scholarly journals Estimating Forest Stand Height in Savannakhet, Lao PDR Using InSAR and Backscatter Methods with L-Band SAR Data

2021 ◽  
Vol 13 (22) ◽  
pp. 4516
Author(s):  
Helen Blue Parache ◽  
Timothy Mayer ◽  
Kelsey E. Herndon ◽  
Africa Ixmucane Flores-Anderson ◽  
Yang Lei ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Forest Stand ◽  
Forest Monitoring ◽  
Synthetic Aperture ◽  
Use Case ◽  
Important Indicator ◽  
L Band ◽  
Sar Data ◽  
Stand Height ◽  
Aperture Radar

Forest stand height (FSH), or average canopy height, serves as an important indicator for forest monitoring. The information provided about above-ground biomass for greenhouse gas emissions reporting and estimating carbon storage is relevant for reporting for Reducing Emissions from Deforestation and Forest Degradation (REDD+). A novel forest height estimation method utilizing a fusion of backscatter and Interferometric Synthetic Aperture Radar (InSAR) data from JAXA’s Advanced Land Observing Satellite Phased Array type L-band Synthetic Aperture Radar (ALOS PALSAR) is applied to a use case in Savannakhet, Lao. Compared with LiDAR, the estimated height from the fusion method had an RMSE of 4.90 m and an R2 of 0.26. These results are comparable to previous studies using SAR estimation techniques. Despite limitations of data quality and quantity, the Savannakhet, Lao use case demonstrates the applicability of these techniques utilizing L-band SAR data for estimating FSH in tropical forests and can be used as a springboard for use of L-band data from the future NASA-ISRO SAR (NISAR) mission.

scholarly journals Mapping potential signs of gas emissions in ice of Lake Neyto, Yamal, Russia, using synthetic aperture radar and multispectral remote sensing data

2021 ◽  
Vol 15 (4) ◽  
pp. 1907-1929
Author(s):  
Georg Pointner ◽  
Annett Bartsch ◽  
Yury A. Dvornikov ◽  
Alexei V. Kouraev
Keyword(s):  
Synthetic Aperture Radar ◽  
Synthetic Aperture ◽  
The Arctic ◽  
Lake Ice ◽  
Gas Emissions ◽  
L Band ◽  
Optical Imagery ◽  
Sar Data ◽  
Sar Imagery ◽  
Aperture Radar

Abstract. Regions of anomalously low backscatter in C-band synthetic aperture radar (SAR) imagery of lake ice of Lake Neyto in northwestern Siberia have been suggested to be caused by emissions of gas (methane from hydrocarbon reservoirs) through the lake’s sediments. However, to assess this connection, only analyses of data from boreholes in the vicinity of Lake Neyto and visual comparisons to medium-resolution optical imagery have been provided due to a lack of in situ observations of the lake ice itself. These observations are impeded due to accessibility and safety issues. Geospatial analyses and innovative combinations of satellite data sources are therefore proposed to advance our understanding of this phenomenon. In this study, we assess the nature of the backscatter anomalies in Sentinel-1 C-band SAR images in combination with very high resolution (VHR) WorldView-2 optical imagery. We present methods to automatically map backscatter anomaly regions from the C-band SAR data (40 m pixel spacing) and holes in lake ice from the VHR data (0.5 m pixel spacing) and examine their spatial relationships. The reliability of the SAR method is evaluated through comparison between different acquisition modes. The results show that the majority of mapped holes (71 %) in the VHR data are clearly related to anomalies in SAR imagery acquired a few days earlier, and similarities to SAR imagery acquired more than a month before are evident, supporting the hypothesis that anomalies may be related to gas emissions. Further, a significant expansion of backscatter anomaly regions in spring is documented and quantified in all analysed years 2015 to 2019. Our study suggests that the backscatter anomalies might be caused by lake ice subsidence and consequent flooding through the holes over the ice top leading to wetting and/or slushing of the snow around the holes, which might also explain outcomes of polarimetric analyses of auxiliary L-band Advanced Land Observing Satellite (ALOS) Phased Array type L-band Synthetic Aperture Radar-2 (PALSAR-2) data. C-band SAR data are considered to be valuable for the identification of lakes showing similar phenomena across larger areas in the Arctic in future studies.

Global Forest Monitoring with Synthetic Aperture Radar (SAR) Data

2016 ◽  
pp. 273-297
Author(s):  
Richard Lucas ◽  
Daniel Clewley ◽  
Ake Rosenqvist ◽  
Josef Kellndorfer ◽  
Wayne Walker ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Forest Monitoring ◽  
Synthetic Aperture ◽  
Sar Data ◽  
Aperture Radar

scholarly journals Spaceborne L-Band Synthetic Aperture Radar Data for Geoscientific Analyses in Coastal Land Applications: A Review

2020 ◽  
Vol 12 (14) ◽  
pp. 2228
Author(s):  
Marco Ottinger ◽  
Claudia Kuenzer
Keyword(s):  
Synthetic Aperture Radar ◽  
Anthropogenic Impacts ◽  
Continuous Mapping ◽  
Synthetic Aperture ◽  
Comprehensive Overview ◽  
Synthetic Aperture Radar Data ◽  
L Band ◽  
Sar Data ◽  
Coastal Land ◽  
Aperture Radar

The coastal zone offers among the world’s most productive and valuable ecosystems and is experiencing increasing pressure from anthropogenic impacts: human settlements, agriculture, aquaculture, trade, industrial activities, oil and gas exploitation and tourism. Earth observation has great capability to deliver valuable data at the local, regional and global scales and can support the assessment and monitoring of land- and water-related applications in coastal zones. Compared to optical satellites, cloud-cover does not limit the timeliness of data acquisition with spaceborne Synthetic Aperture Radar (SAR) sensors, which have all-weather, day and night capabilities. Hence, active radar systems demonstrate great potential for continuous mapping and monitoring of coastal regions, particularly in cloud-prone tropical and sub-tropical climates. The canopy penetration capability with long radar wavelength enables L-band SAR data to be used for coastal terrestrial environments and has been widely applied and investigated for the following geoscientific topics: mapping and monitoring of flooded vegetation and inundated areas; the retrieval of aboveground biomass; and the estimation of soil moisture. Human activities, global population growth, urban sprawl and climate change-induced impacts are leading to increased pressure on coastal ecosystems causing land degradation, deforestation and land use change. This review presents a comprehensive overview of existing research articles that apply spaceborne L-band SAR data for geoscientific analyses that are relevant for coastal land applications.

scholarly journals Forest Fuel Loads Estimation from Landsat ETM+ and ALOS PALSAR Data

2021 ◽  
Vol 13 (6) ◽  
pp. 1189
Author(s):  
Yanxi Li ◽  
Xingwen Quan ◽  
Zhanmang Liao ◽  
Binbin He
Keyword(s):  
Synthetic Aperture Radar ◽  
Synthetic Aperture ◽  
Optical Data ◽  
Fuel Load ◽  
Load Estimation ◽  
Fuel Loads ◽  
Different Types ◽  
L Band ◽  
Sar Data ◽  
Aperture Radar

Fuel load is the key factor driving fire ignition, spread and intensity. The current literature reports the light detection and ranging (LiDAR), optical and airborne synthetic aperture radar (SAR) data for fuel load estimation, but the optical and SAR data are generally individually explored. Optical and SAR data are expected to be sensitive to different types of fuel loads because of their different imaging mechanisms. Optical data mainly captures the characteristics of leaf and forest canopy, while the latter is more sensitive to forest vertical structures due to its strong penetrability. This study aims to explore the performance of Landsat Enhanced Thematic Mapper Plus (ETM+) and Advanced Land Observing Satellite (ALOS) Phased Arrayed L-band Synthetic Aperture Radar (PALSAR) data as well as their combination on estimating three different types of fuel load—stem fuel load (SFL), branch fuel load (BFL) and foliage fuel load (FFL). We first analyzed the correlation between the three types of fuel load and optical and SAR data. Then, the partial least squares regression (PLSR) was used to build the fuel load estimation models based on the fuel load measurements from Vindeln, Sweden, and variables derived from optical and SAR data. Based on the leave-one-out cross-validation (LOOCV) method, results show that L-band SAR data performed well on all three types of fuel load (R2 = 0.72, 0.70, 0.72). The optical data performed best for FFL estimation (R2 = 0.66), followed by BFL (R2 = 0.56) and SFL (R2 = 0.37). Further improvements were found for the SFL, BFL and FFL estimation when integrating optical and SAR data (R2 = 0.76, 0.81, 0.82), highlighting the importance of data selection and combination for fuel load estimation.

scholarly journals Multi-Sensor InSAR Analysis of Progressive Land Subsidence over the Coastal City of Urayasu, Japan

2018 ◽  
Vol 10 (8) ◽  
pp. 1304 ◽  
Author(s):  
Yusupujiang Aimaiti ◽  
Fumio Yamazaki ◽  
Wen Liu
Keyword(s):  
Synthetic Aperture Radar ◽  
Survey Data ◽  
Land Subsidence ◽  
Ground Deformation ◽  
Tohoku Earthquake ◽  
Synthetic Aperture ◽  
Alos Palsar ◽  
The 2011 Tohoku Earthquake ◽  
L Band ◽  
Aperture Radar

In earthquake-prone areas, identifying patterns of ground deformation is important before they become latent risk factors. As one of the severely damaged areas due to the 2011 Tohoku earthquake in Japan, Urayasu City in Chiba Prefecture has been suffering from land subsidence as a part of its land was built by a massive land-fill project. To investigate the long-term land deformation patterns in Urayasu City, three sets of synthetic aperture radar (SAR) data acquired during 1993–2006 from European Remote Sensing satellites (ERS-1/-2 (C-band)), during 2006–2010 from the Phased Array L-band Synthetic Aperture Radar onboard the Advanced Land Observation Satellite (ALOS PALSAR (L-band)) and from 2014–2017 from the ALOS-2 PALSAR-2 (L-band) were processed by using multitemporal interferometric SAR (InSAR) techniques. Leveling survey data were also used to verify the accuracy of the InSAR-derived results. The results from the ERS-1/-2, ALOS PALSAR and ALOS-2 PALSAR-2 data processing showed continuing subsidence in several reclaimed areas of Urayasu City due to the integrated effects of numerous natural and anthropogenic processes. The maximum subsidence rate of the period from 1993 to 2006 was approximately 27 mm/year, while the periods from 2006 to 2010 and from 2014 to 2017 were approximately 30 and 18 mm/year, respectively. The quantitative validation results of the InSAR-derived deformation trend during the three observation periods are consistent with the leveling survey data measured from 1993 to 2017. Our results further demonstrate the advantages of InSAR measurements as an alternative to ground-based measurements for land subsidence monitoring in coastal reclaimed areas.

Monitoring Everglades freshwater marsh water level using L-band synthetic aperture radar backscatter

2014 ◽  
Vol 150 ◽  
pp. 66-81 ◽  
Author(s):  
Jin-Woo Kim ◽  
Zhong Lu ◽  
John W. Jones ◽  
C.K. Shum ◽  
Hyongki Lee ◽  
...  
Keyword(s):  
Synthetic Aperture Radar ◽  
Water Level ◽  
Freshwater Marsh ◽  
Synthetic Aperture ◽  
Radar Backscatter ◽  
L Band ◽  
Aperture Radar
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