scholarly journals Using GEDI Waveforms for Improved TanDEM-X Forest Height Mapping: A Combined SINC + Legendre Approach

2021 ◽  
Vol 13 (15) ◽  
pp. 2882
Author(s):  
Hao Chen ◽  
Shane R. Cloude ◽  
Joanne C. White
Keyword(s):  
High Resolution ◽  
Forest Canopy ◽  
Test Site ◽  
Convergent Series ◽  
Canopy Height ◽  
Ecosystem Dynamics ◽  
Sinc Function ◽  
Vertical Profiles ◽  
Legendre Series ◽  
Vertical Profiling

In this paper, we consider a new method for forest canopy height estimation using TanDEM-X single-pass radar interferometry. We exploit available information from sample-based, space-borne LiDAR systems, such as the Global Ecosystem Dynamics Investigation (GEDI) sensor, which offers high-resolution vertical profiling of forest canopies. To respond to this, we have developed a new extended Fourier-Legendre series approach for fusing high-resolution (but sparsely spatially sampled) GEDI LiDAR waveforms with TanDEM-X radar interferometric data to improve wide-area and wall-to-wall estimation of forest canopy height. Our key methodological development is a fusion of the standard uniform assumption for the vertical structure function (the SINC function) with LiDAR vertical profiles using a Fourier-Legendre approach, which produces a convergent series of approximations of the LiDAR profiles matched to the interferometric baseline. Our results showed that in our test site, the Petawawa Research Forest, the SINC function is more accurate in areas with shorter canopy heights (<~27 m). In taller forests, the SINC approach underestimates forest canopy height, whereas the Legendre approach avails upon simulated GEDI forest structural vertical profiles to overcome SINC underestimation issues. Overall, the SINC + Legendre approach improved canopy height estimates (RMSE = 1.29 m) compared to the SINC approach (RMSE = 4.1 m).

scholarly journals High‐resolution forest canopy height estimation in an African blue carbon ecosystem

2015 ◽  
Vol 1 (1) ◽  
pp. 51-60 ◽  
Author(s):  
David Lagomasino ◽  
Temilola Fatoyinbo ◽  
Seung‐Kuk Lee ◽  
Marc Simard
Keyword(s):  
High Resolution ◽  
Forest Canopy ◽  
Blue Carbon ◽  
Canopy Height ◽  
Height Estimation

scholarly journals Forest canopy height from the Multiangle Imaging SpectroRadiometer (MISR) assessed with high resolution discrete return lidar

2009 ◽  
Vol 113 (10) ◽  
pp. 2172-2185 ◽  
Author(s):  
Mark Chopping ◽  
Anne Nolin ◽  
Gretchen G. Moisen ◽  
John V. Martonchik ◽  
Michael Bull
Keyword(s):  
High Resolution ◽  
Forest Canopy ◽  
Canopy Height ◽  
Multiangle Imaging ◽  
Multiangle Imaging Spectroradiometer

scholarly journals Spaceborne Multifrequency PolInSAR-Based Inversion Modelling for Forest Height Retrieval

2020 ◽  
Vol 12 (24) ◽  
pp. 4042
Author(s):  
Shashi Kumar ◽  
Himanshu Govil ◽  
Prashant K. Srivastava ◽  
Praveen K. Thakur ◽  
Satya P. S. Kushwaha
Keyword(s):  
Forest Canopy ◽  
Linear Regression Analysis ◽  
Tree Canopy ◽  
Canopy Height ◽  
Ecosystem Dynamics ◽  
Amplitude Inversion ◽  
Vegetation Height ◽  
Model Based ◽  
Forest Height ◽  
L Band

Spaceborne and airborne polarimetric synthetic-aperture radar interferometry (PolInSAR) data have been extensively used for forest parameter retrieval. The PolInSAR models have proven their potential in the accurate measurement of forest vegetation height. Spaceborne monostatic multifrequency data of different SAR missions and the Global Ecosystem Dynamics Investigation (GEDI)-derived forest canopy height map were used in this study for vegetation height retrieval. This study tested the performance of PolInSAR complex coherence-based inversion models for estimating the vegetation height of the forest ranges of Doon Valley, Uttarakhand, India. The inversion-based forest height obtained from the three-stage inversion (TSI) model had higher accuracy than the coherence amplitude inversion (CAI) model-based estimates. The vegetation height values of GEDI-derived canopy height map did not show good relation with field-measured forest height values. It was found that, at several locations, GEDI-derived forest height values underestimated the vegetation height. The statistical analysis of the GEDI-derived estimates with field-measured height showed a high root mean square error (RMSE; 5.82 m) and standard error (SE; 5.33 m) with a very low coefficient of determination (R2; 0.0022). An analysis of the spaceborne-mission-based forest height values suggested that the L-band SAR has great potential in forest height retrieval. TSI-model-based forest height values showed lower p-values, which indicates the significant relation between modelled and field-measured forest height values. A comparison of the results obtained from different SAR systems is discussed, and it is observed that the L-band-based PolInSAR inversion gives the most reliable result with low RMSE (2.87 m) and relatively higher R2 (0.53) for the linear regression analysis between the modelled tree height and the field data. These results indicate that higher wavelength PolInSAR datasets are more suitable for tree canopy height estimation using the PolInSAR inversion technique.

scholarly journals Tropical forest canopy height estimation from combined polarimetric SAR and LiDAR using machine-learning

2021 ◽  
Vol 172 ◽  
pp. 79-94
Author(s):  
Maryam Pourshamsi ◽  
Junshi Xia ◽  
Naoto Yokoya ◽  
Mariano Garcia ◽  
Marco Lavalle ◽  
...  
Keyword(s):  
Machine Learning ◽  
Tropical Forest ◽  
Forest Canopy ◽  
Canopy Height ◽  
Polarimetric Sar ◽  
Height Estimation ◽  
Tropical Forest Canopy

scholarly journals Comparison and Evaluation of Different Pit-Filling Methods for Generating High Resolution Canopy Height Model Using UAV Laser Scanning Data

2021 ◽  
Vol 13 (12) ◽  
pp. 2239
Author(s):  
Ying Quan ◽  
Mingze Li ◽  
Yuanshuo Hao ◽  
Bin Wang
Keyword(s):  
High Resolution ◽  
Laser Scanning ◽  
Evaluation Framework ◽  
Canopy Height ◽  
Filter Method ◽  
Individual Tree ◽  
Significant Difference ◽  
Point Interpolation ◽  
Canopy Height Model ◽  
Height Model

As a common form of light detection and ranging (LiDAR) in forestry applications, the canopy height model (CHM) provides the elevation distribution of aboveground vegetation. A CHM is traditionally generated by interpolating all the first LiDAR echoes. However, the first echo cannot accurately represent the canopy surface, and the resulting large amount of noise (data pits) also reduce the CHM quality. Although previous studies concentrate on many pit-filling methods, the applicability of these methods in high-resolution unmanned aerial vehicle laser scanning (UAVLS)-derived CHMs has not been revealed. This study selected eight widely used, recently developed, representative pit-filling methods, namely first-echo interpolation, smooth filtering (mean, medium and Gaussian), highest point interpolation, pit-free algorithm, spike-free algorithm and graph-based progressive morphological filtering (GPMF). A comprehensive evaluation framework was implemented, including a quantitative evaluation using simulation data and an additional application evaluation using UAVLS data. The results indicated that the spike-free algorithm and GPMF had excellent visual performances and were closest to the real canopy surface (root mean square error (RMSE) of simulated data were 0.1578 m and 0.1093 m, respectively; RMSE of UAVLS data were 0.3179 m and 0.4379 m, respectively). Compared with the first-echo method, the accuracies of the spike-free algorithm and GPMF improved by approximately 23% and 22%, respectively. The pit-free algorithm and highest point interpolation method also have advantages in high-resolution CHM generation. The global smooth filter method based on the first-echo CHM reduced the average canopy height by approximately 7.73%. Coniferous forests require more pit-filling than broad-leaved forests and mixed forests. Although the results of individual tree applications indicated that there was no significant difference between these methods except the median filter method, pit-filling is still of great significance for generating high-resolution CHMs. This study provides guidance for using high-resolution UAVLS in forestry applications.

scholarly journals Retrieval of vertical profiles of ozone from high-resolution infrared solar spectra at Rikubetsu, Japan

1997 ◽  
Vol 102 (D25) ◽  
pp. 29981-29990 ◽  
Author(s):  
H. Nakajima ◽  
X. Liu ◽  
I. Murata ◽  
Y. Kondo ◽  
F. J. Murcray ◽  
...  
Keyword(s):  
High Resolution ◽  
Vertical Profiles

scholarly journals Estimate of the D/H ratio in the Martian upper atmosphere from the low spectral resolution mode of MAVEN/IUVS

2020 ◽  
Author(s):  
Jean-Yves Chaufray ◽  
Majd Mayyasi ◽  
Michael Chaffin ◽  
Justin Deighan ◽  
Dolon Bhattacharyya ◽  
...  
Keyword(s):  
High Resolution ◽  
Spectral Resolution ◽  
Quantitative Information ◽  
Upper Atmosphere ◽  
Vertical Profiles ◽  
Low Resolution ◽  
Mars Atmosphere

&lt;p&gt;The recent observations performed with the high-resolution &amp;#8220;echelle mode&amp;#8221; by the Imaging Ultraviolet Spectrograph (IUVS) aboard the Mars Atmosphere and Volatile EvolutioN (MAVEN) mission indicated large deuterium brightness near Ls=270&amp;#176;. The deuterium brightness observed at the beginning of the mission, when Mars was close to its perihelion show brightness ~ 1 kR much larger than the first deuterium detection from Earth ~ 20-50R in 20-21 January 1997 (Ls = 67&amp;#176;). This low brightness of the deuterium emission is consistent with the lack of deuterium observation with the echelle mode of IUVS at solar longitudes around aphelion (Ls = 71&amp;#176;). During southern summer (Ls = 270&amp;#176;), especially near the terminator, the Lyman-&amp;#945; emission observed at 121.6 nm with the &amp;#8220;low resolution mode&amp;#8221; presents some vertical profiles that were not reproducible with models including only the emission from the thermal hydrogen population. In this study, we investigate the possibility to derive quantitative information on the D/H ratio at Mars from the vertical Lyman-&amp;#945; profiles observed with the &amp;#8220;low resolution mode&amp;#8221;, and the main limits of the method.&lt;/p&gt;

Forest canopy height mapping over China using GLAS and MODIS data

2014 ◽  
Vol 58 (1) ◽  
pp. 96-105 ◽  
Author(s):  
Ting Yang ◽  
Cheng Wang ◽  
GuiCai Li ◽  
SheZhou Luo ◽  
XiaoHuan Xi ◽  
...  
Keyword(s):  
Forest Canopy ◽  
Canopy Height ◽  
Modis Data
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