Every scientific experiment starts with the data, which needs to be fine-tuned for the specific use-case. We call this "analysis ready data (ARD)". In some cases, for the sake of reusability and comparability, the specifications on how ARD should be prepared, are well defined - CEOS is working hard in this direction. In many other cases, however, the procedures are not yet mature enough to support standardisation. In Earth Observation (EO) field this is especially true, as the whole community is moving from (semi) manually analysing individual scenes, from the time there were any data barely available, to processing of time-series, now that Landsat and Sentinel made this possible. We are now even facing a problem where there is simply too much of data, with PBs of open and commercial imagery being readily available. Machine learning (ML) approach can address the challenge of shifting through data, but ML as well requires data to be pre-processed for purpose. Therefore, it is essential to have facility, which can generate ARD data customised for the specific analysis' requirements. Sentinel Hub is one of such tools.

Forest monitoring is a prime objective for orbital synthetic aperture radar (SAR) missions. Especially in tropical regions where persistent cloud coverage incapacitates optical satellite observations for large parts of the year, radar remote sensing provides a unique tool for consistent all-year round data acquisition. In contrast to high-frequencies SARs at C- and X-band, L-band radar constitutes a powerful tool to obtain direct information from the full forest strata ranging from the top canopy all the way down to the forest ground. However, despite important advantages, SAR faces various challenges when it comes to potential error sources. As radar backscattering from distributed natural forest targets is profoundly complicated in nature, ill-defined signal fluctuations often limited the reliability of models and applications. To overcome these challenges by improved understanding of the spatial-temporal fluctuations in forest backscatter, coherent, multitemporal and polarimetric observations covering all kinds of environment conditions are required. Nearing 9 years in orbit since its launch in 2014, ALOS-2 has acquired the world’s first long-term pantropical L-band SAR archive fulfilling exactly these requirements.

This paper described the ongoing effort and the scientific benefits of close coordination between more than a dozen ongoing and planned spaceborne SAR missions. Specific Illustrative examples of the scientific and applications benefits are included and described.

The Open Data Cube (ODC), created and facilitated by the Committee on Earth Observation Satellites (CEOS), is an open-source software architecture that continues to grow in popularity around the world. In late 2021, CEOS released a new ODC sandbox tool that provides global users with a free and open programming interface connected to Google Earth Engine datasets. The open-source toolset allows users to run application algorithms using a Google Colaboratory (“Colab”) Python notebook environment [1]. This tool demonstrates rapid creation of science products anywhere in the world without the need to download and process the satellite data. One example application has been developed and demonstrated to support flooding disasters and recovery using Sentinel-1 radar data. This application can be easily used to monitor peak flooding extent, flooding recovery, and the time series flood history of a region.

This paper outlines a comparative study where Sentinel-1 Interferometric Wide Swath (IWS) data obtained from two different sources - the Google Earth Engine and the Sentinel Hub by Sinergise - have been compared with respect to their geometric and radiometric characteristics. Assessed over five study sites with different land cover and topographic features - in Australia, Brazil, Ethiopia, Indonesia and the USA - the results indicate comparable absolute geolocation accuracy between the two sets of data. Radiometric performance was also similar within the main (0 - -30 dB) dynamic range of the data.

In this paper we provide a brief review of the Earth observation requirements for a number key science applications for which spaceborne Synthetic Aperture Radar sensors can contribute with critical measurements. We outline the current state of the science and identify information gaps associated with each application, and subsequently, provide recommendations on how these gaps can be mitigated in the 2020's time-frame by coordination of current and already planned missions, and for the next decade, with a vision for a comprehensive constellation system that would address the outstanding scientific requirements.

Launched in September 2018, NovaSAR-1 is a novel Earth Observation (EO) satellite hosting the only operational spaceborne S-band Synthetic Aperture Radar (SAR), plus an Automatic Identification System receiver for use in ship tracking. Australia's 10% capacity share in this new satellite mission provides the nation with a first-ever sovereign civilian EO satellite capability. The Commonwealth Scientific and Industrial Research Organisation (CSIRO) operates this service as a National Facility for research, supporting science projects that are scoping the application of S-band SAR to an array of terrestrial and marine environments, and implementing background mapping of the continent, which will be key to supporting a wide range of existing research. Utilising a suite of newly designed and implemented acquisition modes, CSIRO have (since October 2019) captured NovaSAR-1 imagery in all Australian states and territories and throughout parts of the neighbouring Pacific region. For Australia, this mission provides significant opportunities to gain experience in satellite operations and creates new opportunities in the field of remote sensing, advancing Australia's imaging radar capability and further developing national EO data analytics expertise.

The amounts of satellite data available to the public have increased dramatically the last few years, in particular thanks to the public open release of certain key Earth observation missions, stimulating the development of new applications that use large volumes of data. With an armada of new high-volume satellite missions around the corner - both public and commercial - data producers and data users alike now risk becoming overwhelmed by the sheer amounts of data to handle, and new solutions to data structures, access and processing tools are required. Analysis-Ready Data, Data Cubes and cloud-based processing solutions are responses to new situation. Some examples of the former two are outlined briefly in this paper, highlighting some specific efforts by the Committee on Earth Observation Satellites (CEOS) and the Open Data Cube (ODC) initiative to address these. Some specific efforts relating to Synthetic Aperture Radar (SAR) are outlined.

NovaSAR-1 SAR operates in S-band (3.2 GHz/9.4 cm) which is a rather uncommon frequency in microwave remote sensing. This study presents a very first assessment of S-band SAR backscatter observed over a tropical forest and wetlands region in the Amazon Basin, compared with near-simultaneous L-band SAR data from ALOS-2 PALSAR-2.Key findings: - S-band found to be sensitive to detection of below-canopy inundation in floodplain forests, with specular double-bounce scattering observed across the full (150 km) swath. - The phenomenon is only observed at HH polarisation. No canopy penetration or below canopy water detection observed in S-band VV polarisation data. - NovaSAR-1 operates with a steep incidence angle range (11°~32°) which results in strong direct backscatter from bare soil and open water surfaces.

This study presents a preliminary assessment of vegetation and inundation characteristics in the Amazon basin using ALOS-2 PALSAR-2 L-band SAR and Sentinel-1 C-band SAR backscatter combined with ICESat-2 Lidar photon height data. Key Findings: -Photon height from ICESat-2 found useful to capture seasonal water level variations along major rivers and open water areas. -Comparisons between Lidar photon height and L- and C-band backscatter along forest-river transects show good agreement for the wet and dry seasons.

Over the past several years Analysis Ready Data has been a major focus for the Committee on Earth Observation Satellites (CEOS). The CEOS Analysis Ready Data concept within the context of Land started in 2015 and has been led by the CEOS Land Surface Imaging Virtual Constellation (LSI-VC) community. LSI-VC has developed the definition that CEOS uses for ARD for Land and the overall framework [1]. The CEOS ARD definition identifies that the major benefit of ARD lies in enabling a broad community of non-remote sensing experts to better use CEOS data; and in increasing the interoperability of products through space and time as a foundation for `Big Data' analyses, future data architectures and the application of AI (artificial intelligence and machine learning) methods. LSI-VC also took the responsibility to coordinate the development of the Product Family Specifications (PFS). An important step in the CARD specification approach is that it is not prescriptive with regard to the data processing approach. This recognises that there are generally multiple approaches and that these will evolve through time. Four PFS have been endorsed by the CEOS LSI-VC community during 2019/2020. These endorsements represent the conclusion of over two years of work since the agreement of the CEOS ARD definition & framework at CEOS Plenary in 2016. The endorsed specifications contain inputs from experts around the world and it demonstrates the resolution of various points of view. It also shows the emerging acceptance of the concept of Analysis Ready Data and the value proposition of the CEOS ARD. As the increase of available EO data and processing platforms offer an unprecedented choice for the users, the need for harmonized data is growing [2]. Thus, over the past few years, there has been an increased interest from the private sector in the CEOS ARD initiative as well, and the expectation is that the availability of CEOS ARD datasets from both institutional and private data providers will increase in the coming years. To address the CEOS ARD long-term view and to ensure a consensus between players is achieved, the CEOS ARD strategy was developed in 2019. The strategy recognises that the private industry has different roles to play within the CEOS ARD initiative such as data users, data providers, data hosts or as providers of processing chains to produce data that meet CEOS ARD specifications. The strategy is also focused on the need, prioritization and continuity of CEOS ARD PFS development including the development of ARD specifications for other thematic areas such as ocean and atmosphere. This paper intends to give an update on the current CEOS ARD for Land accomplishments, and what activities are envisaged for the near future.

NovaSAR-1 is a low-cost spaceborne Synthetic Aperture Radar (SAR) technology demonstrator developed by Surrey Satellite Technology Ltd, UK (SSTL), and Airbus Defence and Space Ltd, with funds of the UK Government [1]. After the successful launch of NovaSAR-1 satellite in September 2018 and completion of the commission phase in August 2019, the Commonwealth Scientific and Industrial Research Organisation (CSIRO) are able to task, capture and access the unique S-band NovaSAR-1 imagery under the partnership of Australia's 10% capacity share in this new satellite mission [2], [3]. In the paper, we introduce the NovaSAR-1 data processing, and present initial results of NovaSAR-1 data performance evaluation and the recent emergency observations of extensive Australian bushfires.

NovaSAR-1 is a technology demonstrator by Surrey Satellite Technology Ltd, UK (SSTL), and Airbus Defence and Space Ltd, funded by the UK Government via the UK Space Agency (UKSA). The NovaSAR-1 satellite utilises S-band Synthetic Aperture Radar (SAR) providing medium and high resolution images of Earth from space. In September 2017, Australia's Commonwealth Scientific and Industrial Research Organisation (CSIRO) became a partner with the UK and India in the NovaSAR-1 mission through a 10 percent time-share [1]. The agreement allows CSIRO to direct the NovaSAR-1 satellite to collect data imagery on a world-wide basis through a range of observation modes with priority over the Australian region for the duration of the 7 year mission. CSIRO has designed a detailed background-, and foreground acquisition strategy for our share of the NovaSAR-1 satellite. This will provide at least two annual wall-to-wall coverages of Australia's landmass as well as supporting a wide range of existing research and basic satellite data acquisition training, to further develop Australia's Earth observation data analytics expertise, and create new opportunities in the field of remote sensing.

In Earth Observation, Analysis Ready Data (ARD) are commonly referred to as satellite data that have been processed to a minimum set of requirements and organised into a form that allows immediate analysis with a minimum of additional user effort and that facilitates interoperability through both time and space with other datasets. The Committee on Earth Observation Satellites (CEOS) is currently developing a set of ARD specifications for both optical and Synthetic Aperture Radar (SAR) satellite data under the so called CARD4L (CEOS Analysis Ready Data for Land) framework [1], [2].The Japan Aerospace Exploration Agency (JAXA) generates global SAR mosaic on an annual basis from data acquired by the JERS-1 SAR, ALOS PALSAR and ALOS-2 PALSAR-2 missions. The mosaic products have been subject to full geometric and radiometric corrections and organised into a format that can be considered ARD. In order for the mosaic products to obtain CARD4L certification, JAXA has undertaken a product alignment assessment of what additional processing steps or ancillary information that would be required for the mosaic products also to be compliant with the CARD4L specifications for Normalised Radar Backscatter. The data products, alignment process and outcome of the assessment are described below.

Analysis Ready Data (ARD) products are enabling users to get first hand satellite data that are `ready to use' for a wide range of applications, including time-series analysis and the way forward to multi-sensor interoperability. The Committee on Earth Observation Satellites (CEOS) is leading the CEOS Analysis Ready Data for Land (CARD4L) initiative. The rationale behind this initiative is to enable users to access products that have been already processed to a certain level. This will allow users to carry out immediate analysis on the data and to address a variety of applications without the extra time and cost that is associated with the data pre-processing steps. The aim of the proposed paper is to give an overview on the work already carried out by the CEOS community on the CARD4L framework, to introduce the processes and steps that Earth Observation (EO) data providers should undertake to have a CARD4L level product as well as the planned steps that CEOS LSIVC will be undertaking to accomplish the CARD4L initiative.

For many land monitoring applications using remote sensing, lack of data is no longer an issue, as it may have been in the past. Programs, such as Copernicus by the European Commission and the Landsat Missions by the United States Geological Survey, have adopted systematic acquisition strategies, and distribute vast amounts of satellite data under open licenses. In parallel, storage and computing capability have evolved to make it cost-effective and practical to process and analyze these data at various scales. Data architecture solutions, such as the Open Data Cube (ODC) and the Copernicus Data and Information Access Services (DIAS), are providing frameworks that make [scientific] analysis much simpler and straightforward. However, enabling non-expert users without the expertise and/or computation resources to pre-process and store low-level data products in order to exploit these capabilities, has proven more challenging. The Committee on Earth Observation Satellites (CEOS1) is working to address this challenge through the CEOS Analysis Ready Data for Land (CARD4L) initiative [1]. CARD4 L is foreseen to enable users to access satellite data products that are `ready to use' for a wide range of land applications. Moreover, CARD4L aims to enable non-expert users access to products that have been processed `far enough' to be suitable for immediate analysis for a range of applications, while ensuring they are not too specific to only be used for particular topics or areas. CARD4L will be an important enabler of the Open Data Cube (ODC) initiative [2]. Through CARD4L, users will be able to easily locate products that are suitable for ingestion into Data Cubes [3], and will have confidence that these different CARD4 L products will limit as far as possible barriers to interoperability.

The Japan Space Exploration Agency Kyoto and Carbon (K&C) Initiative seeks to demonstrate the potential of the Advanced Land Observing Satellite (ALOS) Phased Arrayed L-band Synthetic Aperture Radar (PALSAR) data for addressing regional applications relating to climate change, carbon cycle science, and environmental conservation. This paper outlines the generation of a regional dual-polarization (HH and HV) mosaic for the entire African continent at spatial resolution on the order of 100 m. The main computational and radar science issues undertaken to generate a seamless mosaic with good radiometric and geometric accuracy are summarized. Preliminary investigations into the thematic information provided by the K&C Africa mosaic and comparisons with the JERS-1 SAR mosaic generated as part of the Global Rain Forest Mapping Project are reported, with emphasis placed on characterizing and detecting change in forests and savannas.

The Advanced Land Observing Satellite (ALOS) was developed for detailed observation of the Earth's surface and frequent monitoring of global environmental changes, using high-resolution optical (visible and near infrared push-broom) and active microwave sensors (L-band synthetic aperture radar). ALOS has four mission objectives: cartography, regional observations, disaster observations, and resource exploration. It has been operational since its launch in January 24, 2006, and is acquiring a large amount of land-surface data supported by the Ka-band intersatellite communication system that downlinks to ground receiving stations. A global systematic acquisition strategy is implemented for all three sensors to enable consistent data collection over all land areas on a repetitive basis. Through its three sensors, acquisition strategy, and communication infrastructure, the ALOS mission is aimed to contribute to monitoring water, carbon, and global climate change. In this paper, we describe ALOS and its contribution to global environmental monitoring.

Within the framework of the ALOS Kyoto & Carbon Initiative, the European Commission Joint Research Centre (JRC) is in charge for the generation of a 50 m pixel spacing L-band SAR mosaic over the African continent. The mosaic is generated from full resolution (20 m), dual polarisation (HH+HV) ALOS PALSAR data, acquired from June through October 2007. The mosaic is scheduled for release in the autumn of 2009, and will be made available free of change to scientific users worldwide through the JRC and JAXA. This paper provides a brief overview of the K&C Initiative, and a short description of the procedures employed by the JRC for the Africa mosaic generation.

ALOS/PALSAR has been on the orbit since January 24 2006. After the initial calibration phase, the PALSAR has been being used as the calibrated instrument for the land monitoring. Using the calibration target data of the corner reflectors and the distributed target, it has been confirmed that the PALSAR is well stabilized and calibrated. One of the two major themes that the PALSAR can contribute to, the forest monitoring, is being progressed. The creation of the 50-meter orthorectified multi polarization mosaic, the major part of the providing products, is being generated at Kyoto and Carbon project. Here, the JAXA's contribution, the generation of the Asia SAR mosaic data, is in progress. This paper introduces the PALSAR CALVAL updated information and the quality of the PALSAR ortho-mosaic.

Using L-band SAR data from JERS-1 and ALOS, we produce regional mosaics of Sahara in order to map subsurface geology. A first mosaic of eastern Sahara using more than 1600 JERS-1 scenes allowed the discovery of unknown paleo-rivers, faults, and impact craters. On-going work concerns a new L- band high-quality mosaic of the entire Sahara, based on ALOS/PALSAR data.

The ALOS Kyoto & Carbon Initiative is an international collaborative project led by the JAXA Earth Observation Research Center (EORC). It forms the continuation of JAXA's on-going JERS-1 SAR Global Rain Forest and Global Boreal Forest Mapping project(GRFM/GBFM) into the era of the Advanced Land Observation Satellite (ALOS). The ALOS K & C Initiative has been set up to support the data and information needs required by international environmental Conventions; Carbon Cycle scientists and Environmental Conservation programs (referred below to as the CCCs). Led and coordinated by EORC JAXA, the Initiative is being undertaken by an international Science Team and focuses primarily on defining and optimizing the provision of data products and validated thematic information derived from in-situ and satellite sensors focusing on data acquired from the Phased Array L-band Synthetic Aperture Radar (PALSAR) on-board the Advanced Land Observing Satellite (ALOS). The objective of the ALOS K & C Initiative is to define, develop and validate thematic products derived from ALOS PALSAR data that can be used to meet specific information requirements relating to the CCCs. A key component of this work has been the development of a systematic data acquisition strategy for ALOS which comprises fixed, systematic global observation plans for PALSAR. The strategy is implemented as a top-level foreground mission and with a priority level second only to that of emergency observations. With emphasis on acquiring repetitive and consistent data over continental scales, it ensures that adequate data will be collected to allow the required thematic output products to be developed on a timely basis. The K & C Initiative is based on the three coordinated themes relating to global biomes; Forests, Wetlands, Deserts and Semi-Arid Regions, and a fourth theme dealing with the generation of regional ALOS PALSAR Mosaics. A key word for the Initiative is regional- scale applications and product development, with data requirements in the order of hundreds or thousands of PALSAR scenes for each prototype area. Each theme has identified key products that can be generated from the PALSAR data including land cover, forest change mapping and forest biomass and structure analysis; global wetland inventory compilation and landscape change determination; and freshwater resources and desertification. Each of the products developed will be generated using a combination of PALSAR imagery, in situ measurements and ancillary datasets.An international Scientific Advisory Panel has been established to maintain the scientific relevance of project design and to ensure alignment with other relevant international efforts (e.g. GOFC/GOLD, IGOL, GTOS/TCO). The panel consists of scientists active in the fields of carbon modeling and biophysical parameter retrieval; SAR and image processing, as well as and representatives from GOFC, TCO, FAO, space agencies, universities and public research institutions.

The Advanced Land Observing Satellite (ALOS) is Japan's new-generation Earth Observation satellite, launched in January 2006 by the Japan Aerospace Exploration Agency. ALOS carries two optical instruments (Panchromatic Remote-sensing Instrument for Stereo Mapping and Advanced Visible and Near-Infrared Radiometer type 2) and, to maintain Japan's commitment to spaceborne L-band Synthetic Aperture Radar (SAR), the Phased Array L-band SAR (PALSAR). The successor to the SAR onboard the Japanese Earth Resources Satellite (1992-1998), the PALSAR instrument provides enhanced sensor characteristics, including full polarimetry, variable off-nadir viewing, and ScanSAR operations, as well as significantly improved radiometric and geometric performance. As important as the technical improvements and the reason PALSAR here is referred to as a pathfinder mission for global environmental monitoring is the systematic data-acquisition strategy which has been implemented for ALOS. With a priority second only to emergency observations, the PALSAR observation strategy has been designed to provide consistent, wall-to-wall observations at fine resolution of all land areas on the Earth on a repetitive basis, in a manner which has earlier been conceived only for coarse- and medium-resolution instruments.

The purpose of this letter is to present the results on the study of searching effective parameters that describe the relation between high-resolution synthetic aperture radar (SAR) images and forest parameters. The study is based on the non-Gaussian texture analysis of the polarimetric airborne Pi-SAR data over coniferous forests in Hokkaido, Japan. The radar cross section (RCS) in terms of a forest biomass is first analyzed. It is found that the$hboxL$-band RCS increases steadily with the biomass and saturates at approximately 40 tons/ha. These results are similar to the previous studies. The probability density function of the image amplitude is then investigated, and among Rayleigh, log-normal, Weibull, and$K$-distributions, the$K$-distribution is found to fit best to the$hboxL$-band data of all polarizations, although the Weibull distribution fits equally well. Further, the correlation between the tree biomass and the order parameter of the$K$-distribution in the cross-polarization images is found to be very high, and the order parameter increases consistently with the biomass to approximately 100 tons/ha, which is well beyond the saturation limit of the$hboxL$-band RCS. Thus, the order parameter of the$K$-distribution can be a promising new parameter to estimate the forest biomass from high-resolution polarimetric SAR data in a much wider range than the conventional RCS method.

Biophysical parameters and L-band polarimetry synthetic aperture radar observation data were taken for 59 test sites in Tomakomai national forest, which is located in the northern part of Japan. Correlations between the derived sigmaHH0, sigmaHV0, and sigmaVV0and the biophysical parameters are investigated and yield the following results. 1) The above-ground biomass-sigma0curves saturate above 50 tons/ha for sigmaVV0, 100 tons/ha for sigmaHH0, and over 100 tons/ha for sigmaHV0when all forest species are included in the curves. 2) The sigmaHH0-above-ground biomass curve for one forest species indicates a higher saturation level than that for the other forest species. Dependence on the forest species was absent for VV polarization and low for HV polarization. 3) A simple three-component scattering model indicates that volume scattering accounts for 80%-90% when the above-ground biomass exceeds 50 tons/ha. The surface-scattering components are up to ~20% for young stands, and the volume-scattering components are down to 70%. The origin of the dependency among the forest species was examined for the sigmaHH0-above-ground biomass. It is concluded that a possible cause of the dependency is the different characteristics of the stands rather than forest species

This paper describes the updated status of the PALSAR CAL/VAL and scientific activity of 2005, which is being conducted as a part of the JAXA's ALOS science program. The updated information includes 1) Detailed schedule of the initial calibration phase, 2) Distribution of the calibration targets, 3) Calibration strategy (antenna pattern, polarimetric calibration, absolute calibration, image quality evaluation, noise equivalent sigma-naught), 4) PALSAR data format update, and 5) Yaw steering mode and observation scenario for polarimetry.

Japanese Earth Resources Satellite 1 (JERS-1) synthetic aperture radar (SAR) data were evaluated to map areas of deforestation in a Brazilian Amazo/spl circ/nia test-site. The results were compared with information derived from a Landsat TM multitemporal series. Unambiguous detection of deforested areas was observed only when the entire deforestation process (slash, burning, and terrain clearing) had already occurred. This result recommends further investigations on the effectiveness of horizontal polarization SAR data to map deforestation in a consistent basis. The cross-polarized (horizontal-vertical) channel designed to be in the ALOS/PALSAR system is expected to improve the distinction between forested and recently deforested areas.

In the context of the Global Boreal Forest Mapping project (GBFM), an initiative of the Japan Aerospace Exploration Agency (JAXA), a continental scale radar mosaic of the Eurasian Taiga was compiled. The mosaic is composed of some 520 strip-images (typically covering 80 km by 2500 km each) acquired in 1997-98 by the L-band SAR aboard the JERS-1 spacecraft. The mosaic was assembled in two phases. Coverage in the first stage included the area between the Ural Mountains in the west, Bering Strait in the east, Arctic Ocean in the north and the Korean Peninsula in the south. In the second phase an extended version was produced that comprises the European part of the Boreal ecosystems west of the Ural Mountain and up to the European Union region. Pixel spacing of the high resolution final products is 100 m and map projection is Albers equal-area conical. In this paper selected topics are presented related to a revision of the mosaic geometry. This step was called for to improve the internal consistency and assure proper absolute geolocation of the mosaics with respect to reference data sets. It consists of: i) a data representation (virtual frames) for handling the strip-images in smaller units that are more effective for dealing with local distortions; and ii) inclusion of control points derived from the Landsat GeoCover data sets. Results characterizing the mosaic geometric accuracy in terms of root mean square residuals are reported. Finally, we present, as a first thematic result, a vegetation map at coarse resolution (900 m) derived by a combination of the Global Land Cover 2000 map and the GBFM radar mosaic.

Boreal ecosystems play an essential role in global climate regulation. Forests constitute pools of terrestrial carbon and are generally considered as global sinks of atmospheric CO/sub 2/, contributing to attenuating the greenhouse effect. Large amounts of carbon are also stored in boreal lakes, bogs and wetlands, partially released as CH/sub 4/ and other trace gases to the atmosphere during the spring and summer months. Human activities in the forest zone are however reducing the size of the carbon pool and climate change is triggering shorter winters and earlier thaw onset, changing the natural equilibrium. Given its global importance, there is a need to map and monitor the boreal zone, and as the changes occur on all from local, regional to global scales, fine resolution information over vast areas is required. The Global Boreal Forest Mapping (GBFM) project is an international collaborative undertaking initiated by NASDA in 1996, as a follow-on to the tropical-focused Global Rain Forest Mapping (GRFM) project [A. Rosenqvist et al., (2000)]. Utilising the L-band Synthetic Aperture Radar (SAR) on the Japanese Earth Resources Satellite (JERS-1). one of the main objectives of the GBFM project is the generation of extensive, pan-boreaL SAR image mosaics, to provide snap-shots of the forest wetland and open water status in the mid-1990's. Mosaics over Canada, Alaska. Siberia and Europe have been generated, available on the Internet and on DVD free of charge for research and educational purposes. The GBFM project also entails research activities in North America, Siberia and northern Europe, aimed at advancing scientific applications of L-band SAR data in the boreal zone.

The Advanced Land Observing Satellite (ALOS) is scheduled for launch by the Japan Aerospace Exploration Agency (JAXA) in 2005, and it carries three remote sensing instruments: an L-band polarimetric Synthetic Aperture Radar (PALSAR), an along-track 2.5 metre panchromatic resolution stereo mapper (PRISM) and a 10-metre multi-spectral scanner (AVNIR-2). The successor of the JERS-1 satellite (1992-1998), ALOS not only provides enhanced sensor performance, but also feature an entirely new acquisition concept. Abandoning traditional, local-focused instrument operations, JAXA is implementing a comprehensive acquisition strategy, in which geographical region, sensor mode, acquisition timing and repetition frequency, are fixed in advance, to achieve spatially and temporally consistent, global coverage on a repetitive basis, at the same time as reducing programming and user conflicts.

This paper describes generation of the digital elevation model (DEM) using the L band repeat pass airborne polarimetric Interferometric SAR (Pi-SAR) system, which is jointly developed by Japan Aerospace Exploration Agency (JAXA) and National Institute for Communication Technology (NICT). An image pair acquired over the Tottori calibration site in 2000 had a baseline of less than hundred meters and was used for this interferometric data analysis. Although the quantitative evaluation has not been conducted, the result shows that the detailed feature of the topography in the target area was well obtained.

We examined relationship between forest parameters and /spl sigma//sup 0/ derived by airborne multi-polarization SAR (PiSAR). PiSAR observations and field measurements were simultaneously performed on November 2002 and August 2003. One data set was taken from stands with pure pine (Picea glehnii Masters) forest. More than 70% of the trees in biomass are Picea glehnii Masters in the data set with same stand age. The other data set was taken from the stands where mixture of species is proceeding in some degree. The former data set shows more tight correlations compared to the other and correlation coefficient reaches 0.98. We conclude that (1) the mixture of the species and stand age are two of the major reasons of data scattering between forest parameters and /spl sigma//sup 0/, and (2) the above ground biomass saturation level is about /spl sim/150 tons/ha for L-band /spl sigma//sub HH//sup 0/ and /spl sigma//sub HV//sup 0/ and /spl sim/70 tons/ha for /spl sigma//sub VV//sup 0/ in this akaezomatsu site, using a biomass expansion factor of 1.36 to convert from the trunk biomass to the above-ground biomass.

As the land degradation is a complex process, influenced also by climatic and human-induced factors, its understanding and mapping requires a methodology based on Earth Observation integrated with ancillary data such as socio- economic and, optionally, meteorological data. For this reason, the service, which has been defined, implemented, and validated in close cooperation with End Users, is based both on scaleable indexes - derived from Earth Observation data - and on indicators relevant to the influence of human and animal pressure on natural resources. The ultimate goal is the generation of vulnerability maps to provide to decision makers for prevention purposes.

We used multi-sensor, multi-frequency and multi-polarization SAR data for biophysical parameter retrieval in plantation forests of Northern Japan. The statistical relationships with different biophysical parameters are quite robust for certain frequencies-polarization combination. A combination of different frequencies and polarizations facilitate the retrieval of these parameters with R 2 of 0.95 and rms error of 15.19 tons ha -1 .

The Kyoto & Carbon Initiative is an international collaboration initialised by NASDA in 2000 [1], set out to support dataand information needs raised by certain multinational environmental conventions and by global carbon cycle science, through provision of data products and high level information derived from ALOS, JERS-1 and ADEOS-II data. The conventions primarily in focus are the UNFCCC Kyoto Protocol and the Ramsar Convention on Wetlands, to which fineresolution, multi-scale information about the status and changes in forests and wetlands will be derived. There is apparent synergy with terrestrial carbon cycle science information needs, where improved spatial information about carbon pools, sources and sinks at local, regional to global scales are of high priority. Support to the UN Millennium Development goal on water access, as well as to the UN Convention to Combat Desertification, are

Implementation of systematic Earth observation data acquisition plans over extensive regions, in which the spatial and temporal components of relevant ground targets are adequately taken into account, is a prerequisite for successful retrieval of bio- and geophysical parameters and imperative to accommodate extrapolation of locally developed models to regional scales as required in the context of terrestrial carbon cycle science. Straightforward in concept, but surprisingly uncommon in mission operations thus far, the key characteristics of such a systematic data acquisition strategy are outlined in this short communication.

Forest biomass is one of the key parameters that indicate temporal change of the global continental carbon volumes, and its global estimation is required as described in the Kyoto protocol. NASDA's ALOS science project strongly intends its estimation either solely by SAR or in conjunction with the other optical sensors and the ground truth data. There have been (or are being) developed SAR based methods to estimate the forest biomass, which utilize the relationship between sigma-zero and biomass quantity, those based on coherence of one day separated C band data and L band radar intensity, and those based on forest tree heights and biomass quantities, etc. For the third category, it is expected that Pol-In-SAR might relate the interferometric phase difference at different polarizations to the tree structures and heights, and two-frequency interferometry relates to the phase center difference to the tree height.

The Global Rain Forest Mapping Project (GRFM) is an international collaborative effort initiated and managed by the National Space Development Agency of Japan (NASDA). The main goal of the project is to produce a high resolution wall-to-wall map of the entire tropical rain forest domain in four continents using the L-band SAR onboard the JERS-1 spacecraft. The processing phase, which entails the generation of wide area radar mosaics from the raw SAR data, was split according to the geographic area. In this paper, the focus is on the part related to Africa. The GRFM project's goal calls for the coverage of a continental scale area of several million km/sup 2/ using a sensor with the resolution of tens of meters. In the case of the African continent, this entails the assemblage of some 3900 high resolution SAR scenes into a bitemporal mosaic at 100 m pixel spacing and with known geometric accuracy. While this fact opens up an entire new perspective for vegetation mapping in the tropics, it presents a number of technical challenge. The authors report on the solutions adopted in the GRFM Africa mosaic development and discuss some quantitative and qualitative aspects related to the characterization and validation of the GRFM products. In particular, the mosaic geolocation and its validation are discussed in detail. Indeed, the internal geometric consistency (subpixel accuracy in the coregistration of the two dates), and the absolute geolocation (residual mean squared error of 240 m with respect to ground control points) are key features of the GRFM Africa mosaic.