang City Based on RVI and NDVI. In 2012 2nd International Conference on Remote Sensing, Environment and Transportation Engineering (pp. 1-4). IEEE. https://doi.org/10.1109/RSETE.2012.6260516

Gu, W., Ma, W., Zhou, L., Tang, L., & Huai, H. (2011). RS estimation of chlorophyll-a concentration based on RVI regionalization during algae blooming period in Dianshan Lake. Research of Environmental Sciences, 24(6), 666-672.

Li, H., Zheng, L., Lei, Y., LI, C., & ZHOU, K. (2007). Comparison of NDVI and EVI based on EOS/MODIS data. Progress in geography, 1.

Lillesand, T., Kiefer, R. W., & Chipman, J. (2015). Remote sensing and image interpretation. John Wiley & Sons.

Luo, H., Fang, J., Li, H., Wang, L., Dai, S., & Chen, S. (2014, August). Comparison and analysis NDVI and RVI changes before and after typhoon in Hainan based on HJ-1CCD satellite images. In 2014 The Third International Conference on Agro-Geoinformatics (pp. 1-4). IEEE. https://doi.org/10.1109/Agro-Geoinformatics.2014.6910615

Mather, P. M., & Koch, M. (2011). Computer processing of remotely-sensed images: an introduction. John Wiley & Sons.

Purevdorj, T. S., Tateishi, R., Ishiyama, T., & Honda, Y. (1998). Relationships between percent vegetation cover and vegetation indices. International journal of remote sensing, 19(18), 3519-3535. https://doi.org/10.1080/014311698213795

Rees, W. G. (2013). Physical principles of remote sensing. Cambridge University Press.

USGS. (2019). Using the USGS Landsat Level-1 Data Product. https://www.usgs.gov/land-resources/nli/landsat/using-usgs-landsat-level-1-data-product

Wardlow, B. D., Egbert, S. L., & Kastens, J. H. (2007). Analysis of time-series MODIS 250 m vegetation index data for crop classification in the US Central Great Plains. Remote Sensing of Environment, 108(3), 290-310. https://doi.org/10.1016/j.rse.2006.11.021

Xie, Y., Sha, Z., & Yu, M. (2008). Remote sensing imagery in vegetation mapping: a review. Journal of plant ecology, 1(1), 9-23. https://doi.org/10.1093/jpe/rtm005

Xu, D., & Guo, X. (2014). Compare NDVI extracted from Landsat 8 imagery with that from Landsat 7 imagery. American Journal of Remote Sensing, 2(2), 10-14.

Yuliara, I. M., Sutapa, G. N., & Kasmawan, G. A. (2018). Development and optimization of the ratio vegetation index on the visible and infrared spectrum. International journal of physical sciences and engineering, 2(2), 101-110. https://doi.org/10.29332/ijpse.v2n2.172

Published
2019-08-12
How to Cite
Yuliara, I. M., Ratini, N. N., & Kasmawan, I. G. A. (2019). Comparative Study on NDVI with RVI for Estimated Area and Class Distribution. International Journal of Physical Sciences and Engineering, 3(2), 12-20. https://doi.org/10.29332/ijpse.v3n2.310
Section
Articles