Transcript DEVELOPMENT OF SATELLITE BASED DROUGHT …

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Assessment of drought impact on rice
production in Indonesia by satellite remote
sensing and dissemination with web-GIS
Rizatus Shofiyati, Wataru Takeuchi, Soni Darmawan, and Parwati Sofan
Indonesian Agency for Agricultural Research and Development
Indonesian Center for Agricultural Land Resources Research and Development
Presented at Workshop on Crop Monitoring and Food Security,
the 34th ACRS 2013, Bali-Indonesia, 22 October 2013
1
Background
National Disaster Management
Berau of Indonesia (BNPB) : 2000 - 2007
Events
Events of Natural Disasters
1500
1400
1300
1200
1100
1000
900
800
700
600
500
400
300
200
100
0
Typhoon
Floods and droughts are common
disaster in Indonesia
-Flood occured 1,548
-Drought occured 960
Flood and Landslides
1,548
Flood
Epidemic
Wave and abrasion
Earthquake and Tsunami
960
Earthquake
Pest Infection
Forest Fire
Settlement Fire
Drought
Volcano Eruption
Area of Natural Disasters in Paddy Field (Ha)
Landslides
Typhoon
Agricultural area that suffered disasters
:
-Drought : 1,624,260
-Flood : 1,019,123
-Landslides : 323,658
Source: http://www.bnpb.go.id
Flood
Epidemic
323,658
Wave and abrasion
Earthquake and Tsunami
Earthquake
Pest Infection
Forest Fire
1,019,123
Presented by Lapan (2011)
Flood and Landslides
1,624,260
Settlement Fire
Drought
Volcano Eruption
Landslides
Drought Effects on Rice Crop Damage
in Indonesia
Area damage
(ha)
Source : data processed from the Directorate General of Food Crops Protection
Decreasing of Crop Production
Drought Year
(El nino)
52.5
Crop production (x 106 tons)
50.0
47.5
45.0
-5.85%
-0.33%
Average
49.5 million
tons
20.0
17.5
15.0
12.5
Paddy
Maize
Cassava
10.0
7.5
5.0
2.5
0.0
1993 1994 1995 1996
1997 1998 1999 2000 Year
• Special attention to monitor the condition of crops growth
during the season is encouraged to reduce the damage.
• An early warning of climate change impact would be very
useful in the planning stage of agricultural development
settings.
• Sufficient data and information to anticipate various
situations caused by climate change is critical, as it would
affect agricultural development policy.
Activities of IAARD / MoA’s with Related Agencies
Frequency
Institutions
Activities / Output
Utility
2x / Year
• BMKG
release prospect of season type
season type
• IAHRI (under
coordination
IAARD)
• BMKG
have discussions and issue weather
zone and prediction
weather zone and prediction
• IAARD
• issues recommendation /
guidance of cropping calendar,
supported by rainfall data of
BMKG.
• The information would be used by :
‐ farmer to plan planting time, and
‐ local government to determine
regional planning especially in
agricultural field.
• Weather condition potentially
influence agriculture areas that
could influence national rice
production and decisions on
importing/ exporting rice.
• BPS invites
BMKG, MoA,
LAPAN
to discuss the current and future
climate condition, vegetation
condition, and their impacts on
the agriculture production (mainly
Java island) for releasing of socalled “predictive rice production
numbers”.
3x / Year
SAFE Prototype 2012/13 – 2013/14
• Objective:
– to asses the use of satellite data to monitor the drought
condition of rice field in a near real time;
– to validate the satellite based model on drought with
ground observation data;
– to develop a system based on Web-GIS integrating satellite
based system with existing crop calendar;
– to disseminate the drought information to decision
makers, and the farmer through extension worker;
Expected Output
• Nation wide drought condition data of rice field at sub district
level;
• Satellite based model of drought validated using ground
truth data in Subang and Karawang District, West Java, Klaten,
Central Java, Pasuruan and Ngawi, East Java, South Sulawesi,
and South Kalimantan;
• A Web based system to disseminate drought information to
end users;
Collaboration with Agencies
• Excuting
Agencies
Executing Agency
Activities
• ICALRD – IAARD
of MoA
• Developing the prediction/early warning models of
the potential drought over the agriculture area in
Java island.
• Examining the uncertainties of drought indices and
their ability to detect drought events in Indonesia
and selecting the best drought indices to use in
monitoring.
• Integrating drought analysis by satellite data and
cropping calendar for determining planting time
• Conducting field checking
• Conducting workshop & training
• Supporting • JAXA
Agencies • Univ. Of Tokyo
• LAPAN
• Satellite data provision (ALOS AVNIR-2 and
PALSAR, ALOS-2)
• Training, workshop, and seminar are matters to be
considered during the activity
• Technical supporter, Model development
• Assist the automatic data processing needed for
the continuous monitoring.
• End Users • extension officers, • Conducting field surveys for validation of model
• local government • Conducting workshop & seminar
Overview of the Activities
LAPAN
ICALRD - IAARD
Activities
2010/11
2011/12
2012/13
Implementating model
for operational use
Operational
Dissemination
Developing Web-GIS
Workshop
Applying Model
Product
Technology /
Prototype
R&D
2013/14
Model Validation
Developing Drought Model
(Research Activities)
Integration of Cropping Patterns, Seasonal Rainfall and
Satellite Image Analysis
POTENTIAL
CROPPING CALENDAR
(IAARD)
WET: PS1, PS2, PS3
NORMAL: PS1, PS2, PS3
DRY: PS1, PS2, PS3
Data Used:
Rainfall Data
SEASONAL RAINFALL
PREDICTION
(BMKG)
FORECAST OF
MONTHLY RAINFALL
(mm/month)
PROSPECT OF
BEGINNING OF
SEASON
PROSPECT OF
SEASON TYPE
(WET, NORMAL, DRY)
DROUGHT
IMAGE ANALYSIS
(ICALRD)
NDVI
VCI
Data Used:
KBDI
• MODIS,
• MTSAT
VHI
• AMSER-E
• ALOS AVNIR-2 & PALSAR
(acq before May 2011)
Drought Information System
Satellite
Data
Rainfall Data
Drought
Information
Cropping Calendar
by IAARD
Season Prediction
by BMG
updating integrated
cropping calendar
Drought
Information System
RECOMMENDATIONS :
• Information of drought
vulnerability
• Planting time
Local
Government
Extension
Officer
Farmer
Method & Data Used
 Vegetation Condition Index (VCI) associates with moisture
condition of vegetation:
EVI  EVI min
VCI  100x
EVI max  EVI min
Kogan, 1990
 Thermal Condition Index (TCI) associates with thermal
condition of vegetation:
LSTmax  LST
TCI  100x
LSTmax  LSTmin
Kogan, 1990
 Vegetation Health Index (VHI) represents overall vegetation
health:
VHI  0.5(VCI  TCI )
Kogan, 1990
Classes of Agricultural drought-based VHI
VHI classification (Kogan 2002)
VHI
Classes
VHI > 40
No drought
30 < VHI ≤ 40
Mild drought
20 < VHI ≤ 30
Moderate drought
10 < VHI ≤ 20
Severe drought
VHI ≤ 10
Extreme drought
VHI classification (NESDIS NASA)
VHI
Classes
VHI > 60
Favorable vegetation
36 < VHI ≤ 60
Fair vegetation
VHI ≤ 36
Stressed vegetation
Vulnerability Level of Drought Year 2012
(Source: IAARD, 2012)
Model Development & Application
In 2012
VCI & LSWC to Identify Crop Pattern and Intensity
Source: Takeuchi et al, 2012
KBDI & LSWC to Identify Drought in Indramayu
Source: Takeuchi et al., 2012
Crop Pattern and Intensity in Java Island by MODIS
Existing Crop Calendar
The growing seasons detailed below are existing crop calendar in
Karawang and Subang. They are based on the cultivar planted in the
area which has 90 to 110 days growing period (i.e. Ciherang, IR42,
Cidenok, Mekongga, etc.)
# Sowing Month Harvest Month Notes
1 October
February
2 March
June
3 July
October*)
Northern coast of West Java
(Karawang, Subang, Indramayu)
Northern coast of West Java
(Karawang, Subang, Indramayu)
Northern coast of West Java
(Karawang, Subang, Indramayu)
*) Secondary crops (maize, soybean, longbean), the harvest time is around August
Guidance of Crop Calender 2012-2013
(IAARD 2012)
Rainfall, KBDI, NDVI, LSWC (2009 - 2012) – West Java
VCI, TCI, & VHI of MODIS for Drought of Java
Field Visit for Model Validation
Ground survey for drought
based on ground survey
1. KBDI value 500 – 600  early indication of drought for
paddy filed
2. Drought systems have high accuracy
3. In the some area that have good irrigation and have
water resource, although indicated drought but paddy
field still growth.
3. Ground survey for drought
Kerawang & Bandung West Java
3. Ground survey for drought
Yogyakarta, Central Java
3. Ground survey for drought
Makasar, South Sulawesi
Harvested area since
1993 - 2012
Ten provinces of central areas of
paddy production in Indonesia:
1. West Java
2. Central Java
3. East Java
4. South Sulawesi
5. Nanggroe Aceh Darussalam
6. North Sumatra
7. West Sumatra
8. South Sumatra
9. Lampung
10. Bali & West Nusa Tenggara
Source: BPS, 2013
Indonesia Rice Productivity (1993 – 2012)
Source: BPS, 2013
Web-GIS Development
(on going)
Transfer Data Connection Fasility
Cloud
Computing
IAARD
VPN
UNIV. OF
TOKYO
ICALRD
VPN
LAPAN
Website Crop Monitoring
Web-GIS for Search Available Information
Feed Back From User
Some Workshops held in 2012:
Pariticpants :
LAPAN, BPPT, BMKG, BPS, IPB, BB Padi, BIG, etc
– Some area need to be verified, It does nor meet with area
condition, such as East Nusa Tenggara, South Kalimantan
– More Interactive and integrated :
• Searching menu
• Can show the result analysis by using coordinate / cursor
– In Indonesian version → the user is local people.
End user meeting in 2013
• From BB. Padi :
a. is it possible for variety of paddy field mapping using remote
sensing ? And how ?
b. how to predict the drought ?
c. How about accuration and validation the drought system ?
• From coordinator of farmer :
a. They expect given computer facilities and internet access
b. How to access the systems ? And they hope implemented
training/workshop for them
On Going & Next Activities in 2013/14
• Continue processing and analysing all indices (SPI, VCI, TCI, VHI),
LSWC, and KBDI Using MODIS, MTSAT, and AMSER-E for 2013.
• Developing a system based on Web-GIS integrating satellite based
system.
• Correlated KBDI with Crop Calendar
• Disseminating the drought information through workshop for end
user (decision makers, and the farmer through extension worker).
• Implementing the model for operational use.
Framework of operational use after this prototyping
Data Provider:
LAPAN
JAXA
Satellite data preparation :
Inventory and selection of
basic analytical methods
Satellite data processing :
•digital analysis of satellite imagery,
•identifying drought affected area
•Analysing drought impact to paddy
production by identifying planted
harvested area
ICALRD – IAARD – MoA
LAPAN
Univ. of Tokyo
Preparation of information (spatial &
tabular):
Agriculture affected area by drought,
drought impact to paddy planted area,
harvested area, and paddy production.
Data & Information
Updating
feedback
IAARD, LAPAN, BPS,
PUSDATIN of MoA
Web-GIS based
Information :
User:
Farmer via extension
officer, Agric. Local Office
for Food Crop
•Area affected of drought
•Recommendation :
planting time, crop, etc
Closing Remarks
• Model development:
– NDVI, VHI, LSWC, KBDI (value 500 – 600) can represent
precipitation anomaly and well capture a drought onset day.
– VCI of MODIS, LSWC of AMSER-E, KBDI of MTSAT can be used to
identify crop pattern → the Indices can be used to estimate yield.
• Validation have been done in West Java (Indramayu District), DI
Yogyakarta, South Kalimantan, and South Sulawesi shown same
condition with result derived from satellite data.
• Web based system to disseminate drought information is still
developing:
– More Interactive and integrated
– In Indonesian version → the user is local people
– Conducting Training/Workshop
– Provide Computer and Internet facility
THANK YOU
ICALRD
Jalan Tentara Pelajar No. 12, Cimanggu, Bogor, 16114 INDONESIA
Tel. +62 251 8323012
Fax.+62 251 8311256
Email: [email protected]
http://www.bbsdlp.litbang.deptan.go.id