Role of Earth Observation in Environmental (Forest Fire) Policy Support: Swaziland

Role of Earth Observation in Environmental

(Forest Fire) Policy Support: Swaziland

WISDOM M.D. DLAMINI- Director of Nature Conservation -

Swaziland National Trust Commission

The Role of Earth Observations in Environmental Policy Support: Africa

International START Secretariat,Washington, USA

December 4 - 5, 2014

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PRESENTATION OUTLINE• Background

• Spatial Technologies in Environmental Policy and Decision-Making

• Case: National Fire Policy and Legislation

• Knowledge and Capacity Needs

• Conclusion and Recommendations

BACKGROUND

LOCATION AND SETTING

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BACKGROUNDArea: 17,365 sq. kmPopulation: 1,2 million peopleAgro-based based economyDivergent physiography and climateAltitude that ranges from approximately 50m to 1860m a.s.l.High biodiversity richness in a small areaOne of the largest remaining intact altitudinal gradients of natural ecosystems

in Southern Africa, and is the only place where this continuum is concentrated in a relatively short distance (of about 200 km).

Such an intact gradient holds great significance for biodiversity conservation because it allows ecological processes such as migration and gene flow, and provides ecosystem services necessary for the survival of majority population.

Majority of people and sectors rely on environmental/ecosystem services.Country is member of various numerous MEAs.

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Major ecosystems in Swaziland Montane grassland Sour bushveld Lowveld bushveld Lebombo bushveld Aquatic

July 22, 2012

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BACKGROUNDLimited land and growing population - competing land uses:

Human settlements encroaching to sensitive areas including wetlandsAgriculture especially subsistence agriculture and sugarcane competing with other

land uses especially conservation, livestock farming and human settlements

Land degradationEcosystem degradation and species lossPollution (water and air)Uncontrolled firesDeforestationDisasters – droughts, fires, Climate changeOverlapping mandates on land and environmental resources

managementLimited financial and human resources

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EO-RELATED POLICY • No specific policy or law governing EO.

• Broader National Information and Communication Infrastructure Policy of 2006 provides an overarching framework for the use of ICT for national development.

• Policy specifically highlights that spatial technologies “…will continue to be used in poverty mapping and planning interventions as geo-information facilitates the identification, based on cartographic representations, of the exact needs to be addressed and the attendant plans for such programs”.

• Land Survey Act No. 46 of 1961 governs the surveying and charting of land for purposes of the deeds registration and associated records; does not specifically mentions EO although may be indirectly implied in certain sections.

• NSDI being established,

• National Geospatial Committee in place.

• Swaziland Geospatial Information Society

• The Swaziland Standards Authority promulgating the use of international standards on the use of information technology including spatial information particularly the ISO 19100 series of standards.

Wisdom Mdumiseni

Dlamini

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SPATIAL TECHNOLOGY• Mostly surveying and GIS applications in various areas such as

utility companies, physical planning agencies, water resources, cadastral surveys, environmental monitoring, species atlassing,

photogrammetry, aerial photography, health.

• Other applications include poverty mapping, HIV/AIDS and disability mapping, veterinary disease surveillance, protected area mapping.

• Generally not well coordinated

• Limited data sharing: data bureaucracy

• Limited skills in doing advanced data analysis and modelling – mostly display of thematic maps.

• Few champions

Wisdom Mdumiseni

Dlamini

EARTH OBSERVATION/ SPATIAL TECHNOLOGIES IN ENVIRONMENTAL POLICY

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Land cover map(2009) – SPOT 5 derived Highlights predominant

cultivated dryland (subsistence agriculture) pressure – 20.8%

Settlements expansion Sugarcane pressure Plantation forestry Degraded woodlands (4% of

total land area)

July 22, 2012

Legend

Bare Rock Natural

Biult-up Rural Cluster

Built-up Rural Cluster

Built-up Transport / Industrial

Built-up Urban

Cultivated Dryland

Cultivated Irrigated

Cultivated Sugarcane

Degraded Grassland

Degraded Woodland

Erosion

Grassland

Mines and Quarries

Plantation

Waterbody

Wetland

Woodland

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Deforestation: 2000-2012

July 22, 2012

2001 2002 2003 2004 2005 2006 2007 2008 2009 2010 2011 20120

500

1000

1500

2000

2500

3000

3500

YEAR

AR

EA

(H

EC

TA

RE

S)

Landsat TM-derived data Savannah ecosystem (sour bushbeld and

Lowveld bushveld) most affected primarily due to sugarcane conversion (dam construction), subsistence agriculture and settlements.

Led to development of Forest Policy and Act in 2002 and highlights need for enforcement.

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Mdumiseni Dlamini

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Alien plant invasion pressure Modelled from aerial mapping data

coupled with use of SPOT 5 –derived land cover data

Chromolaena odorata, Lantana camara, Psidium guajava, Acacia mearnsii, amongst several other species are invading rangelands and most ecosystems affected.

Highly disturbed/highly populated areas vulnerable

Wisdom M. Dlamini (2014)

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Click icon to add picture

Chromolaena odorata (Triffid weed)

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Chromolaena odorata


Potential for further spread under climate change

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Bush encroachment: 1989 – 2009 Landsat TM-derived fractional

vegetation cover change Primarily due to Dichrostachys

cinerea and alien/non-native plant invasion


Communal land Reserve

Ranch Control 2

Control 1

Bush encroachment

1971

1979

1997Roques et al. (2002)

from Sirami and Monadjem, 2012

Aerial photo (1998) and SPOT 5 (2008)

Species richness decreased significantly, and this decrease was significantly explained by shrub cover increase at the plot scale (from 24% to 44% on average).

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Malaria risk Model based on NDVI,

NDWI, Land cover (all derived from Landsat ETM) and other spatial data

SPOT 5 data used in MALAREO project

Over 90% reduction in malaria cases since late 1990s/early 2000s.


January to April 2011 May to December 2011

from Cohen et al., 2013

Probability of locally acquired malaria

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Courtesy/UCSF Global Health Group / Swaziland National Malaria Control Program


Malaria risk 2011-2013

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Human population density (from 2007 Census mapping) Highlights spatial distribution of

population


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Poverty head count Based on Swaziland Household

Income and Expenditure Survey (SHIES) and Census mapping


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EARTH OBSERVATIONLimited infrastructure for EO data reception (four institutions have

such from AMESD/MESA programme)Limited bandwidth limits Internet access for most potential usersOnly the main university offers RS module in undergraduate and

graduate levelsMost EO training done in neighboring SA and abroad.Few applications:

Crop yield prediction – particularly using AVHRR (private sector now using precision farming from VHR satellite and UAV imagery)

Land degradation/soil erosion monitoring – Landsat TM/ETM+Water resources management – Landsat TM/ETM+Forest resource assessment – Landsat TM/ETM+Malaria vector monitoring – SPOT/Landsat TM/ETM+Weather forecasting/prediction – MSG

UAV technology being introduced

Wisdom Mdumiseni

Dlamini

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AMESD/MESA THEMA SERVICES

Agricultural Service - monitors the state of the crops and rangeland and provide a yield-outlook (31 products, 6 new proposed covering livestock)

Drought Service monitors drought during the whole year and deliver a decadal “Drought map” and a “Drought Outlook” in support of both agriculture and environmental issues (17 products)

Wildfire Service provides a daily wildfire risk indication (before the fire), continuous active wildfire maps (in real time during the fire season, refreshed every 15 minutes from MSG and MODIS) and monthly burnt area assessments (after the wildfire) (6 products)

Flood Service provides a flood risk indication and a flash flood forecast (before the floods), flood modelling (during the event of floods) and flood damage assessments (after the floods)(9 products)Wisdom

Mdumiseni Dlamini

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MESAKey-users

National Level : Ministries of Agriculture, Natural Resources, Environment

Secondary users/Target usersNational food security Environmental agenciesFarmersNational Statistic OfficeAgrometeorological DepartmentResearch CentresDisaster management agency

Wisdom Mdumiseni

Dlamini

FIRE POLICY AND LEGISLATION CASE STUDY

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AMESD/MESA FIRE TERMINAL

Wisdom Mdumiseni

Dlamini

The EU/AU project addresses five (5) key results areas: Result 1: improve access to earth

observation data. Result 2: development/consolidation of

geo-information service. Result 3: cross-fertilization among the

regions. Result 4: strengthen political and policy

development frameworks. Result 5: adequate technical permanently

capacity at continental, regional and national levels.

Objectives

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PROBLEM IDENTIFICATIONAs part of SAFNet, MODIS burned area product extensively

validated in the early 2000 through SAFARI Campaign.Now validation of VIIRS is on-going with first mission by various

experts from different countries in August 2014.The objective of these campaigns are:

Validation of new remote sensing products (active detection),Improving gas emission estimates and fuel characterization from savannah

fires,capacity building and knowledge and skills transfer between regional and

international experts

AFIS system including mobile app (Android and iOS) developed by SA through input from the network

Wisdom Mdumiseni

Dlamini

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AFIS Android App

Screenshot for Malolotja Nature Reserve, Swaziland:

Information: active fire location locality, time, date, brightness temperature, fire danger index, fire history, burned area


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PROBLEM IDENTIFICATIONFires can be a result of both lightning and human intervention.Fires largely dominated (~ 90%) by anthropogenic fires as with

most of southern Africa.Together with thunderstorms and drought, forest fires are

frequently occurring and a pervasive natural hazard. Used in private and public sectors and by communities for

various purposes:slash burning after clear-felling moribund reduction creating a flush of green grass for livestock.

Wisdom Mdumiseni

Dlamini

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PROBLEM IDENTIFICATIONIncrease in wildfire frequency and magnitude in recent years

(such as the disastrous fires of 2007 and 2008) underlines and emphasizes the importance of understanding the causes and spatial distribution of this phenomena. > 40,000ha of forests burnt, numerous homesteads, livestock and wildlifenational economy severely affected with the ultimate closure of Sappi

Usuthu and downscaling of operations of Peak Timbers (two major forestry companies)

livelihoods of ±8000 employees and their dependents supported by this sector.

Improper fire use coupled with poor grazing management and climate factors have resulted in property and human life loss, land degradation, bush encroachment and alien plant invasion over large communal areas

emissions and possible human health problemsWisdom

Mdumiseni Dlamini

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Spatially explicit data on fire occurrence has not been available for the whole country. Only reports from fire stations on number of monthly fires attended to.

Satellite-detected (e.g. MODIS) active fire and burned areas are now proving insights into the spatial and temporal distribution of fires in the country.

The geographic distribution of fires illustrates the spatial pattern of the current burning practices as a function of land utilization (tenure and use), land physiography and climate.

Evident fire clusters on the western part of the country (largely from grassland and plantation forest fires) and eastern parts (largely sugarcane and protected areas).

Permitting: current legislation requires permit for burning but approval/disapproval not based on scientific information such as previous burn, fire danger, etc.

Wisdom Mdumiseni

Dlamini

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Uncontrolled Fires (MODIS-detected)

July 22, 2012

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Wildfires: 2000-2013 (MODIS – MCD64A1 burned area)

July 22, 2012

2000 2002 2004 2006 2008 2010 2012 20140

20,000

40,000

60,000

80,000

100,000

120,000

140,000

Year

Bu

rne

d a

rea

(h

a)

FIRE SEASONALITY

Janu

ary

Febr

uary

Mar

chApr

ilMay

June Ju

ly

Augus

t

Sept

embe

r

Octob

er

Novem

ber

Decem

ber

0

0.05

0.1

0.15

0.2

0.25

0.3

0.35

0.4

Burned area

Pro

po

rtio

n o

f b

urn

ed

are

a/a

cti

ve

fire

s

MODIS (Aqua) true colour image, 28 July 2007

MODIS (Aqua) true colour image, 31 August 2008

Note the dense smoke also from plantation fires.

Affected parts of the country; visibility low in other areas.

Contributed to the closure of Sappi Usuthu: loss of jobs and national economy

Widespread destruction: >100 homesteads destroyed, 1 fatality and several injuries.

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POLICY RESPONSE/FORMULATIONThere is evidence of uncontrolled and uncoordinated use of

fires.Some fires are trans-boundary in nature!!! To/From South Africa

and Mozambique.Proper fire regimes for Swaziland are not yet fully known. Recent studies indicate land tenure as key driver in addition to

climatic and socio-economic factors are strong predictors of wildfire occurrence.

Policy targets ignitions: anthropogenic sources

Wisdom Mdumiseni

Dlamini

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POLICY RESPONSE/FORMULATIONIn2009, a National Multi-sectoral Bushfire Contingency Plan was

developed in response to 2007/2008 fires: aimed at reducing disaster risks posed by wildfires.

Priority areas ( characterized using MODIS and other spatial data

Fire risk analysis undertaken to ascertain short to medium-term risks

Data mining approach using Bayesian Networks was adopted for inference and prediction in the wildfire problem domain. Dataset containing ~70 variables used.

Wisdom Mdumiseni

Dlamini

POLICY FORMULATION

Variable Mutual Info

Land tenure 0.08506

Precipitation of wettest month 0.06835Minimum temperature of coldest month 0.06468

Household size 0.05167

Dependent 0.04614

Land cover (SPOT 5) 0.04623

Land use 0.03489

Livestock density 0.02727

Goat density 0.02616

A final 9 variables were selected to develop the model

Bayesian network model

Shows probabilistic relationships and conditional dependencies between variables

Policy implications:Prominent influence

of land use and land tenure on overall system

Grazing management (goat and livestock) also has impact.

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Fire risk


Fire p

rob

ab

i...

Fire fre

qu

...

0.00

0.10

0.20

0.30

0.40

0.50

0.60

0.70

0.80

0.90

1.00

Min OutlierMax Outlier

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POLICY IMPLEMENTATIONThis is vital for fire management in Swaziland because land

tenure tends to influence land use, and hence land cover and the resultant fuel loads.

Communal lands, whilst having lower fuel loads influence the neighboring land parcels and vice versa through both landscape and socio-economic linkages.

Need for community-private-public partnerships in managing fires.

Participatory land use planning and integrated land use management is imperative.

Fire management needs to be land use-specific and adaptive, focusing on maximizing beneficial uses whilst countering the negative impacts.

Need for cross-border cooperation to manage transboundary fires and share resources/expertise – MoU signed with South Africa for cooperation.

Wisdom Mdumiseni

Dlamini

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POLICY IMPLEMENTATIONSubsequently in 2011, with the assistance from the FAO, country

embarked on initiative to institute integrated fire management across all land tenures and uses in Swaziland through a harmonized institutional framework (national fire legislation, policy and strategy).

Pilot areas chosen in 2012 for integrated fire management (pilots chosen based on fire frequency/risk maps)

Building on and integrating the Bushfires Contingency Plan.

Policy approach enables the decentralization of fire management decision-making and implementation to stakeholders (including communities) to promote ownership and collective by grass roots level decision-making and implementation.

Focus is establishing and integrating community-based integrated fire management to improve community livelihoods and reduce poverty without costly machinery or resources.

Based on traditional knowledge, existing skills and institutions fire management programs are driven by tangible livelihood benefits to community members. Wisdom

Mdumiseni Dlamini

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POLICY EVALUATIONYet to be done as policy is still under development and pilot

testing.Pilot areas show improvement in management although

irresponsible behaviors continueEvaluation will be on understanding fires in the environmental,

social and economic context focusing:Area burned and damage to propertyFire return period for different ecosystems and land usesSeasonality/intensity

Wisdom Mdumiseni

Dlamini

KNOWLEDGE AND CAPACITY NEEDS

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KNOWLEDGE NEEDSLimited awareness about the value of EOs among decision and policy

makersLack of appreciation of the strategic and critical roles of the environmental

sectors contribution to national socio-economic developmentNeed for more rigorous EO applications in the following areas:

Forest assessment in the context of REDD (MRV)Biodiversity including invasive alien plant monitoringWeather and climate monitoring and predictionHazard prediction - flood, drought, fireLand degradation Water resources Air quality

Provision of accurate and timely short to medium range and long‐term prediction as inputs for early warning for food security and mitigation of the impacts of natural disasters such as droughts and floods

Need for EO to monitor MEA compliance and implementation (particularly the Rio Conventions and related protocols)

Wisdom Mdumiseni

Dlamini

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KNOWLEDGE NEEDS• With respect to fire case:

• Spatial resolution: size of the country requires even finer burned area maps (e.g. Landsat resolution) but temporal resolution is low

• Temporal resolution: high temporal resolution required (MSG fills this gap but is coarse)

Wisdom Mdumiseni

Dlamini

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CAPACITY NEEDSDiminishing government financial budgetary supportLimited access to capacity building resourcesLimited spatial literacy and education on use of spatial technologyInadequate trained personnel including failure to keep up‐to‐date with the ever

changing technology due to limited resources;Limited skills in EO data assimilation and processing – e.g. algorithm development

for local applications (modelling and prediction of environmental changes)Inadequate capacity to generate sector specific information and its disseminationLack of e-science infrastructure for EO education and trainingLack of modern telecommunications infrastructure for efficient exchange of data

and productsMany institutions in the country lack adequate observation network as well as

remote sensingLack of efficient data management systems and real‐time data processing

facilities including forecasting and dissemination systems

Wisdom Mdumiseni

Dlamini

CONCLUSION AND RECOMMENDATION

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CONCLUSIONBig potential for EO application in SwazilandMost applications have been project-basedEO extensively and traditionally used in weather forecasting Landsat TM and SPOT have been leading particularly for land cover

mappingUS data policy has had huge impact on use of EO data for

environmental monitoring and decision-making in the country.MODIS is increasingly being used particularly for fire monitoring.Need for use of long-term EO data to assess environmental changes

such as land cover, climate change etc., as a basis for vulnerability and adaptation assessments.

Infrastructure, institutional and human resource capacity needs linger and hinder further application of EO to solve societal problems.

Wisdom Mdumiseni

Dlamini

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RECOMMENDATIONSDevelop relevant products and conduct workshops to convince decision-

makers of the importance, relevance, and appropriateness of utilizing EO technology.

Support projects that result in building hands-on EO capacity in government and non-government institutions (via collaboration among EO data institutions, the private sector, and national governments).

Organize and reinforce international networks (incl. training opportunity networks) for the use and provision of Earth observations. Support associations such as AARSE.

Enhanced participation of developing countries in the intergovernmental Group on Earth Observations (GEO), AfriGEOSS and the Global Earth Observation System of Systems (GEOSS).

Foster collaboration between developing and developed country research institutions and institutions of higher learning focusing on EO to facilitate knowledge exchange and to achieve international best practices in generation and application of EO products.

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Dlamini

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RECOMMENDATIONSEncourage the development of open-source solutions across and along

the Earth observation value chain.Develop adequate dissemination schemes that reflect the reality of

limited bandwidth in developing countries (the Fundisa disk distribution to Africa, MESA, GEONETCast and SERVIR).

Provide technical and financial support to improved computing infrastructure to enable developing countries to utilise the BIG Earth observation data and to run models as well as perform data management.

Address critical shortage of land based observations in most African countries

Address communication gaps for data exchange between African countries and beyond

Access to products and services from advanced centres to acquire essential data

Foster Research and Development in the EO science and its applications in African institutions

Wisdom Mdumiseni

Dlamini

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TH

AN

K YO

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In memory of my son, Andzile Betive Zanokuhle “Gadzimvelo” Dlamini

Technology

Role of Earth Observation in Environmental (Forest Fire) Policy Support: Swaziland