Combined use of Sentinel-1 and Sentinel-2 data for improving above-ground biomass estimation

Nuthammachot, Narissara; Askar, Askar; Stratoulias, Dimitris; Wicaksono, Pramaditya

doi:10.1080/10106049.2020.1726507

Cited by 76 publications

(53 citation statements)

References 40 publications

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“…For 2D Sentinel-2 multispectral data, we obtained R 2 = 0.62 with RMSE = 43.92 for estimating AGB/C in a Subtropical Chir Pine Forest of Dir Kohistan. Our obtained results in term of RMSE % values of Sentinel-2 imagery for estimating AGB/C seems to be slightly lower but can be par as compared to previous results obtained by Nuthammachot et al (2020), Nuthammachot et al (2018), Pandit et al (2018), and Vafaei et al (2018) which can due to different forest types, altitudinal gradients, etc.…”

Section: Discussionsupporting

confidence: 74%

Comparison of Airborne Laser Scanning (3D) with Sentinel-2 (2D) for Estimating Above Ground Biomass/Carbon Stock in a Subtropical Chir Pine Forest of Balakot, Pakistan

Ullah

Saeed²,

Shafique

et al. 2021

Preprint

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Forest ecosystems act as a sink of atmospheric carbon dioxide in the form of biomass, and plays one of the crucial role for carbon sequestration and in regulating the global carbon cycle. Few studies based on ground sample plots were conducted for estimating forest biomass/carbon stock across Pakistan. This study comparing the first time the potential of three dimensional (3D) airborne laser scanning (ALS) with two dimensional (2D) Sentinel-2 to estimate above-ground biomass/carbon stock (AGB/C) in a Subtropical Chir Pine forest of Balakot, Pakistan. We derived height and density metrics from the ALS canopy height model (CHM), and different metrics from Sentinel-2 images, and were regressed with field measured AGB/C at sample plots locations. We found R2 = 0.86 with RMSE% = 25.70, and R2 = 0.62 with RMSE% = 43.92 for ALS and for Sentinel-2 respectively with ground measured AGB/C at sample plots locations. Our study demonstrated that 3D ALS technology has greater potential and is the most accurate option as compared to 2D Sentinel-2 for regular planning and monitoring of AGB/C in the context of the national forest inventory of Pakistan. Our study will be useful for the accomplishment of the REDD+ in measuring, reporting, and verification of forest resources, and future sustainable utilization of forest, safeguarding the livelihoods of forest-dependent people, and reducing pressure on forest ecosystems.

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Section: Discussionsupporting

confidence: 74%

Comparison of Airborne Laser Scanning (3D) with Sentinel-2 (2D) for Estimating Above Ground Biomass/Carbon Stock in a Subtropical Chir Pine Forest of Balakot, Pakistan

Ullah

Saeed²,

Shafique

et al. 2021

Preprint

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“…Identical improvement in modeling accuracy was noted by Li et al [52] in China. On the other hand, Nuthammachot et al [53] identified that R 2 increased by only 0.02 when Sentinel-1 data was fused to an already highly accurate (R 2 = 0.84%) Sentinel-2 model over a forest area in Indonesia. On the other hand, Navarro et al [20] observed a significant decrease of accuracy for a fused Sentinel-2/Sentinel-1 model, especially over low AGB density.…”

Section: Agb Models Using Sentinel-1 and Sentinel-2 Datamentioning

confidence: 99%

Aboveground Biomass Estimation in Short Rotation Forest Plantations in Northern Greece Using ESA’s Sentinel Medium-High Resolution Multispectral and Radar Imaging Missions

Theofanous

Chrysafis

Mallinis

et al. 2021

Forests

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Plantations of fast-growing forest species such as black locust (Robinia Pseudoacacia) can contribute to energy transformation, mitigate industrial pollution, and restore degraded, marginal land. In this study, the synergistic use of Sentinel-2 and Sentinel-1 time series data is explored for modeling aboveground biomass (AGB) in black locust short-rotation plantations in northeastern Greece. Optimal modeling dates and EO sensor data are also identified through the analysis. Random forest (RF) models were originally developed using monthly Sentinel-2 spectral indices, while, progressively, monthly Sentinel-1 bands were incorporated in the statistical analysis. The highest accuracy was observed for the models generated using Sentinel-2 August composites (R2 = 0.52). The inclusion of Sentinel-1 bands in the spectral indices’ models had a negligible effect on modeling accuracy during the leaf-on period. The correlation and comparative performance of the spectral indices in terms of pairwise correlation with AGB varied among the phenophases of the forest plantations. Overall, the field-measured AGB in the forest plantations plots presented a higher correlation with the optical Sentinel-2 images. The synergy of Sentinel-1 and Sentinel-2 data proved to be a non-efficient approach for improving forest biomass RF models throughout the year within the geographical and environmental context of our study.

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“…Radiometric calibrated values were extracted using digital number (DN) values of each pixel. To increase the image quality, the gamma map filter that was successful over forested regions in previous studies was applied to reduce the speckle effect in 5 × 5 kernel sizes (Abdikan 2018;Nuthammachot et al 2020). The study area has a hilly topography.…”

Section: Remote Sensing Instruments and Data Processingmentioning

confidence: 99%

“…As the SAR systems acquire the image at the line of sight direction, it will be affected by slope and the look angle. To reduce distortions due to terrain variation on backscatter, a radiometric terrain flattening step was applied (Meyer 2019;Nuthammachot et al 2020). Finally, Range Doppler terrain correction was implemented using Shuttle Radar Topography Mission (SRTM) 1 Sec data.…”

Section: Remote Sensing Instruments and Data Processingmentioning

confidence: 99%

“…Even cross-polarized SAR images provide better information on biomass than other polarization in general, Sinha et al (2018) showed that HH polarization resulted in a higher relationship with aboveground biomass than cross-polarized data of C-band Radarsat-2. The C-band SAR is mostly used for estimating aboveground forest biomass in the tropics (Omar et al 2017;Liu et al 2019;Navarro et al 2019;Nuthammachot et al 2020). In general, it is understood that most of the forest-related SAR studies have been conducted in tropical and subtropical domains with a focus on aboveground carbon pools.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Carbon stock estimation by dual-polarized synthetic aperture radar (SAR) and forest inventory data in a Mediterranean forest landscape

Vatandaşlar

Abdikan

2021

J. For. Res.

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Forest ecosystems play a crucial role in mitigating global climate change by forming massive carbon sinks. Their carbon stocks and stock changes need to be quantified for carbon budget balancing and international reporting schemes. However, direct sampling and biomass weighing may not always be possible for quantification studies conducted in large forests. In these cases, indirect methods that use forest inventory information combined with remote sensing data can be beneficial. Synthetic aperture radar (SAR) images offer numerous opportunities to researchers as freely distributed remote sensing data. This study aims to estimate the amount of total carbon stock (TCS) in forested lands of the Kizildag Forest Enterprise. To this end, the actual storage capacities of five carbon pools, i.e. above- and below-ground, deadwood, litter, and soil, were calculated using the indirect method based on ground measurements of 264 forest inventory plots. They were then associated with the backscattered values from Sentinel-1 and ALOS-2 PALSAR-2 data in a Geographical Information System (GIS). Finally, TCS was separately modelled and mapped. The best regression model was developed using the HH polarization of ALOS-2 PALSAR-2 with an adjusted R2 of 0.78 (p < 0.05). According to the model, the estimated TCS was about 2 Mt for the entire forest, with an average carbon storage of 133 t ha−1. The map showed that the distribution of TCS was heterogenic across the study area. Carbon hotspots were mostly composed of pure stands of Anatolian black pine and mixed, over-mature stands of Lebanese cedar and Taurus fir. It was concluded that the total carbon stocks of forest ecosystems could be estimated using appropriate SAR images at acceptable accuracy levels for forestry purposes. The use of additional ancillary data may provide more delicate and reliable estimations in the future. Given the implications of this study, the spatiotemporal dynamics of carbon can be effectively controlled by forest management when coupled with easily accessible space-borne radar data.

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Combined use of Sentinel-1 and Sentinel-2 data for improving above-ground biomass estimation

Cited by 76 publications

References 40 publications

Comparison of Airborne Laser Scanning (3D) with Sentinel-2 (2D) for Estimating Above Ground Biomass/Carbon Stock in a Subtropical Chir Pine Forest of Balakot, Pakistan

Comparison of Airborne Laser Scanning (3D) with Sentinel-2 (2D) for Estimating Above Ground Biomass/Carbon Stock in a Subtropical Chir Pine Forest of Balakot, Pakistan

Aboveground Biomass Estimation in Short Rotation Forest Plantations in Northern Greece Using ESA’s Sentinel Medium-High Resolution Multispectral and Radar Imaging Missions

Carbon stock estimation by dual-polarized synthetic aperture radar (SAR) and forest inventory data in a Mediterranean forest landscape

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