IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 41, NO. 7, JULY 2003

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Special Issue Communications____________________________________________
Systematic Data Acquisitions—A Prerequisite for
Meaningful Biophysical Parameter Retrieval?
Ake Rosenqvist, Anthony K. Milne, and Reiner Zimmermann
Abstract—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, isa 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 paper.
Index Terms—Biophysical parameter retrieval, data consistency, datacontinuity, earth observation strategies, image mosaics, long-term continuity, satellite acquisition planning, spatial consistency, synthetic apertureradar (SAR), temporal homogeneity.

which render them inadequate for most operational purposes. Goldnuggets may certainly be found, but for most applications relating
to phenomena of regional-scale or broader, the fragmentation of thearchives can be expected to seriously limit the usefulness of the data.
Inconsistent data archives is a problem characteristic for fine-resolution sensors that typically are not acquired homogeneously over large
areas, but instead generally collected with local focus over sites thathave been specifically requested by commercial or scientific users. This
results in some passes being acquired systematically over long periodsof time, while the data coverage over neighboring passes may be totallyneglected. Most satellite missions also entail some kind of gap-fillingbackground mission objective when operational resources permit, but
the actual usefulness of such piecemeal global archives is questionable,
as the data are generally acquired without considerations of the impactsof temporal effects. Optical satellites, notably Landsat [1], generally do
better than their microwave counterparts, but cloud cover seriously reduces the availability of useful data over regional scales.
C. Coarse-Resolution Data Archives

I. INTRODUCTION
A. Background
Retrieval of bio- and geophysical parameters from remote sensing
data is an important field of research, and the prospect of extracting
such information in an operational manner with a high degree of accuracy is a strong driver of current scientific work. Meaningful parameter retrieval, however, requires not only the availability of appropriate inversion algorithms, but also that locally developed models canbe applied in an extensive regional context. In terrestrial carbon cycle
research, with its direct impact on economic and political decisionmaking processes—notably the UNFCCC Kyoto Protocol—accurate
assessment and detection of changes in vegetation biomass and carbon
stocks over extensive areas are of paramount importance and a challenge that the implementation of the Protocol imposes on the remotesensing science community. Regional extrapolation becomes imperative if the applications are to be more than of academic interest, andspatiotemporally consistent data, and thus the implementation of systematic data acquisition plans, therefore, becomes a requirement.

The usefulness of systematic and consistent data observations canbe demonstrated by a coarse-resolution sensor such as the National
Oceanic and Atmospheric Administration (NOAA) Advanced VeryHigh Resolution Radiometer (AVHRR), which despite its 1-km
spatial resolution, is utilized extensively worldwide. Its success withrespect to broad use can probably be attributed at least as much toits tremendous data archive, as to the characteristics of the sensor
itself. The AVHRR archive features attributes that are important in thecontext of regional-scale biophysical parameter retrieval: multitemporal wall-to-wall global coverage, consistent sensor characteristics,and availability since the early 1980s. AVHRR data are furthermore
both affordable and easily accessible, which, although not directly
related to the discussion here, are two further key points for wideuse. Applying an AVHRR-type of acquisition strategy directly tofine-resolution sensors is, however, not feasible due to the significantly
higher data rates and associated operational and technical constraints
the improved spatial resolution brings about, and a fine-resolution
observation plan consequently requires a higher degree of planning if
regional fragmentation is to be avoided.

B. Inadequacy of Current Data Archives
Providing long-term systematic and repetitive observations overlarge areas is potentially one of the major strengths of remote sensing
technology, in particular for microwave sensors, which are not limited
by low sun angles or persistent cloud cover. If we limit the discussion
to sensors with a resolution better than about 100 m, however (hereafter, referred to as fine-resolution sensors), it can be argued that theactual usefulness of the satellite data collected during the past threedecades—the so-called “global archive”—may turn out to be very limited, as the data generally lack both spatial and temporal consistency,
Manuscript received April 26, 2002; revised January 8, 2003.
A. Rosenqvist is with the Earth Observation Research Center, National
Space Development Agency of Japan, Tokyo 104-6023, Japan (e-mail:ake@eorc.nasda.go.jp).
A. K. Milne is with the University of New South Wales, Sydney, 2052, Australia (e-mail: t.milne@unsw.edu.au).
R. Zimmermann is with the Max Planck Institute for Biogeochemistry, 07745
Jena, Germany (e-mail: rzimmer@bgc-jena.mpg.de).
Digital Object Identifier 10.1109/TGRS.2003.813358

II. CHARACTERISTICS OF A SYSTEMATIC OBSERVATION STRATEGY
In the design of a systematic data observation strategy for fine-resolution sensors, focused on the collection of data for geo- and biophysical parameter retrieval over regional scales—the requirement formeaningful parameter retrieval as argued for here—the following key
aspects of the plan have to be carefully considered:• regional consistency;• adequate repetition frequency;• accurate timing;• sensor consistency;• long-term continuity.
A. Regional Consistency
Maintaining regional consistency in space and time in the data observation plan is imperative in order to allow extrapolation of locallydeveloped retrieval algorithms to regionally extensive units, e.g., theapplication of a stand-derived biomass retrieval model to an extensive

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IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 41, NO. 7, JULY 2003

ecological region. Spatial consistency in this context refers to large regional coverage without acquisition gaps, while temporal consistency
refers to limiting the time window in the regional data capture so that
temporal variations between neighboring passes are minimized. The
requirement for temporal consistency is primarily determined by theland cover and its seasonal influence and the time period of researchinterest.
Both spatial and temporal consistency are illustrated by the semicontinental Japanese Earth Resources Satellite 1 (JERS-1) synthetic aperture radar (SAR) coverage over northern South America shown in Fig. 1[2], [3]. The nearly 60 passes making up the mosaic were acquiredsequentially during a two-month period in 1996, targeted to coincidewith the predominantly high-water season of the Amazon River Basin.
The seasonal influence on the backscatter is apparent in the data, withinundated forest appearing bright. As water levels change rapidly, a
missed acquisition, or a replacement of one pass with another acquired
during a different season, would interrupt the temporal consistency ofthe dataset and induce errors or uncertainties in the analysis. Notable,
however, is that although the coverage is 99% spatially complete, thefew remaining gaps are not only very apparent visually in the mosaic,
but will obviously also prevent any kind of information extraction in
those specific areas, hence further highlighting the significance of thearguments put forward.
B. Adequate Repetition Frequency
Many terrestrial parameters are in a continuous state of change, andin many cases, it is these changes that are of interest in ecological research and in practical applications. Terrestrial carbon cycle research islargely focused around the change component in vegetation status andcondition, and unless the temporal dynamics of the relevant ground parameters are adequately taken into account, the acquisitions will merely
constitute snapshots in time. Specification of temporal repetition needs
is, thus, an important component to an optimal data acquisition strategy,
in addition to the requirements for spatial and temporal homogeneity.
What is “adequate” depends on the ground parameter of interest andthe repeat capability of the satellite. Net primary production (NPP),
for instance, is a rapidly varying parameter that would require daily
to weekly acquisitions during the vegetation period for adequate sampling, while seasonal flooding dynamics may be sufficient to monitor
on a weekly to monthly basis. Forests, on the other hand, with decadal
growth cycles and interannual changes, may be sufficient to cover at
an annual repetition, or less. Hence, the requirements on the temporalrevisit frequency is highly land cover dependent, and a spatial stratification of the observation area into dominant land cover types may thus
be required in the formulation of a regional-scale acquisition strategy.
C. Accurate Timing
Accurate timing of the observations is another important component
to consider, not only as inconsistent seasonality interrupts temporalconsistency in regional datasets as discussed above, but it may also introduce bias in time series of data. Annual acquisitions of, for example,
forest cover by microwave sensors should preferably be taken under thesame physical and structural circumstances that affect the backscattersignal, meaning that acquisitions should be performed during similar
dielectric conditions of the forest and during the same season to ensure comparability of both components every year. As the occurrenceof such stable conditions may vary considerably from year to year, it
may actually be desirable to have more than just one overpass annuallyin order to enable selection of the best time for dielectric and structural
preconditions. Spring acquisitions should generally be avoided in theboreal and temperate zones, as thaw and snowmelt may obscure actualchanges. In the tropical zone, the dry season is preferred, due to morestable dielectric and larger radiometric dynamic range between baresoils and vegetation cover.
D. Sensor Consistency
Optical sensors can record data in several spectral channels andwith several spatial resolutions simultaneously, thereby bypassing
the need to specifically select a predefined sensor mode for eachdata take. Microwave sensors are much more limited in this respect.
While the JERS-1 and European Remote Sensing 1 and 2 (ERS-1/2)
satellites featured SAR instruments with fixed sensor parameters,
Radarsat, Envisat, and the Advanced Land Observing Satellite(ALOS) allow—or will allow—variable polarizations, off-nadir
angles, and spatial resolutions (ScanSAR). While this, on one hand,brings greater opportunity in being able to more adequately characterize the backscatter of objects and surfaces and, therefore, topotentially devise better retrieval models, it introduces a measure ofconflict, as different applications have different sensor requirements.
A conflict of interest may also arise between locally focused basic
research—e.g., investigations of the effects of variable incidence
angles and polarizations—and the more operational, regional-scale
applications discussed in this short communication, which require
repetitive large-area coverage with a constant fixed configuration. In
order to avoid, or at least to minimize, fragmented acquisitions arisingfrom a number of different sensor combinations, this issue should beaddressed by the science community at an early stage in the mission,and a best “tradeoff” set of sensor parameters should be sought. The
availability of spatially and temporally consistent datasets at regional
scales is more likely to govern the extent ot which remote sensing data
are used for environmental applications in the fugure than a specificsensor configuration.
E. Long-Term Continuity
Assuring long-term decadal continuity of acquisitions with intercomparable sensors is a well-known requirement that will not be dealt
with further here. It is sufficient to note that long-term sensor continuity—both optical and microwave—is imperative to support any kindof climate-change-related research, during and beyond the lifetimes ofindividual satellite missions.
F. Case Examples
Illustrating well the importance of systematic data acquisitions andthe new information that regional-scale datasets may provide, Richey
et al. describe [4] how dual-season JERS-1 SAR mosaics covering theAmazon River Basin were utilized to estimate the areal coverage andinundation status in the river basin at the periods of high water andlow water (high-water mosaic depicted in Fig. 1). Each mosaic wasclassified into flooded and nonflooded areas based on their backscatter
intensities as delineated by image segmentation. The flooding information was subsequently used as input to a regional-scale CO2 emission
model developed, to obtain significantly improved estimates of CO2
fluxes from the rivers and wetlands in the central Amazon River Basin.
The example demonstrates the fundamental importance of maintaining
both spatial and temporal consistency over large areas, as well as that
accurate timing (in targeting the basin at its low and high water levels)
is critical. It also demonstrates the utility of compiling the data into
radiometrically and geometrically consistent image mosaics, without
which the investigation above would not have been feasible.
Another illustrative example is provided by the SAR Imaging for
Boreal Ecology and Radar Interferometry Applications (SIBERIA)
project, in which C- and L-band SAR data were used to derive mapsof forest cover and growing stock volume over a 1 million-km2
region in central Siberia [5]. Using a mobile ground receiving station

IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 41, NO. 7, JULY 20031711

III. CONCLUSION

Fig. 1. JERS-1 SAR mosaic over northern South America, illustrating nearlycomplete coverage with spatiotemporal consistency over subcontinental scales.
(Global Rain Forest Mapping Project © NASDA/METI/JPL/JRC).

transported to nearby Mongolia for this purpose, ERS-1/2 C-band data
in interferometric tandem mode and JERS-1 L-band SAR data could
be acquired simultaneously during two limited-time windows, forminga near-complete two-season coverage over the region. Synergetic
analysis of the multitemporal, multifrequency, and interferometric
information collected allowed for stratification of the forest into fourbiomass classes and ensuing generation of 98 1 : 200 0000-scale map
sheets, which were provided to the Russian Forest Service. Executionof a project like SIBERIA unmistakably relies on the availability ofspatially and temporally consistent data over extensive regions, and
it is evident that the dedicated data observation plans implemented
for ERS and JERS specifically for this campaign were fundamental
prerequisites for its success. SIBERIA also demonstrates the benefitsof multisensor approaches, but as consistent and nearly simultaneous
coverage with several sensors over extensive regions rarely exist,
it underscores the need for closer coordination between the space
agencies in their planning and operations of present and near-futureearth observation missions.

While it may be argued that “meaningful” bio- and geophysical parameters can be extracted even from a single scene without an extensive
spatial and temporal context, we believe that it is time to move on fromlocal-scale research to regional-scale operational applications. Parameter inversion is an important area of research because of its potentialimpact on regional and global-scale issues of public concern. Climatechange and environmental degradation are disquieting realities not only
for the science community, but also for policy makers and the generalpublic, who through a number of international conventions addressingthese issues indicate a will for a change. The general public, furthermore, have the right to demand that the not insignificant resources spenton earth observation worldwide are utilized in favor of the public goodand for the preservation of the environment.
The inability of remote sensing technology to be used for ecologically meaningful data interpretation by a wide community and, consequently, its political acceptance and support is thus not primarily aproblem of its technical complexity, but can be attributed to a large
extent to the lack of spatially comprehensive observations over sufficient long time periods. We believe that the establishment of long-term
spatiotemporally comprehensive data acquisition strategies in line withwhat has been discussed above would greatly stimulate the development of operational applications required to support the regional-scale
information needs posed by climate change science and environmentaltreaties, for the benefit of the public, the science community, as well as
for the space agencies.

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[4] J. R. Richey, J. M. Melack, A. K. Aufdenkampe, V. M. Ballester, andL. L. Hess, “Outgassing from Amazon rivers and wetlands as a large
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[5] C. Schmullius, Ed., “SAR Imaging for Boreal Ecology and Radar Interferometry Applications (SIBERIA) final report,” , 4th Framework Programme of the European Commission, Friedrich-Schiller Univ., Jena,Germany, Rep. Co. ENV4-CT97-0743-SIBERIA, June 2001.