Context to the Post 2015 Framework for DRR and Sustainable Development Goals
The disaster managers from all over the World are looking forward to the World Conference on Disaster Risk Reduction (WCDRR) in Sendai, Japan, where great tsunami took place in 2011 (www.wcdrr.org). The conference is aimed to provide Post-2015 Framework for Disaster Risk Reduction and can set a greater resilience to disasters.
In this context, the momentum has gathered to highlight importance of ecosystems in disaster risk reduction and building resilience in a climate change. The space based information, being a perfect tool for analysing robustness of ecosystems, has a lot to contribute to the Post 2015 Framework for Disaster Risk Reduction and Sustainable Development Goals being defined by the United Nations. This article highlights needs to leverage space technology studying health of ecosystems and protecting ecosystems to play a greater role in disaster risk reduction in the context of changing climate.
Ecosystems, disaster and climate change resilience
Disasters and ecosystems are closely linked, although national disaster management organisations are yet to embrace ecosystems as an instrument for disaster risk reduction (DRR). It is not denied that worldwide the countries are investing in protecting its ecosystems; however, the actors involved in development remain unconcerned about ecosystems due to inadequate understanding of the connection between ecosystems and life threatening disasters. The moment we associates the ecosystems to disasters, the importance of ecosystem will be felt in a day to day life.
Climate change is now well accepted notion and one of important attributes of Ecosystem is its role in developing resilience in a changing climate. Thus, ecosystems are seen as an ‘instrument for disaster risk reduction’, as well as ‘means for building resilience in a changing climate’.
Well managed ecosystems and sustainable development (that ensures ecosystems are not harmed) leads to disaster resilient human settlements. Here are two examples that highlight importance of ecosystems in disaster risk reduction. (1) After a heavy storm broke over the region of Sachseln in Central Switzerland and vast volumes of water and mud destroyed the village of Sachseln, blocked transport network and buried extensive areas of fertile cultivated land; the Swiss Research Institute for Forest carried out studies and one of the conclusions is – there were ten times more landslides in locations with poor quality forest. (2) A massive disaster took place in 2013 in Uttarakhand State of India, which wiped out number of villages/towns and killed several thousand people, is devastating consequence of ignored ecosystems and engineering centred development. This shows that the lesson is yet to be learned in all part of the World.
Space based information for Ecosystem based DRR
The ecosystem does not mean mere existence of formations like forests, mangroves, coastal vegetation or physical structures such as sand dunes. It is essential to understand if those natural entities are indeed efficient ecosystems and play role in preventing disaster risks. This is where role of space based and geospatial information becomes vital in understanding ecosystems.
The space based information not only provides information on extent of ecosystems, but also provides much insight into dynamics of ecosystems, when analysed in conjunction with the field based information at all levels such as biospheres, biomes, landscape, ecosystems, habitats and communities. It is the only tool to monitor remote and difficult areas such as highlands and steep slopes, where role of ecosystem often critical. The information generated from remote sensing is georeferenced and calibrated. Number of advanced sensors in the space provides capacity to monitor ecosystems on frequent basis.
The forest ecosystems are one of the most common ecosystems that need to be assessed for its efficiency and robustness to protect human settlement at risk due to disasters and changing climate. A beyond eye capability of the sensors in the space provides capability to assess efficiency of the forest ecosystems, as these sensor provide important data for analysis and modelling different parameters of the ecosystem. The important parameters that can be studied using space based sensors are height of the forest stands, forest density, biomass, net primary productivity, carbon sequestration capacity etc. The maps (geospatial data) of ecosystems provide basis to understand interaction of ecosystems with surroundings and its impact on health of ecosystem.
Such data provides scientific basis for planning actions for protecting and rejuvenating ecosystems, such as eco-sensitive zoning, ecosystem regeneration, protected area development, forest fire mitigation, sustainable utilization of bioresource etc. These actions further lead to the sustainable development if these integrated into landuse plans, watershed management and infrastructure development projects. An integration of ecosystem protection with developmental planning ensures that the ecosystems remain balanced and robust, and development is resilient to the disaster and climate change.
The geospatial information generated using remote sensing data can be staggered as time series information which can be used in simulation models for climate change prediction, climate extremes and related hazards.
With availability of free or low cost satellite data that provides wide range of information (for example NDVI, rainfall, elevation etc.) to assess ecosystems, the disaster managers should leverage potential of space based information in ecosystem based disaster risk reduction.
 Peter Greminger, Managing the risks of natural hazards in Switzerland – an Alpine Country, XII World Forestry Congress, 2003, Quebec city, Canada)
 Anil K Gupta et al, Uttarakhand disaster 2013 – floods and landslides: lessons of ecology not yet learnt, Vol. 19 No. 4 – October 2013, Environews, International Society of Environmental Botanists.
 Shirish Ravan and P.S. Roy, Satellite remote sensing for ecological analysis of forested landscape. Plant Ecology 131: 129–141, 1997. 129, Kluwer Academic Publishers.