int. j. remote sensing, 2000, vol. 21, no. 6 & 7, 1375–1387

The Global Rain Forest Mapping project—a review
Ã . ROSENQVIST†, M. SHIMADA‡, B. CHAPMAN§,A
A. FREEMAN§, G. DE GRANDI†, S. SAATCHI§ and Y. RAUSTE††Joint Research Centre of the European Commission, Space Applications
Institute, Global Vegetation Monitoring Unit, 21020 Ispra ( VA), Italy‡National Space Development Agency of Japan, Earth Observation ResearchCenter, Roppongi 1-9-9, Minato-ku, Tokyo 106, Japan§ Jet Propulsion Laboratory, California Institute of Technology, Radar Scienceand Engineering Group, 4800 Oak Grove Drive, Pasadena, CA 91109, USA
Abstract. The Global Rain Forest Mapping (GRFM) project is an international
endeavour led by the National Space Development Agency of Japan (NASDA),
with the aim of producing spatially and temporally contiguous Synthetic Aperture
Radar (SAR) data sets over the tropical belt on the Earth by use of the JERS-1
L-band SAR, through the generation of semi-continental, 100 m resolution, image
mosaics. The GRFM project relies on extensive collaboration with the National
Aeronautics and Space Administration (NASA), the Joint Research Centre of theEuropean Commission (JRC) and the Japanese Ministry of International Tradeand Industry (MITI) for data acquisition, processing, validation and productgeneration. A science programme is underway in parallel with product generation.
This involves the agencies mentioned above, as well as a large number of international organizations, universities and individuals to perform  eld activities
and data analysis at di erent levels.
The GRFM project was initiated in 1995 and, through a dedicated dataacquisition policy by NASDA, data acquisitions could be completed within a
1.5-year period, resulting in a spatially and temporally homogeneous coverage toencompass the entire Amazon Basin from the Atlantic to the Paci c; Central
America up to the Yucatan Peninsular in Mexico; equatorial Africa from
Madagascar and Kenya in the east to Sierra Leone in the west; and south-east
Asia, including Papua New Guinea and northern Australia. Over the Amazon
and Congo river basins, the project aimed to provide complete cover at twodi erent seasons, featuring the basins at high and low water. In total, the GRFM
acquisitions comprise some 13 000 SAR scenes, which are currently in the courseof being processed and compiled into image mosaics.
In March 1999, SAR mosaics over the Amazon Basin (one out of two seasonal
coverages) and equatorial Africa (both seasonal coverages) were completed; thedata are available on CD-ROM and, at a coarser resolution, via the Internet.
Coverage of the second-season Amazon and Central America will be completed
during 1999, with the south-east Asian data sets following thereafter. All data arebeing provided free of charge to the international science community for researchand educational purposes.

1. Introduction
1.1. Background
It is well known that forest ecosystems exert a strong in uence on us and ourenvironment at all levels, from local to regional, continental and global. The tropicalInternational Journal of Remote Sensing
ISSN 0143-1161 print/ISSN 1366-5901 online © 2000 Taylor & Francis Ltd
http://www.tandf.co.uk/journals/tf/01431161.html

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Ã . Rosenqvist et al.
Aforests are of particular interest as they are ecosystems with extensive biodiversitythat still cover substantial areas of the Earth. Although it is well known that global
forests in certain areas are cleared rapidly, it is di cult to assess the exact extent
and impact of such activities for several reasons. For environmental conservation,
global change modelling, etc., we need to be able to assess the current status of theforests accurately, but as changes occur very quickly, the need for up-to-date information is often di cult to satisfy, in particular on a regional or global scale. The only
viable means to accomplish this task is indeed by using space-borne remote sensing
techniques. In the tropical region Synthetic Aperture Radar (SAR) data areparticularly appropriate, as microwave signals penetrate the persistent cloud cover.
1.2. T he JERS-1 satellite
The Japanese Earth Resources Satellite 1 (JERS-1) was launched by NASDA
and MITI in February 1992; it stayed in operation for 6.5 years, until contact waslost in October 1998. The satellite operated an L-band SAR (23.5 cm/1275 MHz)
with horizontal (HH ) co-polarization, 35ß look angle and a recurrence cycle of 44days. It also carried optical sensors (which were not utilized within the GRFM
project), as well as an on-board data recorder which enabled global data coverage
and rapid access to acquired data.
Several features made JERS-1 particularly suitable for forest monitoring, mostnotably the low L-band frequency SAR, which is more sensitive to above-groundbiomass than other (C-band) SAR instruments in orbit. L-band signals are also
sensitive to standing water below the forest canopy—a unique characteristic among
all contemporary Earth observation satellites ( both optical and microwave). The
orbital con guration also made JERS-1 particularly suitable for large-area mapping,
as data were acquired with adjacent passes on consecutive days (i.e. a speci c pass
was acquired one day after the pass immediately east of it). This acquisition manner
yielded temporally homogeneous data even over large areas, albeit with a discrete
temporal gradient running in east-to-west direction.
1.3. T he Global Rain Forest Mapping project
The concept of large-area seasonal mapping by L-band SAR originated from theJet Propulsion Laboratory (JPL) which, in 1994, proposed a dual-season mapping
venture over the Amazon basin by JERS-1. This coincided with the end of the
JERS-1 System Veri cation Program at NASDA and the subsequent, very timely,
increased operational availability of the satellite that followed. The Amazon mapping
concept evolved at NASDA to cover the entire equatorial belt, and hence theestablishment of the Global Rain Forest Mapping (GRFM) project (Rosenqvist
1996). The large amounts of data generated by such a global endeavour, however,incited NASDA and JPL to extend collaboration to include the Joint ResearchCentre of the European Commission (JRC), experienced in tropical forest monitoring
through the TREES and the ERS-1 Central Africa Mosaicking Projects (e.g.
Malingreau and Duchossois 1995, Malingreau et al. 1995), and to MITI, via the
Earth Remote Sensing Data Analysis Center (ERSDAC).
The major objectives of the GRFM project were to create spatially and temporally
consistent JERS-1 L-band SAR image mosaics at 100 m resolution (derived fromfull-resolution data) covering the entire equatorial belt, and to provide these as‘ready-to-use’ data sets freely and openly to the international science communityand educational institutions as tools to help improve our understanding of theGlobal and regional land cover characterization

1377

tropical ecosystems. It was explicitly noted that the data should be used for scienti cand educational purposes only.
The GRFM project was o cially initiated by NASDA in 1995, and collaborationagreements were established with NASA and the JRC, through which the tasks inthe data  ow, from satellite acquisitions to mosaic generation and CD-ROM production, were allotted. The NASA tasks are being performed through the JPL and the
Alaska SAR Facility (ASF), while on the side of the JRC, they are performed by theSpace Applications Institute.
The work distribution is to a large extent a result of the availability of personnel,
equipment and know-how, as well as of other ongoing projects and regional interestsof the organizations involved. Although the overall project goal was to generateuniform products (i.e. mosaics) for all areas, deviations in terms of radiometry andgeometry inevitably do occur as a result of di erences in the SAR processors,
mosaicking software, etc. Since all GRFM activities have been covered by eachparticipating organization internally—no exchange of funds has been required—it
has not been possible, nor desired, to impose wide-ranging production standards.
Nevertheless, the radiometric and geometric characteristics of each mosaic are documented and provided together with the data when delivered. The contributions fromeach organization are summarized in table 1.
2. Product generation and data  ow
2.1. Down-link and raw data processing
Data acquisition scheduling was performed by NASDA and all acquired data(some 13 000 scenes) were recorded onto the satellite Mission Data Recorder andsubsequently down-linked either at the NASDA Earth Observation Center (EOC)in Hatoyama, north of Tokyo, or at the ASF in Fairbanks, Alaska.
Raw data processing is performed at NASDA and at the ASF for each of theirrespective areas (see table 1). All data are processed to full resolution (18 m ground
resolution at three looks) ground range amplitude products, corresponding to the
16-bit ‘Level 2.1’ product from NASDA (Shimada 1996) and the 8-bit ASF highresolution standard product from the ASF (Bicknell 1992). The choice to perform
Table 1. GRFM project work distribution. AM—Amazon and Central America; AFR—
equatorial Africa; SEA—South-East Asia and north Australia; NG—New Guinea island.
NASDA
Projectmanagement
Data down-link
Raw data
processing
Validation andpost-calibration
100 m productgeneration
Mosaic generation
CD-ROM
production

ERSDAC

ASF

JPL

JRC

AM, AFR, SEA
and NGAM, AFR, SEA
and NG
AFR, SEA
and NG
SEA

NG

AM

AFR

SEA

NG

AM

AFR

AM (one season)and SEA
AM, AFR, SEA
and NGNG

AM, AFR, SEA
and NGAM

AM
AFR( both seasons)AM, AFR, SEA
and NG

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Ã . Rosenqvist et al.
A

full-resolution processing (and subsequent  ltering to lower resolution), rather thansigni cantly faster low-resolution quick-look processing, was motivated by the scienti c need for the highest achievable radiometric quality of the  nal mosaics.
This goal, however, has its cost and the raw data processing step has consequently
proven to be the most time consuming part of the GRFM project. As of March
1999, ASF has all but  nalized the processing of their share, where some 10% of thesecond Amazon coverage remains. NASDA EOC, in turn, who commenced processing in November 1996, following an up-grade of their processor, have  nalized
the processing of Africa, New Guinea and north Australia, while the major parts ofSouth-East Asia still remain in the pipeline. Limited processor throughput at NASDA
EOC, where on average some 75 scenes per week are processed, has however
prompted NASDA to develop a new SAR processor dedicated to the JERS-1 science
activities at NASDA Earth Observation Research Center (EORC). The new EORC
processor was put into operation in early 1999, signi cantly speeding up the processing of the remaining data. In order to assure regional homogeneity for all thesouth-east Asian mosaics, NASDA also plans to re-process New Guinea island andnorthern Australia with the new processor.
2.2. Generation of low-resolution data and calibration/validation
The next step in the GRFM processing chain entails downsampling of the fullresolution scenes from 12.5 m pixel spacing to low-resolution framelets of 100 m pixel
size. In order to maintain highest possible radiometric resolution, downsampling is
performed by either wavelet decomposition (Africa) or by block averaging in power
domains within an 8 pixel Ö 8 pixel window. The radar texture, calculated as thecoe cient of variation within the same window, is computed in the same step. This
results in one amplitude image and one texture image, both co-registered and witha geometry corresponding to the original full-resolution scenes.
Validation of the image radiometry (and geometry) and additional calibration
are performed on the 100 m resolution framelets. Although the data processed by
the ASF have proven to have comparably stable radiometry, a standardized antenna
patterns correction, derived from analysis of a large number of scenes over uniform
rain forest regions, is employed by JPL. Additional calibration of deviating framelets
is only occasionally required. The data processed by NASDA EOC on the other
hand, display signi cant antenna pattern variations and random gain deviations
that, for the African data, encouraged the JRC to implement a supervised calibration
procedure where corrections are applied to all scenes (Rauste et al. 1999a). The
radiometric quality of the new NASDA EORC processor, which will be used for all
South-East Asian data, remains to be veri ed.
2.3. Generation of 100 m regional mosaics
The image mosaicking procedures developed and utilized at NASDA, JPL and
the JRC vary on several points, but the basic concepts can be illustrated by the JRC
procedure (Rauste 1999, Rauste et al. 1999b) now described.
Using the 100 m framelets together with their orbital header information as input,
image mosaicking is performed by means of block adjustment. Relative scene displacements, calculated by image correlation in the overlapping areas between scenes( both in azimuth and range directions), are used as observations in the adjustment
procedure. Ground control points for absolute geolocation, derived from e.g. existing
maps (with varying quality) and the World Vector Shoreline data set, are added as

Global and regional land cover characterization

1379

additional observations with higher weight. As a  rst step, only the transformation
parameters are calculated, and the result is scanned for gross errors or other outliers
which need to be corrected before the actual mosaic is assembled. The steps ofparameter calculation and geometric veri cation are repeated until acceptable geometric accuracy has been achieved. In order to assure relative co-registration between
mosaics acquired at di erent seasons ( both the Amazon basin and the Congo basin
were acquired at two seasons), block adjustment is performed for all scenes covering
the region simultaneously. For the case of Africa (excluding Madagascar which istreated separately), this involves some 3600 scenes, resulting in a normal equation
matrix larger than 10 000 lines by 10 000 columns. Still, the calculation can be
performed within a few hours. Once the transformation parameters have been calculated, the geometry is  xed and the actual mosaic generation can either be completed
in one single step, or it can be performed in sub-regions and assembled at a laterstage. From a computational point of view the latter is more feasible, as simultaneous
mosaicking of 3600 scenes currently requires some 20 hours of computation time.
The characteristics of the JRC output are 100 m nominal ground resolution, amplitude and texture mosaics in Mercator projection with 240 m root mean square error(RMSE) absolute geolocation accuracy and 56 m (RMSE) relative internal accuracy.
The procedure employed at JPL for the Amazon and Central America corresponds largely to the JRC  ow described above. The major di erence is that leastsquares block adjustment is applied to data from one season only and the second
coverage is recti ed scene-by-scene to the  rst ‘master’ mosaic. The characteristicsof the JPL output are 100 m nominal ground resolution, amplitude and texture
mosaics on a latitude/longitude grid. The  nal versions of the South American
mosaics have not yet been generated and appraisal of the geometric accuracy
hence remains.
The mosaicking algorithm currently applied by NASDA di ers from the JRC
and JPL procedures in that orbital information is used to compute the approximate
position for the scene in the mosaic, followed by image correlation in the overlapping
areas of neighbouring scenes for  ne adjustment. An improved version of the algorithm is foreseen for South-East Asian mosaic generation.
2.4. CD-ROM generation
All mosaics generated within the GRFM project will be featured on CD-ROM
at 100 m and 500 m ground resolution (Chapman et al. 1998). Due to the large sizesof the 100 m data  les (typically 400–600 Mbytes), it was considered necessary to
divide the 100 m canvases into smaller regional mosaics, or tiles, (typically corresponding to 5ß Ö 5ß , 30–40 Mbytes or 80–100 scenes) in order to ensure that users
with relatively limited computer capacity can display and work with the data.
Adjacent tiles can be re-assembled to form larger units if so desired. An educational
CD-ROM aimed at high schools and universities with restricted computer resources
and limited knowledge of SAR, is also foreseen, featuring educational documentationand selected mosaics at 100 and 500 m resolution. As of early 1999, two CD-ROM
sets have been released.
2.5. Internet accessAll 500 m resolution mosaics are subsequently being made available on theInternet for on-line browsing and, for non-commercial purposes, for downloading.

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Ã . Rosenqvist et al.
A

CD-ROM sets containing 100 m resolution data are available on request. The
following websites are currently available:
E
E
E
E

NASDA/Japan (http://www.eorc.nasda.go.jp/Sciences/Forest/);
JPL/USA (http://southport.jpl.nasa.gov/GRFM/);
JRC/EC (http://www.gvm.sai.jrc.it/);Satellus/Sweden ( http://www.satellus.se/projects/GRFM).

3. Coverages and acquisition schedules
3.1. Data acquisition scheduling
The data acquisitions were scheduled with the particular intention of obtaining,as far as possible, temporally homogeneous data coverages over extensive areas.
Radiometric di erences between adjacent swaths could be minimized by taking
advantage of the fact that two adjacent JERS-1 swaths were acquired with only
1-day time di erence, and special attention was thus paid to avoid temporal gaps in
the acquisitions. Inevitably, gaps nevertheless did occasionally occur due to satellite
manoeuvres, acquisition con icts, etc., and missing passes were in such cases either
re-scheduled or replaced by scenes from the existing archive, as far as possible taking
the seasonality of the missing pass into consideration. A side e ect of the sequential
acquisition scheme, which should be borne in mind when analysing data overextensive areas, is a distinct temporal gradient (1 day/60 km) which runs in an
east-to-west direction.
3.2. South and Central America
The GRFM coverage over South and Central America ( gure 1(a)) extends over
the area latitude 14ß S to 12ß N and longitude 50ß W to 80ß W. The  rst coverage,
extending over the whole Amazon river basin ( gure 2), was acquired over a 62-day
period in 1995, starting in Belém in September and ending in Equador in November( hence the temporal gradient). The acquisitions coincide with the annual low-watermark of the Amazon river, as measured in Manaus. A second acquisition, featuring
the corresponding high-water peak, was performed during the period May to August
1996. This second coverage also includes the Pantanal wetlands, the north-westernpart of the South American continent and Central America ( gure 1(a)). The twocoverages together amount to some 5000 scenes.
Figures 2 and 3 illustrate the multi-scale characteristics of the GRFM mosaics.
The former  gure portrays the Amazon river basin at a low resolution, showing
semi-continental scale features such as drainage patterns and geomorphologic features. Regional di erences within the mosaic are also apparent at this scale: while
low water prevails in the central and eastern part of the basin,  ooded forest areas(appearing bright in L-band SAR imagery) can be seen in Peru, in the westernmost
part of the basin. Figure 3 is an extract from the same mosaic, but displayed with
100 m pixel spacing, exhibiting local-scale features such as shifting cultivation anddeforestation patterns (Rondônia).
3.3. Equatorial Africa
The African GRFM acquisitions ( gure 1(b)), comprising some 3950 scenes,
feature east, central and west Africa (9.5ß S–9.5ß N/40ß E–14ß W), which were acquired
in one sweep in early 1996. Acquisitions commenced in Kenya in January and ended
by the Atlantic coast two months later, in March 1996. Central Africa was re-visited
in October–November the same year, in order to—in analogy with the Amazon

Global and regional land cover characterization

1381

(a)

(b)

(c)

Figure 1. GRFM coverage over (a) South and Central America, (b) equatorial Africa and(c) South-East Asia and northern Australia.

1382

Ã . Rosenqvist et al.
A

Figure 2. JERS-1 SAR mosaic covering the Amazon Basin at low water (October–December
1995). Original mosaic pixel size 100 m. JERS-1 GRFM © NASDA/MITI/JPL/JRC.

Figure 3. Rondônia, Brazil. Full-resolution extract from the GRFM Amazon mosaic( gure 2). Shifting cultivation can be seen on the left-hand side of the image and cattle
ranges on the right. JERS-1 GRFM © NASDA/MITI/JPL/JRC.

Global and regional land cover characterization

1383

acquisitions —feature seasonal variations in the Congo river basin ( gure 4).
Madagascar was covered in February 1997.
An extract from a temporal composite mosaic, using data acquired in February(red) and November (green) 1996, together with a radar texture mosaic image (blue)is shown in  gure 5. The area featured is the con uence of the Congo and Ubangi
rivers. Forest areas which were inundated during both acquisitions appear brightwhite in the image, while areas that were inundated at only one occasion appear

Figure 4. GRFM mosaics over equatorial Africa (west Africa and Madagascar not shown).
The colour composite area shows the extent of the dual-seasonal coverage. (R—radar
amplitude February 1996; G—radar amplitude November 1996; B—aradar texture
February 1996). JERS-1 GRFM © NASDA/MITI/JRC/JPL.

Figure 5. Con uence of the Congo and Ubangi rivers in Central Africa. Dual-season composite GRFM mosaic. (R—radar amplitude February 1996; G—radar amplitude
November 1996; B—radar texture February 1996). JERS-1 GRFM © NASDA/MITI/
JRC/JPL.

1384

Ã . Rosenqvist et al.
Abright yellow or orange. Rough surfaces, due to the higher texture, appear with ablueish tone. The  oodplain forest, with its homogeneous structure, lacks the blue
tone and is easily distinguishable from the more textured dryland forest, as can beseen along the tributary (Kwa river) which stretches eastwards from the centre
right-hand part of the image.
3.4. South-East Asia (including Papua New Guinea) and north Australia
Acquisition planning over South-East Asia was complicated by several factors,
primarily by the fact that the region consists of a large number of islands distributed
over extensive sea areas. The uniform blanket acquisition approach, as was practised
for the other two continents, was consequently not considered feasible. The region
was therefore instead divided into a number of sub-areas ( basically represented by
the main islands ( gure 1(c))) over which data were acquired over a larger time span.
Temporal uniformity was nevertheless maintained within each sub-region. The
acquisitions, which were limited to one single coverage per sub-region, resulted insome 4300 scenes and were performed according to the following schedule.
E
E
E
E
E
E

Papua New Guinea/Irian Jaya: March–April 1996 ( gure 6).
Malay Peninsular and Sumatra: August–September1996.
Borneo/Kalimantan, Java and Sulawesi: September–October 1996.
N. Australia (above S20ß ): October–November 1996.
The Philippines: December1996.
Burma, Thailand, Cambodia, Laos and Vietnam: January–February 1997.

4.

GRFM science projects
A scienti c programme is underway within the context of the GRFM projectwith the aim of exploiting the use of JERS-1 SAR data and the GRFM products inthe tropical region. These so-called GRFM Science Projects are independently managed by researchers and scientists from a large number of organizations and universities worldwide. The activities include mapping of the spatial and temporal distributionof annual  ooding in the Amazon and Congo river basins (Freeman et al. 1996,
Costa et al. 1997, Miranda et al. 1997, Rosenqvist and Birkett 1999), studies ofsecondary growth and deforestation patterns (Hashimoto and Tsuchiya 1995),
investigations of microphyte vegetation in water reservoirs, geomorphologic studies

Figure 6. Papua New Guinea/Irian Jaya. GRFM mosaic (March–April 1996). JERS-1
GRFM © NASDA/MITI/ERSDAC.

Global and regional land cover characterization

1385(Forsberg et al. 1998), estimations of regional emissions of trace gases from the oodplain environments (Rosenqvist et al. 1998), forest classi cations in the Amazon
and Central Africa (Siqueira et al. 1997, De Grandi et al. 1998), regional-scale
vegetation studies (Hess et al. 1998, Leysen et al. 1998), and others. Figure 7 showsa land cover classi cation over the Gamba Complex in Gabon, derived from thedual-season Africa GRFM mosaic.
In collaboration with, among others, the Brazilian National Institute for Space
Research (INPE), the Brazilian National Institute for Amazonian Research (INPA)
and the University of California Santa Barbara (UCSB),  eld measurements were
performed simultaneously with the GRFM acquisitions in several parts of the
Amazon during both satellite overpasses. The activities included both videography
and photography from a small aeroplane along a number of pre-determined  ightlines as well as ground-based measurements in areas or transects of speci c interest.
Field measurements were also performed in connection with the GRFM acquisitions
over northern Australia, which coincided with an airborne SAR campaign (AIRSAR
Paci c Rim deployment ). The AIRSAR campaign included  ights over severaltransects and subsequent ground measurements.
5.

Future perspectives
With all the GRFM acquisitions completed and the JERS-1 satellite still functional, in 1996 NASDA decided to proceed with a new global forest mapping venturewith a focus on the boreal forest belt in Siberia, Canada, Alaska and northern
Europe, thus establishing the Global Boreal Forest Mapping (GBFM) project.
The objectives of the GBFM project are similar to those of the GRFM, i.e.

Figure 7.

Land cover classi cation of the Gamba Complex, Gabon (Saatchi et al. 1998).

1386

Ã . Rosenqvist et al.
Acontinental-scale mosaic generation and an active science programme. In addition
to the collaboration partners involved in the GRFM, the National Swedish Space
Board, via the Swedish Space Corporation Subsidiary Satellus, is also involved as a
Science Node for research activities in the northern European boreal zone. Contacts
were also established with the German Aerospace Research Establishment (DLR)
and the European Space Agency (ESA), for coordination of data acquisitions andscienti c activities in the Siberian region.
Boreal data acquisitions started in late 1996 and the major parts of the targetedareas were completed successfully before the on-board data recorder was taken outof operation in August 1997. Through direct down-links by ASF, the Tromsø Satellite
Station in Norway and the mobile DLR ground station located in Ulaanbaatar in
Mongolia, data acquisitions continued over certain areas until contact with the
JERS-1 was  nally lost in October 1998. Through the collaboration with DLR
and the SIBERIA project (Schmullius et al. 1999), simultaneous JERS-1 andERS-1/ERS-2 acquisitions were performed over central Siberia in 1996 and 1997.
It is anticipated that both GRFM and GBFM acquisitions will be repeated in a
10-year time frame within the framework of the NASDA Global Forest Mapping
Program, by use of the polarimetric L-band SAR instrument on-board the Advanced
Land Observation Satellite (Wakabayashi et al. 1998), scheduled for launch by
NASDA in 2002.
References
Bicknell, T., 1992, Alaska SAR Facility SAR Processor System User’s Guide to Products.
Report JPL D-9362, NASA JPL, Pasadena, CA, USA.
Ã ., 1998, Rain Forest Mapping Project toChapman, B., Taylor, V. B., and Rosenqvist, A
Release CD-ROMs. Eos T ransactions of the American Geophysical Union, 79, 417–418.
Costa, M. P. F., Novo, E. M. L. M., Mitsuo II, F., Mantovani, J. E., Ballester, M. V., andAhern, F. J., 1997, Classi cation of  oodplain habitats (Lago Grande, Brazilian
Amazon) with RADARSAT and JERS-1 data. In RADARSAT for Amazonia: Resultsof ProRADAR Investigations (Ottawa: Canada Centre for Remote Sensing, Natural
Resources Canada), pp. 149–161.
Ã ., Rauste, Y., Mayaux, P., Simmard, S., and Saatchi, S.,
De Grandi, G. F., Rosenqvist, A
1998, Flooded Forest Mapping at Regional Scale in the Central Africa Congo River
Basin. Retrieval of Bio-physical Parameters from SAR Data for Land Applications.
ESA Ref. SP-441 (Noordwijk, The Netherlands: ESA ESTEC), pp. 253–260.
Ã ., and Miranda, F. P., 1998, Tectonic fault
Forsberg, B. R., Hashimoto, Y., Rosenqvist, A
control of wetland distributions in the Central Amazon revealed by JERS-1 radar
imagery. T he Quaternary International, in press.
Freeman, A., Chapman, B., and Alves, M., 1996, The JERS-1 Amazon Multi-seasonal
Mapping Study (JAMMS). Proceedings International Geoscience and Remote Sensing
Symposium (IGARSS’96), L incoln, USA, 1996, 27–31 May 1996 (IEEE Publications),
pp. 830–833.
Hashimoto, Y., and Tsuchiya, K., 1995, Investigation of tropical rain forest in Central
Amazonia, Brazil, based on JERS-1 SAR images. Journal of Geography, 104, 827–842(in Japanese).
Hess, L. L., Novo, E. M. L. M., Dalton, M. V., Holt, J. W., and Melack, J. M., 1998,
Large-scale vegetation features of the Amazon Basin visible on the JERS-1 low-water
Amazon mosaic. Proceedings of the International Geoscience and Remote Sensing
Symposium (IGARSS’98). Seattle, USA, 1998, vol. II (Piscataway, NJ: IEEE), IEEE
Catalog No. 98CH36174, pp. 843–846.
Leysen, M., De Grandi, G. F., and Rauste, Y., 1998, Tropical Forest Mapping by Radar
Remote Sensing: Operational Applications at Global Scale. Retrieval of Bio-physicalParameters from SAR Data for Land Applications. ESA Ref. SP-441 (Noordwijk, The
Netherlands: ESA ESTEC), pp. 261–267.

Global and regional land cover characterization

1387

Malingreau, J. P., Achard, F., D’souza, G., Stibig, H. J., D’souza, J., Estreguil, C., andEva, H., 1995, AVHRR for Global Tropical Forest Monitoring : the Lessons of the
TREES project. Remote Sensing Reviews, 12, 29–40.
Malingreau, J. P., and Duchossois, G., 1995, The TREES/ERS-1 SAR’94 Project. ESA EOQBulletin, 48, 1–5.
Ã ., andMiranda, F. P., Fonseca, L. E. N., Beisl, C. H., Rosenqvist, A
Figueiredo, M. D. M. A. M., 1997, Seasonal Mapping of  ooding extent in the vicinityof the Balbina Dam (Central Amazonia) using RADARSAT and JERS-1 data. In
RADARSAT for Amazonia: Results of ProRADAR Investigations (Ottawa: Canada
Centre for Remote Sensing, Natural Resources Canada), pp. 187–191.
Rauste, Y., 1999, Compilation of Bi-temporal JERS-1 SAR Mosaics over the African Rain
Forest Belt in the GRFM Project. Presented at the International Geoscience and Remote
Sensing Symposium (IGARSS’99), Hamburg, Germany, 1999, 28 June–2 July 1999
(IEEE Publications), 2, 750–752.
Ã ., Perna, G., andRauste, Y., De Grandi, G. F., Pasquali, P., Holecz, F., Rosenqvist, A
Franchino, E., 1999a, Radiometric calibration of JERS-1 SAR data in connection
with the GRFM Africa mosaic compilation. JERS-1 Science Program ’99, PI Reports
pp. 92–98 (Japan: National Space Development Agency of Japan, Earth Observation
Research Centre).
Rauste, Y., Richards, T., De Grandi, G. F., Perna, G., Franchino, E., and Rosenqvist,
Ã ., 1999b, Compilation of the GRFM Africa (JERS-1 SAR) mosaics using multiA
temporal block adjustment. JERS-1 Science Program ’99, PI Reports pp. 99–108(Japan: National Space Development Agency of Japan, Earth Observation ResearchCentre).
Ã ., 1996, The Global Rain Forest Mapping Project by JERS-1 SAR. International
Rosenqvist, A
Archives of Photogrammetry and Remote Sensing, 31, (B7 ), 594–598.
Ã ., and Birkett, C., 1999, Analysis of forest inundation dynamics in the Congo
Rosenqvist, A
River Basin by use of JERS-1 SAR mosaics and TOPEX/POSEIDON Radar Altimeter
Data. Presented at the International Geoscience and Remote Sensing Symposium(IGARSS’99), Hamburg, Germany, 1999. 28 June–2 July 1999, IEEE Publications, 5,2754–2758 (catalogue number 99CH36293).
Ã ., Forsberg, B. R., Pimentel, T., and Richey, J. E., 1998, Using JERS-1 L-band
Rosenqvist, A
SAR to Estimate Methane Emissions from the Jaú River  oodplain (Amazon/Brazil).
Proceedings of the International Geoscience and Remote Sensing Symposium(IGARSS’98), Seattle, USA, 1998, 6–10 July 1998, vol. III (Piscataway, NJ: IEEE),IEEE Catalog No. 98CH36174, pp. 1623–1625.
Schmullius, C., Holz, A., and Vietmeier, J., 1999, SIBERIA—Results from the IGBP Boreal
Forest Transect. Proceedings of the International Geoscience and Remote Sensing
Symposium (IGARSS ’99), Hamburg, Germany, 28 June–2 July 1999, vol. IV(Piscataway, NJ: IEEE), IEEE Catalog No. 99CH36293, pp. 2118–2120.
Shimada, M., 1996, Radiometric and geometric calibration of JERS-1 SAR. Advances in Space
Research, 17, 79–88.
Siqueira, P., Chapman, B., Saatchi, S., and Freeman, A., 1997, Amazon rainforest
visualization/ classi cation enabled by supercomputers (ARVORES). Proceedings ofthe International Geoscience and Remote Sensing Symposium (IGARSS’97), Singapore,
3–8 August 1997, vol. I (Piscataway, NJ: IEEE), IEEE Catalog No. 97CH36042,
pp. 104–106.
Wakabayashi, H., Ito, N., and Hamazaki, H., 1998, PALSAR system on the ALOS.
Proceedings of SPIE EurOPT O series, Sensors, Systems, and Next-Generation Satellites
II, Barcelona, Spain, 21–25 Sept. 1998 (International Society of Optical Engineering),
pp. 181–189.