Version 1
: Received: 3 April 2017 / Approved: 4 April 2017 / Online: 4 April 2017 (10:02:56 CEST)
How to cite:
Risdiyanto, I.; Fakhrul, M. Examination of Multi-Spectral Radiance of the Landsat 8 Satellite Data for Estimating Biomass Carbon Stock at Wetland Ecosystem. Preprints2017, 2017040020. https://doi.org/10.20944/preprints201704.0020.v1
Risdiyanto, I.; Fakhrul, M. Examination of Multi-Spectral Radiance of the Landsat 8 Satellite Data for Estimating Biomass Carbon Stock at Wetland Ecosystem. Preprints 2017, 2017040020. https://doi.org/10.20944/preprints201704.0020.v1
Risdiyanto, I.; Fakhrul, M. Examination of Multi-Spectral Radiance of the Landsat 8 Satellite Data for Estimating Biomass Carbon Stock at Wetland Ecosystem. Preprints2017, 2017040020. https://doi.org/10.20944/preprints201704.0020.v1
APA Style
Risdiyanto, I., & Fakhrul, M. (2017). Examination of Multi-Spectral Radiance of the Landsat 8 Satellite Data for Estimating Biomass Carbon Stock at Wetland Ecosystem. Preprints. https://doi.org/10.20944/preprints201704.0020.v1
Chicago/Turabian Style
Risdiyanto, I. and Muhamad Fakhrul. 2017 "Examination of Multi-Spectral Radiance of the Landsat 8 Satellite Data for Estimating Biomass Carbon Stock at Wetland Ecosystem" Preprints. https://doi.org/10.20944/preprints201704.0020.v1
Abstract
The assessment of biomass carbon stocks was conducted at plot scale as a sample to estimate for all vegetation areas by using destructive sampling and or allometric equation method. Remote sensing is one of the techniques can be used to estimate and mapping biomass carbon stock for the entire areas. The objectives of the study are the identification and determine the range of electromagnetic wave of Landsat 8 satellite data that most suitable for assessing and mapping biomass carbon stock distribution. This research analyses exponential regression equation between spectral radiance values (Lλi) for with biomass measurement results on the field to find the best correlation based on the coefficient of determination value (R2). It also analyses the relationship between field biomass and NDVI value (Normal Differences Vegetation Index) from satellite data. The study area consists of 54.9% bush (Bs), 24.5% scrub (Sc), 16.8% secondary forest (Sf), while the rest (3.8%) is a water body. The with average biomass carbon stock value 4.11 tons.ha-1, 64.43 tons.ha-1, and 85.36 tons.ha-1, for strata Sc, Bs, and Sf respectively. Spectral radiance of SWIR (Shortwave Infra-Red) band 6 is determined as a spectral characteristic that can be used to estimating carbon stock with following the equation Y= 12657(EXP(-0.642(Lλband6)) with r2 = 0.75. Correlation NDVI and field biomass showed the low r2 value (0.08), so in this study, NDVI cannot be used to estimate the biomass carbon stock.
Environmental and Earth Sciences, Environmental Science
Copyright:
This is an open access article distributed under the Creative Commons Attribution License which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
