scholarly journals The Role of Time-Series L-Band SAR and GEDI in Mapping Sub-Tropical Above-Ground Biomass

2021 ◽  
Vol 9 ◽  
Author(s):  
Unmesh Khati ◽  
Marco Lavalle ◽  
Gulab Singh
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
Field Data ◽  
Large Scale ◽  
Test Site ◽  
Above Ground Biomass ◽  
Retrieval Accuracy ◽  
Ground Biomass ◽  
L Band ◽  
Field Plots

Physics-based algorithms estimating large-scale forest above-ground biomass (AGB) from synthetic aperture radar (SAR) data generally use airborne laser scanning (ALS) or grid of national forest inventory (NFI) to reduce uncertainties in the model calibration. This study assesses the potential of multitemporal L-band ALOS-2/PALSAR-2 data to improve forest AGB estimation using the three-parameter water cloud model (WCM) trained with field data from relatively small (0.1 ha) plots. The major objective is to assess the impact of the high uncertainties in field inventory data due to relatively smaller plot size and temporal gap between acquisitions and ground truth on the AGB estimation. This study analyzes a time series of twenty-three ALOS-2 dual-polarized images spanning 5 years acquired under different weather and soil moisture conditions over a subtropical forest test site in India. The WCM model is trained and validated on individual acquisitions to retrieve forest AGB. The accuracy of the generated AGB products is quantified using the root mean square error (RMSE). Further, we use a multitemporal AGB retrieval approach to improve the accuracy of the estimated AGB. Changes in precipitation and soil moisture affect the AGB retrieval accuracy from individual acquisitions; however, using multitemporal data, these effects are mitigated. Using a multitemporal AGB retrieval strategy, the accuracy improves by 15% (55 Mg/ha RMSE) for all field plots and by 21% (39 Mg/ha RMSE) for forests with AGB less than 100 Mg/ha. The analysis shows that any ten multitemporal acquisitions spanning 5 years are sufficient for improving AGB retrieval accuracy over the considered test site. Furthermore, we use allometry from colocated field plots and Global Ecosystem Dynamics Investigation (GEDI) L2A height metrics to produce GEDI-derived AGB estimates. Despite the limited co-location of GEDI and field data over our study area, within the period of interest, the preliminary analysis shows the potential of jointly using the GEDI-derived AGB and multi-temporal ALOS-2 data for large-scale AGB retrieval.

scholarly journals Benchmarking the Retrieval of Biomass in Boreal Forests Using P-Band SAR Backscatter with Multi-Temporal C- and L-Band Observations

2019 ◽  
Vol 11 (14) ◽  
pp. 1695 ◽  
Author(s):  
Cartus ◽  
Santoro ◽  
Wegmüller ◽  
Rommen
Keyword(s):  
Boreal Forests ◽  
Forest Site ◽  
Above Ground Biomass ◽  
Retrieval Accuracy ◽  
Ground Biomass ◽  
Multi Temporal ◽  
L Band ◽  
Semi Empirical ◽  
Relative Root ◽  
Band Image

The planned launch of a spaceborne P-band radar mission and the availability of C- and L-band data from several spaceborne missions suggest investigating the complementarity of C-, L-, and P-band backscatter with respect to the retrieval of forest above-ground biomass. Existing studies on the retrieval of biomass with multi-frequency backscatter relied on single observations of the backscatter and were thus not able to demonstrate the potential of multi-temporal C- and L-band data that are now available from spaceborne missions. Based on spaceborne C- and L-band and airborne P-band images acquired over a forest site in southern Sweden, we investigated whether C- and L-band backscatter may complement retrievals of above-ground biomass from P-band. To this end, a retrieval framework was adopted that utilizes a semi-empirical model for C- and L-bands and an empirical parametric model for P-band. Estimates of above-ground biomass were validated with the aid of 20 m-diameter plots and a LiDAR-derived biomass map with 100 m × 100 m pixel size. The highest retrieval accuracy when not combining frequencies was obtained for P-band with a relative root mean square error (RMSE) of 30% at the hectare scale. The retrieval with multi-temporal L- and C-bands produced errors of the order of 40% and 50%, respectively. The P-band retrieval could be improved for 4% when using P-, L-, and C-bands jointly. The combination of C- and L-bands allowed for retrieval accuracies close to those achieved with P-band. A crucial requirement for achieving an error of 30% with C- and L-bands was the use of multi-temporal observations, which was highlighted by the fact that the retrieval with the best individual L-band image was associated with an error of 61%. The results of this study reconfirmed that P-band is the most suited frequency for the retrieval of above-ground biomass of boreal forests based on backscatter, but also highlight the potential of multi-temporal C- and L-band imagery for mapping above-ground biomass, for instance in areas where the planned ESA BIOMASS P-band mission will not be allowed to acquire data.

scholarly journals Estimation of Above Ground Biomass Using Support Vector Machines and ALOS/PALSAR data

2019 ◽  
Vol 41 (2) ◽  
pp. 95-104 ◽  
Author(s):  
Thota Sivasankar ◽  
Junaid Mushtaq Lone ◽  
Sarma K. K. ◽  
Abdul Qadir ◽  
Raju P.L. N.
Keyword(s):  
Vital Role ◽  
Support Vector ◽  
Above Ground Biomass ◽  
Alos Palsar ◽  
Hilly Terrain ◽  
Retrieval Accuracy ◽  
Ground Biomass ◽  
Vector Machines ◽  
L Band ◽  
Forest Aboveground Biomass

L-band Synthetic aperture radar (SAR) data has been extensively used for forest aboveground biomass (AGB) estimation due to its higher saturation level. However, SAR backscatter is highly influenced by the topography characteristics along with the bio-geophysical properties of vegetation and underneath soil characteristics. This has limited the accuracy of directly relating the SAR backscatter with above ground biomass in highly undulated terrain. In this study, it has been observed that terrain degree of slope and aspect plays a vital role in influencing the SAR backscatter in addition with AGB. Because of this, the degree of slope and aspect along with SAR backscatter in HH (transmit and receive polarizations are horizontal) and HV (transmit horizontal and receive vertical) polarizations have been considered as inputs for Support Vector Machine (SVM) to improve the biomass retrieval accuracy. Our results demonstrate that the accuracy of AGB estimation over hilly terrain can be significantly improved by considering topographical characteristics in addition to L-band backscatter.  

Combining Sentinel-1 and ALOS-2 observations for soil moisture retrieval

2021 ◽  
Author(s):  
Anna Balenzano ◽  
Giuseppe Satalino ◽  
Francesco Lovergine ◽  
Davide Palmisano ◽  
Francesco Mattia ◽  
...  
Keyword(s):  
Time Series ◽  
Soil Moisture ◽  
Temporal Resolution ◽  
Surface Soil ◽  
Earth Science ◽  
Observation System ◽  
Final Report ◽  
Surface Soil Moisture ◽  
Error Characterization ◽  
L Band

<p>One of the limitations of presently available Synthetic Aperture Radar (SAR) surface soil moisture (SSM) products is their moderated temporal resolution (e.g., 3-4 days) that is non optimal for several applications, as most user requirements point to a temporal resolution of 1-2 days or less. A possible path to tackle this issue is to coordinate multi-mission SAR acquisitions with a view to the future Copernicus Sentinel-1 (C&D and Next Generation) and L-band Radar Observation System for Europe (ROSE-L).</p><p>In this respect, the recent agreement between the Japanese (JAXA) and European (ESA) Space Agencies on the use of SAR Satellites in Earth Science and Applications provides a framework to develop and validate multi-frequency and multi-platform SAR SSM products. In 2019 and 2020, to support insights on the interoperability between C- and L-band SAR observations for SSM retrieval, Sentinel-1 and ALOS-2 systematic acquisitions over the TERENO (Terrestrial Environmental Observatories) Selhausen (Germany) and Apulian Tavoliere (Italy) cal/val sites were gathered. Both sites are well documented and equipped with hydrologic networks.</p><p>The objective of this study is to investigate the integration of multi-frequency SAR measurements for a consistent and harmonized SSM retrieval throughout the error characterization of a combined C- and L-band SSM product. To this scope, time series of Sentinel-1 IW and ALOS-2 FBD data acquired over the two sites will be analysed. The short time change detection (STCD) algorithm, developed, implemented and recently assessed on Sentinel-1 data [e.g., Balenzano et al., 2020; Mattia et al., 2020], will be tailored to the ALOS-2 data. Then, the time series of SAR SSM maps from each SAR system will be derived separately and aggregated in an interleaved SSM product. Furthermore, it will be compared against in situ SSM data systematically acquired by the ground stations deployed at both sites. The study will assess the interleaved SSM product and evaluate the homogeneous quality of C- and L-band SAR SSM maps.</p><p> </p><p> </p><p>References</p><p>Balenzano. A., et al., “Sentinel-1 soil moisture at 1km resolution: a validation study”, submitted to Remote Sensing of Environment (2020).</p><p>Mattia, F., A. Balenzano, G. Satalino, F. Lovergine, A. Loew, et al., “ESA SEOM Land project on Exploitation of Sentinel-1 for Surface Soil Moisture Retrieval at High Resolution,” final report, contract number 4000118762/16/I-NB, 2020.</p>

scholarly journals Integrated radar and lidar analysis reveals extensive loss of remaining intact forest on Sumatra 2007–2010

2015 ◽  
Vol 12 (22) ◽  
pp. 6637-6653 ◽  
Author(s):  
M. B. Collins ◽  
E. T. A. Mitchard
Keyword(s):  
Average Rate ◽  
Forest Biomass ◽  
Forest Monitoring ◽  
Synthetic Aperture ◽  
Lidar Data ◽  
Above Ground Biomass ◽  
Swamp Forest ◽  
L Band ◽  
Field Plots ◽  
Change Map

Abstract. Forests with high above-ground biomass (AGB), including those growing on peat swamps, have historically not been thought suitable for biomass mapping and change detection using synthetic aperture radar (SAR). However, by integrating L-band (λ = 0.23 m) SAR from the ALOS and lidar from the ICESat Earth-Observing satellites with 56 field plots, we were able to create a forest biomass and change map for a 10.7 Mha section of eastern Sumatra that still contains high AGB peat swamp forest. Using a time series of SAR data we estimated changes in both forest area and AGB. We estimate that there was 274 ± 68 Tg AGB remaining in natural forest (≥ 20 m height) in the study area in 2007, with this stock reducing by approximately 11.4 % over the subsequent 3 years. A total of 137.4 kha of the study area was deforested between 2007 and 2010, an average rate of 3.8 % yr−1. The ability to attribute forest loss to different initial biomass values allows for far more effective monitoring and baseline modelling for avoided deforestation projects than traditional, optical-based remote sensing. Furthermore, given SAR's ability to penetrate the smoke and cloud which normally obscure land cover change in this region, SAR-based forest monitoring can be relied on to provide frequent imagery. This study demonstrates that, even at L-band, which typically saturates at medium biomass levels (ca. 150 Mg ha−1), in conjunction with lidar data, it is possible to make reliable estimates of not just the area but also the carbon emissions resulting from land use change.

scholarly journals Evaluation of modeled global carbon dynamics: analysis based on global carbon flux and above-ground biomass data

2016 ◽  
Author(s):  
Bao-Lin Xue ◽  
Qinghua Guo ◽  
Tianyu Hu ◽  
Yongcai Wang ◽  
Shengli Tao ◽  
...  
Keyword(s):  
Spatial Patterns ◽  
Carbon Flux ◽  
Large Scale ◽  
Gross Primary Production ◽  
Carbon Dynamics ◽  
Global Scale ◽  
Above Ground Biomass ◽  
Carbon Cycles ◽  
Ground Biomass ◽  
Global Carbon

Abstract. Dynamic global vegetation models are useful tools for the simulation of carbon dynamics on regional and global scales. However, even the most validated models are usually hampered by the poor availability of global biomass data in the model validation, especially on regional/global scales. Here, taking the integrated biosphere simulator model (IBIS) as an example, we evaluated the modeled carbon dynamics, including gross primary production (GPP) and potential above-ground biomass (AGB), on the global scale. The IBIS model was constrained by both in situ GPP and plot-level AGB data collected from the literature. Independent validation showed that IBIS could reproduce GPP and evapotranspiration with acceptable accuracy at site and global levels. On the global scale, the IBIS-simulated total AGB was similar to those obtained in other studies. However, discrepancies were observed between the model-derived and observed spatial patterns of AGB for Amazonian forests. The differences among the AGB spatial patterns were mainly caused by the single-parameter set of the model used. This study showed that different meteorological inputs can also introduce substantial differences in AGB on the global scale. Further analysis showed that this difference is small compared with parameter-induced differences. The conclusions of our research highlight the necessity of considering the heterogeneity of key model physiological parameters in modeling global AGB. The research also shows that to simulate large-scale carbon dynamics, both carbon flux and AGB data are necessary to constrain the model. The main conclusions of our research will help to improve model simulations of global carbon cycles.

scholarly journals Evaluation of the Sensitivity of SMOS L-VOD to Forest Above-Ground Biomass at Global Scale

2020 ◽  
Vol 12 (9) ◽  
pp. 1450
Author(s):  
Arnaud Mialon ◽  
Nemesio J. Rodríguez-Fernández ◽  
Maurizio Santoro ◽  
Sassan Saatchi ◽  
Stéphane Mermoz ◽  
...  
Keyword(s):  
Large Scale ◽  
Correlation Coefficients ◽  
Global Scale ◽  
Above Ground Biomass ◽  
Ground Biomass ◽  
Northern Latitudes ◽  
Ocean Salinity ◽  
Good Proxy ◽  
Using Data ◽  
The Tropics

The present study evaluates the L band Vegetation Optical Depth (L-VOD) derived from the Soil Moisture and Ocean Salinity (SMOS) satellite to monitor Above Ground Biomass (AGB) at a global scale. Although SMOS L-VOD has been shown to be a good proxy for AGB in Africa and Tropics, little is known about this relationship at large scale. In this study, we further examine this relationship at a global scale using the latest AGB maps from Saatchi et al. and GlobBiomass computed using data acquired during the SMOS period. We show that at a global scale the L-VOD from SMOS is well-correlated with the AGB estimates from Saatchi et al. and GlobBiomass with the Pearson’s correlation coefficients (R) of 0.91 and 0.94 respectively. Although AGB estimates in Africa and the Tropics are well-captured by SMOS L-VOD (R > 0.9), the relationship is less straightforward for the dense forests over the northern latitudes (R = 0.32 and 0.69 with Saatchi et al. and GlobBiomass respectively). This paper gives strong evidence in support of the sensitivity of SMOS L-VOD to AGB estimates at a globale scale, providing an interesting alternative and complement to exisiting sensors for monitoring biomass evolution. These findings can further facilitate research on biomass now that SMOS is providing more than 10 years of data.

Growth and yield response of winter wheat to soil warming and rainfall patterns

2010 ◽  
Vol 148 (5) ◽  
pp. 553-566 ◽  
Author(s):  
R. H. PATIL ◽  
M. LAEGDSMAND ◽  
J. E. OLESEN ◽  
J. R. PORTER
Keyword(s):  
Climate Change ◽  
Soil Moisture ◽  
Winter Wheat ◽  
Rainfall Amount ◽  
Growth And Yield ◽  
Above Ground Biomass ◽  
Soil Warming ◽  
Ground Biomass ◽  
Rainfall Frequency ◽  
Crop Development

SUMMARYIt is predicted that climate change will increase not only seasonal air and soil temperatures in northern Europe but also the variability of rainfall patterns. This may influence temporal soil moisture regimes and the growth and yield of winter wheat. A lysimeter experiment was carried out in 2008/09 with three factors: rainfall amount, rainfall frequency and soil warming (two levels in each factor), on sandy loam soil in Denmark. The soil warming treatment included non-heated as the control and an increase in soil temperature by 5°C at 100 mm depth as heated. The rainfall treatment included the site mean for 1961–90 as the control and the projected monthly mean change for 2071–2100 under the International Panel on Climate Change (IPCC) A2 scenario for the climate change treatment. Projected monthly mean changes in rainfall compared to the reference period 1961–90 show, on average, 31% increase during winter (November–March) and 24% decrease during summer (July–September) with no changes during spring (April–June). The rainfall frequency treatment included mean monthly rainy days for 1961–90 as the control and a reduced frequency treatment with only half the number of rainy days of the control treatment, without altering the monthly mean rainfall amount. Mobile rain-out shelters, automated irrigation system and insulated heating cables were used to impose the treatments.Soil warming hastened crop development during early stages (until stem elongation) and shortened the total crop growing season by 12 days without reducing the period taken for later development stages. Soil warming increased green leaf area index (GLAI) and above-ground biomass during early growth, which was accompanied by an increased amount of nitrogen (N) in plants. However, the plant N concentration and its dilution pattern during later developmental stages followed the same pattern in both heated and control plots. Increased soil moisture deficit was observed only during the period when crop growth was significantly enhanced by soil warming. However, soil warming reduced N concentration in above-ground biomass during the entire growing period, except at harvest, by advancing crop development. Soil warming had no effect on the number of tillers, but reduced ear number and increased 1000 grain weight. This did not affect grain yield and total above-ground biomass compared with control. This suggests that genotypes with a longer vegetative period would probably be better adapted to future warmer conditions. The rainfall pattern treatments imposed in the present study did not influence either soil moisture regimes or performance of winter wheat, though the crop receiving future rainfall amount tended to retain more green leaf area. There was no significant interaction between the soil warming and rainfall treatments on crop growth.

Sign in / Sign up

Export Citation Format

Share Document