The Function of Remote Sensing in Support of Environmental Policy

Abstract

Limited awareness of environmental remote sensing’s potential ability to support environmental policy development constrains the technology’s utilization. This paper reviews the potential of earth observation from the perspective of environmental policy. A literature review of “remote sensing and policy” revealed that while the number of publications in this field increased almost twice as rapidly as that of remote sensing literature as a whole (15.3 versus 8.8% yr−1), there is apparently little academic interest in the societal contribution of environmental remote sensing. This is because none of the more than 300 peer reviewed papers described actual policy support. This paper describes and discusses the potential, actual support, and limitations of earth observation with respect to supporting the various stages of environmental policy development. Examples are given of the use of remote sensing in problem identification and policy formulation, policy implementation, and policy control and evaluation. While initially, remote sensing contributed primarily to the identification of environmental problems and policy implementation, more recently, interest expanded to applications in policy control and evaluation. The paper concludes that the potential of earth observation to control and evaluate, and thus assess the efficiency and effectiveness of policy, offers the possibility of strengthening governance.

Full text

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Remote Sensing 2010, 2, 1731-1750; doi:10.3390/rs2071731

Remote Sensing
ISSN 2072-4292
www.mdpi.com/journal/remotesensing
Article
The Function of Remote Sensing in Support of Environmental
Policy
Jan de Leeuw 1,2,*, Yola Georgiadou 2, Norman Kerle 2, Alfred de Gier 2, Yoshio Inoue 3,
Jelle Ferwerda 2, Maarten Smies 4 and Davaa Narantuya 5
1 International Livestock Research Institute (ILRI), Nairobi, Kenya
2 ITC, University of Twente, Enschede, The Netherlands; E-Mails: georgiadou@itc.nl (Y.G.);
kerle@itc.nl (N.K.); degier@itc.nl (A.G.); j.g.ferwerda@utwente.nl (J.F.)
3 NIAES, Ecosystem Research Group, Tsukuba, Japan; E-Mail: yinoue@affrc.go.jp
4 Frogs International Environmental Management and Consultancy, The Hague, The Netherlands; E-
Mail: maarten@smies.org
5 Ministry of Environment, Ulan Bataar, Mongolia; E-Mail: dnarantuya@yahoo.co.uk
* Author to whom correspondence should be addressed; E-Mail: j.leeuw@cgiar.org;
Tel.: +254-20-422-4831.
Received: 20 May 2010; in revised form: 13 June 2010 / Accepted: 17 June 2010 /
Published: 12 July 2010

Abstract: Limited awareness of environmental remote sensing’s potential ability to
support environmental policy development constrains the technology’s utilization. This
paper reviews the potential of earth observation from the perspective of environmental
policy. A literature review of “remote sensing and policy” revealed that while the number
of publications in this field increased almost twice as rapidly as that of remote sensing
literature as a whole (15.3 versus 8.8% yr−1), there is apparently little academic interest in
the societal contribution of environmental remote sensing. This is because none of the
more than 300 peer reviewed papers described actual policy support. This paper describes
and discusses the potential, actual support, and limitations of earth observation with respect
to supporting the various stages of environmental policy development. Examples are given
of the use of remote sensing in problem identification and policy formulation, policy
implementation, and policy control and evaluation. While initially, remote sensing
contributed primarily to the identification of environmental problems and policy
implementation, more recently, interest expanded to applications in policy control and
evaluation. The paper concludes that the potential of earth observation to control and
OPEN ACCESS

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evaluate, and thus assess the efficiency and effectiveness of policy, offers the possibility of
strengthening governance.
Keywords: earth observation; remote sensing; environment; policy; governance

1. Introduction
Remotely sensed earth observation (EO) has revolutionized our understanding of our dynamic
environment. The array of remotely sensed EO techniques expanded in the 1970s when digital satellite
borne imagery complemented aerial photography, which had been available since the early 20th
century. Today, the number of EO systems designed to observe and monitor environmental processes
is large and continues to grow. Government support for this is strong, as many environmental remote
sensing systems are publicly funded, and an increasing number of countries invest in
EO infrastructure.
Environmental concern is a major driver for the public support to earth observation. The reverse is
true as well; EO stimulates environmental awareness and concern. In An Inconvenient Truth, Gore [1]
describes how a single image of the earth, taken in December 1968 by a crew member of the Apollo 8
mission, “exploded into the consciousness of mankind. In fact, within two years of this picture being
taken, the modern environmental movement was born. The Clean Air Act, the Clean Water Act, the
Natural Environmental Policy Act, and the first Earth Day all came about within a few years of this
picture being seen for the first time”.
Satellite borne remote sensing and modern environmental policy thus came of age at the same time.
The launch of the first Landsat satellite in the early 1970s coincided with the development of the first
environmental policies, and the subsequently established environmental protection agencies created the
initial demand for environmental EO products.
Following an increase of Landsat applications in the 1970s, in the early 1980s, the question was
raised whether the market could recover the costs of earth observation. The Landsat program, which
was commercialized in 1982 (a decision reversed in 1992 for military reasons) resulted in a fall back of
the utilization of and the non military societal benefits obtained from remote
sensing [2]. Since then, the debate has continued between proponents of commercialization and those
arguing that the societal benefits of environmental EO merit continuing public support.
Commercialization of environmental EO assumes that viable markets exist. The demand for
environmental EO, however, depends considerably on policy and market opportunities, and should
thus be considered in the context of societal demand and the policies the EO serves. The countries
represented in the Group on Earth Observation (GEO) recognized this dependency on societal demand,
while agreeing in February 2005 to develop a Global Earth Observation System of Systems (GEOSS).
This initiative aims to develop the societal benefits of EO in nine specific benefit areas [3,4].
A systematic insight in, and awareness of, how remote sensing may contribute to environmental
policy can help to enlarge the societal demand for EO applications. However, existing reviews of
environmental EO applications are structured according to products, techniques, or benefit areas, rather
than the function they have, with respect to the policy they support. In this paper, we review the

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potential, actual contribution, and limitations of EO from the perspective of their support for
environmental policy.
2. Environmental Policy
Good governance requires effective and efficient policies. Policies, in turn, require information to
assess the need and urgency to develop policy, to mobilize instruments for implementation, to control
and enforce proper execution, and to monitor and evaluate policy effects. Lack of information, which
previously may have hampered the efficiency and effectiveness of policies, is rapidly overcome, while
emerging information techniques change the practice of environmental policy [5]. Hence, given this
changing technical arena and our ambition to better understand the relation between EO and policy, it
would be interesting to consider the contribution of remote sensing from a functional perspective; in
other words, how does remote sensing contribute towards enhancing the effectiveness and efficiency
of environmental policies?
Several policy models have sought to unravel the policy making process in a number of
phases [6]. In this paper, we use the policy cycle to review the potential and actual use of remote
sensing in support of environmental policy.
Several policy scientists have criticized the policy cycle approach. They point out that policy is
rarely the product of an orderly sequence of stages (or steps in the cycle), where a problem is defined,
alternative solutions are analyzed, the best solution is selected and implemented by the executive
branch, and later evaluated and revised accordingly, as if on conveyor belt [7]. Sabatier’s [8]
assessment of the policy cycle heuristic consists of several criticisms, including the lack of causal
drivers that govern the policy process within and across stages, the top-down legalistic bias, and the
bracketing-out of multiple levels of government involved. However, the popularity of the policy cycle
metaphor continues unabated because it allows us to analyze the complexities of the real world [9]. For
the purposes of this research, the policy cycle is particularly useful because it helps the matching of
information needs and gaps with stages in the policy cycle. Thus, the cycle helps with the alignment of
remote sensing information technology with the policies underlying environmental management.
Following Esty [5], we divide the policy process into a series of stages—in this case, problem
identification and the formulation, implementation, control, and evaluation of policy (Figure 1). We
use this structure to review the function of EO in supporting these various parts of the policy cycle,
while surveying not only the potential and current use of remote sensing, data gaps, and knowledge
deficiencies, but also governance questions.

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Figure 1. Scheme of a policy cycle.

3. Problem Identification
Revenga [10] argues that EO has the potential to assess the necessity of developing policy. There
are however, few publicly available documented cases describing how remote sensing influenced
actual policy development. The detection of the ozone hole is probably the best documented example
of EO triggering policy development [11]. Concern about the detrimental effect of chlorofluorocarbons
(CFCs) on the ozone layer [12] stimulated the US Congress to commission NASA to develop a sensor
(TOMS) to monitor the state of the ozone layer. The sensor, launched in 1978 on-board the NIMBUS
satellite, did not report any anomalies until 1986, when NASA confirmed (Figure 2) that the deepening
and enlargement of the size of the ozone hole had indeed occurred since the late 1970s [13]. This
confirmation, based on re-analysis of the TOMS data, responded to a paper one year earlier, which
woke up the world by reporting a steady decline of spring ozone concentrations over one British
Antarctic Survey research station [14]. In response to these findings, the 1987 Montreal Protocol [15]
prescribed a 50% reduction, and four years later, a complete ban on the use of hard CFCs.
Figure 2. Size and depth (Dobson units) of the ozone hole in October of 1979, 1982, and
1985, as detected by TOMS [16].

IMPLEMENT
EVALUATE
CONTROL
PROBLEM
FORMULATE
POLICY
CYCLE

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What was new in the remote sensing data? After all, the British Antarctic Survey reported earlier a
reduction in spring ozone concentration over their Antarctic research station. The remote sensing
confirmed that this record from a single station was not an anomaly, and revealed the size and depth of
the hole more convincingly than an entire array of ground based sensors could.
Recognition of environmental problems is frequently confirmed, but rarely initiated by earth
observation; other sources of information generally precede quantification by earth observation. For
example, the recent remotely sensed detection of increased water turbidity due to dredging (Figure 3)
in Northern Poyang Lake, China [17], which was followed by a ban on sand mining, was preceded by
reports expressing concern about the impacts of dredging [18,19]. The findings of Wu et al. [17],
however, which quantified the extent of the problem, and which had been communicated to provincial
government officials half a year before the ban, probably placed the issue higher on the
political agenda.
Figure 3. Water turbidity (blue = clear, white = turbid) and distribution of vessels (red
dots) in Northern Poyang Lake, China (Courtesy Wu Guofeng).

Apart from these examples, few other sources attribute the formulation of environmental policy to
remote sensing. Presumably, this is because the diffuse nature of the process leading to policy
formulation makes it difficult to assess the precise contribution of EO. Remote sensing contributes,
however, increasingly to high level influential policy studies. One example is the FAO’s global Forest
Resource Assessments [20], which, while based on reports from national forest surveys, have a
separate remote sensing survey since the 1990s, as a complement to the main assessment report. Other
examples of policy relevant information from EO include the recent assessments of the rate of polar
sea ice cover reduction [21] and the melting of the Arctic [22] and Antarctic ice caps and the Third and
Fourth Assessment Reports of the Intergovernmental Panel on Climate Change [23,24]. Through these
channels, remote sensing contributed without doubt to the development of policies on climate change
adaptation and mitigation, deforestation, and trade in forest products.
It will be clear that earth observation infrastructure and products, such as satellites, imaging devices,
and imagery, are required to enable the support of international policies, and there have been various
initiatives to assess the needs and existing capacity. For example, the second report on the adequacy of
the global observing systems for climate in support of the UNFCCC [25], which identified that climate
observation systems were not adequate, led to a stronger commitment of governments to address these
inadequacies and to produce a true global climate observing infrastructure.

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The function of remote sensing in this phase can thus be resumed as providing information for
scrutinizing the necessity to address environmental problems. As indicated above, remote sensing does
not champion in initiating problem recognition. Remote sensing has however, unrivalled potential in
verifying objectively whether problems exist, and to assess their extent and magnitude synoptically
across a range of scales. Additionally, with the gradual construction of the remotely sensed archive,
remote sensing can make assessments over longer time periods than most other data collection
techniques could.
4. Policy Implementation
Current environmental policy literature distinguishes between traditional regulatory instruments,
where the nation state or a union of states (e.g., European Union) specifies the goal to be achieved and
how, and new environmental policy instruments (so-called NEPIs), which delegate substantial
regulatory power to non-state actors [26]. Here we consider traditional regulatory policy instruments
including, for example, (i) legislation specifying the liability for environmental damage, (ii) spatial
planning, (iii) environmental impact assessment, (iv) financial instruments, and (v) disaster risk
management, all of which are specified by state actors or unions of states. How can these policy
instruments be supported by remote sensing, and what are the strengths and limitations of this support?
4.1. Legislation
The implementation of environmental legislation creates demand for EO. The ESA website of
successful EO products [27] describes, for example, how a remote sensing company supplies radar
based measurement of subsidence to assist an oil company to decide how much water to inject to
counter the downward movement. At first, this might be perceived as a case where the demand for EO
emerges from the private market in the form of an oil company contracting the EO industry. The
demand for EO, however, emerges because legislation stimulates oil companies to avoid subsidence
related damage claims.
Environmental legislation and liability for damage stimulate demand for EO also as a result of
development of corporate environmental policy. The introduction of ISO 14001 in 1996 facilitated the
implementation of environmental management in company operations. This ISO standard allows
companies to certify that they conform, and ensure compliance with environmental laws and
regulations. Remote sensing could support implementation of the ISO standards, for example, as
follows. Most countries use “normal oilfield practice” as a condition for (exploration and) production
concessions, which implies that the concession holder returns the concession in its original condition
(i.e., before oilfield development started) once production ceases. In the 1990s, Shell used remote
sensing to establish the baseline situation for oil and gas development projects in Russia. Historic RS
data may be used to establish an environmental baseline retrospectively, in cases where oilfields are
being abandoned without an available environmental baseline that is reliable. Remote sensing
continues to be underused in establishing environmental baselines and in supporting corporate
environmental policy.

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4.2. Spatial Planning
While GIS is the primary analytical platform for spatial planning, remote sensing plays an important
subsidiary role. Remote sensing (including aerial photography) can supply baseline information for
land-use and other forms of spatial planning in areas where maps are not available, such as in
developing countries [28]. Remote sensing also fills a gap in areas with a mapping record by providing
the data to update maps, because planning starts with a review of the current situation, which cannot be
assessed from outdated maps. The legal implications of the accuracy of the information used in
planning might further require currency of information. Comparison with historic remote sensing
imagery is frequently used to analyze environmental change to understand those trends requiring
consideration from a policy perspective. Finally, remote sensing is used as an input for the modelling
of alternative land use options (e.g., agriculture or biological conservation). Hence, remote sensing
contributes to the improvement of spatial planning in a variety of ways.
4.3. Environmental Impact Assessment
Environmental impact assessment (EIA) is “the process of identifying, predicting, evaluating, and
mitigating biophysical, social, and other effects of development proposals prior to major decisions
being taken and commitments made” [29]. Nowadays, EIA is compulsory and is included in the
environmental legislation of most countries. Increasingly, environmental impacts are considered in
their spatial context, while visually assessing the spatial implications and expected impacts of a
number of alternative scenarios [30]. EIA in general, and spatially explicit EIA in particular, require
reliable and up to date spatial information, because EIAs consider specific and localized development
activities, such as the construction of roads or the opening of mines, the impact of which varies
spatially. Remote sensing contributes to this, while it allows the updating of the baseline spatial
information, such as vegetation and land use, to the current status [31].
4.4. Financial Instruments
Financial policy instruments include subsidies, taxation, and direct interventions. In 2010, €43
billion will go, for example, to farmers in the European Union as direct income support. Farmers are
eligible to these subsidies if they maintain their land in good agricultural and environmental condition,
and comply with standards on public, plant and animal health, and animal welfare. Payment eligibility
is the responsibility of the EU member states, for which each country needs an Integrated
Administration and Control System, including a land Parcel Identification System (LPIS). The LPIS
provides a unique identifier to each land parcel and its owner (the claimant), and is used to register
applications for the subsidies and payments made. The development, update, and revision of the LPIS,
which can be based on existing maps and documents from national land registers, is increasingly based
on high resolution aerial photography and satellite imagery.
The use of EO in beach nourishment [32] is another example of remote sensing supporting the
implementation of a direct financial intervention in the Netherlands [33]. Beach nourishment aims to
restore the coastal protection offered by dunes and beaches weakened by shore erosion. Airborne laser
altimetry is used to estimate the volume of sand required for beach nourishment by measuring the

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elevation of the dry parts of the beach; sonar is used for the underwater parts (Figure 4). This
information is used to direct the companies contracted to nourish the beaches. Maintenance of coastal
defence lines is a task of the central government (Ministry of Public Works), which uses a financial
instrument to achieve its policy objective of improving coastal defence through beach nourishment.
EO contributes to the efficacy and efficiency of achieving this policy, while assessing the volume of
sand required.
Figure 4. Laser altimetry and sonar bathymetry used to measure beach elevation is used to
estimate the volume of sand required to restore the coastal defence function of the beach
(Courtesy D. van der Vlag, [33]).

Financial instruments also trigger the use of EO in the context of the Kyoto protocol, which requires
reliable and transparent approaches for the estimation of carbon stocks and for the emission and
removal of greenhouse gases from agriculture, forestry, and other land uses. The use of remote sensing
has been advised to support the accounting of carbon credits, while assessing carbon stocks, carbon
sequestration by vegetation [34,35], and the implementation of payments under the REDD+
(Reduction of Emissions from Deforestation and Forest Degradation) policy [36], which is currently
under discussion.
4.5. Disaster Risk Management
Given the spatial, and frequently dynamic nature of all aspects of disaster risk (hazard, elements at
risk, vulnerability, disaster risk, and disasters) and also of the commonly considered phases of the
disaster cycle (mitigation, preparedness, early warning, response, and recovery), remote sensing is
superbly suited to study and monitor disaster risk [37]. This, however, does not happen in a policy
context that is always equally well established. Hazard and risk assessment are increasingly part of
urban and regional planning policies, with spatial analysis, frequently supported by remote sensing
data, serving to assess the probability of loss in a given area and for given time periods due to
environmental hazards. In particular, policies designed to limit losses due to floods or wildfires are
employed and aided by RS data [38,39]. Remote sensing has also become a critical tool for hazard
types that are more difficult to assess, such as seismic hazards. By providing detailed information on
the hazard’s spatio-temporal characteristics, remote sensing not only supports implementation of
policies aimed at loss reduction, such as requirements for adequate construction standards or no-build
zones, but also for such policies to be defined in detail in the first place.

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While RS-based response to natural disasters is naturally ad hoc and case-driven, a policy
framework for international support to disaster response based in satellite imagery has been developed.
The International Charter “Space and Major Disasters”, established in 1999, provides for rapid image
acquisition and damage map production, and is widely seen as a successful example of international
cooperation. However, while the Charter operates within the framework of Space Law, i.e., the legally
binding Outer Space Treaty, and the United Nations’ non-binding Remote Sensing Principles, it
employs a best-effort approach with no legal binding, and no liability is assumed for the resulting
mapping products [40].
5. Policy Control
5.1. Policy Enforcement
RS information is increasingly used in policy control, with the purpose of enforcing policy and
promoting compliance to regulations, as well as to detecting and avoiding fraud. Examples showing
the potential of remote sensing in verifying compliance to regulations on an ad hoc basis include
control on illegal drugs production[41], land use impacts on protected areas [42], illegal logging [43],
and urban sprawl in China [44]. More recently, dedicated operational applications have been
developed to control illegal marine fisheries [45] and marine oil spills [46,47].
5.2. Fraud
Earth observation is used in environmental policy control in agriculture [48]. While the EU, as
explained in Section 4.4, subsidizes farmers, its member states are obliged to check and report
compliance to regulations under the EU Common Agricultural Policy (CAP). The EU supports
individual member states in implementing information systems that combine remote sensing and land
parcel based information for the purpose of cross checking whether received subsidies comply with
EU regulations. Pedersen [49] gives a detailed description of the use of remote sensing in crop subsidy
control in Denmark. While initially developed to detect subsidy fraud, the CAP system has recently
been expanded to also include compliance with environmental directives. Remote sensing is also used
to detect fraud related to the Federal Crop Insurance Program set up by the US Department of
Agriculture, which supports farmers in overcoming drought risks [50].
5.3. Compliance to International Treaties
It has been recognized since the mid 1990s [51] that EO has the potential to verify compliance
toward international treaties [52-54], and increasingly, EO is used by governments in implementing
their commitments to these treaties, while controlling and demonstrating their compliance. Remote
sensing is also increasingly used by treaties to verify compliance of contracting and non-contracting
parties, such as, for example, the treaty to restrict the proliferation of nuclear weapons [55]. Remotely
sensed evidence of non-compliance has been used to mobilize signatories of this treaty to increase
political pressure for the enforced compliance of non-compliant states.
More recently, interest has increased in the application of EO to enforce compliance with
international environmental treaties, such as, for example, the Ramsar convention [56]. The application

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of remote sensing to enforce compliance with international environmental treaties, although
technically feasible, is not straightforward because these treaties typically lack a framework to enforce
compliance. Although RS alone cannot enforce compliance, since countries are sovereign to decide
whether to react, RS can be used as evidence in the case of non-compliance and in the dissemination of
remote sensing information that reveals lack of enforcement. This may increase pressure on
non-compliant parties to improve performance.
5.4. Legal Aspects and Potential of Remote Sensing
The use of RS imagery as a source of information to support non-compliance or fraud ultimately
requires admission of the remotely sensed information as evidence in court [57]. RS data’s
admissibility as evidence depends, amongst others factors, on the possibility of accurately detecting
fraud and non-compliance in the imagery. The advent of sub-meter resolution satellite imagery greatly
increased the potential of EO in policy control, as this allows for the accurate detection of indicators
that are either not, or only poorly, discernable with lower resolution imagery. Purdy [57] further
discusses the acceptance of EO as a source of evidence and privacy issues as barriers to the use of
satellite imagery in policy control.
The potential of EO in policy control has long been recognized [58] and Purdy [57] concludes that
the greatest use of remote sensing may lie in the field of compliance and enforcement. It is also our
impression that remote sensing has a much wider potential for application in policy control than has
been realized so far. It remains difficult, however, to assess the actual use and potential of this market.
While the use of satellite imagery has been prescribed as one of the ways to demonstrate compliance in
case of EU agricultural policy, and the ESA developed RS techniques which could be employed by
individual member states, it remains unclear to what extent remote sensing is being used for this
purpose in actual practice. One reason for this could be the aforementioned lack of publications
reporting on the actual use of earth observation, but it might also be a deliberate choice, as detailed
explanations on how RS is used in policy control might trigger control avoidance strategies.
The market of EO in control would appear very attractive when imagining that this would require
continuous monitoring. It is questionable, however, whether continuous monitoring would be required;
the rumour that remote sensing is used might affect behaviour such that incidental control would
suffice. No studies so far have been undertaken to assess how detection of fraud and non-compliance
by EO influences behaviour, and we suggest it would be interesting to study this.
6. Policy Evaluation
There are two main categories of purpose for policy evaluation [59]. The first is to evaluate whether
the intended goals for which a policy has been designed have been achieved. Related to this is the
desire to learn whether the chosen policy instruments have been effective. The second is to evaluate
the impacts of policy other than those it was designed (i.e., to assess possible unintended
consequences).

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6.1. Evaluating Achievement of Intended Impacts
Tian et al. [60] used a time series of remote sensing imagery to confirm whether objectives for
which a policy was designed were met, while confirming that the rate of urban growth, which was high
in the period between 1986 and 1999, slowed down after government policy aimed to reduce
expansion of the urban area into agricultural lands. These authors attribute the reported reduction in
urban expansion to this change in policy.
In case of the Montreal protocol, it is more difficult, based on remotely sensed information alone, to
attribute the observed stabilization of the ozone hole (Figure 5) to policy. It is the congruence of the
remote sensing record and predictions made by process based atmospheric chemistry models, which
strengthen the confidence that the stabilization is attributable to the ban on CFCs.
Figure 5. Stabilization of the springtime size (millions km2 7 September–13 October) of
the Antarctic ozone hole since the middle of the 1990s [16].
1,9701,9801,990
Year
2,000
0
10
20
30
Size ozone hole

The above example indicates that, while remote sensing allows for the detection of whether a
system changes as expected, it remains more difficult to attribute such change to policy impact. Impact
analysis assumes causation, the inference of which is complicated when using observational data, as is
frequently the case in remote sensing studies, rather than data from designed experiments. This
problem is common in ex post impact evaluation, and a number of analytical techniques have been
proposed to overcome this [61], such as, for example, BACI (before-after, control-impact)
designs [62]. The ability to attribute an outcome to the policy designed to achieve this outcome has
clear societal benefits; it allows the reconsideration and adaptation of the policy concerned and we
suggest that remote sensing, notwithstanding the above caveat, holds far more potential for ex post
policy impact assessment than so far explored.
6.2. Evaluating Unintentional Side Effects
Remote sensing also holds the potential for evaluating the unintended side effects that are inherent
to any policy. The dredging in Poyang Lake, for example, started in 2001 as a result of a policy to ban
sand mining on the Yangtze River, following frequent accidents between commercial navigation and

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dredging vessels [63]. This policy, which solved the problem of navigation on the Yangtze River,
resulted in increased water turbidity in northern Poyang Lake (Figure 3) as an unintended side effect.
Another example is the use of remote sensing to assess the land use efficiency and environmental
side effects of two rural development pathways in northern Argentina [64]. The observation that
government sponsored colonization programs were leading to the expansion of low productivity
agriculture at the expense of forest, while increased yields per hectare in areas with large market driven
soybean farming resulted in enhanced agricultural output on a reduced area, led Grau et al. [64] to
conclude that large scale market driven rural development better balanced nature conservation and
food production by having a significantly higher agricultural land use efficiency and, therefore,
allowing for more land to be retained for nature conservation.
Many policy driven interventions influence the space where these interventions are implemented.
The above examples indicate that remote sensing has the potential to evaluate such localized policy
side effects, and as such, to provide for the information required to reconsider and eventually
adapt policy.
7. A Review of Policy in the Remote Sensing Literature
While reviewing the above, it was noticed that most of the examples were published outside the
peer reviewed literature. This raised our interest in the question as to whether, and to what extent, peer
reviewed literature contributes to the debate on the policy support of remote sensing. We therefore
executed a literature search for papers on “remote sensing OR earth observation AND policy”
published from 1991 onwards [65], which retrieved 302 peer reviewed papers. The number of remote
sensing papers that refer to policy increased from 1991 to 2007 by 15.3% annually, which is
significantly higher (two sample t-test, t = 19.1, d.f. = 16, P < 0.001) than the 8.8% growth rate of the
remote sensing literature as a whole (Figure 6).
Figure 6. Trends in the total number of remote sensing papers (?) and number of RS
papers referring to policy (o) published between 1991 and 2007 as retrieved from
ISI records.
19901995200020052010
Year
1
10
100
1000
10000
Number of publications

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The trend displayed in Figure 6 suggests an increasing interest of the remote sensing community in
the relation between EO and policy. However, although all papers associated policy to remote sensing,
not a single of these 302 papers described the actual support of EO to a specific policy. Instead, the
majority of papers demonstrate or claim a potential of EO to support environmental policy. Other
papers relate EO to policy while considering policies to support the EO industry financially [66],
policies for the acquisition, access, and distribution of remote sensing data [4], or policies as an
explanatory variable in empirical research.
8. Discussion
Our review revealed that the various phases of environmental policy require up-to-date and synoptic
spatial information, at various spatial scales, on the state of the environment and the extent and
magnitude of environmental and policy impacts over larger areas. Earth observation is ideally suited
for this, as a large number of variables relevant to environmental policy, but by far not all, can be
detected remotely. Moreover, remote sensing permits repeated and consistent assessment and
monitoring of the environment; it allows independent control and its quality can be assessed. As such,
it is a tool with some very desirable characteristics for supporting environmental policy.
Why, given this potential, is remote sensing not used more widely? It has been stated frequently that
remote sensing may address user requirements more cost effectively than traditional environmental
information acquisition methods. Having the potential to be more cost effective, however, does not
automatically lead to utilization of remote sensing. It makes a difference whether the technology is
introduced in an existing or a new market; cost of market development might prohibit the opening of
new markets, while competition with vested interest might frustrate the introduction of remote sensing
in markets served by more traditional data capture methods. In these cases, one might consider [67]
suggestions to compare the costs and value of the information provided by remote sensing to
other techniques.
Apart from cost effectiveness, one also has to consider characteristics which determine the user’s
appreciation of the value of the information, such as its accuracy, reliability, consistency, and
timeliness of delivery. Increasing standards for accuracy, reliability, and consistency are important
fields of remote sensing research, as they increase the competitiveness of remote sensing products
relative to traditional earth and atmosphere based measurements. The importance of timeliness of
delivery in post hazard assessment has been stressed in drought [68], flood, and other hazard impact
assessments [69]. Timeliness of information delivery is also crucial in radar detection of illegal fishing
boats, as well as illegal oil spills, to allow the navy to intercept suspect vessels [45].
The examples given in this review confirm the picture that environmental policy creates a demand
for remote sensing. This has implications for the possibility of financing remote sensing applications,
as the opportunities for funding differ throughout the policy cycle. The best opportunities to acquire
financial support are within the policy implementation phase, because of the significant budgets
typically available for policy implementation. Likewise, it should be possible to mobilize budgets for
policy control from within operational interventions, as good governance requires a more proactive
attitude towards policy enforcement and control of fraud. Most examples of the use of EO for policy
evaluation, rather than being intentionally integrated into the implementation of running policy, appear

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to have been developed by interested researchers. Remote sensing, with the caveats given, has great
potential to evaluate policy, but budgets for policy evaluation are typically more difficult to acquire as
this evaluation tends to be “forgotten” when implementing policy. Evaluation is considered an integral
part of any policy cycle, and it is here that the effectiveness of governance could be assessed.
Financing from within existing policies is not straightforward for the problem identification function of
EO, as it precedes the implementation of policy and the release of the related budgets.
Considering the use of EO in a policy context made us realize how policy dependent EO is. There is
a potential for policy independent environmental EO applications, for example, in precision
agriculture [70] and insurances [71-73]. Apart from this, there are certainly possibilities for
commercialization within the context of environmental policies, particularly where budgets are
available from within operational policy interventions. From a societal perspective, however, there is a
need for those activities, which are more difficult to link to budgets within running policies, such as the
timely recognition of problems and the critical evaluation of policy outcomes. We suggest that
generous public funding should remain available to support those functions of EO which cannot be
covered from within operational environmental policy interventions.
In this review, we argue that the societal support for environmental remote sensing applications
relies strongly on the question of whether remote sensing addresses policy relevant issues. This is
because policies largely determine the demand for EO products. The major societal benefit EO could
make to environmental policy is to improve a policy’s effectiveness and efficiency. The review has
shown that remote sensing may contribute to this while supporting the need to address environmental
problems, to implement interventions to address these issues, to control whether policies are executed,
and to evaluate whether such policies influence the system as intended. It is interesting to note that
initially (in the 1970s and 1980s), remote sensing was used almost exclusively to identify problems
and contribute to the implementation of policy. More recently, interest also developed in applying
remote sensing in policy control and evaluation. It is information on these later parts of the policy
cycle which allows remote sensing to assess whether policy is effective. This assessment of the
effectiveness of a policy forms a crucial part of good governance, and we suggest that remote sensing
holds the potential to contribute to governance while filling this information gap.
Initially, those typically urging for policy development, the public and NGOs, had limited access to
remotely sensed information, since the technical expertise required to process satellite imagery was
restricted to state agencies. The proliferation of freely available satellite imagery and image processing
capacity has resulted in increased capacity outside government. This trend is further stimulated by the
availability of web-based information systems, such as Google Earth and Google Maps, which provide
users easy access to satellite imagery. Nowadays, researchers, as well as NGOs, apply RS to mobilize
support for cases requiring policy development, a process which has been called satellite imagery
activism [74]. The media play an important role here, while distributing remote sensing studies to wide
audiences. This enhances the effectiveness of the remote sensing information, because wider
awareness increases the demand for policy development.
Our literature review was focused on the specific search within those papers that dealt with earth
observation and environmental policy. If we turn to the wider policy literature, we find stark divisions
regarding the role of technical information (which includes remote sensing) in policy making. Policy
scholars are divided between those who express confidence in the capacity of bureaucratic circles to

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acquire and use high quality technical information by integrating the talents of large numbers of
technical specialists and those who “have frequently concluded that such information is often -and,
perhaps, primarily -used to legitimate decisions reached on other grounds, that is, prior to an
adequate analysis of the magnitude of the problem and the probable consequences of alternative
policies” [6]. For example, in spatial policy making, some assume geo-information to be an objective
and scientifically accurate resource, with the role of providing spatially relevant information to rational
decision making. Critics argue that geo-information and spatial policy do not have an unproblematic,
linear, and direct relationship [75]. In choosing between policy options, political arguments are more
salient than scientific arguments. “The question is not whether planning will reflect politics, but whose
politics it will reflect. What values and whose values will planners seek to implement?” [76]. However,
things are gradually changing. Remote sensing is now increasingly appearing in scholarly articles by
political scientists—notably the 2009 Nobel Prize winner Elinor Ostrom [77], who argues that the
study of complex ecosystems requires the conduct of “long-term research programs that use research
methods that focus at different temporal and spatial scales, such as time series remote images,
repeated on-the-ground social-ecological surveys of local stakeholders and their forests, and
experimental laboratory studies.”
Most papers reviewed in our literature search presented remote sensing techniques and claimed
their potential to support policy. Fewer papers linked to an actual policy, while even fewer related to a
specific part of the policy cycle. We are not aware of any peer reviewed papers analyzing the
contribution of remote sensing to specific policy. The limited interest in the contribution of EO to
environmental policy fits into a picture phrased by Quevauviller [78], who noticed while writing about
R&D research funded by the European Union, that ‘research to support any environmental policy
should be feeding the policy-making process directly’, but that ‘in many instances this is still far from
being the case’. Currently, other media, such as the Internet and professional non-peer reviewed
literature, disseminate experiences with respect to how EO applications support environmental policy.
Continued support for remote sensing depends however, on how well the remote sensing community
articulates and demonstrates the benefits of remotely sensed information to the public sake.
The GIS and remote sensing academic community have only recently started to conduct
cross-disciplinary research. Carton’s [79] research in deliberative spatial policy-making practices in
the Netherlands shows that the use of geo-information can resolve or deepen the conflict between
policy actors. Moody [80] argues that only part of the potential of GIS in policy formulation has been
reached, and it can be expected that more of this potential will be reached as GIS applications are used
more frequently. We suggest that the academic remote sensing community could deepen our insight in
the interaction between the EO and its societal context, and propose to consider bridging this gap,
while more explicitly stimulating scientific debate and research on this interaction.
This paper reviewed the use, potential, and limitations of remote sensing in support of
environmental policy. We highlighted how the contribution and limitations of remote sensing differ
between the various parts of a policy cycle in the anticipation that this insight will enable
policy-makers to appreciate the policy supporting potential of earth observation and the remote sensing
community to address, more effectively, the opportunities offered by environmental policy.