PPT - Asia-RiCE

Report
Background

Rice and poverty coincide in Asia, home to over 70% of the
world’s poor (900 million people) and where almost 90%
of the world’s rice is produced and consumed.

The Indonesian population continues to grow rapidly,
meanwhile commodity prices are rising and the available
arable land area is decreasing.

In most of the developing world, rice availability is equated
with food security and closely connected to political
stability: Rice price increases have caused social unrest in
several countries, most recently during the food crisis of
2008.
Rice for Asia and INDONESIA
indispensable staple food crop for billions of people
Consumption  139 kg/capita/year (Indonesia)
Asian countries are responsible for approximately 90% of the world
rice production and consumptions.
•Dominated by
Asian countries
•Distributed in
wide range of
climatic zones
FAOSTAT [2011]
Cont...
 Rice is still the Main Components of Food Security (80% of
national carbohydrate needs)
 Paddy field in Indonesia (8,106,562 million ha (MoA, 2012))
 40% Indonesian paddy field located in Java Island (60% of
national food production)
 Increasing of Demand (Quantity) + 1.5% / year
 in 2025 : the need of rice in Indonesia is around 58.6 million tons
(Dry Milled Rice) →12.91 million ha Paddy field
 2010 – 2014: Target is to maintain self-sufficiency of 5
commodities (rice and corn, soybean, sugar, & meat)
 Surplus target of rice : 10 million tons in 2014
Kepulauan Riau
Bangka Belitung
Papua Barat
DKI Jakarta
Maluku Utara
Maluku
Papua
Gorontalo
Sulawesi Barat
Sulawesi Tenggara
Sulawesi Utara
Bengkulu
Riau
Kalimantan Timur
Kalimantan Tengah
Nusa Tenggara Timur
Jambi
DI Yogyakarta
Sulawesi Tengah
Bali
Kalimantan Barat
4000000
Banten
6000000
Aceh
8000000
Nusa Tenggara Barat
10000000
Kalimantan Selatan
Sumatera barat
Lampung
Sumatera Selatan
Sumatera Utara
Sulawesi Selatan
12000000
Jawa Tengah
Jawa Timur
Jawa Barat
Ton
Rice production per-province (1993 – 2011)
Source: BPS, 2012
• Approximately 40.33% of those in Indonesia, which
is an area of ​3.25 million hectares are in Java.
• To support nearly 53.82% (36,831,357 tons) of
national food production.
• in 2011 the harvested area increased to 13.57
million hectares with productivity of 5.02 tons /
hectare.
2000000
0
300.00
250.00
239.00
257.39
261.23
265.12
200.00
150.00
100.00
50.00
0.00
46.02
42.74
2010
2015
53.36
49.55
2020
2025
Year
Population (million)
Rice needs million GKG/year
•
Agricultural information esp. cultivated area, growth and yield
of major crops → important for food policy and economic
planning.
•
At present: crop acreage, production & other agricultural
information → National Bureau of Statistics of Indonesia :
‐
Report summary of several administrative levels
‐
Sampling based on classical statistics (ubinan).
‐
Rice productivity data collected through the Crop Cutting
Survey using SUB-S form based on household approach by a
direct measurement in 2.5x2.5m crop cutting plot.
‐
The data collection is conducted in every subround (fourmonthly) with Sub-district Statistic Coordinator (called KSK
as coordinator of Sub Disrict Statistik) and KCD being the
enumerator.
 Remote sensing data is expected can support crop
monitoring and strengthening food security
 IAARD is going to determine to research strategy
to use remote sensing for food security program
State of the Art of Remote Sensing Utilization
for National Agriculture Development
• Identification of present landuse → paddy field and upland
agriculture in crop production centers, for supporting the
implementation and enforcement of UU Lahan Pertanian
Berkelanjutan.
• Updating and auditing land resources mapping & identification
to support : OPTIMIZING EXISTING AGRICULTURAL LAND
• Monitoring paddy growing stages, and estimating paddy
planting and harvesting area.
• Detecting flood or drought affected area → providing
recommendations for mitigation.
• Providing near real time information of paddy field condition by
integrating with other information (such as Cropping Calendar)
in an Integrated System Information for food stock policy.
 Updating more detailed map of paddy field by verifying and
using more precise satellite data
 Completing agricultural landuse planning for special
commodities and precision farming,
 Site selection of local food potential for food diversification
based on resources and post harvest handling,
 Auditing tertiary irrigation system for water management
 Monitoring agricultural crops production management,
 Agricultural hazards monitoring related to crop insurance.

Operationally used :
• Since 1972 : Land Resources Mapping (ICALRD , MoA)→
Recommendation for Agric. Planning → Aerial photograph, Landsat,
etc
• Since 2007 : Integrated / Dinamic Cropping Calendar
http://katam.info/main.aspx (IAHRI - ICALRD - IAARD – MoA) based
on Rainfall data
• Vegetation (Greeness) monitoring (LAPAN & BPPT) → MODIS

On going project since 2012 :
• Agricultural Land Resources Information System part of Agricultural
Resources Management Information System (ICALRD – IAARD – MoA)
→ Optic and SAR data
• Indonesia Rice Crop Monitoring from Space webgms.iis.u-
tokyo.ac.jp/DMEWS/INDONESIA (Collaboration ICALRD of MoA – JAXA
& Univ. Of Tokyo – LAPAN)
MOVING FORWARD
• Ministry of Agriculture has envisaged that RS and
GIS have a prominent role in promoting efforts for
supporting food security.
• Accurate information is indispensable for making
policies related to the spatial distribution of rice
fields, water resource management, annual
production projections, and market predictions.
• The major challenge of using remote sensing for
estimating rice and crop production area: 1)
increasing accuracy and 2) standardization of
models.
1. LAPAN : (Indonesian Agency for Aeronautic and Aerospace)
• Supply satellite data
• Methodology
• Support the availability UAV
2. Universities (IPB, UGM, IPB, ITS, UI, BINUS, dll):
• Methodology
• Capacity building
3. BPPT : (Agency Assessment for Application Technology)
• Methodology
4. Central Beureau Statistic & PUSDATIN of MoA:
• Field sampling methodology
• Field data measurement and field work for collecting data
Project Name
Institutions
1.
Asia Rice – GEOGLAM :
Group Earth Observation
Global Agriculture
Monitoring
Team:
JAXA (Japan), ISRO (India), GISTDA
(Thailand),, VAST/STI (Vietnam), LAPAN
(Indonesia), ICALRD/MOA (Indonesia),
MRC, IRSA (China)
Supported by :
SIMBIOSS (Australia), and RESTEC (Japan)
2.
SAFE – APRSAF : Satellite
ICALRD of MoA, LAPAN (Indonesia)
Aplication for Environment – JAXA, Univ of Tokyo, National Institute for
Asia Pasific Regional Space
Agro-Environmental Sciences - NIAES
Agency Forum
(Japan)
3.
RIICE : RS-Based Information
& Insurance for Crop in
Emerging Economies
ICALRD/IAARD-MoA (Indonesia), IRRI
(Phillipines), SARMAP (Switzerland)
Objective:
 To assess existing model using multi-spectral optical
remote sensing data as well as SAR data, for estimating
planted area, yield, and production of paddy.
 To apply methods or model to obtain a map of planted
area, yield, and production of rice derived from remote
sensing data
Expected Output of Year I (2013/14):
 Selected Satellite based model of estimating planted,
harvested area, and production of paddy in the center of
paddy area validated using ground truth data
 Paddy yield information at sub district level of acreage, area
harvested, and production of paddy derived from remote
sensing data analysis in in the center of paddy area.
Collaboration with Agencies
Executing Agency
• Excuting
Agencies
Activities
• LAPAN
• PUSDTAIN of MoA
• BPS
• Developing models of paddy cropping pattern in
Java island.
• Examining model to identify paddy growing stage
and its abilty to estimate yield.
• Conducting workshop & training
• Satellite data provision (ALOS AVNIR-2 and
• Supporting • JAXA
PALSAR, ALOS-2)
Agencies
• National Institute for
Agro-Environmental • Remote Sensing Application and Training: (1)
Rice yield estimation by SAR data backscatter,
Sciences (NIAES),
(2) The use of empirical model which use
Japan:
relationship between vegetation index and yield.
• Supporting for fieldwork & the use of rice
monitoring software
• Training, workshop, and seminar are matters to
be considered during the activity
• Technical supporter, Model development
• End Users
• Assist the automatic data processing needed for
the continuous monitoring.
• AIAT – IAARD of MoA • Conducting field surveys for validation of model
• Conducting workshop & seminar
• Local Government
 Satellite
data.
data analyzed : 16 days-composite MODIS
 Methods
used : EVI, using LAPAN Model to
estimate planted, harvested area, and production
of paddy in the center of paddy area validated
using ground truth data.
 Data
field collected from Subang area
Framework of operational use after this prototyping
Satellite data processing :
• digital analysis of satellite imagery,
• identifying paddy growing stage
• estimating paddy harvested area
and production of paddy
ICALRD – IAARD – MoA
LAPAN
Data Provider:
LAPAN
JAXA
Satellite data
preparation :
Inventory and
selection of basic
analytical methods
Preparation of information
(spatial & tabular):
paddy planted area, harvested
area, and estimates of paddy
production.
Data & Information
Updating
feedback
IAARD, LAPAN, BPS,
PUSDATIN of MoA
User:
BPS, PUSDATIN of MoA,
Agric. Local Office for
Food Crop
Web-GIS based
Information
 Remote sensing technology could be used as a second
opininon information for predicting rice area and rice yield.
 Improvement of accuracy and standardization of models
urgently needed for research
 Need sinergism of national institutional support the vision
of a successful RS +GIS/ Geo-spatial Technology in any
government organization.
TERIMA KASIH
21

similar documents