Agriculture Information System Building Provincial Capacity for Crop Forecasting and Estimation John Latham DDN 1

Outline Project background Project objectives Details on key actions and activities SUPARCO role 2

General Context Improvement of the capacity of the federal and provincial governments to collect and analyze agricultural information through the development of efficient data systems and market outlook reporting is fundamental for the timeliness and quality of information available to public and private sector decision makers. Accurately estimating and forecasting agriculture statistics is essential to a country’s economy, financial stability, and development. In Pakistan, traditional list frame survey has proved to produce discrepancies in crop estimates. A rigorous analysis of area frame versus list frame designs must be completed so that the costs and benefits of each methodology can be identified and a robust country-wide survey can be designed. 3

Background The project concerns the improvement of the capacity of provincial governments to collect, analyze and report on timely agricultural information and strengthening universities for supporting provincial CRSs, initially of Punjab and Sindh provinces. It focuses on enhancing and improving current systems for the integral use of remotely sensed data into existing data collection, analysis, and dissemination mechanisms building on and using indigenous capacities supported by additional capacities of FAO, UMD and USDA. It also includes the development of complementary systems to integrate remotely-sensed data for improving crop status monitoring, area estimates and yield forecasting in collaboration with SUPARCO. 4

1.Improve capacity to estimate and forecast crop production through the use of satellite imagery and field data Area Frame sampling system Improved crop yield modeling Land cover database – stratification & sample allocation Crop masks Capacity building of Provincial Crop Reporting Services & Universities 2.Improve capacity to provide crop estimates and forecasts to the public Fully functional operational units Geospatial Systems i.Crop information portal ii.Global Agricultural Monitoring (GLAM) iii.Smart phone application (MAGIS) iv.Area Frame Sampling System (AFSS) Automation Through Mobile Technology Crop reporting: bulletins, newsletter Market outlook improvement Overview Objectives and Outputs 5

Satellite based Area Frame Sampling System Objective 1: Improve capacity to estimate and forecast crop production through the use of satellite imagery and field data 6

SUPARCO uses satellite based area frame sampling, a fully operational system for the estimation of crop areas The satellite based area frame technique uses a stratification process to group homogenous areas in order to use statistical inference to estimate crop areas Sampling Unit Punjab South Zone brokendown into PSU (red) Agriculture zones/ Strat/PSU Satellite based Area Frame Sampling 7

Punjab and Sindh provinces had been divided into 608,000 segments of 30Ha. Total 314 segments were selected out of population (608,000). Hence sampling ratio is about 0.05%. All segments are digitized on physical boundaries having an area of about Ha Formula for area estimate is: Formula for calculating variance Satellite based Area Frame Sampling 8

Regression estimates Results are issued after two weeks of the second acquisition of the cropped area by SUPARCO and about 5-6 months earlier than the provincial Crop Reporting Services estimates. Uses twice image coverage for major crops. CV's for each crop are calculated but correlation between ground information and classified crop pixels is not calculated Study had been carried out implementing regression estimator on Sindh for several crops each season and year. 9

Comparison area frame/list frame results 10

Area (000 ha) Production (000 tons) Yield (kg/ha) Wheat 11

Improved Crop yield modeling using GLAM data Objective 1: Improve capacity to estimate and forecast crop production through the use of satellite imagery and field data 12

Blend of Satellite and Ground Systems Ancillary Ground Data SPOT 5 SPOT 5 (2.5, 5, 10 m) MODIS NDVI 250 MODIS NDVI 250m Rainfall Max / Min Temp Irrigation Fertilizer Field Info AnalysisAnalysis Forecast/EstimationForecast/Estimation Crop Yield Modelling 13

Land Cover Database of Pakistan Objective 1: Improve capacity to estimate and forecast crop production through the use of satellite imagery and field data 14

SUPARCO in collaboration with FAO has mapped land cover;  Punjab and Sindh province: First phase (completed)  KP and Baluchistan : 2nd phase (in-Progress) SPOT 5 satellite was used for interpretation and classification purpose, using 36 classes. Land cover database of Pakistan Concise, reliable, accurate and standardized aggregated land cover information in the following areas: Planning & development Agriculture Disasters & hazards monitoring Forest management Water resources Environment Irrigation Geological surveys Wild life habitat assessment Concise, reliable, accurate and standardized aggregated land cover information in the following areas: Planning & development Agriculture Disasters & hazards monitoring Forest management Water resources Environment Irrigation Geological surveys Wild life habitat assessment 15

Land Cover Map – Punjab Tree Closed Water Body Tree Crop 16

Land Cover Map – Sindh Crop-Irrigated Saline Fields Natural Vegetation-tree open in wetland Wet Areas-water body 17

The Land Cover of Pakistan: Details at district level 18

Crop Mask Objective 1: Improve capacity to estimate and forecast crop production through the use of satellite imagery and field data 19

Crop Mask Crops mask information is required to formulate and implement appropriate risk management strategies with respect to; Food insecurity Disaster : e.g. floods Climate change Planning agricultural infrastructure Core of the crop yield forecasting and monitoring system Aggregate the results to higher administrative levels Crops/ floods modelling systems. SUPARCO in collaboration with FAO is developing a crop mask (for Punjab and Sindh) both for Rabi (Wheat, Potato) and Kharif crops (Sugar cane, Cotton, Rice) using multi date high resolution remote sensing imagery - 5m. 20

Wheat crop Mask (Upper Sindh Zone) 21

Wheat crop Mask: Punjab South Zone 22

Potato crop Mask (Punjab) 23

Crop Mask (Field Validation) 24

Capacity building of Provincial Crop Reporting Services & Universities Objective 1: Improve capacity to estimate and forecast crop production through the use of satellite imagery and field data 25

Objective Improvement of the capacity of provincial governments to collect, analyze and report on timely agricultural information. Capacity building of Provincial Crop Reporting Services and Universities Components Capacity building/Trainings (local and foreign) Strengthening of image processing lab Funding support for operational activities (FAO,USDA,UMD,SUPARCO) Secretary Agriculture Sindh handing over smart phones at inauguration of CRS Nucleus lab 26

Targeted local trainings Sr.DatePunjabSindhKPKBaluchistanUAFSAUTTotal Feb April June June Nov Feb April June Jan April Total

Strengthening of Nucleus lab Objective 2: Improve capacity to provide crop estimates and forecasts to the public 28

EquipmentsCRS PunjabCRS Sindh Computer Server T11011 Hard Drives22 Computer Server T62022 Hard Drives22 Workstations33 Monitor66 UPS11 HP A3 Color Laser Printer22 Networking Equipment (Switch etc)11 GPS Garmin11 Samsung Galaxy Note 212 APC Symmetra 6 KVA22 Micro Swims12 PTCL Cloud Device12 Mitsubishi General Air Conditioner11 Software'sCRS PunjabCRS Sindh PCI geomatica Server1In process Nucleus Lab at CRS Punjab Nucleus Lab at CRS Sindh CRS of Punjab and Sindh 29

MAGIS and GLAM system installed at University of Agriculture, Faisalabad (UAF) MAGIS and GLAM system installed at Sindh Agriculture University, Tandojam (SAUT) ComponentUAFSAUT Computer Server T62001 Workstations03 UPS01 HP A3 Color Laser Printer 02 Networking Equipment01 GPS Garmin01 Samsung Galaxy Note 204 APC Symmetra 6 KVA01 Micro Swims04 PTCL Cloud Device04 Monitor06 Hard Drives02 Software's UAFSAUT PCI geomatica Server1In process Universities 30