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7931 KiB

Open AccessArticle

Deformation Trend Extraction Based on Multi-Temporal InSAR in Shanghai

by Jie Chen, Jicang Wu, Lina Zhang, Junping Zou, Guoxiang Liu, Rui Zhang and Bing Yu

Remote Sens. 2013, 5(4), 1774-1786; https://doi.org/10.3390/rs5041774 - 11 Apr 2013

Cited by 39 | Viewed by 8809

Abstract

Shanghai is a modern metropolis characterized by high urban density and anthropogenic ground motions. Although traditional deformation monitoring methods, such as GPS and spirit leveling, are reliable to millimeter accuracy, the sparse point subsidence information makes understanding large areas difficult. Multiple temporal space-borne [...] Read more.

Shanghai is a modern metropolis characterized by high urban density and anthropogenic ground motions. Although traditional deformation monitoring methods, such as GPS and spirit leveling, are reliable to millimeter accuracy, the sparse point subsidence information makes understanding large areas difficult. Multiple temporal space-borne synthetic aperture radar interferometry is a powerful high-accuracy (sub-millimeter) remote sensing tool for monitoring slow ground deformation for a large area with a high point density. In this paper, the Interferometric Point Target Time Series Analysis method is used to extract ground subsidence rates in Shanghai based on 31 C-Band and 35 X-Band synthetic aperture radar (SAR) images obtained by Envisat and COSMO SkyMed (CSK) satellites from 2007 to 2010. A significant subsidence funnel that was detected is located in the junction place between the Yangpu and the Hongkou Districts. A t-test is formulated to judge the agreements between the subsidence results obtained by SAR and by spirit leveling. In addition, four profile lines crossing the subsidence funnel area are chosen for a comparison of ground subsidence rates, which were obtained by the two different band SAR images, and show a good agreement. Full article

(This article belongs to the Special Issue Remote Sensing by Synthetic Aperture Radar Technology)

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1553 KiB

Open AccessArticle

Estimating CO₂ Sequestration by Forests in Oita Prefecture, Japan, by Combining LANDSAT ETM+ and ALOS Satellite Remote Sensing Data

by Kazadi Sanga-Ngoie, Kotaro Iizuka and Shoko Kobayashi

Remote Sens. 2012, 4(11), 3544-3570; https://doi.org/10.3390/rs4113544 - 19 Nov 2012

Cited by 18 | Viewed by 8828

Abstract

CO₂ sequestration of the forests in Oita Prefecture, Japan, was estimated using satellite remote sensing data. First, hybrid classification of the optical LANDSAT ETM+ data was performed using GIS to produce a detailed land cover map. CO₂ sequestration for each forest [...] Read more.

CO₂ sequestration of the forests in Oita Prefecture, Japan, was estimated using satellite remote sensing data. First, hybrid classification of the optical LANDSAT ETM+ data was performed using GIS to produce a detailed land cover map. CO₂ sequestration for each forest type was calculated using the sequestration rates per unit area multiplied by the forest areas obtained from the land cover map This results in 3.57 MtCO₂/yr for coniferous, 0.77 MtCO₂/yr for deciduous broadleaf, and 2.25 MtCO₂/yr for evergreen broadleaf, equivalent to a total of 6.60 MtCO₂/yr for all the forest covers in Oita. Then, two different methodologies were used to improve these estimates by considering tree ages: the Normalized Difference Vegetation Index (NDVI) and the stem volume methods. Calculation using the NDVI method shows the limitation of this method in providing detailed estimations for trees older than 15 years, because of NDVI saturation beyond this age. In the stem volume method, tree ages were deduced from stem volume values obtained by using PALSAR backscattering data. Sequestration based on tree age forest subclasses yields 2.96 MtCO₂/yr (coniferous) and 0.31 MtCO₂/yr (deciduous broadleaf forests). These results show the importance of using not only detailed forest types, but also detailed tree age information for more realistic CO₂ sequestration estimates. In so doing, overestimation of the sequestration capacity of forests could be avoided, and the information on the status and location of forest resources could be improved, thereby leading to sounder decision making in sustainable management of forest resources. Full article

(This article belongs to the Special Issue Remote Sensing by Synthetic Aperture Radar Technology)

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2760 KiB

Open AccessArticle

Characteristics of Decomposition Powers of L-Band Multi-Polarimetric SAR in Assessing Tree Growth of Industrial Plantation Forests in the Tropics

by Shoko Kobayashi, Yoshiharu Omura, Kazadi Sanga-Ngoie, Ragil Widyorini, Shuichi Kawai, Bambang Supriadi and Yoshio Yamaguchi

Remote Sens. 2012, 4(10), 3058-3077; https://doi.org/10.3390/rs4103058 - 15 Oct 2012

Cited by 24 | Viewed by 7249

Abstract

A decomposition scheme was applied to ALOS/PALSAR data obtained from a fast-growing tree plantation in Sumatra, Indonesia to extract tree stem information and then estimate the forest stand volume. The scattering power decomposition of the polarimetric SAR data was performed both with and [...] Read more.

A decomposition scheme was applied to ALOS/PALSAR data obtained from a fast-growing tree plantation in Sumatra, Indonesia to extract tree stem information and then estimate the forest stand volume. The scattering power decomposition of the polarimetric SAR data was performed both with and without a rotation matrix and compared to the following field-measured forest biometric parameters: tree diameter, tree height and stand volume. The analytical results involving the rotation matrix correlated better than those without the rotation matrix even for natural scattering surfaces within the forests. Our primary finding was that all of the decomposition powers from the rotated matrix correlated significantly to the forest biometric parameters when divided by the total power. The surface scattering ratio of the total power markedly decreased with the forest growth, whereas the canopy and double-bounce scattering ratios increased. The observations of the decomposition powers were consistent with the tree growth characteristics. Consequently, we found a significant logarithmic relationship between the decomposition powers and the forest biometric parameters that can potentially be used to estimate the forest stand volume. Full article

(This article belongs to the Special Issue Remote Sensing by Synthetic Aperture Radar Technology)

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3706 KiB

Open AccessArticle

Mapping of Ice Motion in Antarctica Using Synthetic-Aperture Radar Data

by Jeremie Mouginot, Bernd Scheuchl and Eric Rignot

Remote Sens. 2012, 4(9), 2753-2767; https://doi.org/10.3390/rs4092753 - 18 Sep 2012

Cited by 182 | Viewed by 12871

Abstract

Ice velocity is a fundamental parameter in studying the dynamics of ice sheets. Until recently, no complete mapping of Antarctic ice motion had been available due to calibration uncertainties and lack of basic data. Here, we present a method for calibrating and mosaicking [...] Read more.

Ice velocity is a fundamental parameter in studying the dynamics of ice sheets. Until recently, no complete mapping of Antarctic ice motion had been available due to calibration uncertainties and lack of basic data. Here, we present a method for calibrating and mosaicking an ensemble of InSAR satellite measurements of ice motion from six sensors: the Japanese ALOS PALSAR, the European Envisat ASAR, ERS-1 and ERS-2, and the Canadian RADARSAT-1 and RADARSAT-2. Ice motion calibration is made difficult by the sparsity of in-situ reference points and the shear size of the study area. A sensor-dependent data stacking scheme is applied to reduce measurement uncertainties. The resulting ice velocity mosaic has errors in magnitude ranging from 1 m/yr in the interior regions to 17 m/yr in coastal sectors and errors in flow direction ranging from less than 0.5° in areas of fast flow to unconstrained direction in sectors of slow motion. It is important to understand how these mosaics are calibrated to understand the inner characteristics of the velocity products as well as to plan future InSAR acquisitions in the Antarctic. As an example, we show that in broad sectors devoid of ice-motion control, it is critical to operate ice motion mapping on a large scale to avoid pitfalls of calibration uncertainties that would make it difficult to obtain quality products and especially construct reliable time series of ice motion needed to detect temporal changes. Full article

(This article belongs to the Special Issue Remote Sensing by Synthetic Aperture Radar Technology)

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1239 KiB

Open AccessArticle

Polarimetric Decomposition Analysis of ALOS PALSAR Observation Data before and after a Landslide Event

by Chinatsu Yonezawa, Manabu Watanabe and Genya Saito

Remote Sens. 2012, 4(8), 2314-2328; https://doi.org/10.3390/rs4082314 - 7 Aug 2012

Cited by 64 | Viewed by 9479

Abstract

Radar scattering mechanisms over landslide areas were studied using representative full polarimetric parameters: Freeman–Durden decomposition, and eigenvalue–eigenvector decomposition. Full polarimetric ALOS (Advanced Land Observation Satellite) PALSAR (Phased Array type L-band Synthetic Aperture Radar) datasets were used to examine landslides caused by the 2008 [...] Read more.

Radar scattering mechanisms over landslide areas were studied using representative full polarimetric parameters: Freeman–Durden decomposition, and eigenvalue–eigenvector decomposition. Full polarimetric ALOS (Advanced Land Observation Satellite) PALSAR (Phased Array type L-band Synthetic Aperture Radar) datasets were used to examine landslides caused by the 2008 Iwate-Miyagi Nairiku Earthquake in northern Japan. The Freeman–Durden decomposition indicates that areas affected by large-scale landslides show dominance of the surface scattering component in both ascending and descending orbit data. The polarimetric parameters of eigenvalue–eigenvector decomposition, such as entropy, anisotropy, and alpha angle, were also computed over the landslide areas. Unsupervised classification based on the H- plane explicitly distinguishes landslide areas from others such as forest, water, and snow-covered areas, but does not perform well for farmland. A landslide area is difficult to recognize from a single-polarization image, whereas it is clearly extracted on the full polarimetric data obtained after the earthquake. From these results, we conclude that 30-m resolution full polarimetric data are more useful than 10-m resolution single-polarization PALSAR data in classifying land coverage, and are better suited to detect landslide areas. Additional information, such as pre-landslide imagery, is needed to distinguish landslide areas from farmland or bare soil. Full article

(This article belongs to the Special Issue Remote Sensing by Synthetic Aperture Radar Technology)

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10504 KiB

Open AccessArticle

An Approach to Mapping Forest Growth Stages in Queensland, Australia through Integration of ALOS PALSAR and Landsat Sensor Data

by Daniel Clewley, Richard Lucas, Arnon Accad, John Armston, Michiala Bowen, John Dwyer, Sandy Pollock, Peter Bunting, Clive McAlpine, Teresa Eyre, Annie Kelly, João Carreiras and Mahta Moghaddam

Remote Sens. 2012, 4(8), 2236-2255; https://doi.org/10.3390/rs4082236 - 2 Aug 2012

Cited by 20 | Viewed by 9075

Abstract

Whilst extensive clearance of forests in the eastern Australian Brigalow Belt Bioregion (BBB) has occurred since European settlement, appropriate management of those that are regenerating can facilitate restoration of biomass (carbon) and biodiversity to levels typical of relatively undisturbed or remnant formations. However, [...] Read more.

Whilst extensive clearance of forests in the eastern Australian Brigalow Belt Bioregion (BBB) has occurred since European settlement, appropriate management of those that are regenerating can facilitate restoration of biomass (carbon) and biodiversity to levels typical of relatively undisturbed or remnant formations. However, maps of forests are different stages of regeneration are needed to facilitate restoration planning, including prevention of further re-clearing. Focusing on the Tara Downs subregion of the BBB and on forests with brigalow (Acacia harpophylla) as a component, this research establishes a method for differentiating and mapping early, intermediate and remnant growth stages from Japan Aerospace Exploration Agency (JAXA) Advanced Land Observing Satellite (ALOS) Phased-Array L-band Synthetic Aperture Radar (PALSAR) Fine Beam Dual (FBD) L-band HH- and HV-polarisation backscatter and Landsat-derived Foliage Projective Cover (FPC). Using inventory data collected from 74 plots, located in the Tara Downs subregion, forests were assigned to one of three regrowth stages based on their height and cover relative to that of undisturbed stands. The image data were then segmented into objects with each assigned to a growth stage by comparing the distributions of L-band HV and HH polarisation backscatter and FPC to that of reference distributions using a z-test. Comparison with independent assessments of growth stage, based on time-series analysis of aerial photography and SPOT images, established an overall accuracy of > 70%, with this increasing to 90% when intermediate regrowth was excluded and only early-stage regrowth and remnant classes were considered. The proposed method can be adapted to respond to amendments to user-definitions of growth stage and, as regional mosaics of ALOS PALSAR and Landsat FPC are available for Queensland, has application across the state. Full article

(This article belongs to the Special Issue Remote Sensing by Synthetic Aperture Radar Technology)

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1598 KiB

Open AccessArticle

Four-Component Scattering Power Decomposition Algorithm with Rotation of Covariance Matrix Using ALOS-PALSAR Polarimetric Data

by Mitsunobu Sugimoto, Kazuo Ouchi and Yasuhiro Nakamura

Remote Sens. 2012, 4(8), 2199-2209; https://doi.org/10.3390/rs4082199 - 25 Jul 2012

Cited by 14 | Viewed by 7300

Abstract

The present study introduces the four-component scattering power decomposition (4-CSPD) algorithm with rotation of covariance matrix, and presents an experimental proof of the equivalence between the 4-CSPD algorithms based on rotation of covariance matrix and coherency matrix. From a theoretical point of view, [...] Read more.

The present study introduces the four-component scattering power decomposition (4-CSPD) algorithm with rotation of covariance matrix, and presents an experimental proof of the equivalence between the 4-CSPD algorithms based on rotation of covariance matrix and coherency matrix. From a theoretical point of view, the 4-CSPD algorithms with rotation of the two matrices are identical. Although it seems obvious, no experimental evidence has yet been presented. In this paper, using polarimetric synthetic aperture radar (POLSAR) data acquired by Phased Array L-band SAR (PALSAR) on board of Advanced Land Observing Satellite (ALOS), an experimental proof is presented to show that both algorithms indeed produce identical results. Full article

(This article belongs to the Special Issue Remote Sensing by Synthetic Aperture Radar Technology)

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1620 KiB

Open AccessArticle

C-Band SAR Imagery for Snow-Cover Monitoring at Treeline, Churchill, Manitoba, Canada

by Frédérique C. Pivot

Remote Sens. 2012, 4(7), 2133-2155; https://doi.org/10.3390/rs4072133 - 13 Jul 2012

Cited by 24 | Viewed by 8221

Abstract

RADARSAT and ERS-2 data collected at multiple incidence angles are used to characterize the seasonal variations in the backscatter of snow-covered landscapes in the northern Hudson Bay Lowlands during the winters of 1997/98 and 1998/99. The study evaluates the usefulness of C-band SAR [...] Read more.

RADARSAT and ERS-2 data collected at multiple incidence angles are used to characterize the seasonal variations in the backscatter of snow-covered landscapes in the northern Hudson Bay Lowlands during the winters of 1997/98 and 1998/99. The study evaluates the usefulness of C-band SAR systems for retrieving the snow water equivalent under dry snow conditions in the forest–tundra ecotone. The backscatter values are compared against ground measurements at six sampling sites, which are taken to be representative of the land-cover types found in the region. The contribution of dry snow to the radar return is evident when frost penetrates the first 20 cm of soil. Only then does the backscatter respond positively to changes in snow water equivalent, at least in the open and forested areas near the coast, where 1-dB increases in backscatter for each approximate 5–10 mm of accumulated water equivalent are observed at 20–31° incidence angles. Further inland, the backscatter shows either no change or a negative change with snow accumulation, which suggests that the radar signal there is dominated by ground surface scattering (e.g., fen) when not attenuated by vegetation (e.g., forested and transition). With high-frequency ground-penetrating radar, we demonstrate the presence of a 10–20-cm layer of black ice underneath the snow cover, which causes the reduced radar returns (−15 dB and less) observed in the inland fen. A correlation between the backscattering and the snow water equivalent cannot be determined due to insufficient observations at similar incidence angles. To establish a relationship between the snow water equivalent and the backscatter, only images acquired with similar incidence angles should be used, and they must be corrected for both vegetation and ground effects. Full article

(This article belongs to the Special Issue Remote Sensing by Synthetic Aperture Radar Technology)

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752 KiB

Open AccessArticle

High Resolution Mapping of Peatland Hydroperiod at a High-Latitude Swedish Mire

by Nathan Torbick, Andreas Persson, David Olefeldt, Steve Frolking, William Salas, Stephen Hagen, Patrick Crill and Changsheng Li

Remote Sens. 2012, 4(7), 1974-1994; https://doi.org/10.3390/rs4071974 - 29 Jun 2012

Cited by 27 | Viewed by 9943

Abstract

Monitoring high latitude wetlands is required to understand feedbacks between terrestrial carbon pools and climate change. Hydrological variability is a key factor driving biogeochemical processes in these ecosystems and effective assessment tools are critical for accurate characterization of surface hydrology, soil moisture, and [...] Read more.

Monitoring high latitude wetlands is required to understand feedbacks between terrestrial carbon pools and climate change. Hydrological variability is a key factor driving biogeochemical processes in these ecosystems and effective assessment tools are critical for accurate characterization of surface hydrology, soil moisture, and water table fluctuations. Operational satellite platforms provide opportunities to systematically monitor hydrological variability in high latitude wetlands. The objective of this research application was to integrate high temporal frequency Synthetic Aperture Radar (SAR) and high spatial resolution Light Detection and Ranging (LiDAR) observations to assess hydroperiod at a mire in northern Sweden. Geostatistical and polarimetric (PLR) techniques were applied to determine spatial structure of the wetland and imagery at respective scales (0.5 m to 25 m). Variogram, spatial regression, and decomposition approaches characterized the sensitivity of the two platforms (SAR and LiDAR) to wetland hydrogeomorphology, scattering mechanisms, and data interrelationships. A Classification and Regression Tree (CART), based on random forest, fused multi-mode (fine-beam single, dual, quad pol) Phased Array L-band Synthetic Aperture Radar (PALSAR) and LiDAR-derived elevation to effectively map hydroperiod attributes at the Swedish mire across an aggregated warm season (May–September, 2006–2010). Image derived estimates of water and peat moisture were sensitive (R² = 0.86) to field measurements of water table depth (cm). Peat areas that are underlain by permafrost were observed as areas with fluctuating soil moisture and water table changes. Full article

(This article belongs to the Special Issue Remote Sensing by Synthetic Aperture Radar Technology)

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1097 KiB

Open AccessArticle

Three-Component Power Decomposition for Polarimetric SAR Data Based on Adaptive Volume Scatter Modeling

by Yi Cui, Yoshio Yamaguchi, Jian Yang, Sang-Eun Park, Hirokazu Kobayashi and Gulab Singh

Remote Sens. 2012, 4(6), 1559-1572; https://doi.org/10.3390/rs4061559 - 29 May 2012

Cited by 39 | Viewed by 9841

Abstract

In this paper, the three-component power decomposition for polarimetric SAR (PolSAR) data with an adaptive volume scattering model is proposed. The volume scattering model is assumed to be reflection-symmetric but parameterized. For each image pixel, the decomposition first starts with determining the adaptive [...] Read more.

In this paper, the three-component power decomposition for polarimetric SAR (PolSAR) data with an adaptive volume scattering model is proposed. The volume scattering model is assumed to be reflection-symmetric but parameterized. For each image pixel, the decomposition first starts with determining the adaptive parameter based on matrix similarity metric. Then, a respective scattering power component is retrieved with the established procedure. It has been shown that the proposed method leads to complete elimination of negative powers as the result of the adaptive volume scattering model. Experiments with the PolSAR data from both the NASA/JPL (National Aeronautics and Space Administration/Jet Propulsion Laboratory) Airborne SAR (AIRSAR) and the JAXA (Japan Aerospace Exploration Agency) ALOS-PALSAR also demonstrate that the proposed method not only obtains similar/better results in vegetated areas as compared to the existing Freeman-Durden decomposition but helps to improve discrimination of the urban regions. Full article

(This article belongs to the Special Issue Remote Sensing by Synthetic Aperture Radar Technology)

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2112 KiB

Open AccessArticle

A Phase-Offset Estimation Method for InSAR DEM Generation Based on Phase-Offset Functions

by José Claudio Mura, Muriel Pinheiro, Rafael Rosa and João Roberto Moreira

Remote Sens. 2012, 4(3), 745-761; https://doi.org/10.3390/rs4030745 - 20 Mar 2012

Cited by 19 | Viewed by 8460

Abstract

This paper presents a novel method for estimating the absolute phase offset in interferometric synthetic aperture radar (SAR) measurements for digital elevation model (DEM) generation. The method is based on “phase-offset functions (POF),” relating phase offset to topographic height, and are computed for [...] Read more.

This paper presents a novel method for estimating the absolute phase offset in interferometric synthetic aperture radar (SAR) measurements for digital elevation model (DEM) generation. The method is based on “phase-offset functions (POF),” relating phase offset to topographic height, and are computed for two different overlapping interferometric data acquisitions performed with considerably different incidence angles over the same area of interest. For the purpose of extended mapping, opposite viewing directions are preferred. The two “phase-offset functions” are then linearly combined, yielding a “combined phase-offset function (CPOF)”. The intersection point of several straight lines (CPOFs), corresponding to different points in the overlap area allows for solving the phase offset for both acquisitions. Aiming at increasing performance and stability, this intersection point is found by means of averaging many points and applying principal component analysis. The method is validated against traditional phase offset estimation with corner reflectors (CR) using real OrbiSAR-1 data in X- and P-band. Full article

(This article belongs to the Special Issue Remote Sensing by Synthetic Aperture Radar Technology)

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Review

Jump to: Research

10295 KiB

Open AccessReview

Recent Trend and Advance of Synthetic Aperture Radar with Selected Topics

by Kazuo Ouchi

Remote Sens. 2013, 5(2), 716-807; https://doi.org/10.3390/rs5020716 - 5 Feb 2013

Cited by 249 | Viewed by 31726

Abstract

The present article is an introductory paper in this special issue on synthetic aperture radar (SAR). A short review is presented on the recent trend and development of SAR and related techniques with selected topics, including the fields of applications, specifications of airborne [...] Read more.

The present article is an introductory paper in this special issue on synthetic aperture radar (SAR). A short review is presented on the recent trend and development of SAR and related techniques with selected topics, including the fields of applications, specifications of airborne and spaceborne SARs, and information contents in and interpretations of amplitude data, interferometric SAR (InSAR) data, and polarimetric SAR (PolSAR) data. The review is by no means extensive, and as such only brief summaries of of each selected topics and key references are provided. For further details, the readers are recommended to read the literature given in the references theirin. Full article

(This article belongs to the Special Issue Remote Sensing by Synthetic Aperture Radar Technology)

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