What is in the Sink? Technological Support for National Inventories of Forest Carbon

Kenneth R. Richards1

Krister P. Andersson2

(1) Corresponding author. School of Public and Environmental Affairs, Indiana University, Bloomington

Indiana, 47405, USA, kenricha@indiana.edu (2) Center for the Study of Institutions, Population and Environmental Change (CIPEC), Indiana University,

Bloomington, Indiana, USA Abstract

This paper provides an overview and assessment of forest inventory tools that will be useful to policy analysts and government decision-makers who are interested in the measurement aspects of an international carbon sequestration program. The paper examines whether it is possible to develop national level inventories of forest carbon given the current capacity of remote sensing and forest inventory. Based on the review of forest inventory tools and methods, the paper considers the advances in biomass and carbon estimation science that would be most useful for purposes of an international carbon sink program based on a national inventory approach. The fundamental conclusion of the review is that there is no combination of Aoff-the-shelf@ technologies, practices and methods that will suffice to measure and monitor national carbon sinks. Remote sensing, will provide inputs to biomass models, which are then used to estimate carbon stocks. For the remote sensing measurements to be of use, the models must first be developed. Introduction

Protection and expansion of carbon sinks are likely to play an integral role in any

meaningful international effort to stem the rise of atmospheric carbon dioxide. Terrestrial

ecosystems play an important part in the global carbon cycle, with land use change contributing

approximately 20 percent of gross global carbon emissions, while terrestrial absorption of carbon

removes just slightly more (IPCC 2000). Hence, terrestrial ecosystems, taken as a whole, appear

to be a net sink for carbon. The potential, however, is much greater. A modest decrease in

emissions from land use change and a small percent increase in terrestrial absorption could

significantly reduce net carbon emissions to the atmosphere, at least temporarily.

The 1997 Kyoto Protocol to the 1992 United Nations Framework Convention on Climate

Change includes provisions to encourage countries to protect and expand their carbon sinks.

Those provisions, however, are unlikely to accomplish their purpose if and when the Protocol

enters into force. The main problem is that under any reasonable interpretation of the Protocol, the

measurement and monitoring requirements are fundamentally unworkable, requiring judgments

regarding social processes that cannot be observed or measured objectively. The root to this

problem is that the Protocol emphasizes a project-by-project (PBP) approach to implementation

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that invites deception by project implementers, while providing no feasible safeguards against such

cheating (Richards and Andersson, 2000).

Reliable, accurate, science-based monitoring is an integral part of any incentive-based

approach to environmental regulation, even in the international arena. Recognizing the importance

of measurability and enforceability, Andersson and Richards (2001) have proposed an alternative

approach to an international carbon sink program - a national inventory (NI) approach, based on

the principle that a fundamental requirement of an international carbon sequestration program is to

have a monitoring system that is feasible and can indeed be implemented in a transparent fashion.

To this end the national inventory approach eliminates the most problematic elements of the Kyoto

carbon sink scheme, including reliance on the 1990 baseline, the activity-based delineation of

Kyoto and non-Kyoto lands, the differentiation of Adirect human-induced@ land-use changes and

Ahuman-induced@ activities from other causes of changes in the national carbon stock,

measurement of non-forest carbon reservoirs in wood products and agricultural systems, and any

project-by-project accounting.

In place of the cumbersome project-by-project approach incorporated in the Kyoto

Protocol, the national inventory scheme substitutes a system under which nations receive credit or

incur debits in their carbon accounts for increases or decrements in their national stock of forest

carbon, regardless of the cause of the change. Under this approach the measurement issue shifts

from one of evaluating human effects, intent, and timing of intervention, to one of measuring

purely physical changes in carbon stocks. This raises the question, of course, as to whether the

methods and technology exist, or will exist in the foreseeable future, to conduct reliable,

transparent, and economical national level assessments of forest carbon stocks. In fact, the

design of a program should be carried out simultaneously, not sequentially, with assessment of

measurement and monitoring capabilities. Program design must consider technical capability, and

technical capability should be developed to meet program needs. Properly conducted, the process

is iterative.

The purpose of this paper is to provide an overview and assessment of forest inventory

tools that will be useful to policy analysts and government decision-makers who are interested in

the measurement aspects of an international carbon sequestration program. The paper also

examines whether it is possible to develop national level inventories of forest carbon given the

current capacity of remote sensing and forest inventory. Based on the review of forest inventory

tools and methods, the paper considers the advances in biomass and carbon estimation science

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that would be most useful for purposes of an international carbon sink program based on the

national inventory approach.

The fundamental conclusion of this review is that there is no combination of Aoff-the-

shelf@ technologies, practices and methods that will suffice to measure and monitor national

carbon sinks. It is important to recognize that in the measurement of national carbon inventories,

the role of remote sensing is to provide inputs (estimates of independent variables) for carbon

models. Remote sensing does not directly measure carbon stocks. The challenge for estimating

national carbon inventories is that the available carbon models do not adequately cover all forested

areas of the world. For the remote sensing measurements to be of use, models that can reliably

estimate carbon stocks must first be developed. Even for regions for which carbon models have

been developed, there is often no consensus in the scientific community regarding which models or

methods are most appropriate.

Developing new models and calibrating them for reliable results will require considerable

initial fieldwork. Moreover, even with carbon models in hand, estimates based on remotely sensed

data will have to be regularly supplemented and confirmed with significant field measurements,

also known as ground-truthing in this context. Thus, remote sensing is no magic bullet for the

national inventory approach, but a promising technology that can be developed in parallel with the

carbon models in anticipation of the measurement and monitoring needs of an international carbon

sequestration program.

The next section examines the information requirements of the Kyoto Protocol approach

to carbon sequestration, focusing on the divergence between the needed information and current

or future capacities to provide that information. The paper then briefly describes the national

inventory approach to carbon sequestration commitments and describes the information

requirements for that approach. The discussion then turns to concepts related to estimating

carbon stocks and changes in carbon stocks at the national level, and the types of information that

are needed to model those estimates. The section that follows describes the role that remote

sensing tools can play in the development and use of carbon models. The paper then describes the

remote sensing tools that are available for gathering the data on the independent variables of the

forest carbon models, and examines where pending technical developments are likely to improve

forest carbon stock estimates. The following section illustrates the challenges of developing a

national inventory by considering recent work in Russia and Uganda. Finally in the discussion and

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conclusions, the paper raises several issues that governments should address as they consider

future investments in remote sensing and forest science research and development.

Information Requirements for Carbon Sinks under the Kyoto Protocol

The Kyoto Protocol includes several provisions that are intended to encourage countries

to protect and expand their carbon sinks (Table 1). Among these, Article 3.3 provides for

countries to use the “net changes in greenhouse gas emissions by sources and removals by sinks

from direct human-induced land-use change and forestry activities, limited to afforestation,

reforestation and deforestation since 1990, measured as verifiable changes in carbon stocks in

each commitment period” to meet national commitments to limit emissions. Article 3.4 requires

each Annex I country to provide “data to establish its level of carbon stocks in 1990 and to enable

an estimate to be made of its changes in carbon stocks in subsequent years.” Artic le 5.1 requires

Annex I parties to have a national system for estimating removals of greenhouse gases by sinks.

To support the requirements of Article 5.1, Article 5.2 requires the Conference of the Parties to

the Kyoto Protocol to develop “methodologies for estimating anthropogenic… removals by sinks

of all greenhouse gases” as well as adjustments to be applied when the accepted methods are not

used.

While the exact implication of these four provisions remains open to interpretation, at a

minimum they require countries, and by implication third party monitors, to develop measurements

Table 1: Summary of Kyoto Protocol Provisions Related to Carbon Sinks

Article Provision

3.3 Human-induced net changes in removals by sinks from afforestation, reforestation, and deforestation activities since 1990 shall be used to meet commitments of Annex I countries.

3.4 Annex I countries must provide data to establish their level of carbon stocks in 1990 and subsequent years.

5.1 Annex I countries must have a system for estimating greenhouse gas removals by sinks.

5.2 The IPCC and the Conference of the Parties have to agree upon methods for estimating removals by sinks.

6.1 To meet their commitments parties can trade emission reduction credits that result from “enhancing anthropogenic removals by sinks.”

12 The clean development mechanism allows generation of certified emission reductions by projects in non-Annex I countries that can be transferred to Annex I parties for use in meeting the emission limitations. The conference of Parties must develop procedures to measure and monitor project activities.

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that segregate direct human-induced changes in terrestrial carbon stocks from all other changes in

carbon stocks, to measure changes that result from afforestation, reforestation and deforestation

separately from changes that occur from any other action, and to differentiate those changes

according to whether they are caused by actions that occurred before or after 1990. Skole and

Qi (1999) have suggested that these observations must reveal the intention associated with human

activities. Moreover this complex analysis is to be conducted in a “transparent and verifiable

manner” (Article 3.3).

Article 6.1 provides a trading mechanism under which Annex I countries can transfer

“emission reduction units resulting from projects aimed at … enhancing anthropogenic removals

by sinks of greenhouse gases” provided that removal by sinks in such projects is “additional to any

that would otherwise occur.” Article 12 also describes a clean development mechanism that

allows Annex I parties to comply with their emission limitations by using certified emission

reductions from projects in non-Annex I countries. Emission reductions from projects under the

clean development mechanism must be “certified by operational entities”, must provide “[r]eal,

measurable and long-term benefits related to the mitigation of climate change”, and must be

additional to any that would occur in the absence of the certified project. The Conference of the

Parties is responsible to elaborate “modalities and procedures with the objective of ensuring

transparency, efficiency and accountability through independent auditing and verification of project

activities” (Article 12.7).

The provisions of Article 6 require countries to isolate not only the physical effect of

individual projects, but to determine whether those effects would have been incorporated in the

countries’ other emission abatement or sink enhancement activities. Measuring changes over time

in carbon levels on the site of a sequestration project is challenging but feasible. However, the

project analysis described by Article 6 also requires establishing a reference case based on a

counterfactual set of assumptions about what would have happened in the absence of the project.

For projects occurring in complex market economies, the process of creating a reference case

often thrusts the analysis into the realm of conjecture, eliminating any pretense of reproducible

results and objectivity (Richards and Andersson 2000). Moreover, meaningful estimates of the

real effects of carbon removal projects must also account for off-site effects, i.e., any additional

emission of carbon from other sites that is caused by the certified project. For example, when an

area of cropland is converted to forest plantation, the demand for cropland as an input to

agricultural production does not disappear. Existing forests may be cleared to meet that demand

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and land that would otherwise have been planted in forest may be kept in agriculture. These off-

site or “leakage” effects are extremely difficult to estimate, and virtually none of the pilot projects

in the forestry sector provide this important part of the analysis (Richards and Andersson 2000).

It is unclear whether the clean development mechanism described in Article 12 extends to

carbon sinks and sequestration. If the Conference of Parties to the Convention eventually decides

that forestry activities are included under the clean development mechanism, then all of the

measurement difficulties associated with the provisions of Article 6 will apply to Article 12 as

well. In fact, the difficulties associated with estimating the effects of carbon removal projects

under the clean development mechanism are likely to be even greater because of the limited

record keeping and documentation of non-industrialized (non-Annex I) countries.

After reviewing the many difficulties associated with the Kyoto Protocol approach to

sinks, Skole and Qi (1999) conclude that the “implications suggest that accurate budgeting of

global carbon or national level emissions inventories will be difficult unless we account for all

possible sources and sinks with improved estimation accuracy through a well-specified operational

program.”

There are several additional problems associated with the vagueness of the definitions

used in the Kyoto Protocol (Skole and Qi 1999; IPCC 2000). First, how will forests be defined?

For example, the FAO defines forests as areas with a fractional tree cover of greater than 10

percent. Following that lead, will all land areas with more than 10 percent tree cover be defined

as forests? Second, how can specific impacts be defined as “direct human-induced”? When a

country allows a forest fire of natural origin to burn uncontrolled, is that a human-induced change?

Third, how will changes within land-use types be treated? For example, would harvesting a forest

such that cover is reduced from 100 percent to 20 percent be ignored because the forest does not

pass the 10 percent threshold into deforestation, while elimination of the last 20 percent would

constitute full deforestation?

All of these factors – ill-defined reference cases (baselines), leakage, limited historical

records, and undefined terms – suggest that it will be impossible to implement the Kyoto Protocol

provisions for carbon sinks, now or in the future.

Information Requirements for Carbon Sinks under the National Inventory Approach

In contrast to the Kyoto Protocol’s project-by-project approach to sinks, the national

inventory approach rewards (debits) countries for increases (decreases) in carbon stocks in

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forests regardless of causation, the type of activity that led to the change, whether the activity was

human-induced or not, and when the activity that led to the increase occurred (Andersson and

Richards 2001). Because of this there are no projects as such under the national inventory

approach. The system is one that shifts the focus from inputs and intentions for carbon

sequestration to effects and accomplishments only. The national inventory approach focuses on

forests only, leaving changes that are more difficult to measure, such as increases in wood product

carbon sinks or stocks of carbon on agricultural land and soils, out of the calculus for the present.1

Similarly, whether forest soils are included in the national inventory approach becomes a technical

issue, i.e., can changes in forest soil carbon stocks be accurately and economically measured?

The national inventory approach to a carbon sequestration program requires both more

and less information than the project-by-project approach of the Kyoto Protocol. Whereas the

Kyoto Protocol requires measures of carbon stock changes only on lands subject to afforestation,

deforestation, and reforestation, the national inventory approach includes all forest lands, including

those that exhibit increases in carbon stocks from natural regeneration or decreases from partial

or selective harvesting, as long as the changes in carbon stock can be estimated with current

means. Thus, the information requirement under the national inventory approach may be more

spatially extensive.2 At the same time, the Kyoto Protocol requires information of a fundamentally

different nature. While the national inventory approach looks only at physical stocks of carbon at

various points in time, the Kyoto Protocol requires additional information and judgments, including

(1) whether the observed changes in carbon stocks were caused by afforestation, reforestation,

and deforestation, or some other activity such as regeneration, thinning, ecosystem maturation, or

fire; (2) whether the observed changes were caused by humans or occurred naturally, (3) whether

the event causing the change occurred prior to 1990 or since, and (4) in the case of projects,

whether the removals by sequestration projects would have occurred in the absence of the project

and whether the project has had countervailing effects on the larger economy or ecosystem. Thus

the information requirements for purely physical data for the national inventory approach may be

1 Exclusion of non-forest agricultural areas from the national inventory approach is simply a concession to the difficulty involved in systematically and accurately estimating changes in carbon stocks on these types of land. Should it become possible to cost-effectively estimate changes in those sinks with an accuracy similar to that of the forest carbon sink, then it may be reasonable to include a wide range of agricultural sinks. 2 It is possible, however, to interpret Article 3.4 to require countries to provide full carbon accounting of carbon stocks and changes in carbon stocks on all forest lands, regardless of the cause of the changes. Under this interpretation of Article 3, the information requirements of the national inventory approach are strictly less than the Kyoto Protocol approach.

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greater than the Kyoto approach, but the latter requires substantially more (possibly unavailable)

information regarding social, legal, and economic information.

There may be considerable variation in carbon stocks on a particular site from one year to

the next. Harvesting and other management practices can lead to considerable changes over

time. By increasing the spatial and time scales of observations much of the variability is reduced,

allowing countries to assess their long-term trends in carbon stocks (Schlamdinger and Marland

2000).

But is it possible to measure the fluxes in forest carbon with sufficient accuracy with the

existing set of tools and methods? That is the fundamental challenge of the national inventory

approach. A quick calculation, presented only as a thought exercise, can help illustrate the

importance of accurate and reliable measurements in national inventories.

The size of the total global carbon pool in vegetation has been estimated at 466 gigatonnes

of carbon (IPCC 2000). Suppose that during a particular five-year commitment period there is in

fact no change in the size of the global carbon sink. However, if there were even a one percent

drift in the measurement of that carbon stock, say to the positive side, it would appear that there

had been a gain of approximately 4.7 gigatonnes of carbon over the commitment period, or

approximately 0.93 gigatonnes per year. The annual global emission of carbon from industrial

sources is approximately 6.3 gigatonnes (IPCC 2000). Even if the global community aimed to

reduce annual emissions by 10 percent (they have not been so ambitious), that would suggest that

net annual emissions must decline by only 0.63 gigatonnes per year. In this example, because of

the small error in measurement of the size of the global carbon stock in sinks, countries would

estimate that they had more than met their emissions reduction targets based on sinks alone and

not be obliged to undertake any source reduction actions. In fact, when estimates based on

existing carbon inventory techniques are subject to uncertainty analysis, it is not uncommon to see

15 percent or greater standard errors in the estimate of the mean of a country’s forest carbon pool

estimates (Nilsson et al. 2000, Jonas et al. 1999, Balzter and Shivdenko 2001, National Biomass

Study 1998). Clearly, the uncertainty in the sink measurements could substantially undermine

efforts to reduce net emissions by overwhelming the carbon source emission estimates.

The central question then becomes whether the existing technology and methods are, or

could be, sufficient to achieve the necessary accuracy in estimating national inventories of forest

carbon sinks. This paper addresses this question by reviewing the state of the art for the

technologies and methods that could be employed for national inventories of forest carbon sinks.

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After reviewing existing research on, and policy experiments with, these inventory approaches, we

assess the potential of the national inventory approach from the perspective of whether it is

possible to develop a reliable system for monitoring forest carbon.

Measuring Carbon Stocks in Forests

To implement the national inventory approach to an international carbon sequestration

program, it will be necessary to measure the amount of carbon standing in the forests of national

parties at regular intervals over time and, more importantly, to estimate the periodic change in

those carbon stocks. As a practical matter, forest carbon stock estimates cannot be measured

directly, even for small plots, because doing so is both destructive and expensive. Thus, for small-

scale ecosystem carbon analysis at the plot level, researchers take samples of ecosystem

components, measure their biomass and carbon content, calculate the carbon per unit volume of

that component, and then estimate the volume of the component on the site in question. From

these calculations they derive estimates of on-site carbon stocks.

Even estimating the volume of each component can be resource intensive for sites of

significant size, so researchers have developed models that correlate easily observed or measured

characteristics of forests to the variables of interest. For example, for a given forest type and age,

it may be possible to relate a sample measurement of tree diameters on the site in question to the

total biomass on the site. One of the simplest forms of forestry models, the allometric model,

relates diameter at breast height (DBH) and canopy height to forest biomass.

With information about the average carbon density of the biomass components, it is

possible to use allometric models to derive estimates of the total carbon stocks. One challenge to

the use of allometric models for estimating carbon stocks is that many of the existing models were

established with data from industrial or government-managed forests that are not representative of

the majority of forests on the globe. Moreover, there is often no consensus regarding which

models are most accurate for a given region and type of forest.

Gradually alternative carbon models have developed that express carbon stocks as a

function of any number of forest characteristics. A typical carbon model of the carbon content of

a forest stand might include some combination of the following independent variables that are

listed in Figure 1 (NBS 1998, Gluck et al 2000, K. Brown 1996, S. Brown 1999, MacDicken

1997).

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Figure 1. A Generic Biomass Model for Estimating Carbon in Above -Ground Woody Biomass

C = /(D, A, L, R, H, O, S, F, P, Cr, B, W)

where

C = total carbon in the stand, D = average tree diameter at breast-height A = stand age L = leaf area index H = canopy height O = canopy cover R = total area of the stand S = stems per unit area F = forest type P = species Cr = crown height B = bole height W = crown width Cl = leaf cluster index Another challenge in the application of allometric models to carbon stock estimates is that

the models can be sensitive to the species composition of the forest, the age and history of the

forest, the soil type, climate, and solar exposure. Incorporating these additional factors would

require developing more sophisticated carbon models, but the range and combination of

independent variables is great.

Developing new biomass and carbon models can be an expensive process as it involves

field research and sampling over extensive areas. However, there are methods, such as double

regression sampling, importance sampling, and randomized branch sampling, that can be used

individually or in tandem to substantially reduce the cost of measurement by reducing the amount

of harvesting involved in the sampling process (Lucas and Tickle 1999). Of these, double sampling

is one of the most common methods used for forest inventories. Double sampling, also referred to

as two-phase sampling, is used when the variable of interest is expensive to assess and when the

variables of interest happen to have a strong relationship with a proxy variable. For example, if

you are primarily interested in above-ground biomass in forests, then it might be more cost

effective to sample variables such as leaf area index3 (LAI) or normalized difference vegetation

3 Leaf Area Index, the total one sided surface area of leaves above a given area of ground, is one of the most important determinants of reflectance in a given vegetated terrain. LAI is a unitless [m2/m2] ratio of the total leaf area (measured on one side of the leaf only) for a given unit of ground area (Green 1998). LAI is derived from both ground measurements and indirect estimations from remote sensing instruments. Discovering the correlation between the two for different forest types is valuable for calibrating the allometric models.

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index (NDVI)4 from satellite imagery before you consider where to sample carbon variables with

costly and time-consuming ground measurements. One of the advantages of recent remote

sensing technologies is that they provide many useful proxy variables that can be used for double -

sampling in carbon sink monitoring (Banko 1998, European Commission 1997).

The Relation between Carbon Models and Remote Sensing

To implement the national inventory approach it is necessary to examine whether and how

countries can develop credible, reproducible estimates of the size of their national forest carbon

sinks. As discussed above, this involves scaling up from the methods that are commonly used at

the plot or forest-stand level to derive landscape, regional and national estimates. The scaling-up

process necessarily involves using various models to correlate measurable forest parameters to

biomass and carbon estimates. Many of the essential variables for the forest carbon model, such

as DBH and stand age, require field measurement. Nevertheless, recent research on forest

carbon monitoring points to the potential utility of various remote sensing technologies as a

valuable complement to field measurement of several carbon model input variables

(MacDicken,1997; S. Brown, 1999; K. Brown, 1996; Banko,1998; Gluck et al 2000). Figure 2 lays

out the basic steps of the forest carbon measurement process and explains how satellite data can

be of use in each step of this process.

Satellite Data

When acquiring raw satellite data it is particularly important to consider (a) the end-use of the

imagery data, and (b) the comparability of the cloud-free images.

4 Vegetation indices, such as NDVI are often used to reduce data volume and condense the information content from satellite imagery. A NDVI image shows the difference between the surface reflectance (brightness) in the visible red and the near infrared wavelengths. It is primarily used as a single value that shows the amount of vegetation cover. It was developed by Compton Tucker primarily for use with AVHRR data using field data collected from herbaceous canopies, primarily crops. Tucker showed that reflectance varies with biomass in a herbaceous canopy in a predictable manner (Green 1998). As MacDicken (1997) notes, “correlation between NDVI and ground based data has yielded information about the quantity of standing biomass and is the approach that most researchers take to imply biomass, but it is problematic due to [the presence of external] factors that can affect NDVI value.”

Figure 2: The Forest Carbon Measurement Process Using Remote Se nsing Technology

Satellite data à Gross classification à Sampling à Fieldwork à Detailed classification à Biomass models à Carbon estimates

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End use. Appendix 1 provides an overview of most of the available types of satellite imagery

products available to the land cover change research community. The end use of the data should

determine which imagery data product to acquire. Table 2 describes the comparative advantages

of each of these products as they pertain to forest carbon estimates. If, for instance, the satellite

data will be used for estimating forest area only, the most useful data product will probably be

different from one that will be used to identify different forest types.

Comparability. Since the purpose of conducting national inventories of forest carbon is to

estimate changes in the forest-bound carbon overtime, it is essential that the satellite imagery that

is acquired to facilitate the estimation procedure, is comparable for all different points in time.

Even if the exact same type of data product is acquired for the baseline date as well as for the

end-of-the-period date, seasonal variability may make the two products incomparable. For some

satellite products, an image of a tropical forest during the rainy season is not comparable to an

image of that same forest during the dry season, which complicates the process of estimating the

changes of many carbon model variables.

Moreover, to ensure comparability the purchased images need to be processed to minimize the

influence of several undesired sources of variance. Such processing may involve several different

tasks depending upon the product and its end use. Two commonly recommended processing tasks

are geo-registration (assigning an exact geographic location for each pixel of the image), and

atmospheric calibration (allowing for atmospheric variability to being held constant across multiple

points in time), but several other tasks may be necessary to achieve comparable measures.

Gross Classification

After processing the raw image, computer programs may be used to carry out a gross

classification of the satellite image. This gross classification provides the researcher with an

overview of the main characteristics of the studied land area, i.e. the spatial extent of forested

areas and their variability in terms of different forest types and degree of degradation. Such

information may be critical inputs for strategic decisions about what type of sample stratification

would be most appropriate when defining where ground measurements should be carried out.

Most optical remote sensing instruments can distinguish between forest and non-forest.

Instruments with multi-spectral bands can be used to determine specific forest types. If the

instrument has fine-resolution spectral and spatial characteristics, these distinctions are usually

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easier to make. A subsequent section of this paper discusses the instruments that can provide

such information.

Sampling

If the quantity of carbon sequestered or released from forests is the dependent variable, a

stratified sampling design based on remote sensing estimates of forest types and their respective

carbon density and variability is appropriate. Such a design will reduce the number of field

measurements that are necessary to reach the desired level of accuracy by making direct

measurements of representative areas and extrapolating the collected data to similar areas. Since

carbon density is not directly measurable by remote sensing instruments, an indirect measurement

method must be employed. For example, leaf area index has proven to be a good proxy variable

for carbon density in some forests and can be used for stratifying areas according to their carbon

density.

Forest carbon pools can be placed on a continuum of carbon density. Carbon tends to be

most concentrated in old growth forests and least concentrated in recently deforested or burnt

areas. A national inventory program primarily focuses upon the total changes that occur within the

entire forest carbon pool. The total variation in the forest carbon pool can sometimes be driven by

large variations of carbon concentrations on relatively small areas. For example, if the estimated

annual uptake of atmospheric carbon for a 100 hectare forest is determined to be 100 tonnes/year,

this uptake could conceivably be offset by emissions if only one half hectare burns down that

same year. If only 15 large trees were removed by selective cutting it could be enough to make

the hypothetical 100-hectare forest a net source rather than a sink for that year. It is therefore

useful for a program interested in change to be able to detect the change hot spots – the areas

that have shown the greatest variance during the year with regards to carbon concentration. It is

important that a sufficient number of ground measurements are carried out in such hot spot areas.

One of remote sensing’s most valuable capacities is to detect deforestation and degree of

degradation.

Fieldwork

Field measurement is the core component of any effort to estimate forest carbon stocks. On –

the-ground measurements of several variables, such as DBH, and positive species identification,

are carried out on selected forest plots within the study area. Selected plots may be either

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permanent or temporary. The number of plots needed will vary with the degree of homogeneity of

the strata and accuracy requirements.

Fine resolution satellite images can also be used to “air-truth” inaccessible areas. Because of

poor or non-existing infrastructure, it is sometimes not possible for a field team to get to the

sampled ground measurement plots.5 A substitute often used in these situations is a survey flight

with a small aircraft. As our colleagues in the Uganda Biomass study can appreciate, this can be a

rather expensive substitute. Projects such as the National Biomass Study in Uganda therefore

welcome the increased availability of new satellite instruments with very fine spatial resolution,

such as the IKONOS satellite (see discussion of instrument characteristics below), which

potentially could replace the expensive survey flights without compromising on accuracy.

Detailed Classification

Field measurements from the selected forest plots are then used to re-classify the image into

several classes of forest carbon density. The accuracy of the classification process is directly

related to the amount of field data that is available. The more field data, the more accurate the

classification. Re-classification, also called supervised classification, can be a tremendously time-

consuming process, and it is also an exercise that can generate a great deal of error if the

researcher is not careful.

Biomass Models

Biomass regression models that estimate carbon stocks in specific stands use a variety of

variables measured by satellites such as area of forest stand, canopy cover, leaf area index, and

NDVI, and estimate the stock of woody, above-ground biomass. A forest stand’s biomass density

depends to a large extent on its structure. Because it is difficult for most remote sensing

instruments to measure forest structure directly, biomass models based primarily on remote

sensing data have not been very successful in terms of prediction power for one-shot estimates.

For time series measurements, however, the accuracy may improve as it is possible to explore

5 Even though these inaccessible areas are the least exposed to human intervention and therefore often show only small variations in carbon fluctuations over time, it is nevertheless important to verify that there have not been any new human encroachments or natural disturbances such as fires in the areas. It is normally sufficient to verify these occurrences passively, without a need to make through ground measurements.

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relationships between the changes in a combination of reflectance variables with the change in

biophysical variables derived from ground measurements.

Double sampling techniques are key for discovering such relationships because the

reflectance and biophysical information for allometric models must come from the same

geographical area. The less discrepancy there is between the geographic locations of ground

measurements and the reflectance information, the better the prospects for accurate specifications

of allometric models.

Carbon Estimates

Estimating the changes in carbon stock during a specific period of time can be done in two

ways. First, for a given area change can be measured as the difference between the estimate of

carbon stock at the beginning of the period and the stock at the end of the period. Second, the

size of a change in the carbon stock can be estimated directly without inventorying the entire

carbon stock. Both alternatives rely on the carbon models for producing the estimates, at specified

confidence intervals.

At each one of the seven steps outlined in Figure 2 there are sources of error that should be

explicitly addressed in the presentation of the carbon estimation’s results. It is one thing to define

the margin of error for each of the seven steps, but to estimate an aggregate standard error of

estimates that take into account sampling and measurement errors for all seven steps is more

complicated.

In summary, remote sensing instruments can play a significant role in improving the accuracy

of national forest inventories, especially if employed early in the monitoring process. Starting the

national inventory process by analyzing satellite images is both cost-saving and accuracy-

enhancing. As the technology improves, so will the viability of using a combination of

complimentary remote sensing instruments in the estimate of woody biomass stocks and changes.

Experimental research on how to combine different technologies and measurement methods can

provide useful lessons for other countries that are discussing how to do national inventories of their

forest carbon. These experiences can also give policy makers an idea of how accurate the results

of a monitoring program could be with the existing instruments and methods. Before we examine

the empirical evidence from two such experiences, we review the most commonly used remote

sensing instruments for carbon monitoring.

16

Remote Sensing Tools and Applications

As depicted in Figure 1, even if there were sufficient carbon models to cover the wide

range of forest types and circumstances in the world=s forests, there would remain the significant

challenge of gathering the inputs for these models across all forests. To aid in this process,

scientists have employed a variety of remote sensing methods that provide data about the type of

forest (F), its spatial extent (R), canopy cover (O), canopy height (H)6, stems per stand (S), Leaf

area index (L) and with some instruments even the degree of succession and approximate stand

age (A) without the need to dispatch field research teams to measure those parameters. This

section examines the tools that are currently or soon will be available for gathering the data on

those forest parameters.

Optical Remote Sensing

Aerial photographs collected from airplanes, have long been used to estimate the extent of

different types of land use over sizable regions. The difficulty with aerial photography is that the

footprint of each image is relatively small and the sampling can be irregular and expensive.

For nearly three decades, satellites have provided repeated optical images of the world’s

geography that have been useful in estimating the scope of the world=s forests. Satellite data is

captured in a series of images as the satellite passes over the earth’s surface. Thus to cover large

geographic areas, a mosaic or set of images covering different subsets of that area are used. The

images vary in terms of spatial resolution (smallest discernible area also called ‘minimum mapping

unit’), geographic coverage or extent for one image, frequency of pass over specific sites

(temporal resolution), and time periods over which they have operated, meaning that the satellite-

sensor combinations that have been deployed vary with respect to their usefulness in providing

data that can be used to estimate past and future carbon stocks. One of the limitations of optical

systems for carbon monitoring is that they detect vegetation reflectance only during daylight hours

and cannot penetrate cloud cover to return images of the land cover below.

There are many satellite-based systems of varying sophistication that gather data about

land use through passive optical (essentially photographic) methods. These systems vary in terms

of their resolution. Some, such as the Landsat TM, the SPOT HRV, JERS-1:OPS, and the

IKONOS have very high spatial and spectral resolution and, in some cases, can detect variations

6 With Vegetation Canopy Lidar (VCL) only

17

in land-use on areas as small as 15 meters square. Where the fine resolution instruments are

particularly useful for detecting land-use fragments, changes in small areas and partial

deforestation, the coarse resolution instruments such as the NOAA AVHRR, ADEOS OCTS

and the EOS-AM:MODIS systems can be more useful in detecting trends and changes at the

continental and global scale. (Some of the high resolution passive optical systems can also be

used to estimate canopy closure and leaf area index, parameters that can be useful in estimating

biomass.)

Coarse resolution passive optical instruments can provide global images as frequently as

daily. Even the fine resolution instruments provide complete global coverage every 14 to 45 days,

depending upon the orbital path.

There is a limited historical record available for estimating baselines of carbon from

satellite imagery. Most systems have only been deployed in the last ten years. Two of the

systems, the Landsat instruments and the NOAA AVHRR instruments, have provided a record

that extends back into the early 1970s. While those data sets are valuable for estimating the

geographic extent of forest coverage, however, taken by themselves they provide limited insight

into the carbon stock associated with the forest areas.

While satellite imagery is a useful tool, it does have serious limitations. As mentioned

above, the instrument can only gather information when there are clear conditions with adequate

sunlight. Also, when the leaf area index exceeds 3 to 4, satellite imagery is insensitive to further

change, and so cannot detect thickening of the forest biomass.

There are advances in optical remote sensing that may increase its usefulness in

estimating carbon stocks. Single optical images are only two dimensional, and hence are primarily

of use in determining the area of various land-use types. Multi-angle sampling can increase the

ability of optical instruments to characterize forest structure and therefore more accurately infer

biomass (Skole and Qi 1999). Such approaches could assist in deriving estimates of the leaf

cluster index and how the canopy structure affects rates of photosynthesis (Ahern and Chen

1999). The recently deployed ASTER system on the EOS-AM platform is expected to contribute

to multi-angle sampling and research.

By using multi-spectral images that provide various reflection patterns, it is possible to

correlate the optical images to additional attributes of the forest such as composition and age.

Synthetic Aperture Radar

18

Synthetic aperture radar (SAR) instruments employ microwave to gather information

about the extent and nature of forests. These systems aim a microwave signal at the ground and

receive information back in the form of backscatter. Scientists have been able to correlate those

backscatter messages to important forest characteristics such as canopy height, area coverage,

and forest type. One of the main advantages of the SAR technology is that it is not sensitive to

cloud cover or daylight, and thus each pass around the globe returns more information than the

optical systems.

Most SAR devices are single -band instruments that use a specific wavelength. Currently

SAR instruments include X-band (wavelength ~3.5 cm), C-band (wavelength ~5.6 cm), L-band

(wavelength ~24 cm) and P-band (wavelength ~65 cm). One important limitation of the SAR

technology is that the signal is often scattered by the vegetation it is measuring. As a result, the

C-band instruments tend to saturate at biomass levels as low as 20-40 tonnes per hectare (Milne

et al. 1999). This is a serious limitation when mature tropical forests often carry biomass levels of

200 to 400 tonnes per hectare. Recent research is demonstrating that the longer wavelength

instruments can penetrate further into the biomass and hence saturate only at higher levels. It

appears that with current methods the L-band instruments can measure biomass densities in the

range of 60 to 100 tonnes per hectare (Milne et al. 1999), and P-band instruments may be able to

detect biomass in the range of 100-200 tonnes per hectare.

Recognizing that SAR’s tendency to saturate at relatively low densities is the main

constraint to the technology’s use in biomass estimates, research continues to push this saturation

level higher. Work with multiple SAR frequencies appear to be able to raise the saturation level to

250 tonnes per hectare and adding multiple polarization can increase the threshold as high as 400

tonnes per hectare. Further, the air craft-based CARABAS-II moves the SAR down from the P-

band to the VHF-band and may push the saturation level as high as 1000 tonnes per hectare,

presenting an entirely acceptable sensitivity, even in densely vegetated areas. One limitation of the

VHF instrument to date is that it cannot be deployed in space because of ionospheric distortions.

Advances in the SAR technology promise to provide increased opportunities to correlate

backscatter signals such as leaf area index and branch surface/volume ratios (Milne et al. 1999).

Promising research into the use of multiple polarization interferometric systems may eventually

increase the usefulness of this technology as the backscatter signals of these instruments are

correlated to important forest characteristics such as leaf area index, leaf area density and

biomass density. One serious limitation of the SAR technology for estimating national inventories

19

of above-ground biomass and carbon is that it is sensitive to topographical changes. As a

consequence, its application is mostly limited to flat or gently rolling areas (Rosenqvist et al. 1999).

LIDAR

The final category of remote sensing devices, representing the most recent

developments, use optical laser altimeters to gather three-dimensional information about the

vertical distribution of plant surfaces throughout the sampled forest. This technology is capable of

Table 2: Summary of Remote Sensing Instruments

Advantages Disadvantages Potential Contribution to Inputs of Allometric Models

Optical: Aircraft • Detailed images • Flexibility in geographic targets

• Small area • Expensive • Sensitive to daylight

and cloud cover

• Canopy height (H) • Canopy cover (O) • Total area of stand (R)

Optical: Satellite (high resolution)

• Detect small (15 m)2 changes in land use and deforestation with ETM+ panchromatic

• Frequent global coverage (weekly to semi-monthly)

• Long historical record of global images (early 1970s)

• Multi-angle sampling can characterize forest structure

• Sensitive to daylight and cloud cover

• Insensitive to differences in dense biomasses

• Canopy cover (O) • Leaf area index (up to level of

3 or 4) (L) • Total area of stand (R) • Leaf cluster index (Cl)

Optical: Satellite (coarse resolution)

• Detect trends at the continental and global scale

• Very frequent global coverage (daily to weekly)

• Long historical record of global images (early 1970s)

• Sensitive to daylight and cloud cover

• Total area of stand (R)

Synthetic Aperture Radar

• Not dependent upon daylight or cloud cover

• Use of multiple polarization can increase measurable density to 400 tonnes per hectare

• Saturation at relatively low levels of biomass density

• Only used on relatively flat topography

• Canopy height (H) • Total area of stand (R) • Forest type (F) • Leaf area index (L) • Branch surface to volume

ratios Synthetic Aperture Radar (VHF)

• Not dependent upon daylight or cloud cover

• Measures biomass density up to 1000 tonnes per hectare

• Airplane deployment only

• Only used on relatively flat topography

• Canopy height (H) • Total area of stand (R) • Forest type (F) • Leaf area index (L) • Branch surface to volume

ratios LIDAR • Characterizes 3-D structural

characteristics of forests • Useful in steeply sloped areas

• Airplane deployment only

• Narrow coverage with each pass

• Leaf area index (L) • Canopy height (H) • Canopy cover (O) • Stems per unit area (S) • Bole height (B) • Crown width (W)

20

providing high-resolution direct measurement of forest structure variables that are crucial in

calculating woody above-ground biomass. Quantification of variables, such as tree crown volume

and degree of succession (an indication of disturbance of a stable forest and the recentness of

such an event), can then be used to calculate the above-ground biomass of the sampled area by

means of biomass models (Drake et al. 2000).

Early pilot studies indicate that the Vegetation Canopy Lidar will facilitate accurate

estimates of forestry-related carbon sequestration and emissions. In particular, one pilot study of

dense-canopy tropical forests, carried out in collaboration between the University of Maryland and

La Selva Biological Research Station in Costa Rica, mapped the forest floor and estimated forest

biomass more accurately than with any previous estimation methods (Blair et al 1999).

A Suite of Remote Sensing Instruments

As this overview suggests, no single remote sensing instrument is will suffice to provide

the important data inputs on both biophysical characteristics and the area coverage of various

land-uses and forest types. It will almost certainly be necessary to develop an approach that

combines data from coarse and fine resolution optical sensors, multispectral SAR, and Lidar.

Table 2 provides a comparison of the contributions that each remote sensing technology could

make to an international system designed to monitor national inventories.

The Need for Ground Measurements

While remote sensing can provide crucial measurements of some variables that go into the

models used to estimate the carbon stocks of a particular forest, the predictive power of such

models will be quite low unless they are fed by complementary ground measurements of other

forest structure variables (see Figure 1). Field measurements entail dispatching research teams to

the forests to collect samples that can be used to validate the models. It is generally held that

while such field measurements are expensive they represent the single most accurate way to

estimate the carbon content of a forest stand. Hence, using field measurement samples to check

estimates based on allometric models calculated with remotely sensed data is an economical

compromise between cost and accuracy for the wider-scale carbon inventories.

Is The National Inventory Approach Viable in the Real World?

21

As mentioned earlier, one of the main challenges for the national inventory approach to

carbon accounting is to show that it is possible to estimate carbon pool fluxes with sufficient

accuracy. Drawing on recent empirical research on carbon sink monitoring, we suggest that by

incorporating remote sensing technologies and their applications in a sensible way, it is possible to

produce sufficiently accurate estimates of above ground woody biomass in forests at a national

level to make the national inventory approach a viable climate policy option. We base this

optimistic assessment on the reports of two very different carbon inventory experiences: the full

carbon account of Russia (Nilsson et al. 2000) and the National Biomass Study of Uganda

(National Biomass Study 1998). Both research projects are taking advantage of a variety of data

products generated by remote sensing platforms, such as Landsat, SPOT, JER, RADAR and

AVHRR.

Carbon Inventory for Russia

In their enormous undertaking to quantify the entire 1990 carbon flux balance of Russia,

Sten Nilsson and his colleagues at the International Institute for Applied Systems Analysis

(IIASA) combined extensive ground measurements with remotely sensed products to construct

biomass models that calculated the total terrestrial carbon sink. The sink estimates were then

subtracted from the 1990 emission data for the country. The results indicate that in 1990, Russia

was a net source of 527 teragrams of carbon. The uncertainties involved in this estimate,

however, were so large that they exceeded the actual estimate of net emissions. The uncertainty

range was calculated as 129 percent of the estimate=s mean value without taking into account

any biases, which often can be substantial as well (Nilsson et al. 2000). Interestingly, the study=s

estimate of above ground, woody biomass for the 1990 baseline was much more accurate. The

study estimated that the reported size of the country=s 1990 forest carbon stock to be 1,707

teragrams of carbon with an uncertainty band of only 18 percent around the estimated mean.

The study=s results have important implications for national inventories. First, it will be

impossible to verify country reports of net carbon dioxide emissions unless uncertainties of

measurements are reduced considerably. Second, a comparable set of methods needs to be

developed for each country that will result in reliable estimates and specify its level of uncertainty.

Finally, the study shows the importance of applying the criteria of measurability to climate

mitigation policies -- only measurable offsets should be included in the formula to calculate a

country=s net emissions.

22

The results of IIASA=s study are encouraging for the national inventory approach to

carbon sink quantification. They clearly demonstrate that using an integrated approach based on

both remote sensing and ground measurement techniques, an acceptable level of accuracy can be

achieved for national inventories of forest carbon pools. These results confirm empirical studies in

a neighboring country, Finland, where Landsat TM images were used as a complement to forest

plot measurements to quantify the country=s inventory of aboveground, woody biomass. There,

the results had an estimated uncertainty band of 15 per cent around the mean of the estimated

national biomass stock (Hyppaa et al 1999).

The National Biomass Study (NBS) of Uganda7

In an ongoing project to monitor changes in woody biomass in Uganda, the national

biomass study has developed a set of useful methods for biomass inventories. Relying mostly on

SPOT imagery, the project used double sampling techniques for 6000 forest plots to establish

allometric regression models between above ground biomass and reflectance variables captured

by the SPOT satellite. In the on-going monitoring these models are used to estimate changes in

biomass variables for updated satellite imagery. The base line study came up with a standard error

of approximately 30 percent of the mean of the national biomass stock estimate (NBS 1998). The

project is currently involved in calculating changes in the biomass stock between the baseline

years (1996-1998) and the present (2000-2001). The NBS assesses the uncertainty range of this

result to be less than 10 percent (Personal communication with Paul Drichi on September 21,

2001).

The NBS project managers believe that with improved integration of sophisticated

measurement methods and better technologies (better models, better sampling techniques, better

knowledge of change processes and better satellite instruments) the error margins will continue to

drop without making the monitoring program more expensive. Currently, the NBS operates on an

annual budget of a mere US$ 400,000. The NBS project staff indicate that with a slight increase in

funding, the project would be able to acquire more fine resolution products and train more remote

7 The case study is based on secondary data and interviews with researchers associated with the forestry sector in Uganda. We are particular grateful for the informative input from Dr. Paul Drichi, Director of the National Biomass Study, Dr. John Kabogozza of Makerere University=s Forestry Department and Nathan Vogt, Research Assistant at the Center for the Study of Institutions, Population and Environmental Change (CIPEC) at Indiana University.

23

sensing analysts. These are two of the current bottlenecks that prevent the project from achieving

even more impressive results in the near future (Drichi 2001).

As diverse as the experiences of Russia and Uganda might be, both inventories

demonstrate the viability of the national inventory approach, if limited to the measurable stock of

above-ground, woody biomass. Key for both cases’ positive results has been their creative use of

remote sensing technology.

Discussion and Conclusions

This overview has considered the types of information that will be needed to implement a

national inventory approach to carbon sequestration and reviewed the instruments, both existing

and planned, that may be able to contribute to development of that information. It provides some

preliminary insights for the policy makers who must decide how to implement an international

carbon sink program. First, biomass and carbon estimates are based on models that correlate key

biophysical characteristics to biomass and carbon density. Remote sensing only provides the data

input for key independent variables for estimating carbon inventories. To develop national

inventories around the globe, it will be necessary first to expand considerably and improve upon

the available carbon models. This will require undertaking substantial field measurements and

research.

Second, no individual remote sensing instrument will provide all of the monitoring

information needed to run the models. It is likely that some combination of instruments including

optical, radar and Lidar instruments will be required. Nations will need to plan ahead to assure

that the instruments are deployed and available to provide the temporal and geographic scope of

coverage required.

Third, even when carbon inventory models are fully available for all forest types, there will

continue to be a need for various degrees of field measurements to ground-truth the models’

estimates. This will require a substantial international organization of technically trained foresters.

Fourth, an international carbon-trading program needs to establish normative guidelines

with acceptable remote sensing methods for carbon accounting. Apart from crucial local

information on time and place, such methods need to consider the availability of remote sensing

data and existing forest inventory capabilities in participating countries.

There are still several questions that will have to be examined as the international

community develops agreements on carbon sinks. First, there is a very real risk that the

24

uncertainty about the size of national carbon sinks, and the changes in those sinks, could

overwhelm the relatively accurate estimates of national carbon emissions from sources. It is

important to determine how precise the measurements of carbon stands need to be. A related

question is whether the optimal precision of measurements is determined by an economic

balancing of costs versus benefits of additional accuracy, or alternatively whether it must be

treated as a hierarchical issue where changes in carbon sinks should not even be included in the

national commitments if they can not be measured with a particular precision.

Second, countries will have to evaluate how much it will cost to achieve the needed

accuracy. The reason to include carbon sinks in a program of international commitments and

trading of emission quotas is that they represent a low-cost alternative to controlling atmospheric

concentrations of carbon through emissions limits alone. However, if the implementation costs,

including measurement and monitoring costs, are greater than the potential savings associated with

including carbon sinks in the trading and commitment regime, then there is no reason to expand

beyond a program based on sources alone.

Third, it is necessary to examine what kinds of physical and institutional infrastructure that

will be needed to implement a monitoring system capable of estimating national forest carbon

inventories on a regular basis. The discussion above suggests that existing configurations of

instruments and platforms may be inadequate to provide reliable estimates. It is likely that a new

satellite platform that integrates passive optical and multiple wavelength, polarimetric SAR may be

needed to accomplish the considerable task of gathering the data for the allometric models.

Further, the data from the new platform may need to be augmented with data from a LIDAR

instrument. Who will be responsible for operating and maintaining the new platform? What sort

of organizational arrangements will best serve the needs of the international community?

Fourth, the international body will have to determine for which types of forests and

geographic regions there are already adequate biomass models, and where it will be necessary to

develop new ones. How will those models be developed? Similarly, it is clear that no matter what

methods of estimation are used, it will be necessary to continue to provide ground-truthing or field

measurements. How will those measurements be implemented, by whom, and at what

frequency?

Finally, how will the program define forests for inclusion in the national inventory? It is

now obvious that the criterion for inclusion is that forests must meet a threshold for measurable

carbon. If the program cannot measure the carbon, then it cannot measure changes in carbon.

25

The problem is that the definition of what can be estimated with carbon models changes as

measurement technologies and methods improve. Moreover, the choice of where to focus

research in estimation methods will effect which countries and regions progress most quickly with

respect to these threshold issues.

26

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Appendix: Remote Sensing Instruments and Platforms

Optical Instruments - Passive Instrument Name Characteristics Availability of Historical Record Host Country

Landsat: TM, ETM+, MSS High resolution; TM & ETM+ spectral ~30m; MSS ~60m; TM thermal 120m; ETM panchromatic ~15m

MSS 1972; TM 1982; ETM+ 1999

USA

SPOT: HRV, HRVIR High resolution ~25m 1986- present France/Sweden/Belgium JERS-1: OPS; (JERS = Japanese Earth Resources Satellite)

High resolution 1992-1998 Japan

IRS: PAN, LISS, WiFS High resolution ~25m 1995-present India ADEOS: AVNIR High resolution 1996-1997 Japan CBERS: CCD and IR-MSS High resolution 1999-Present Brazil/China IKONOS High resolution 1999-Present USA EOS-AM: MODIS, ASTER, MISR Moderate resolution (Ahern and

Chen) MODIS is too rough to sense small parcel changes;

1999-Present USA/JAPAN

EO-1: ALI and Hyperion High resolution 2000 USA ALOS: AVNIR-2 and PRISM High resolution 2002 JAPAN NOAA: AVHRR Coarse resolution 1970’s-Present USA SPOT: VEGETATION Coarse resolution 1998-present France/EU/ Sweden/Belgium ERS: ATSR, ATSR-2; (ERS = Earth Resources Satellite)

Coarse resolution 1991-present Europe

ADEOS: OCTS Coarse resolution 1996-1997

Japan

CBERS: WFI Coarse resolution 1999-Present Brazil/China EOS-AM: MODIS Coarse resolution 1999-Present USA ADEOS-II: GLI Coarse resolution 2000 Japan ENVISAT: MERIS, AATSR Coarse resolution 2001 Europe

29

Appendix: Remote Sensing Instruments and Platforms (Continued)

Synthetic Aperture Radar (SAR) - Active Microwave Instrument Name Characteristics Availability of Historical Record Host Country

SEASAT L-band HH pol.; L-band = 24 cm wave length

1976 USA

SIR-A;B;C; SIR=Space Shuttle Imagaing Radar L-HH; L-HH;XLC 1981; 1984;1994 USA ALMAZ S-band HH pol 1992-1993 Russia ERS AMI (ERS-2)

C-band (short wavelength); VV pol; C band = 5 cm wave length

1991-present Europe

JERS-1 SAR L-band long wavelength; HH pol. 1992-1998; failed in 1998 Japan Radarsat-1 C-band; HH pol 1995-present Canada ENVISAT ASAR C-band polarimetric 2001 Europe Radarsat-2 C-band polarimetric 2001 Canada ALOS L-band polarimetric 2002 Japan LightSAR L-band CARABAS Aircraft-based SAR P-band - very

long wavelength; no space borne systems yet; 20-90 Mhz; P-band = 68 cm wavelength

BioSAR Aircraft-based SAR P-band - very long wavelength; no space borne systems yet; 80-120 Mhz

future/halted

CARABAS-II Moves the SAR down from P to VHF-band - Probably 30-47Mhz for large scale mapping, and 30-80 for ultra-wide; below 100 Mhz

Optical Laser (LIDAR) – Active

Instrument Name Characteristics Availability of Historical Record Host Country Vegetation Canopy LIDAR (VCL) Vertical resolution of 1-2 meters 2000 USA