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

Ton

12000000 10000000 8000000 6000000 4000000 2000000 0

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.

300.00

250.00

200.00

150.00

100.00

50.00

0.00

239.00

42.74

257.39

46.02

261.23

49.55

265.12

2010 2015 Population (million) 2020 2025

Year

Rice needs million GKG/year 53.36

• • 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 (four monthly) 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

1.

2.

Project Name

Asia Rice – GEOGLAM : Group Earth Observation Global Agriculture Monitoring SAFE – APRSAF : Satellite Aplication for Environment – Asia Pasific Regional Space Agency Forum

Institutions

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) ICALRD of MoA, LAPAN (Indonesia) JAXA, Univ of Tokyo, National Institute for Agro-Environmental Sciences - NIAES (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 Activities • • Excuting Agencies • Supporting Agencies End Users • • • • • • • LAPAN PUSDTAIN of MoA BPS JAXA National Institute for Agro-Environmental Sciences (NIAES), Japan: • • • • • • • 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 PALSAR, ALOS-2) Remote Sensing Application and Training: (1) Rice yield estimation by SAR data backscatter, (2) The use of empirical model which use 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 AIAT – IAARD of MoA Local Government • • • • Technical supporter, Model development Assist the automatic data processing needed for the continuous monitoring.

Conducting field surveys for validation of model Conducting workshop & seminar

 Satellite data analyzed : 16 days-composite MODIS data.

 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

Data Provider: LAPAN JAXA

Satellite data preparation : Inventory and selection of basic analytical methods • • • Satellite data processing : digital analysis of satellite imagery, identifying paddy growing stage estimating paddy harvested area and production of paddy

ICALRD – IAARD – MoA LAPAN

Preparation of information (spatial & tabular): paddy planted area, harvested area, and estimates of paddy production.

IAARD, LAPAN, BPS, PUSDATIN of MoA

Data & Information Updating feedback

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

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