scholarly journals Sensitivity of L-Band SAR Backscatter to Aboveground Biomass of Global Forests

2016 ◽  
Vol 8 (6) ◽  
pp. 522 ◽  
Author(s):  
Yifan Yu ◽  
Sassan Saatchi
Keyword(s):  
Aboveground Biomass ◽  
L Band

scholarly journals Regional Tropical Aboveground Biomass Mapping with L-Band Repeat-Pass Interferometric Radar, Sparse Lidar, and Multiscale Superpixels

2020 ◽  
Vol 12 (12) ◽  
pp. 2048
Author(s):  
Charlie Marshak ◽  
Marc Simard ◽  
Laura Duncanson ◽  
Carlos Alberto Silva ◽  
Michael Denbina ◽  
...  
Keyword(s):  
Aboveground Biomass ◽  
Airborne Lidar ◽  
Lidar Data ◽  
Single Model ◽  
Tropical Regions ◽  
Full Waveform ◽  
Applicable Range ◽  
L Band ◽  
Airborne Lidar Data ◽  
Synergistic Relationships

We introduce a multiscale superpixel approach that leverages repeat-pass interferometric coherence and sparse AGB estimates from a simulated spaceborne lidar in order to extend the NISAR mission’s applicable range of aboveground biomass (AGB) in tropical forests. Airborne and spaceborne L-band radar and full-waveform airborne lidar data are used to simulate the NISAR and GEDI mission, respectively. In addition to UAVSAR data, we use spaceborne ALOS-2/PALSAR-2 imagery with 14-day temporal baseline, which is comparable to NISAR’s 12-day baseline. Our reference AGB maps are derived from the airborne LVIS data during the AfriSAR campaign for three sites (Mondah, Ogooue, and Lope). Each tropical site has mean AGB of at least 125 Mg/ha in addition to areas with AGB exceeding 700 Mg/ha. Spatially sampling from these LVIS-derived AGB reference maps, we approximate GEDI AGB estimates. To evaluate our methodology, we perform several different analyses. First, we partition each study site into low (≤100 Mg/ha) and high (>100 Mg/ha) AGB areas, in conformity with the NISAR mission requirement to provide AGB estimates for forests between 0 and 100 Mg/ha with a RMSE below 20 Mg/ha. In the low AGB areas, this RMSE requirement is satisfied in Lope and Mondah and it fell short of the requirement in Ogooue by less 3 Mg/ha with UAVSAR and 6 Mg/ha with PALSAR-2. We note that our maps have finer spatial resolution (50 m) than NISAR requires (1 hectare). In the high AGB areas, the normalized RMSE increases to 51% (i.e., <90 Mg/ha), but with negligible bias for all three sites. Second, we train a single model to estimate AGB across both high and low AGB regimes simultaneously and obtain a normalized RMSE that is <60% (or <100 Mg/ha). Lastly, we show the use of both (a) multiscale superpixels and (b) interferometric coherence significantly improves the accuracy of the AGB estimates. The InSAR coherence improved the RMSE by approximately 8% at Mondah with both sensors, lowering the RMSE from 59 Mg/ha to 47.4 Mg/h with UAVSAR and from 57.1 Mg/ha to 46 Mg/ha. This work illustrates one of the numerous synergistic relationships between the spaceborne lidars, such as GEDI, with L-band SAR, such as PALSAR-2 and NISAR, in order to produce robust regional AGB in high biomass tropical regions.

scholarly journals Impacts of Spatial Variability on Aboveground Biomass Estimation from L-Band Radar in a Temperate Forest

2013 ◽  
Vol 5 (3) ◽  
pp. 1001-1023 ◽  
Author(s):  
Chelsea Robinson ◽  
Sassan Saatchi ◽  
Maxim Neumann ◽  
Thomas Gillespie
Keyword(s):  
Spatial Variability ◽  
Aboveground Biomass ◽  
Temperate Forest ◽  
Biomass Estimation ◽  
L Band

scholarly journals Evaluation of ALOS/PALSAR L-Band Data for the Estimation of Eucalyptus Plantations Aboveground Biomass in Brazil

2015 ◽  
Vol 8 (8) ◽  
pp. 3802-3811 ◽  
Author(s):  
Nicolas Baghdadi ◽  
Guerric Le Maire ◽  
Jean-Stephane Bailly ◽  
Kenji Ose ◽  
Yann Nouvellon ◽  
...  
Keyword(s):  
Aboveground Biomass ◽  
Alos Palsar ◽  
L Band

scholarly journals Large Area Aboveground Biomass and Carbon Stock Mapping in Woodlands in Mozambique with L-band Radar: Improving Accuracy by Accounting for Soil Moisture Effects Using the Water Cloud Model

2022 ◽  
Vol 14 (2) ◽  
pp. 404
Author(s):  
Yaqing Gou ◽  
Casey M. Ryan ◽  
Johannes Reiche
Keyword(s):  
Soil Moisture ◽  
Aboveground Biomass ◽  
Cloud Model ◽  
Large Area ◽  
Moisture Effects ◽  
Radar Imagery ◽  
Water Cloud ◽  
L Band ◽  
The Difference ◽  
Moisture Conditions

Soil moisture effects limit radar-based aboveground biomass carbon (AGBC) prediction accuracy as well as lead to stripes between adjacent paths in regional mosaics due to varying soil moisture conditions on different acquisition dates. In this study, we utilised the semi-empirical water cloud model (WCM) to account for backscattering from soil moisture in AGBC retrieval from L-band radar imagery in central Mozambique, where woodland ecosystems dominate. Cross-validation results suggest that (1) the standard WCM effectively accounts for soil moisture effects, especially for areas with AGBC ≤ 20 tC/ha, and (2) the standard WCM significantly improved the quality of regional AGBC mosaics by reducing the stripes between adjacent paths caused by the difference in soil moisture conditions between different acquisition dates. By applying the standard WCM, the difference in mean predicted AGBC for the tested path with the largest soil moisture difference was reduced by 18.6%. The WCM is a valuable tool for AGBC mapping by reducing prediction uncertainties and striping effects in regional mosaics, especially in low-biomass areas including African woodlands and other woodland and savanna regions. It is repeatable for recent L-band data including ALOS-2 PALSAR-2, and upcoming SAOCOM and NISAR data.

scholarly journals Influence of surface water variations on VOD and biomass estimates from passive microwave sensors

2021 ◽  
Author(s):  
Emma Bousquet ◽  
Arnaud Mialon ◽  
Nemesio Rodriguez-Fernandez ◽  
Catherine Prigent ◽  
Fabien Wagner ◽  
...  
Keyword(s):  
Soil Moisture ◽  
Surface Water ◽  
Aboveground Biomass ◽  
Passive Microwave ◽  
Microwave Emission ◽  
Retrieval Algorithm ◽  
Water Fraction ◽  
Standing Water ◽  
Flooded Forests ◽  
L Band

&lt;p&gt;Vegetation optical depth (VOD) is a remotely sensed indicator characterizing the attenuation of the Earth's thermal emission at microwave wavelengths by the vegetation layer. At L-band, VOD can be used to estimate and monitor aboveground biomass (AGB), a key component of the Earth's surface and of the carbon cycle. We observed a strong anti-correlation between SMOS (Soil Moisture and Ocean Salinity) L-band VOD (L-VOD) and soil moisture (SM) anomalies over seasonally inundated areas, confirming previous observations of an unexpected decline in K-band VOD during flooding (Jones et al., 2011). These results could be, at least partially, due to artefacts affecting the retrieval and could lead to uncertainties on the derived L-VOD during flooding. To study the behaviour of SMOS satellite L-VOD retrieval algorithm over seasonally inundated areas, the passive microwave L-MEB (L-band Microwave Emission of the Biosphere) model was used to simulate the signal emitted by a mixed scene composed of soil and standing water. The retrieval over this inundated area shows an overestimation of SM and an underestimation of L-VOD. This underestimation increases non-linearly with the surface water fraction. The phenomenon is more pronounced over grasslands than over forests. The retrieved L-VOD is typically underestimated by ~10% over flooded forests and up to 100% over flooded grasslands. This is mainly due to the fact that i) low vegetation is mostly submerged under water and becomes invisible to the sensor; and ii) more standing water is seen by the sensor. Such effects can distort the analysis of aboveground biomass (AGB) and aboveground carbon (AGC) estimates and dynamics based on L-VOD. Using the L-VOD/AGB relationship from Rodriguez-Fernandez et al. (2018), we evaluated that AGB can be underestimated by 15/20&lt;sup&gt;&lt;/sup&gt;Mg ha&lt;sup&gt;-1&lt;/sup&gt; in the largest wetlands, and up to higher values during exceptional meteorological years. Such values are more significant over herbaceous wetlands, where AGB is ~30 Mg ha&lt;sup&gt;-1&lt;/sup&gt;, than over flooded forests, which have typical AGB values of 150-300 Mg ha&lt;sup&gt;-1&lt;/sup&gt;. Consequently, to better estimate the global biomass, surface water seasonality has to be taken into account in passive microwave retrieval algorithms.&lt;/p&gt;

scholarly journals Aboveground Forest Biomass Estimation Combining L- and P-Band SAR Acquisitions

2018 ◽  
Vol 10 (7) ◽  
pp. 1151 ◽  
Author(s):  
Michael Schlund ◽  
Malcolm Davidson
Keyword(s):  
Aboveground Biomass ◽  
Boreal Forests ◽  
Laser Scanning ◽  
Forest Biomass ◽  
European Space Agency ◽  
Low Frequency ◽  
Biomass Estimation ◽  
Retrieval Performance ◽  
In Situ Data ◽  
L Band

While considerable research has focused on using either L-band or P-band SAR (Synthetic Aperture Radar) on their own for forest biomass retrieval, the use of the two bands simultaneously to improve forest biomass retrieval remains less explored. In this paper, we make use of L- and P-band airborne SAR and in situ data measured in the field together with laser scanning data acquired over one hemi-boreal (Remningstorp) and one boreal (Krycklan) forest study area in Sweden. We fit statistical models to different combinations of topographic-corrected SAR backscatter and forest heights estimated from PolInSAR for the biomass estimation, and evaluate retrieval performance in terms of R2 and using 10-fold cross-validation. The study shows that specific combinations of radar observables from L- and P-band lead to biomass predictions that are more accurate in comparison with single-band retrievals. The correlations and accuracies between the combinations of SAR features and aboveground biomass are consistent across the two study areas, whereas the retrieval performance varied for individual bands. P-band-based retrievals were more accurate than L-band for the hemi-boreal Remningstorp site and less accurate than L-band for the boreal Krycklan site. The aboveground biomass levels as well as the ground topography differ between the two sites. The results suggest that P-band is more sensitive to higher biomass and L-band to lower biomass forests. The forest height from PolInSAR improved the results at L-band in the higher biomass substantially, whereas no improvement was observed at P-band in both study areas. These results are relevant in the context of combining information over boreal forests from future low-frequency SAR missions such as the European Space Agency (ESA) BIOMASS mission, which will operate at P-band, and future L-band missions planned by several space agencies.

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