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Space technology assistsSpace technology assistsMongolia herders & farmersMongolia herders & farmers
to reduce disaster riskto reduce disaster risk
By PhD. N.Togtokh, PhD. R.Oyun, MongoliaBy PhD. N.Togtokh, PhD. R.Oyun, Mongolia
UNITED NATIONS OFFICE AT VIENNA15th United Nations/International Astronautical Federation Workshop on“Space Education and Capacity Building for Sustainable Development”
ContentContent
1. Global change affects the livelihoods of rural population2. Disaster risk reduction: “Ideas-Actions-Achievements”3. Space technology assists the herder & farmers 4. Community participation5. Indigenous knowledge of the herders used
to predict risk of coming winter and spring6. Partnership and Capacity building7. Examples on use of satellite remote sensing for DRR8. e-Soum - new challenge for space technology
1. Global change affects1. Global change affectsthe livelihoods of rural populationthe livelihoods of rural population
• Global change affects Mongolia:– Climate warming is twice as rapidly
as the global average. – The epicenter of atmospheric pressure
changes located in Mongolia
• The faster the climate changes, the greater the risk of disaster:
– Increase of variability and extremes– Steppe grasslands are vulnerable
to such changes, – Pastoral animal husbandry and
arable farming is at great risk,– 1999-2003 severe droughts, dzud
disasters caused :
• Increase in poverty: – 36 per cent poverty nationally,– 43 per cent in the rural population
Agriculture GDP
10%
15%
20%
25%
30%
35%
40%
1998
1999
2000
2001
2002
2003
Animal husbandry is national wealthAnimal husbandry is national wealth
• Since 1999 in Mongolia consequent drought and dzud disaster have affected natural pasture resources and caused mass loss of animals.
• Mongolia had lost one third of its livestock• Poverty incident in rural area has reached to 43%.
Risk of animal husbandryRisk of animal husbandry
2. DRR: 2. DRR: ““Ideas Ideas -- Actions Actions –– AchievementsAchievements””
• “Lessons Learnt” case studies:– Dzud of 1999-2000– Drought of 2002– Hazardous windstorm of 2001 and 2002– Early warning and emergency management system – Disaster management information system
• Risk studies and assessments:– Impact assessment of climate change – Livelihoods of herders and farmers – Policy recommendations
• “Ideas - Actions - Achievements” pilots:– Methodology to assess hazard, vulnerability and risk– Risk prediction for coming winter and spring– Introducing liquid gas to rural herders and small restaurants– Restocking the herders with high productive sire– Carpet knitting with “male” wool of camel
• “Risk manager” information system development:– Integrated database for rural county– Community information center at rural county– Partnership for communication and information sharing– Integrated information processing techniques and software– www.agronet.mn Internet web site
3. Space technology assists the herder & farmers3. Space technology assists the herder & farmers
• Communication:– Data network with VSAT– Mobile phone
• Positioning of ground true data provided by the herders, farmers:
– Notes on local weather– Vegetation biomass– Animal bodyweight– Air pressure, temperature– Hazards, extreme events
• Positioning and mapping of data provided by the local government:
– Wells– Livestock location by winter stand– Crop fields
• Mapping of local environment:– Cloud, weather, climatic norms– Pasture vegetation– Snow coverage – Extreme temperature– Soil moisture
Information and Computer Center,
MNE
Institute of Meteorology and
Hydrology
NOAA AVHRR data
Weather forecast
JEMR Consulting LLC.
Meteorological Society, NGO AgroSoft LLC.
Agriculture Risk Study Center, NGO
Local Community Information and Training
Center
National Agency for Disaster Management
Disaster management
Local climate, weather study
Integrated Information Processing
Database, www.agronet.mn
Agriculture Bank Incomnet LLC.VSAT datanet
Local branch of Agriculture Bank
Local disaster management staff, professional service units, rescue team
Local Meteorological
Station
Telephone
Local FM radio
NOAA Intelsat
Color Printer
Public Bulletin Board Local
community, herders
Weather Forecast and Hazard Warning Information Flow Ulaanbaatar and Erdenedalai county (Dundgobi province)
Information to the herders
Meteo. station: Tsagaa
Field measurement dweather, soil moistu
crop observation
Gatsuurt Crop far
AgroSoft: Database, DEM , W eb masteringJEMR Consulting: Integrated information processing
National Rem ote
Sensing Center
Agriculture Risk Study Center: Coordination partnership,
contracting, information service
Exchange V irtual: Cloud> ICC L3
Im age processingsystem
3D M ap 1: NDVI
3D M ap 2: RT
3D M ap 3: W10
Secretary PC
Im age processingsystem
County database:
DEM,Statistics
D igitizing
Database
www.agronet.m nWeb Master
Meteorological Society
Ground data: formal, informal
Portable field equipment: Barom eter, thermom eter,
anim om eter
National Agency for Meteorology, Hydrology
& Environmental Monitoring
Meteorological database
Gatsuurt Company Headquarter
e-m ail
Secretary PC Printed maps
Company post
Printed maps
Agro
M anager
Institute of Meteorology, Hydrology:
Weather forecast: weekly, monthly
Synoptic engineer
Information flow: Ulaanbaatar – Tsagaannuur crop farm
Information to the farmers
4. Community participation in disaster risk reduction4. Community participation in disaster risk reduction
• Monthly and seasonal weather prediction around the living area:
– Indigenous knowledge of nomads on astrology and nature has been accumulated over thousands of years and passed from generation to generation
• Local climate, weatherand hazard monitoring:
– Observation and notes– Use of barometers, thermometers
• Interpretation of satellite images, verification of class maps:
– Name of local land represent their specifics and in some cases match well with natural color composite of images
– Easy interpretation of images and verification of classification results with good knowledge on their native land
Discussion with local government and community of Erdenedalai county
The herders notes on local weather
5. Indigenous knowledge of the herders used5. Indigenous knowledge of the herders usedto predict risk of coming winter and springto predict risk of coming winter and spring
• Herders’ observation:– Every year in full moon night of middle month
of the autumn the herders D.Bor, S.Dashdorj and D.Tavanjin from Gobi-Ugtaal and Tsagaandelger counties of Dundgobi province claim up the Bagazalaa mountain
– They observe the moon, stars, airflow and morning sun rise;
• They determine:– What is the most risk of coming winter and
spring? – Is there any threatening hazards expected
(snowfalls, extreme cold, epidemic diseases, etc.)?
• Predicting time: – 6-7 months a head, from October of current
year to March-April of the next year.
• Observing area:– Visible area with approximate radius of 100
km around the mountain.
Herders’ observation at Bagazalaa mountain
Participatory risk prediction Participatory risk prediction andand decision makingdecision making
• Next morning discussion is important to conclude risk prediction, formulate management tactics, make decision.
• The herders introduce their prediction
• Risk study team introduce:– Official weather prediction for coming 6
months– The results of vegetation index, pasture
capacity and animal bodyweight monitoring
– The results of evaluation of previous year risk prediction
– What lessons was learnt from past winter, spring and summer
• The local government and the herders make decision on:
– Animal and pasture capacity is sufficient for predicted winter and spring condition?
– If no? • Amount of additional fodder for vulnerable
part of the herds• Where is the new location to move herds?
Where will be less snowfall and less cold?• If above 2 measures are not appropriate, so
to slaughter animals and sale on the market, and restocking again next spring
6. Partnership and Capacity building6. Partnership and Capacity building
• Series of workshops on community information center, disaster risk reduction and training on use of thematic maps and computer conducted with support of public and private stakeholders:
– National Agency for Disaster Management, – National IT Park– National Remote Sensing Center– Mongolia Development Gateway NGO– MIDAS/MONITA NGO
• Local government of 15 counties encouraged participation of rural communities in activities towards disaster risk reduction
Workshop at Erdenedalai county
Óðãà ì àëæëû í è í äåêñ áà óðãàö
y = 250,01x2 - 36,533x + 1,9194R2 = 0,9582
0,400,60
0,801,001,201,40
1,601,80
0,05 0,07 0,09 0,11 0,13 0,15
Óðãàì àë æë û í èí ä åêñ
ªâë
èéí
óðãà
ö
7. Pasture vegetation monitoring, 20047. Pasture vegetation monitoring, 2004Vegetation map produced at the county meteorological station with ground data
High correlation between biomass and vegetation index
Biomass, c/hVegetation indexPasture, affected by locust Pasture for winter
precipitation
Weekly vegetation index map, June-July
July - August
August - September precipitation
Weekly vegetation index map, June-July
July - August
August - September
May-October weekly vegetation index maps
Pasture vegetation monitoring, 2005Pasture vegetation monitoring, 2005
Steppe vegetation, 2005.08.20
y = -552.89x2 + 241.26x - 24.511R2 = 0.9974
0.0
0.5
1.0
1.5
2.0
2.5
3.0
0.050 0.070 0.090 0.110 0.130 0.150 0.170 0.190 0.210 0.230
Vegetation index
Bio
mas
s, c
/h
Gobi vegetation, 2005.08.20
y = -68.701x2 + 37.005x - 1.9224R2 = 0.9583
0.0
0.5
1.0
1.5
2.0
2.5
3.0
0.050 0.070 0.090 0.110 0.130 0.150 0.170 0.190 0.210 0.230
Vegetation index
Bio
mas
s, c
/h
Vegetation index and Biomas sÝðä ýí ýä àë àé ñóì , 2005.06.24
y = 7.6251x + 0.0341R2 = 0.7246
00.1
0.20.3
0.40.50.6
0.70.8
0.91
0 0.02 0.04 0.06 0.08 0.1 0.12 0.14
Vegetation index
Bio
mas
s
2005.10.02-08
Relationships between vegetation index and biomass
Animal bodyweight monitoring, 2004Animal bodyweight monitoring, 2004--20052005
Sheep bodyweight and green mass, 2005.08.15-09.20
y = -0.9916x2 + 7.8634x - 8.3423R2 = 0.7616
0
1
2
3
4
5
6
7
8
0 0.5 1 1.5 2 2.5 3 3.5 4 4.5 5Monthly increase in sheep bodyweight, kg
Gre
en m
ass,
c/h
Winter is coming …
Climatic norm and microClimatic norm and micro--climatic class mapsclimatic class maps
-24 -23 -22 -21 -20 -19 -18 -17 -16 -15 -14-24 -23 -22 -21 -20 -19 -18 -17 -16 -15 -14
January climatic norm: Air temperature Micro-climatic class map
Micro-climatic class parameters
Ulaanbaatar city, Nalaikh district - 14.2 ± 1.168 ± 41861 ± 1835
- 16.2 ± 0.988 ± 41711 ± 1894
- 18.6 ± 0.826 ± 31520 ± 1463
- 19.9 ± 0.714 ± 31416 ± 1362
- 23.5 ± 0.862 ± 21387 ± 1261
January airtemperature norm, oC
Slope angle, oAltitude, mClass number
- 14.2 ± 1.168 ± 41861 ± 1835
- 16.2 ± 0.988 ± 41711 ± 1894
- 18.6 ± 0.826 ± 31520 ± 1463
- 19.9 ± 0.714 ± 31416 ± 1362
- 23.5 ± 0.862 ± 21387 ± 1261
January airtemperature norm, oC
Slope angle, oAltitude, mClass number
Information and Communication Technology Authority of Mongolia
supports e-Soum
National Petroleum company NIC/Petrovis supports e-Soum
Signing of MoU to collaborate towards establishing e-Kara Korum
as model for e-Soum
Event for launching e-Soum web site and partnership for e-Kara Korum
8. 8. ee--SoumSoum initiative is new challenge for space technologyinitiative is new challenge for space technology
• Mongolia’s IT community and Risk study team have initiated ‘e-Soum’ project proposal:
– to establish a sustainable system that enable the monitoring, assessment, prediction and warning of changes both natural and human-made environments, structures and systems with use of advanced information and communication technology.
– to assist people in understanding, evaluating and coping with complex systems, sharing knowledge to create new ones, and actively participating in management and decision-making processes in order to achieve sustainability
– Meanwhile more than 50 organizations are supporting e-Soum