Forest Above-Ground Biomass Estimation Using Single-Baseline Polarization Coherence Tomography with P-Band PolInSAR Data

Zhang, Haibo; Wang, Changcheng; Zhu, Jianjun; Fu, Haiqiang; Xie, Qinghua; Shen, Peng

doi:10.3390/f9040163

Cited by 18 publications

(12 citation statements)

References 64 publications

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“…These two sites have been used as reference sites for remote sensing of boreal forest many times and the sites have then been described in detail in many publications, e.g., [4,10,12,33,[41][42][43][44][45][46][47].…”

Section: Study Sitesmentioning

confidence: 99%

On the Sensitivity of TanDEM-X-Observations to Boreal Forest Structure

2019

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The structure of forests is important to observe for understanding coupling to global dynamics of ecosystems, biodiversity, and management aspects. In this paper, the sensitivity of X-band to boreal forest stem volume and to vertical and horizontal structure in the form of forest height and horizontal vegetation density is studied using TanDEM-X satellite observations from two study sites in Sweden: Remningstorp and Krycklan. The forest was analyzed with the Interferometric Water Cloud Model (IWCM), without the use of local data for model training, and compared with measurements by Airborne Lidar Scanning (ALS). On one hand, a large number of stands were studied, and in addition, plots with different types of changes between 2010 and 2014 were also studied. It is shown that the TanDEM-X phase height is, under certain conditions, equal to the product of the ALS quantities for height and density. Therefore, the sensitivity of phase height to relative changes in height and density is the same. For stands with a phase height >5 m we obtained an root-mean-square error, RMSE, of 8% and 10% for tree height in Remningstorp and Krycklan, respectively, and for vegetation density an RMSE of 13% for both. Furthermore, we obtained an RMSE of 17% for estimation of above ground biomass at stand level in Remningstorp and in Krycklan. The forest changes estimated with TanDEM-X/IWCM and ALS are small for all plots except clear cuts but show similar trends. Plots without forest management changes show a mean estimated height growth of 2.7% with TanDEM-X/IWCM versus 2.1% with ALS and a biomass growth of 4.3% versus 4.2% per year. The agreement between the estimates from TanDEM-X/IWCM and ALS is in general good, except for stands with low phase height.

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Section: Study Sitesmentioning

confidence: 99%

On the Sensitivity of TanDEM-X-Observations to Boreal Forest Structure

2019

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“…The spectral characteristics in the optical data are mainly used to indicate the changes in the moisture and chlorophyll content of the crop leaves [ 2 , 3 ]. In the PolSAR data, the backscatter information of the multiple polarimetric channels are used to describe the structure, orientation distribution and dielectric constant characteristics of crops [ 4 , 5 , 6 , 7 , 8 , 9 ]. Generally speaking, the optical and PolSAR data can characterize different properties of crops.…”

Section: Introductionmentioning

confidence: 99%

A Crop Classification Method Integrating GF-3 PolSAR and Sentinel-2A Optical Data in the Dongting Lake Basin

Gao

Wang

et al. 2018

Sensors

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With the increasing of satellite sensors, more available multi-source data can be used for large-scale high-precision crop classification. Both polarimetric synthetic aperture radar (PolSAR) and multi-spectral optical data have been widely used for classification. However, it is difficult to combine the covariance matrix of PolSAR data with the spectral bands of optical data. Using Hoekman’s method, this study solves the above problems by transforming the covariance matrix to an intensity vector that includes multiple intensity values on different polarization basis. In order to reduce the features redundancy, the principal component analysis (PCA) algorithm is adopted to select some useful polarimetric and optical features. In this study, the PolSAR data acquired by satellite Gaofen-3 (GF-3) on 19 July 2017 and the optical data acquired by Sentinel-2A on 17 July 2017 over the Dongting lake basin are selected for the validation experiment. The results show that the full feature integration method proposed in this study achieves an overall classification accuracy of 85.27%, higher than that of the single dataset method or some other feature integration modes.

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“…This evaluates the quality of local interferometric fringes and provides scattering information for ground objects. The generation of coherence map is much easier comparing to InSAR results, thus, this metric has been proved to be efficient as well as versatile and can be applied to many fields including water body recognition [22][23][24][25], disaster monitoring and relief [26][27][28][29], forest biomass extraction [30][31][32][33], target detection, and archeological protection [21,[34][35][36][37]. As for mining applications, [38] used coherence maps to identify underground mining-induced surface collapse.…”

Section: Introductionmentioning

confidence: 99%

Evaluating the Feasibility of Illegal Open-Pit Mining Identification Using Insar Coherence

Wang

Chen

et al. 2020

Remote Sensing

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Illegal open-pit mining causes environmental harm and undermines sustainable development. Conventional monitoring approaches such as field research and unmanned aerial vehicle (UAV) imagery are time-consuming and labor-intensive, making large-scale monitoring difficult. In comparison, optical remote sensing imagery can cover large areas but is vulnerable to adverse weather conditions and is not sensitive to vertical ground changes. As open-pit excavation causes sudden changes in the scattering properties of ground objects along with dramatic vertical deformation, we evaluated the feasibility of using interferometric synthetic aperture radar (InSAR) coherence to identify illegal mining activities. Our method extracts the coherence coefficient from two SAR images taken on different dates, applies thresholding and filtering to extract a decorrelation map, and then overlays this with legal mining boundaries and optical satellite images to identify illegal mining activities. For three test cases in southwestern Inner Mongolia, China, 49 legal mining sites were correctly detected (with an accuracy of 90.74%) as well as six illegal mining sites. Ground truthing confirmed the presence of ongoing activity at one of these sites. Our study shows that InSAR coherence is suitable for the identification of mining activities, and our method provides a new approach for the detection and monitoring of illegal open-pit mining.

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Forest Above-Ground Biomass Estimation Using Single-Baseline Polarization Coherence Tomography with P-Band PolInSAR Data

Cited by 18 publications

References 64 publications

On the Sensitivity of TanDEM-X-Observations to Boreal Forest Structure

On the Sensitivity of TanDEM-X-Observations to Boreal Forest Structure

A Crop Classification Method Integrating GF-3 PolSAR and Sentinel-2A Optical Data in the Dongting Lake Basin

Evaluating the Feasibility of Illegal Open-Pit Mining Identification Using Insar Coherence

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