In this paper, we examine the role of polarimetry in synthetic aperture radar (SAR) interferometry. We first propose a general formulation for vector wave interferometry that includes conventional scalar interferometry as a special case. Then, we show how polarimetric basis transformations can be introduced into SAR interferometry and applied to form interferograms between all possible linear combinations of polarization states. This allows us to reveal the strong polarization dependency of the interferometric coherence. We then solve the coherence optimization problem involving maximization of interferometric coherence and formulate a new coherent decomposition for polarimetric SAR interferometry that allows the separation of the effective phase centers of different scattering mechanisms. A simplified stochastic scattering model for an elevated forest canopy is introduced to demonstrate the effectiveness of the proposed algorithms. In this way, we demonstrate the importance of wave polarization for the physical interpretation of SAR interferograms. We investigate the potential of polarimetric SAR interferometry using results from the evaluation of fully polarimetric interferometric shuttle imaging radar (SIR)-C/X-SAR data collected during October 8-9, 1994, over the SE Baikal Lake Selenga delta region of Buriatia, Southeast Siberia, Russia.

Polarimetric SAR interferometry

The wealth of complementary data available from remote sensing missions can hugely aid efforts towards accurately determining land use and quantifying subtle changes in land use management or intensity. This study reviewed 112 studies on fusing optical and radar data, which offer unique spectral and structural information, for land cover and use assessments. Contrary to our expectations, only 50 studies specifically addressed land use, and five assessed land use changes, while the majority addressed land cover. The advantages of fusion for land use analysis were assessed in 32 studies, and a large majority (28 studies) concluded that fusion improved results compared to using single data sources. Study sites were small, frequently 300–3000 km 2 or individual plots, with a lack of comparison of results and accuracies across sites. Although a variety of fusion techniques were used, pre-classification fusion followed by pixel-level inputs in traditional classification algorithms (e.g., Gaussian maximum likelihood classification) was common, but often without a concrete rationale on the applicability of the method to the land use theme being studied. Progress in this field of research requires the development of robust techniques of fusion to map the intricacies of land uses and changes therein and systematic procedures to assess the benefits of fusion over larger spatial scales.

/pdf/a-review-of-the-application-of-optical-and-radar-remote-2snukgp7pb.pdf

A review of the application of optical and radar remote sensing data fusion to land use mapping and monitoring

This study presents a new global baseline of mangrove extent for 2010 and has been released as the first output of the Global Mangrove Watch (GMW) initiative. This is the first study to apply a globally consistent and automated method for mapping mangroves, identifying a global extent of 137,600 km 2 . The overall accuracy for mangrove extent was 94.0% with a 99% likelihood that the true value is between 93.6–94.5%, using 53,878 accuracy points across 20 sites distributed globally. Using the geographic regions of the Ramsar Convention on Wetlands, Asia has the highest proportion of mangroves with 38.7% of the global total, while Latin America and the Caribbean have 20.3%, Africa has 20.0%, Oceania has 11.9%, North America has 8.4% and the European Overseas Territories have 0.7%. The methodology developed is primarily based on the classification of ALOS PALSAR and Landsat sensor data, where a habitat mask was first generated, within which the classification of mangrove was undertaken using the Extremely Randomized Trees classifier. This new globally consistent baseline will also form the basis of a mangrove monitoring system using JAXA JERS-1 SAR, ALOS PALSAR and ALOS-2 PALSAR-2 radar data to assess mangrove change from 1996 to the present. However, when using the product, users should note that a minimum mapping unit of 1 ha is recommended and that the error increases in regions of disturbance and where narrow strips or smaller fragmented areas of mangroves are present. Artefacts due to cloud cover and the Landsat-7 SLC-off error are also present in some areas, particularly regions of West Africa due to the lack of Landsat-5 data and persistence cloud cover. In the future, consideration will be given to the production of a new global baseline based on 10 m Sentinel-2 composites.

The Global Mangrove Watch—A New 2010 Global Baseline of Mangrove Extent

The primary objective of the TanDEM-X mission is the generation of a global, consistent, and high-resolution digital elevation model (DEM) with unprecedented global accuracy. The goal is achieved by exploiting the interferometric capabilities of the two twin SAR satellites TerraSAR-X and TanDEM-X, which fly in a close orbit formation, acting as an X-band single-pass interferometer. Between December 2010 and early 2015 all land surfaces have been acquired at least twice, difficult terrain up to seven or eight times. The acquisition strategy, data processing, and DEM calibration and mosaicking have been systematically monitored and optimized throughout the entire mission duration, in order to fulfill the specification. The processing of all data has finally been completed in September 2016 and this paper reports on the final performance of the TanDEM-X global DEM and presents the acquisition and processing strategy which allowed to obtain the final DEM quality. The results confirm the outstanding global accuracy of the delivered product, which can be now utilized for both scientific and commercial applications.

Generation and performance assessment of the global TanDEM-X digital elevation model

The status, changes, and disturbances in geomorphological regimes can be regarded as controlling and regulating factors for biodiversity. Therefore, monitoring geomorphology at local, regional, and global scales is not only necessary to conserve geodiversity, but also to preserve biodiversity, as well as to improve biodiversity conservation and ecosystem management. Numerous remote sensing (RS) approaches and platforms have been used in the past to enable a cost-effective, increasingly freely available, comprehensive, repetitive, standardized, and objective monitoring of geomorphological characteristics and their traits. This contribution provides a state-of-the-art review for the RS-based monitoring of these characteristics and traits, by presenting examples of aeolian, fluvial, and coastal landforms. Different examples for monitoring geomorphology as a crucial discipline of geodiversity using RS are provided, discussing the implementation of RS technologies such as LiDAR, RADAR, as well as multi-spectral and hyperspectral sensor technologies. Furthermore, data products and RS technologies that could be used in the future for monitoring geomorphology are introduced. The use of spectral traits (ST) and spectral trait variation (STV) approaches with RS enable the status, changes, and disturbances of geomorphic diversity to be monitored. We focus on the requirements for future geomorphology monitoring specifically aimed at overcoming some key limitations of ecological modeling, namely: the implementation and linking of in-situ, close-range, air- and spaceborne RS technologies, geomorphic traits, and data science approaches as crucial components for a better understanding of the geomorphic impacts on complex ecosystems. This paper aims to impart multidimensional geomorphic information obtained by RS for improved utilization in biodiversity monitoring.

Linking the Remote Sensing of Geodiversity and Traits Relevant to Biodiversity—Part II: Geomorphology, Terrain and Surfaces

New global forest/non-forest maps from ALOS PALSAR data (2007–2010)

Abstract Four global mosaics of Advanced Land Observing Satellite (ALOS) Phased Arrayed L-band Synthetic Aperture Radar (SAR) HH and HV polarization data were generated at 25 m spatial resolution using data acquired annually from 2007 to 2010. Variability in L-band HH and HV gamma-naught (γ0) for forests was observed between regions, with this attributed to differences in forest structure and vegetation/surface moisture conditions. Region-specific backscatter thresholds were therefore applied to produce from each annual mosaic, a global map of forest and non-forest cover from which maps of forest losses and gain were generated. The overall agreement with forest/non-forest assessments using the Degree Confluence Project, the Forest Resource Assessment and Google Earth images was 85%, 91% and 95% respectively. Using 2007 as a baseline, decreases of 0.040 and 0.028 dB (with a 0.006 dB 99% confidence level) were observed in the HH and HV γ0 respectively over the same areas suggesting a decrease in forest area and/or increased smoothing of the global surface at the L-band radar observation over the four-year period. The maps provide a new global resource for documenting the changing extent of forests and offer opportunities for quantifying historical and future dynamics through comparison with historical (1992–1998) Japanese Earth Resources Satellite (JERS-1) SAR and the forthcoming (from 2014) ALOS-2 PALSAR-2 data. Four year PALSAR mosaics and the forest/non-forest data, which were generated and analyzed in this paper, are opened to the public for free downloading albeit with coarser resolutions (WWW1). Future distribution of the higher (original) resolution datasets from PALSAR as well as the ALOS-2/PALSAR-2 is planned.

New Global Forest/Non-Forest Maps from ALOS PALSAR data (2007-2010)

This paper summarizes the calibration and validation results of the JAXA's new airborne polarimetric interferometric L-band synthetic aperture radar, i.e., Pi-SAR-L2, developed in 2011-2012 and started the operation in April of 2012. Pi-SAR-L2 is enhanced for the radiometric and geometric performances with 85MHz bandwidth and the accurate Inertial Navigation System. Polarimetric and geometric calibration has been conducted using the corner reflectors and the forest at Tomakomai-forest in Hokkaido. Statistical evaluation of the data acquired at the various test sites determined the noise equivalent sigma-zero as -54dB, which is significantly low enough value to apply the Pi-SAR-L2 at the various research areas.

http://ieeexplore.ieee.org/iel7/6690576/6704984/06705047.pdf

Calibration and validation of the Pi-SAR-L2

Detecting Mountainous Landslides by SAR Polarimetry: A Comparative Study Using Pi-SAR-L2 and X-band SARs

The Japan Aerospace Exploration Agency (JAXA) has produced the world's first 10m resolution L-band SAR global mosaic datasets. These data sets were generated to monitor forest changes from the 1990s to present. SRTM-3 (90m resolution) DEM was used to correct the terrain-induced SAR intensity variations and the ortho-rectification. Both corrections were applied for geometric and radiometric calibration purposes. The data sets are useful to monitor the temporal forest cover and forest change, and were used to derive forest/non-forest information.

Takeshi Motooka

Papers

New global forest/non-forest maps from ALOS PALSAR data (2007–2010)

New Global Forest/Non-Forest Maps from ALOS PALSAR data (2007-2010)

Calibration and validation of the Pi-SAR-L2

Detecting Mountainous Landslides by SAR Polarimetry: A Comparative Study Using Pi-SAR-L2 and X-band SARs

Generation of 10m resolution PALSAR and JERS-SAR mosaic and forest/non-forest maps for forest carbon tracking