Presentation on theme: "1 www.litbang.deptan.go.id Indonesian Agency for Agricultural Research and Development Indonesian Center for Agricultural Land Resources Research and Development."— Presentation transcript:
1 www.litbang.deptan.go.id Indonesian Agency for Agricultural Research and Development Indonesian Center for Agricultural Land Resources Research and Development Indonesian Agency for Agricultural Research and Development Indonesian Center for Agricultural Land Resources Research and Development Assessment of drought impact on rice production in Indonesia by satellite remote sensing and dissemination with web-GIS Assessment of drought impact on rice production in Indonesia by satellite remote sensing and dissemination with web-GIS Presented at Workshop on Crop Monitoring and Food Security, the 34th ACRS 2013, Bali-Indonesia, 22 October 2013 Rizatus Shofiyati, Wataru Takeuchi, Soni Darmawan, and Parwati Sofan
Source: http://www.bnpb.go.id Background Floods and droughts are common disaster in Indonesia -Flood occured 1,548 -Drought occured 960 960 1,548 1,624,260 1,019,123 323,658 Agricultural area that suffered disasters : -Drought : 1,624,260 -Flood : 1,019,123 -Landslides : 323,658 National Disaster Management Berau of Indonesia (BNPB) : 2000 - 2007 Presented by Lapan (2011)
Drought Effects on Rice Crop Damage in Indonesia Source : data processed from the Directorate General of Food Crops Protection Area damage (ha)
Decreasing of Crop Production Drought Year (El nino) -0.33% -5.85% 45.0 47.5 50.0 52.5 Paddy Crop production (x 10 6 tons) Year Average 49.5 million tons 0.0 2.5 5.0 7.5 10.0 12.5 15.0 17.5 20.0 19931994199519961997199819992000 Maize Cassava
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 / MoAs with Related Agencies FrequencyInstitutionsActivities / OutputUtility 2x / Year BMKGrelease prospect of season typeseason type IAHRI (under coordination IAARD) BMKG have discussions and issue weather zone and prediction weather zone and prediction 3x / Year 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 so- called predictive rice production numbers.
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 Executing AgencyActivities Excuting Agencies 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 Agencies JAXA 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, local government unit farmers Conducting field surveys for validation of model Conducting workshop & seminar
Overview of the Activities Activities LAPANICALRD - IAARD 2010/112011/122012/132013/14 R & D Technology / Prototype Product Operational Developing Drought Model (Research Activities) Model Validation Developing Web-GIS Workshop Implementating model for operational use Dissemination Applying Model
Integration of Cropping Patterns, Seasonal Rainfall and Satellite Image Analysis POTENTIAL CROPPING CALENDAR (IAARD) SEASONAL RAINFALL PREDICTION (BMKG) DROUGHT IMAGE ANALYSIS (ICALRD) WET: PS1, PS2, PS3 NORMAL: PS1, PS2, PS3 DRY: PS1, PS2, PS3 FORECAST OF MONTHLY RAINFALL (mm/month) PROSPECT OF BEGINNING OF SEASON PROSPECT OF SEASON TYPE (WET, NORMAL, DRY) NDVI KBDI VHI VCI Data Used: Rainfall Data Data Used: MODIS, MTSAT AMSER-E ALOS AVNIR-2 & PALSAR (acq before May 2011)
Drought Information System Satellite Data Local Government Farmer Drought Information Rainfall Data Extension Officer Season Prediction by BMG Cropping Calendar by IAARD updating integrated cropping calendar RECOMMENDATIONS : Information of drought vulnerability Planting time Drought Information System
Method & Data Used Vegetation Condition Index (VCI) associates with moisture condition of vegetation: Thermal Condition Index (TCI) associates with thermal condition of vegetation: Vegetation Health Index (VHI) represents overall vegetation health: Kogan, 1990
Source: Takeuchi et al, 2012 VCI & LSWC to Identify Crop Pattern and Intensity
Source: Takeuchi et al., 2012 KBDI & LSWC to Identify Drought in Indramayu
Crop Pattern and Intensity in Java Island by MODIS
Existing Crop Calendar #Sowing MonthHarvest MonthNotes 1OctoberFebruaryNorthern coast of West Java (Karawang, Subang, Indramayu) 2MarchJune Northern coast of West Java (Karawang, Subang, Indramayu) 3JulyOctober*)Northern coast of West Java (Karawang, Subang, Indramayu) 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.) *) Secondary crops (maize, soybean, longbean), the harvest time is around August
Guidance of Crop Calender 2012-2013 (IAARD 2012)
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
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 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 Data Provider: LAPAN JAXA Data & Information Updating Web-GIS based Information : Area affected of drought Recommendation : planting time, crop, etc Web-GIS based Information : Area affected of drought Recommendation : planting time, crop, etc Preparation of information (spatial & tabular): Agriculture affected area by drought, drought impact to paddy planted area, harvested area, and paddy production. IAARD, LAPAN, BPS, PUSDATIN of MoA User: Farmer via extension officer, Agric. Local Office for Food Crop feedback
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
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