Estimation of the forest stand mean height and aboveground biomass in Northeast China using SAR Sentinel-1B, multispectral Sentinel-2A, and DEM imagery

Liu, Yanan; Gong, Wenyin; Xing, Yunqi; Hu, Xiangyun; Gong, Jianya

doi:10.1016/j.isprsjprs.2019.03.016

Cited by 101 publications

(46 citation statements)

References 56 publications

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“…The VH polarization with a coefficient of 0.504 at p = 0.01 had a higher significant correlation than that of the VV polarization, which had a coefficient of 0.410 at p = 0.05. The Sentinel-1 SAR backscatter values from the VH polarization are more robust and accurate than those based on the VV polarization for biomass estimation [39]. The fused-image bands integrating WV-3 and Sentinel-1 SAR images can provide higher correlation with AGB compared to individual variables exclusively from either the WV-3 or SAR data.…”

Section: Relationship Of the Measured Agb With Remote Sensing Variablesmentioning

confidence: 99%

Biomass Estimation for Semiarid Vegetation and Mine Rehabilitation Using Worldview-3 and Sentinel-1 SAR Imagery

Bao

et al. 2019

Remote Sensing

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The surface mining activities in grassland and rangeland zones directly affect the livestock production, forage quality, and regional grassland resources. Mine rehabilitation is necessary for accelerating the recovery of the grassland ecosystem. In this work, we investigate the integration of data obtained via a synthetic aperture radar (Sentinel-1 SAR) with data obtained by optical remote sensing (Worldview-3, WV-3) in order to monitor the conditions of a vegetation area rehabilitated after coal mining in North China. The above-ground biomass (AGB) is used as an indicator of the rehabilitated vegetation conditions and the success of mine rehabilitation. The wavelet principal component analysis is used for the fusion of the WV-3 and Sentinel-1 SAR images. Furthermore, a multiple linear regression model is applied based on the relationship between the remote sensing features and the AGB field measurements. Our results show that WV-3 enhanced vegetation indices (EVI), mean texture from band8 (near infrared band2, NIR2), the SAR vertical and horizon (VH) polarization, and band 8 (NIR2) from the fused image have higher correlation coefficient value with the field-measured AGB. The proposed AGB estimation model combining WV-3 and Sentinel 1A SAR imagery yields higher model accuracy (R 2 = 0.79 and RMSE = 22.82 g/m 2 ) compared to that obtained with any of the two datasets only. Besides improving AGB estimation, the proposed model can also reduce the uncertainty range by 7 g m −2 on average. These results demonstrate the potential of new multispectral high-resolution datasets, such as Sentinel-1 SAR and Worldview-3, in providing timely and accurate AGB estimation for mine rehabilitation planning and management.

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Section: Relationship Of the Measured Agb With Remote Sensing Variablesmentioning

confidence: 99%

Biomass Estimation for Semiarid Vegetation and Mine Rehabilitation Using Worldview-3 and Sentinel-1 SAR Imagery

Bao

et al. 2019

Remote Sensing

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“…Accurate models with optical data can be achieved using the high spatial resolution (<10 m), where the pixel size approximates the size of the study object [118]. In particular, using Sentinel-2 data, it has been reported medium accuracy in local and regional scale studies [119,120]. Thus, the production of AGB maps, with Sentinel-2 data, has a great potential to expand to forest management and monitoring decisions on a regional scale.…”

Section: Biomass Estimationmentioning

confidence: 99%

The Potential of Sentinel-2 Satellite Images for Land-Cover/Land-Use and Forest Biomass Estimation: A Review

Isbaex¹,

Coelho²

2021

Forest Biomass - From Trees to Energy

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Mapping land-cover/land-use (LCLU) and estimating forest biomass using satellite images is a challenge given the diversity of sensors available and the heterogeneity of forests. Copernicus program served by the Sentinel satellites family and the Google Earth Engine (GEE) platform, both with free and open services accessible to its users, present a good approach for mapping vegetation and estimate forest biomass on a global, regional, or local scale, periodically and in a repeated way. The Sentinel-2 (S2) systematically acquires optical imagery and provides global monitoring data with high spatial resolution (10–60 m) images. Given the novelty of information on the use of S2 data, this chapter presents a review on LCLU maps and forest above-ground biomass (AGB) estimates, in addition to exploring the efficiency of using the GEE platform. The Sentinel data have great potential for studies on LCLU classification and forest biomass estimates. The GEE platform is a promising tool for executing complex workflows of satellite data processing.

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“…Weather dependence (Liu et al, 2019) Cannot penetrate through clouds; therefore, image is acquired only in clear weather.…”

Section: On the Basis Of Applicationmentioning

confidence: 99%

A Comparative Assessment of Remote Sensing Imaging Techniques: Optical, Sar and Lidar

Agrawal

Khairnar

2019

Int. Arch. Photogramm. Remote Sens. Spatial Inf. Sci.

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Abstract. Remote sensing is a popular technique that is using in the mapping and monitoring of earth features. Early remote sensing was predominantly passive, i.e. it depends upon the sun for energy. Till the last decade, optical imaging is mainly used in remote sensing works. Over the time, significant innovations and improvements have been made in the active remote sensing which resulted in the form of sophisticated imaging techniques like Synthetic Aperture RADAR (SAR) and Light Detection And Ranging (LiDAR). These advancements promoted the use of multi-sensor and multi-source data in remote sensing projects. This highlights the need to review these imaging techniques. Therefore, this review work is carried out. In this review, different imaging techniques are discussed and compared. Optical, SAR and LiDAR techniques are first summarized and then they are compared on the basis of technical specification and working. Finally, an in-depth assessment is made on the applicability of these imaging techniques in different fields.

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Estimation of the forest stand mean height and aboveground biomass in Northeast China using SAR Sentinel-1B, multispectral Sentinel-2A, and DEM imagery

Cited by 101 publications

References 56 publications

Biomass Estimation for Semiarid Vegetation and Mine Rehabilitation Using Worldview-3 and Sentinel-1 SAR Imagery

Biomass Estimation for Semiarid Vegetation and Mine Rehabilitation Using Worldview-3 and Sentinel-1 SAR Imagery

The Potential of Sentinel-2 Satellite Images for Land-Cover/Land-Use and Forest Biomass Estimation: A Review

A Comparative Assessment of Remote Sensing Imaging Techniques: Optical, Sar and Lidar

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