New techniques give decision makers an edge |
| |||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
LARST Tools: Local Applications of Remote Sensing Techniques - Operational fire information systems |
||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
The Local Application of Remote Sensing Techniques (LARST) project has produced a variety of remote sensing tools to help decision makers plan for and monitor a huge range of environmental problems. They can also be used to provide early warning of threats to food security (like locust outbreaks), human and animal health (by predicting epidemic outbreaks), threats to forestry (like fire) as well as threats to water resources, and fisheries. Remote sensing techniques like these give decision makers the tools they need to properly design, implement and monitor new policies. The techniques are already in use around the world to solve a range of problems, from detecting fire risks in Nicaragua, Mexico and Botswana, to estimating rainfall and avoiding famine in Ethiopia. Project Ref: FRP35:
Research Programmes:
Relevant Research Projects:
Rationale: In many poor countries; decision makers with responsibility for natural resources often do not know what they could do (choices), nor what they should do (inadequate information) to improve matters. Shared information on the state of the problem is an essential component of environmental governance (i.e. collective management of the environment by and for the stakeholders). Consequently there is a need for better (thematic, timeliness and large coverage) environmental information to support a) design, implementation and monitoring of policies (particularly at regional and national level) and b) to support timely environmental monitoring for early warning and strategic response (particularly at provincial and local level), in the fields of food security, water resources, health, conservation, fisheries, forestry, etc. LARST outputs: LARST outputs were and still are critical for improving natural resources governance, through dissemination of suitable information to stakeholders for timely management response. LARST forestry is one element in a cluster of LARST outputs. The LARST approach (Local Application of Remote Sensing Techniques) aimed at:
We consider here the whole LARST cluster, as it will bring more opportunities for outputs to be used in a wider context. The main LARST tools and applications areas can be summarized as follows:
The LARST approach has been implemented in Africa, Central America and South-East Asia, essentially between 1990 and 2000. Outputs have included:
n/a
During the last 20 years, the world has evolved, and constraints have moved. For example:
The new challenges still include, for example, for many poor countries, the lack of relevant knowledge to adapt and integrate the information further into local practices, still too slow internet access to allow large data transfer. LARST outputs would benefit from being clustered/working in synergy with
Clustering with RNRRS: Given its cross-cutting nature, LARST approach could potentially benefit (but not necessarily cluster with) a number of outputs, including:
How the outputs were validated: Scientific/technical validation of algorithms for the extraction of relevant information (fire, vegetation, temperature, …) has taken place in the framework of research, and often published in the scientific literature. It is important to appreciate that the LARST approach was breaking new grounds 20 years ago, contributing to raising the awareness and knowledge on the potential available through new technologies to support appropriately and cost effectively decision making in country. Although difficult to demonstrate, we believe that LARST activities have been a pillar in the international community in improving near-real time access to useful earth observation information. While there has been limited systematic validation exercise of the various LARST outputs, according to RIUP validation definition, there is evidence showing the interest in the tools and products developed, as illustrated in the following section. Where the Outputs were Validated: Fire Information System – MARENA (Ministry of Environment and Natural Resources – Forestry department) – Managua – Nicaragua: During the first season, 1996, LARST fire information detected many more fires than the forestry department believed possible. While these figures were unwanted (and denied) by the latter, they were welcomed by local ecologists and environmentalists aware of the real situation on the ground. An independent assessment demonstrated that the satellite monitoring information provided the best estimate of fire occurrence nationwide. Since then the system has been used operationally to serve many departments, at local, regional and national levels, both in Nicaragua and in several Central American countries. Information received early in 2006 indicated that the LARST system was still in use, some 9 years after the end of the project [1]. Rainfall Estimation for Malaria prediction– Health Centre – of Niono – Mali: In this semi-endemic region, malaria transmission essentially varies according to the level of temperature and water (mosquito breeding). A system was developed and installed to forecast malaria epidemics, based on the assessment of unusual rainfall events estimated using LARST remote sensing. A participatory evaluation workshop with health stakeholders from local to national level, produced approval and further improvements resulting in an efficient, user-friendly methodology, adapted to the Mali health system [2]. Fire Information System – Indonesia: the receiving stations that were positioned in the 1990s were vital in obtaining an overview and understanding of the nature of the fire problem, particularly based on the 1997/98 data. The EU, JICA and GTZ funded projects in Sumatra and Kalimantan, working together with the Indonesian Forestry Department, relied on these data in their recommendations for fire control and suppression. Overall, there has been in the last 20 years a steady increase in the number of institutions using earth observation data and information, and LARST type outputs, world wide, paying credit to the timeliness, usefulness and cost effectiveness of this sustainable information. [1] Bismarck Valdez M. (2006) ‘Informe sobre monitoreo de incendios forestales - satellite NOAA 2005’, Ministerio del Ambiente y los Recursos Naturales (MARENA) y Sistema Navional de Información Ambiental (SINIA), Managua, Nicaragua, 22p. [2] Flasse (2002) ‘Environmental Information for Malaria Control: Malaria control support system in Mali – participatory workshop’ Flasse Consulting, 27p. Who are the Users? There are many users for LARST type outputs, at all levels, from ministers to local communities. For example, the fire information is used to influence decision-making on crew movement on the ground and for recommendations to political officials, agencies, and institutions as well as specific procedural direction to districts and other land management agencies dealing with fire management and policies. Where the outputs have been used: LARST type tools and information usage has increased over the years, whether used as developed during the 90’s, or in derivative form using new satellite data, improved algorithms, and better communication channels. Here are some examples: Drought assessment – rainfall estimates in Ethiopia: Ethiopia uses the LARST approach to produce timely rainfall estimates in its early warning system, which in 2002-2003 enabled famine mitigation measures to be put in place before drought-related disaster became critical. This resulted in food aid being delivered to communities in the affected area before they abandoned their villages, saving many lives, as well as livelihoods. As a consequence, there is demand to improve the system to cover the whole country sufficient for use in decision making at district level. Fire information systems are used for example in Nicaragua (see above), in Mexico (Comisión Nacional para el Conocimiento y Uso de la Biodiversidad) [3], in Botswana [4] and in South Africa as near real time fire fighting tools [5]. Vegetation Productivity Indicator: A LARST approach giving important early indications on the type of productivity season compared to the norm is currently being used by various initiatives, such as SADC GeoNetwork [6] and EC crop monitoring bulletins world wide [7]. Locust monitoring using satellites: many locust affected Sahelian countries access this service for vegetation and rainfall map to assist their routine locust control operations [8]. Locust outbreak prediction in South Africa: LARST vegetation status and rainfall estimation are being used by the South African Agricultural Research Council, Institute for Soil, Climate and Water, working in close collaboration with locust control units, to predict plague outbreaks, one of which has just been predicted in the last months, and recently the number of locusts has been increasing rapidly.
Scale of Current Use: Earth observation data, when timely accessed and integrated into decision makers’ practices are invaluable. With the awareness of its potential and the increase in thematic products, there is an increasing demand and rare are the countries not relying, in one way or another, on such information. The quality and appropriateness of products vary, and can only be effective when adapted to the needs in synergy with increased knowledge transfer to allow their appropriate usage. Lessons Learned and Uptake Pathways Promotion of Outputs: The EC (Development) were very impressed with impact from the LARST approach and (among others) developed a programme to make LARST type techniques available in every country in Africa. Called MTAP/PUMA this 11M€ programme installed hardware and software in all countries in Africa, but ran out of time before they could get the LARST applications operational. The follow-on 21M€ AMESD programme will continue some of the dissemination work, but will work mainly at regional and continental level where environmental governance is weakest. These actions, together with the US supported Food Early Warning System (FEWS), play an important role in i) continuous awareness raising on problems arising, and ii) ensuring sustainable access and use of environmental information. Potential Barriers Preventing Adoption of Outputs: All the usual problems that one gets when working with under-resourced government departments, including the brain drain. How to Overcome Barriers to Adoption of Outputs: These barriers reduce as countries get wealthier. Lessons Learned: Keep plugging away especially on knowledge management for decision makers. We worked in Ethiopia in the early 90’s. Ten years later they had developed the response capability to be able to make use of the information properly, and consequently saved so many lives and livelihoods. It takes time for institutions to evolve new working practices when faced with completely new kinds of information. Poverty Impact Studies: Benefits from the use of information from satellites, as in the LARST approach, are usually derived from improved decisions in local/national departments,. These range from improved local irrigation, to prediction of malaria epidemics, via better informed management of the natural resources, all impacting on people’s lives and livelihoods. There has not been, to our knowledge, any independent evaluation of the indirect impact on poverty. Direct and Indirect Environmental Benefits: LARST generates information in cost effective ways, using existing satellites. The environmental impact from better environmental governance using LARST type information to improve decision making, is expected to be strongly positive in the short, medium and long term. Adverse Environmental Impacts: None Coping with the Effects of Climate Change, or Risk from Natural Disasters: The ability to use satellite data in cost effective ways will assist with knowledge management, especially for decision makers, and as a result will assist in coping with effects of climate change. See also under Description and the Annex LARST Forestry / LARST TOOLS Introduction: LARST Forestry, and LARST outputs in general, are not typical RNRRS research outputs, partly due to their multi-theme applications, i.e. cross-cutting focus, and their technical characteristics and wide geographical applications. While we have tried to fill the Proforma questionnaire as best as we could, we felt important to extract the essence of LARST tools output and potential. Using the general structure of the Proforma, it is presented here, in the next 4 pages. Summary Description of the research output(s) Rationale: In many poor countries, decision makers with responsibility for natural resources often do not know what they could do (choices), nor what they should do (inadequate information) to improve matters. Shared information on the state of the problem is an essential component of environmental governance (i.e. collective management of the environment by and for the stakeholders). Consequently there is a need for better (thematic, timeliness and large coverage) environmental information a) to support design, implementation and monitoring of policies (particularly at regional and national level) and b) to support timely environmental monitoring for early warning and strategic response (particularly at provincial and local level), in the fields of food security, water resources, health, conservation, fisheries, forestry, etc. LARST outputs: LARST outputs were and still are critical for improving natural resources governance, through dissemination of suitable information to stakeholders for timely management response. LARST forestry is one element in a cluster of LARST outputs. The LARST approach (Local Application of Remote Sensing Techniques) aimed at:
We consider here the whole LARST cluster, as it will bring more opportunities for outputs to be used in a wider context. The main LARST tools and applications areas can be summarized as follows:
Validation (examples) of the research output(s) Fire Information System – MARENA (Ministry of Environment and Natural Resources – Forestry department) – Managua – Nicaragua: During the first season, 1996, LARST fire information detected many more fires than the forestry department believed possible. While these figures were initially unwanted (and denied) by the latter, they were welcomed by local ecologists and environmentalists aware of the real situation on the ground. An independent assessment demonstrated that the satellite monitoring information provided the best estimate of fire occurrence nationwide. Since then the system has been used operationally to serve many departments, at local, regional and national level, both in Nicaraguan and several Central American countries. Information received early in 2006 indicated that the LARST system was still in use, some 9 years after the end of the project. Rainfall Estimation for Malaria prediction– Health Centre of Niono – Mali: In this semi-endemic region, malaria transmission essentially varies according to the level of temperature and water (mosquito breeding). A system was developed and installed to forecast malaria epidemics, based on the assessment of unusual rainfall events estimated using LARST remote sensing. A participatory evaluation workshop with health stakeholders from local to national level produced approval and further improvements resulting in an efficient, user-friendly methodology, adapted to the Mali health system. (examples) LARST type tools and information usage has increased over the years, whether used as developed during the 90’s, or in derivative form using new satellite data, improved algorithms, and better communication channels. Here are some examples: Drought assessment – rainfall estimates in Ethiopia: The National Meteorological Services use the LARST approach to produce timely rainfall estimates in its early warning system, which in 2002-2003 enabled famine mitigation measures to be put in place before drought-related disaster became critical. This resulted in food aid being delivered to communities in the affected area before they abandoned their villages, saving many lives, as well as livelihoods. As a consequence, there is demand to improve the system to cover the whole country sufficient for use in decision making at district level. Fire information systems are used for example in Nicaragua (see above), in Mexico (Comisión Nacional para el Conocimiento y Uso de la Biodiversidad), in Botswana and in South Africa as near real time fire fighting tools. Vegetation Productivity Indicator: A LARST approach giving important early indications on the type of productivity season compared to the norm is currently being used by various initiatives, such as SADC GeoNetwork and EC crop monitoring bulletins world wide. Locust monitoring using satellites: many locust affected Sahelian countries access this service for vegetation and rainfall map to assist their routine locust control operations. The EC (Development) were very impressed with impact from the LARST approach and (among others) developed a programme to make LARST type techniques available in every country in Africa. Called MTAP/PUMA this 11M€ programme installed hardware and software in all countries in Africa, but ran out of time before they could get the LARST applications operational. The follow-on 21M€ AMESD programme will continue some of the dissemination work, but will work mainly at regional and continental level where environmental governance is weakest. These actions, together with the US supported Food Early Warning System (FEWS), play an important role in i) continuous awareness raising on problems arising, and ii) ensuring sustainable access and use of environmental information. Benefits from the use of information from satellites, as in the LARST approach, are usually derived from improved decisions in local/national departments. These range from improved local irrigation to prediction of malaria epidemics, via better informed management of the natural resources, all impacting on people’s lives and livelihoods. There has not been, to our knowledge, any independent evaluation of the indirect impact on poverty. Extreme poverty is often associated with ‘marginal’ environments, where livelihoods are strongly dependent on climate variability. Climate variability is expected to increase with climate change. There is therefore great need to improve climate risk management in such countries. LARST provides tools for tracking many seasonal resource changes, providing good early warning for preparedness and response, so reducing impact from (e.g.) droughts or floods. In addition, there is a rapidly growing need to cope with climate change and its impact on natural resource based livelihoods. Managing climate variability will become even more important under a changing climate. It is imperative that we make best use of the tools that we already possess, to improve food security for the remote rural poor especially in the poorest countries. In relation to Africa, other actions have gone some way to take LARST approach further.
An example of how LARST tools contribute to environmental governance: Contribution to Forestry Governance using LARST Fire information tools. At National Scale: LARST shows the extent of the overall forest fire problem (where, when and how much is burned each year): useful information for developing policy on forest fire reduction/prevention, where required. At Provincial or district scale: LARST helps planning by prioritising problem fire areas for response and then provides early warning with seasonal risk for preparedness and actions to prevent/control fires and protect important resources. At local scale: LARST shows fire risk and where fires are burning now for appropriate response. M&E: trends in fires and burned area (as above) shows where policies, plans and practices have been effective, and where not. As an indicator, detected fires indicate the presence of people, and can be used in protected area management to show where protection is needed now/ soon/working well, etc. Similarly, it can help identify logging concessionaires using fire to drive away the poor denizens of the forest. Potential poverty impact assumptions While in any LARST type project there is a large component of knowledge transfer and capacity building, the main unknown is the exact way in which stakeholders will choose to use the new information. Where environmental governance is well developed, the information is extremely useful for identifying problem areas in real time. Where environmental governance is immature, LARST type techniques provide information indicating the scale and nature of problems and the need for governance structures to be developed. LARST generates information in cost effective ways, using existing satellites. The environmental impact from better environmental governance using LARST type information to improve decision making, is expected to be strongly positive in the short, medium and long term. Annex 1. Acronyms AMESD African Monitoring of Environment for Sustainable Development BRIMP Botswana Rangeland Inventory Monitoring Project CCAA Climate Change Adaptation in Africa DFID Department for International Development EC European Commission EU European Union EUMETCast EUMETSAT's Broadcast Service for Environmental Data FAO Food and Agriculture Organisation of the United Nations FEWS Famine Early Warning System GIS Geographical Information System GTZ German International Cooperation for Sustainable Development ICOSAMP Information Core for Southern African Migrant Pests JICA Japan International Cooperation Agency JRC Joint Research Centre LARST Local Applications of Remote Sensing Techniques MARENA Ministerio del Ambiente y Recursos Naturales MTAP Meteorological Transition in Africa Project PUMA Preparation for the Use of MSG in Africa RNRRS Renewable Natural Resources Research Strategy SADC Southern Africa Development Community Relevant Research Projects,
with links to the
|
For relevant research projects, with links to further information
|
|||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||||
