1. Project activities and outputs Final Review Meeting
Agriculture Information System Building Provincial Capacity for Crop Forecasting and Estimation
Project activities and outputs
Final Review Meeting
29 Sep 2016

2. Background
Reliable food security policy and proper agriculture land use planning depends on frequent and accurate information on crops productivity and agriculture land use statistics.
The traditional methods of crops statistics face the difficulties on timely deliverance of statistics and lack use of latest technologies like geospatial applications.
There was a need for an objective, standardized and possibly cheaper and faster technology to monitor agriculture and generate quality statistics.
In 2005, the Federal Government mandated SUPARCO to implement a satellite based crop monitoring program to ensure a prompt and temporal supply of agriculture information, with high level of accuracy. The result led to establish an international collaboration to improve CRSs capacity of integrating Remote Sensing data and advanced geospatial technologies in their crop monitoring tasks.

3. The Project
Improvement the capacity of provincial governments to collect, analyze and timely report on agricultural information
Focus on
Enhancing the integral use of remotely sensed satellite data into existing data collection and analysis
Developing complementary systems to improve crop area estimates and yield forecasts, as well as crop status monitoring and assessment

4. Specific Objectives
Improve CRSs capacity to forecast and estimate crop production through the use of remote sensing, field data, and other relevant information
Enhance CRSs capacity to produce timely market-oriented reports containing actionable information for farmers and other interested in the crop market

5. Beneficiaries
The Crop Reporting Agency, SUPARCO and the other government departments through more cost effective, timely, and reliable methods and technologies for producing agricultural statistics
The Government of Pakistan which will be better able to attract development investment with improvements in monitoring the country’s most important asset (i.e. agriculture)
Universities
The farmers of Pakistan who will be better able to plan their investments
The people of Pakistan who will have increased food security due to better agricultural statistics

6. Main Areas of Activities
Develop methods and tools to improve quality of agricultural statistics based on the integral use of geospatial information
Implement operational units at CRSs and Universities
Build human and technical capacity in integral use of remote sensing, GIS and statistics
Create knowledge base for scaling methods, tools, and capacities to other Pakistan entities and universities
Support Universities with equipment, human and technical capacity development, consultations
University of Agriculture, Faisalabad (UAF)
Sindh Agriculture University, Tandojam

7. Project outcomes
Land cover Punjab
Increased knowledge for the design and implementation of an operational agriculture survey that improves quality of statistics using geospatial data
Increased accuracy and decreased costs of field measurements and data collection
Implementing sustainable methodologies and tools that improve the quality of geospatial information used
Trained in country geospatial professionals capable to improve monthly crop forecasting bulletin
Dissemination of lessons learned from the project to other entities in Pakistan
Area frame sampling
GLAM Pakistan

8. Project Objectives and Outputs
Improve the capacity of two provincial agricultural authorities (Punjab and Sindh) to estimate and forecast crop production through the use of satellite imagery and field data, as well as other relevant information.
Improved approaches and survey methodology, peer reviewed, and validated for the generation of timely crop area estimates for major crops (provincial)
Revised field data collection methodology tested in the field in 2 provinces of Punjab and Sindh during the Rabi or Kharif season and
Set-up fully functional operational units in offices of the selected provincial Crop Reporting Services (Punjab and Sindh)
Trainings for staff of SUPARCO, CRS, and MINFAL in statistics, remote sensing, GIS and mobile computing to improve crop acreage and yield estimation.

9. Project Objectives and Outputs
Establish a capacity for two provincial agricultural crop reporting services (Punjab and Sindh) to provide crop estimates and forecasts to the public through regular and timely market-oriented reports containing actionable information useful for decision-making by farmers and other interested in the crop market.
“After action plan” that addresses how Pakistan can move forward in provincial level crop reporting after this project has ended.
Assessments showing provincial (Punjab and Sindh) crop reporting services capable of utilize remotely-sensed satellite imagery, field and other data.

10. Results Achieved Overall Benefits
Developed sustainable methods and tools which improve the quality of Pakistan's agricultural statistics based on the integral use of geospatial technology.
Built human and technical capacity in integral use of remote sensing, and GIS, and statistics.
Created a knowledge base for scaling methods, tools, and capacities to other departments and ministries within Pakistan.
Within the scope of the project, results will be used to support other developing countries as part of FAO's Global Strategy for Agriculture within South Asia.

11. Results Achieved Project components
Capacity building of Provincial Crop Reporting Services & Universities
Geospatial Technologies for Agriculture Information Systems
Crop Information Portal
Global Agricultural Monitoring of Pakistan (GLAM- Pakistan)
Mobile Agricultural Geo-tagging Information System (MAGIS)
Area Frame Sampling System (AFSS) Automation using smart phones
Land Cover database of Pakistan (LCCS)
Crop Masks of major Rabi and Kharif crops
Improvement in Area Frame Sampling System
Market Outlook improvement
Improvement of crop reporting

12. Activities by Project’s Objective / Output

13. Output 1.1: Improved approaches and survey methodology, peer reviewed, and validated for the generation of timely crop area estimates for major crops (provincial)
Activities
1.1: Assess the current local methodology and identify areas for improvement;
1.2: Improve the Area Frame approach through the development of a high resolution land cover dataset in Punjab and Sindh provinces;
1.3: Undertake 8 training workshops in the use and integration of satellite imagery data and approaches;
1.4: Convene technical consultations for lessons learning;
1.5: Prepare a detailed technical report;
1.6: Organize a workshop to review and discuss the findings of the parallel surveys and validate the methodology;
1.7: Review the potential of scaling up the results of the project to other;
1.8: Enhance existing crop forecasting reports and support their dissemination;
1.9: Demonstrate advantages of cooperative use and sharing of field, imagery and derived data.

14. Output 1.1: Improved approaches and survey methodology, peer reviewed, and validated for the generation of timely crop area estimates for major crops (provincial)
Assess methodological improvements:
A series of technical consultations sessions and meetings were held with provincial CRSs and Universities to assess methodology, develop capacity and assist in using tools/data and implemented methods of field survey and crop monitoring, estimation and forecasting.
Baseline technical reports were produced to support description of current status and recommendations for improved methodologies of crop estimates and forecasts.

15. Output 1.1: Improved approaches and survey methodology, peer reviewed, and validated for the generation of timely crop area estimates for major crops (provincial)
Improvement of field survey:
The Automatic Ground Information Collection System (AGICS) was developed by SUPARCO in consultation with CRSs to facilitate collection and transmission of data related to crops by using smartphones with real time data transmission.
The information collected is used for improving accuracy assessment which enhanced the reliability of data on crop estimates.
CRSs of Punjab and Sindh have been equipped and trained in using these tools during their field surveys, enhancing the reliability of collection, storage and analysis

16. Output 1.1: Improved approaches and survey methodology, peer reviewed, and validated for the generation of timely crop area estimates for major crops (provincial)
Tree Closed
Water Body
Tree Crop
Land cover database:
To improve the Area Frame approach, a national land cover mapping program was initiated by SUPARCO with the development of a high resolution land cover datasets. The first three completed provinces are Punjab, Sindh and KP-FATA. Baluchistan and GB are in progress.
FAO’s land cover approach/tools and standard classification system LCCS were used to create a harmonized and extensive representation of land cover features.
Land Cover atlases of Punjab, Sindh, and KPK-FATA have been produced illustrating land cover information at district level in aggregated and cartographic form as well as tabular statistics per district.

17. Land Cover of Punjab Province: Details at district level

18. Output 1.1: Improved approaches and survey methodology, peer reviewed, and validated for the generation of timely crop area estimates for major crops (provincial)
Crop Masks:
Spatial information about crops (crop mask) can be effectively used in many cases: appropriate risk management strategies with respect to food insecurity, biodiversity and environmental sustainability, flooding impact studies, change analyses, and more.
SUPARCO, under the technical supervision of FAO, has developed the methodology to create standardized and updated crop mask both for Rabi and Kharif crops using high resolution remote sensing imagery.
Reports have been produced on crop masking methodology and results for the season (wheat and potato) and (rice, cotton and sugarcane)

19. Output 1.1: Improved approaches and survey methodology, peer reviewed, and validated for the generation of timely crop area estimates for major crops (provincial)
Crop Masks:
Crop masks are produced annually for main RABI (wheat and potato) and KHARIF (rice, cotton and sugarcane) crops.
Reports are being published on crop masking methodology and results for the season and
ESRI spatial database for and have been documented and published through the FAO metadata catalogue Geonetwork. Datasets are delivered by crop type and administrative zone.

20. Wheat crop Mask: Punjab South Zone

21. 27 trainings / technical workshops and 260 participants
Output 1.1: Improved approaches and survey methodology, peer reviewed, and validated for the generation of timely crop area estimates for major crops (provincial)
27 trainings / technical workshops and 260 participants
Training workshops in the use and integration of satellite imagery data and approaches:
Objective to improve the capacity of provincial CRS departments/governments and University staff to collect, analyze and report on timely agricultural information.
Series of local and foreign training workshops and technical consultations sessions were conducted.
Focus on utilization of global positioning systems, mobile computing, Remote Sensing and GIS and field data collection.
With 27 trainings/technical workshops and around 260 participants, local staff has been qualified in using methods and tools for crop estimates, forecast and reporting.

22. Output 1.1: Improved approaches and survey methodology, peer reviewed, and validated for the generation of timely crop area estimates for major crops (provincial)
Training workshops in the use and integration of satellite imagery data and approaches:
Targeted Local Trainings (remote sensing, GIS, area frame, modelling, Crop Portal use, GLAM use, analysis and statistics of crop data)
Local Workshops (Agriculture Information System at Islamabad, Pakistan)
Targeted Foreign Trainings (Remote Sensing at University of Maryland-Washington DC)
Market Outlook (Commodity Balance Sheet compilation and Shock Impact Simulation Model implementation)

23. Trainings and study tours
27 trainings / technical workshops
260 participants from CRSs, SUPARCO, Universities and more

24. More on capacity development: tools and data
Land cover mapping training at Islamabad
Workshop on Crop Information Portal at Lahore
GLAM training at University of Agriculture, Faisalabad
Training at the University of Maryland

25. More on capacity development: equipment
Briefing to Secretary Agriculture Punjab on field data transmission through smart phones
Secretary Agriculture Sindh handing over smart phones for field data transmission
MAGIS and GLAM system being installed at SUPARCO Islamabad
Training on RS/GIS Application at NCRG, Karachi

26. More on capacity development: field data collection
Training/testing mobile application (AFSS)
Field data collection

27. More on capacity development: field data collection
Jins-war Proforma used for Gardawari.
Transmission of geo-tagged field data (jins-war data) through smart phones
Training of
CRS officials

28. Output 1.2: Revised field data collection methodology tested in the field in 2 provinces of Punjab and Sindh during the Rabi or Kharif season and
Activities
2.1: Arrange procurement, transportation and training of the GPS/PDA equipment;
2.2: Implement a field campaign in the cropping season;
2.3: Organize workshop to review and discuss the findings.

29. Output 1.2: Revised field data collection methodology tested in the field in 2 provinces of Punjab and Sindh during the Rabi or Kharif season and
Activities
2.1: Arrange procurement, transportation and training of the GPS/PDA equipment;
2.2: Implement a field campaign in the cropping season;
2.3: Organize workshop to review and discuss the findings.

30. Output 1.2: Revised field data collection methodology tested in the field in 2 provinces of Punjab and Sindh during the Rabi or Kharif season and
Equipment for field survey, data analysis and dissemination:
All necessary automation and analysis equipment and software under the programme have been procured, installed and made operational at all the five locations: CRSs of Punjab and Sindh, UAF, SAUT and SUPARCO
Secretary Agriculture Sindh handing over smart phones at inauguration of CRS Nucleus lab

31. Nucleus Lab at CRS Sindh Nucleus Lab at CRS Punjab
Output 1.2: Revised field data collection methodology tested in the field in 2 provinces of Punjab and Sindh during the Rabi or Kharif season and
Strengthening of Nucleus Lab:
Need for strengthening labs already established at provincial CRS HQs to make them familiar with Remote Sensing
Additional equipment was supplied trainings provided for efficient running of the laboratories
Nucleus Lab at CRS Sindh
MAGIS and GLAM system installed at Sindh Agriculture University, Tandojam (SAUT)
MAGIS and GLAM system installed at University of Agriculture, Faisalabad (UAF)
Nucleus Lab at CRS Punjab

32. Output 1.2: Revised field data collection methodology tested in the field in 2 provinces of Punjab and Sindh during the Rabi or Kharif season and
Field survey automation tools:
Applications for smartphone were developed and implemented for field data collection, transmission and storage tasks.
The Mobile Agricultural Geo-Tagging Information System (MAGIS) is a mobile based application which has been developed to support CRSs and their crop reporters in improving data collection efficiency.
The Area Frame Sampling System (AFSS) is mobile based web app for real time collection of ground data along with ground photograph in support of automation of area frame survey in Punjab and Sindh provinces.
Mobile Agricultural Geo-Tagging Information System (MAGIS)

33. Output 1.3: Set-up of fully functional operational units in offices of the two selected provincial Crop Reporting Service (Punjab and Sindh) whereby a small team is fully able to provide valuable agricultural crop statistics derived from the integration of ground truth data and earth observation satellite systems.
Activities
3.1: Continue design, and testing of improved sampling strategies (by land cover data);
3.2: Provide support to increased use of LCCS in the area frame sampling;
3.3: Produce report on the use of LCCS in agricultural surveys;
3.4: Continue refinement of sampling design for crops survey through the area frame approach.

34. Output 1.3: Set-up of fully functional operational units in offices of the two selected provincial Crop Reporting Service (Punjab and Sindh) whereby a small team is fully able to provide valuable agricultural crop statistics derived from the integration of ground truth data and earth observation satellite systems.
Improved Area Frame sampling strategy and optimization through land cover data:
Area frame methodology is a cornerstone of probability sampling.
By optimizing samples, satellite based Area Frame improves reliability and timeliness of agriculture statistics with minimum resources.
For the last 8 years, SUPARCO and FAO have developed and tested the methodology to estimate area under different major crops.
The area frame sampling design has been reviewed in Punjab and Sindh and new polygon were introduced in Central Punjab, breaking into three zones and similarly two new zones were introduced in Sindh on the left bank of Indus. The ground truthing teams were assigned to carry out survey of these new polygons to test the validity of improvement.
Agriculture zones/ Strata/PSU
Punjab South Zone broken down into PSU (red)
Sampling Unit

35. Output 1.3: Set-up of fully functional operational units in offices of the two selected provincial Crop Reporting Service (Punjab and Sindh) whereby a small team is fully able to provide valuable agricultural crop statistics derived from the integration of ground truth data and earth observation satellite systems.
Improved Area Frame sampling strategy and optimization through land cover data:
The Land Cover database has helped improve the existing Area Frame Sampling system by:
Providing baseline Agriculture and Non Agriculture Spatial information;
Refining the stratum classification by allocating the improved stratum class;
Comparative analysis.
Agriculture zones/ Strata/PSU
KP-FATA Land Cover

36. Improved data collection methodology and tools:
Output 1.3: Set-up of fully functional operational units in offices of the two selected provincial Crop Reporting Service (Punjab and Sindh) whereby a small team is fully able to provide valuable agricultural crop statistics derived from the integration of ground truth data and earth observation satellite systems.
Improved data collection methodology and tools:
The procurement and distributions of smartphones/GPSs kits and the development of ad-hoc web applications have dramatically improved quality, accuracy and timing of field survey by CRSs. Tests and trainings have been conducted for the purpose.
Mobile Agricultural Geo-Tagging Information System (MAGIS)
Area Frame Sampling System (AFSS) Automation through Mobile Technology
The University of Maryland has been piloting the use of the MAGIS/GeoODK Android application for electronic field data collection in collaboration with the Crop Reporting Services of Punjab and Sindh Provinces
SUPARCO developed Android based Area Frame Sampling System (AFSS) application tool that has been made available to CRSs for real-time transmission of geo-tagged ground data along with photograph.

37. Output 1.4: Trainings for staff of SUPARCO, CRS, and MINFAL in statistics, remote sensing, GIS and mobile computing to improve crop acreage and yield estimation, and improve the capability of the provincial CRSs to utilize satellite imagery and other data for producing crop estimation and forecasts.
Activities
4.1: Assess local training needs in each of 2 province;
4.2: Develop training material for short in-country training ;
4.3: Undertake training activities through the University of Maryland (UMD);
4.4: Development of protocols and/or procedures to address potential future decommissioning and/or introduction of new satellite;
4.5: Conduct specialized, short-term US-based training.

38. Provincial Shock Impact Simulation Model
Output 1.4: Trainings for staff of SUPARCO, CRS, and MINFAL in statistics, remote sensing, GIS and mobile computing to improve crop acreage and yield estimation, and improve the capability of the provincial CRSs to utilize satellite imagery and other data for producing crop estimation and forecasts.
Capacity development:
The needs for training initiatives have been identified continuously, adjusting the training programme of following events according to such evolving needs.
The FAO model for outlook and exogenous shocks (SISMOD) was developed for Sindh and Punjab.
Econometric shock simulation model to forecast possible food gaps and assistance needs.
Training on provincial/district level commodity balance sheet and SISMod for market monitoring and food security analysis was provided.
Provincial Shock Impact Simulation Model

39. Geo GLAM Pakistan Application
Output 1.4: Trainings for staff of SUPARCO, CRS, and MINFAL in statistics, remote sensing, GIS and mobile computing to improve crop acreage and yield estimation, and improve the capability of the provincial CRSs to utilize satellite imagery and other data for producing crop estimation and forecasts.
Capacity development:
The University of Maryland held a 2 weeks foreign training in Washington DC on “Pakistan Satellite-Based Crop Monitoring”
Topics addressed:
Agricultural Monitoring using remote sensing and GIS
Geo GLAM
National and Global crop forecasting and reporting of crop statistics
Designing and implementation of area frame
MAGIS
How FAS produce forecasts for Pakistan
GLAM system installation and maintenance
Demonstration of crop information portal
Decision
10 participants from CRSs, SUPARCO and Universities
Geo GLAM Pakistan Application

40. Output 1.4: Trainings for staff of SUPARCO, CRS, and MINFAL in statistics, remote sensing, GIS and mobile computing to improve crop acreage and yield estimation, and improve the capability of the provincial CRSs to utilize satellite imagery and other data for producing crop estimation and forecasts.
Training Materials:
Full details of the techniques adapted and procedures followed were published in the form of technical reports to share the experiences of the project:
Pakistan: Advanced Training on Monitoring of Crops through Satellite Technology;
Pakistan: How SUPARCO Makes Crop Forecasts and Estimates based on integral use of RS data;
Methodology/working manual for preparation of Crop Masks;
Reports on provincial (Sindh and Punjab) crop masks for Rabi (wheat and potato) and Kharif (sugarcane, cotton and rice) crops.

41. Output 2.1: Development of an “after action plan” that addresses how Pakistan can move forward in provincial level crop reporting after this project has ended particular emphasis will be developed on what happens after the project’s conclusion, and explicitly built on what was covered in the project.
Activities
1.1: Analyse findings and learning from the project vs the previous activities for the design and implementation of robust, simple, and reliable sampling survey and field collection methods;
1.2: Prepare a plan for scaling up to national level of the methodology and tools tested in the field;
1.3: Creation of an improved crop forecasts and commodity report outlook.

42. Crop reporting and timely information dissemination:
Output 2.1: Development of an “after action plan” that addresses how Pakistan can move forward in provincial level crop reporting after this project has ended particular emphasis will be developed on what happens after the project’s conclusion, and explicitly built on what was covered in the project.
Crop reporting and timely information dissemination:
Timely information dissemination plays a significant role in policy formulations and management regarding food security and environmental sustainability
Crop reporting and timely information dissemination system include;
Monthly Crop Bulletin (Pak-SCMS)
Provincial CRSs bulletins
Technical reports
E-bulletins
Project website

43. Crop reporting and timely information dissemination:
Output 2.1: Development of an “after action plan” that addresses how Pakistan can move forward in provincial level crop reporting after this project has ended particular emphasis will be developed on what happens after the project’s conclusion, and explicitly built on what was covered in the project.
Crop reporting and timely information dissemination:
Monthly Crop Bulletin (Pak-SCMS)
~ 30 pages (Sep 2016)
Jan 2011 – Sep 2016
Example of content:
CROP SITUATION
(NDVI): CROP GROWTH PROFILES AT DIVISIONAL & PROVINCIAL LEVEL
VEGETATION DIFFERENCE
TEMPORAL VEGETATION CHANGES
AGRO-MET CONDITIONS
DAILY HYDROLOGICAL STATUS AT INDUS BASIN
IRRIGATION WATER SUPPLY SITUATION
FERTILIZER SITUATION
FIELD VIEW
AGRICULTURE RECOMMENDATIONS

44. Normalized Difference Vegetation index Profile at Division Level
Output 2.1: Development of an “after action plan” that addresses how Pakistan can move forward in provincial level crop reporting after this project has ended particular emphasis will be developed on what happens after the project’s conclusion, and explicitly build on what was covered in the project.
Normalized Difference Vegetation index Profile at Division Level
Crop reporting and timely information dissemination:
Provincial CRSs monthly bulletins
~ 24 pages (Aug 2016)
Mar 2014 – Aug 2016
Example of content:
Crop Situation Summary
Average Market Price
Normalized Difference Vegetation index (NDVI Graph) Growth Profile at Division Level, Average maximum & minimum
Monthly Temperature & Rainfall
Whether summary and expected in current month
Irrigation water supply and canal water withdrawal
Tarbela and Mangla dam water inflow and outflow
Pest Scouting Report
Kharif Crop Situation
Sugarcane crop area estimate

45. Crop reporting and timely information dissemination:
Output 2.1: Development of an “after action plan” that addresses how Pakistan can move forward in provincial level crop reporting after this project has ended particular emphasis will be developed on what happens after the project’s conclusion, and explicitly build on what was covered in the project.
Crop reporting and timely information dissemination:
Technical Reports
Pakistan: How SUPARCO Makes Crop Forecasts and Estimates based on integral use of RS data
Pakistan: Advanced Training on Monitoring of Crops through Satellite Technology
Punjab CRS: Base Line Survey
Sindh CRS: Base Line Survey

46. Documents
Overall list of documents produced by the project

47. Crop reporting and timely information dissemination:
Output 2.1: Development of an “after action plan” that addresses how Pakistan can move forward in provincial level crop reporting after this project has ended particular emphasis will be developed on what happens after the project’s conclusion, and explicitly build on what was covered in the project.
Crop reporting and timely information dissemination:
E-bulletins (tri-monthly)
Aug 2013 – Jun 2016
dissemination
Based on project website
Example of content:
Focus on: main article
Hot topics: 2 additional topics
What’s new of current period
Events of current and future
Seminars/Conferences
Relevant Publications
Advertised Jobs

48. Crop reporting and timely information dissemination:
Output 2.1: Development of an “after action plan” that addresses how Pakistan can move forward in provincial level crop reporting after this project has ended particular emphasis will be developed on what happens after the project’s conclusion, and explicitly build on what was covered in the project.
Crop reporting and timely information dissemination:
Project website
Jan 2012 – Sep 2016
Temporarily FAO hosted
Main Menu:
Project
Methodologies and Tools
Geospatial Systems
Data and Information
Bulletins and Reports
Case Studies
Capacity Development
Documents
News / Events

49. Output 2.2: Assessments showing provincial (Punjab and Sindh) crop reporting services capable to utilize remotely-sensed satellite imagery, field and other data for producing and making available to the public timely market-oriented reports on crop estimation and forecasts.
Activities
2.1: Review current approach for the compilation of periodic/monthly crop bulletin/forecast; refine the reports; and improve their quality, content, and timeliness.

50. Crop Information Portal
Output 2.2: Assessments showing provincial (Punjab and Sindh) crop reporting services capable to utilize remotely-sensed satellite imagery, field and other data for producing and making available to the public timely market-oriented reports on crop estimation and forecasts.
Geospatial Technologies for Agriculture Information Management, Analysis and Dissemination:
The high quality agricultural statistics are important to formulate policy and planning for food security. The advancement in Earth observation, Navigation and Communication satellites along with availability of high bandwidth mobile communication make it feasible to report information, about a vast area in near real time. Implemented systems are:
Global Agricultural Monitoring (GLAM) for Pakistan
Crop Information Portal (CIP)
Mobile Agricultural Geo-Tagging Information System (MAGIS)
Area Frame Sampling System (AFSS), Automation through Mobile Technology
Geo GLAM
AFSS
Crop Information Portal
MAGIS

51. Output 2.2: Assessments showing provincial (Punjab and Sindh) crop reporting services capable to utilize remotely-sensed satellite imagery, field and other data for producing and making available to the public timely market-oriented reports on crop estimation and forecasts.
Geospatial Technologies for Agriculture Information Management, Analysis and Dissemination:
Global Agricultural Monitoring (GLAM) for Pakistan
Set of tools for customized queries to compare current season conditions with previous seasons or time steps within the current season
Geo GLAM
The system includes
Image visualization/ downloading
Image masking
Vegetation condition monitoring
Graphical interpretation
Automated generation of NDVI/NDWI graphs
Histogram analysis

52. Crop map of average wheat production period 2008-2012
Output 2.2: Assessments showing provincial (Punjab and Sindh) crop reporting services capable to utilize remotely-sensed satellite imagery, field and other data for producing and making available to the public timely market-oriented reports on crop estimation and forecasts.
Architecture
Geospatial Technologies for Agriculture Information Management, Analysis and Dissemination:
Crop Information Portal (CIP)
Web based, open source platform developed to support the analysis and dissemination of Pakistan's crop data and related climatic, agronomic, hydrologic and economic variables.
The system includes
Static Web section for system's resources sharing
Modules of crop and related variables filtering and analysis
WEB mapping area for local or remote datasets display and analysis
Metadata catalogue (Geonetwork) to describe and disseminate geospatial information.
Crop map of average wheat production period

53. Three operational implementations: National instance at SUPARCO
Output 2.2: Assessments showing provincial (Punjab and Sindh) crop reporting services capable to utilize remotely-sensed satellite imagery, field and other data for producing and making available to the public timely market-oriented reports on crop estimation and forecasts.
Geospatial Technologies for Agriculture Information Management, Analysis and Dissemination:
Crop Information Portal (CIP)
Web based, open source platform developed to support the analysis and dissemination of Pakistan's crop data and related climatic, agronomic, hydrologic and economic variables.
Three operational implementations:
National instance at SUPARCO
Provincial instance at CRS Punjab
Provincial instance at CRS Sindh

54. Output 2.2: Assessments showing provincial (Punjab and Sindh) crop reporting services capable to utilize remotely-sensed satellite imagery, field and other data for producing and making available to the public timely market-oriented reports on crop estimation and forecasts.
Geospatial Technologies for Agriculture Information Management, Analysis and Dissemination:
MAGIS
Allow crop reporters to collect digital, geo-referenced data in the field and relay these data via the cell phone network or via internet
AFSS
Android based smart phones with application software have been made available to CRS Punjab, through the project, for real-time transmission of geo-tagged field surveys data
The University of Maryland has been piloting the use of the MAGIS/GeoODK Android application for electronic field data collection in collaboration with the Crop Reporting Services of Punjab and Sindh Provinces
SUPARCO developed Android based Area Frame Sampling System (AFSS) application tool that has been made available to CRSs for real-time transmission of geo-tagged ground data along with photograph.

55. Sustainability
The project provides local institutions with methods and tools to produce higher quality agricultural statistics in a more cost efficient manner
The project successfully raised the capacity within the partner institutions and stakeholders to access and use tools and data, to ensure continuous functioning and applications of methodologies and techniques to monitoring, estimates areas and forecast yields of crops in Pakistan.
The project was aligned to UNDAF, CPFs and Organizational Results. The project does not tackle inequalities directly.
Implemented technologies were designed for simplicity of use to enhance the chance of technical sustainability. Trainings were provided to relevant IT staff members in the host institutions. Routine system maintenance is similar to that normally associated with other web-based applications and is expected to be within the capacity of the IT staff of the host institutions.
The improvement realized with this project will be sustained under the SUPARCO and CRS traditional (and long standing) funding levels from the Government of Pakistan.
The project promotes self-reliance and sustainability by providing SUPARCO and CRS with methods and tools to produce higher quality agricultural statistics in a more cost efficient manner.
The project successfully raised the capacity within the partner institutions and stakeholders to access and use tools and data, to ensure continuous functioning and applications of methodologies and techniques to monitoring, estimates areas and forecast yields of crops in Pakistan.
The project was aligned to UNDAF, CPFs and Organizational Results. The project does not tackle inequalities directly.
The technologies provided through the project were designed for simplicity of use to enhance the chance of technical sustainability. Technical training for maintenance of tools and geospatial systems was provided to relevant IT staff members in the host institutions. Routine system maintenance is similar to that normally associated with other web-based applications and is expected to be within the capacity of the IT staff of the host institutions.
The improvement realized with this project will be sustained under the SUPARCO and CRS traditional (and long standing) funding levels from the Government of Pakistan

56. Elements of success
Improved approach and survey methodology for the generation of timely crop area estimates for major crops at provincial level in Pakistan.
Improved capacity of officials of provincial CRSs, Faculty members of Universities to use geospatial technology for rapid and cost effective data collection and reliable crops statistics generation.
Strengthened geospatial nucleus laboratories at Punjab and Sindh CRS headquarters.
Improved reporting capacity of different stakeholders of the project by taking advantage of tailor made systems such as GLAM, MAGIS, AFSS and Crop Information Portal which meet their requirements in crop monitoring, data collection and analysis, data access and information dissemination.
Developed new and highly accurate, standard based, land cover baseline for the Provinces of Sindh, Punjab and KP to support the improvement of the area frame sampling and crop estimation programs. This baseline is fundamental also for future applications such as agro-ecological zoning, digital soil fertility mapping, land suitability, land use land cover planning, climate change studies and precision agriculture etc.

57. Follow-up Actions
The project has paved the way for future geospatial technology based studies such as agro-ecological zoning, digital soil fertility mapping, land suitability, land use land cover planning, climate change studies and precision agriculture etc.
The spin offs of the current project and extension of technology to other fields through national and international support shall help improve the situation and address various issues impeding timely flow of quality data and its sharing with public.
FAO will be able to scale the lessons learned in this project to other countries worldwide as part of FAO’s Global Strategy for Agriculture.

58. Project activities and outputs Final Review Meeting
Agriculture Information System Building Provincial Capacity for Crop Forecasting and Estimation
Project activities and outputs
Final Review Meeting
29 Sep 2016