Transcript SG3 TECHNOLOGY - Space and Upper Atmosphere Research

PROJECT PROPOSAL
Statistics Research and Information
Directorate (SRID)
Ministry of Food and Agriculture (MoFA),
Ghana
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INTRODUCTION AGRICULTURAL STATISTICS
OF
GHANA
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DEMOGRAPHY
 Population =24.66 Million
 Population growth rate = 2.5%/annum(2010 Census)
GDP CONTRIBUTION
 Agric. Product (GDP) growth rate = 6 %
 Agriculture Growth Rate = 4%
 Crops GDP contribution = 66%
AGRICULTURE STATISTICS-GHANA
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LAND
 Total Land area = 23,853,900ha
 Agricultural land Area=13,628,179ha
(57.1%)
 Cultivated Area= 7,458,000ha (54.7%)
CROPS
Staples:
(Cassava, Cocoyam, Yam, Maize, Rice,
Millet, Sorghum, Plantain)
Vegetables :
(Tomato, Pepper, Okro, Egg Plant, Onion,
Asian Vegetables )
Fruits:
(Pineapple, Citrus, Banana, Cashew,
Pawpaw, Mangoes,
Industrial Crops:
(Cocoa, Oilpalm, Coconut, Coffee, Cotton,
Kola, and Rubber)
GHANA AGRICULTURE
SUB-SECTORS BY GDP(%)
Fisheries
Forestry
7.6
11.1
Livestoc
k 7.1
Cocoa
14.3
Crops
59.9
MANDATE OF SRID/MoFA
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
ESTIMATE CROP AREAS, YIELD AND PRODUCTION
OF 8 MAJOR FOOD & TREE CROPS

DETERMINE AVAILABLE WATER RESOURCE FOR
PRODUCTION*

DETERMINES NET FOOD PRODUCTION, ESTIMATES
FOOD DEMAND AND FOOD BALANCE SHEET

PROVIDES FOOD SECURITY EARLY WARNING
SIGNALS
STRENGHT AND WEAKNESSES OF SRID/MOFA IN
AGRICULTURE STATISTICS MANAGEMENT
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STRENGHT
Enumerators (Agric.
Extension Agents
(AEAs)
Field Survey Cost USD 2.0 MILLION
Financial Strength Little
RS/GIS Usage
LITTLE
Existing RS/GIS
AGHRIMET, EU-EMMAPlatform
AMESD (not for local
studies)
Data Processing
Computers
Equipment
Data Collection
Tapes, GPS
Equipment
Transport
Motorbikes, BICYCLES
WEAKNESSES
Personnel

OBSOLATE DATA COLLECTION
METHODS
The compass and tape method results in
less area coverage for data collection)

LESS CAPACITY (STAFF AND
EQUIPMENT)
MoFA commits as much as 19% of its staff
to just sample surveys

HIGH COST AND TIME CONSUMING
SURVEYS.
Cost of Annual Surveys= U$ 2million
WHY RS-GIS IN AGRICULTURE DATA
MANAGEMENT - CAPABILITIES
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
Map the extent and distribution of individual crop types

Ability to capture, store, manage and update agricultural
data

Monitor agricultural conditions and early assessment of
production

Improved quality of decision making by government
officials given the timely and up-to-date access to reliable
information

Enhance Strategic planning
NATURE OF PROJECT
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Development of RS/GIS-based PROTOCOLS and
Spatial Database System for collection, Storage
and Maintenance of Agricultural Statistics through
Capacity Building of MoFA/SRID Staff
Design
and implement a practical and
operational approach for the collection &
management of agricultural statistics in
Ghana on annual basis using a methodology
that
combines
geospatial
technologies
(remote sensing, GIS, GNSS) and targeted
field data collection at LOCAL/DISTRICT
LEVEL.
WHY THIS PROJECT - BENEFITS TO SRID/MOFA
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 REDUCED COST OF SAMPLE SURVEYS
 REDUCE STAFF STRENGHT FOR SAMPLE SURVEYS
 ENSURES ACURATE & RELIABLE DATA
 EASY MANAGEMENT OF DATA - ASIS
 IMPROVE POLICY
 SOUND PLANNING
 CAPACITY BUILDING IN RS/GIS
EXPECTED OUTPUTS & OTHER APPLICATIONS
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EXPECTED OUTPUTS
 ESTABLISHED CUSTOMIZED WEB-BASED
AGRICULTURAL SPATIAL
INFORMATION SYSTEM (ASIS) (e.g.
spatial and a-spatial information components)
in a GIS-database form that enables storage,
data search and access, cartographic overlay
operations and the linking to models for crop
production estimation). This ASIS can be
viewed as the future spatial decision support
system for MoFA’s decisions regarding
agriculture and sustainable development.
 ESTABLISHED PROTOCOL for
standardized annual data collection and
database updating of agricultural statistics of
major crops of Ghana based on the integrated
use of remote sensing, GIS, GNSS and field
data.
 ESTABLISHED PROTOCOL for the integration
of the GIS-based MoFA-ASIS with the
statistical database currently available at SRID.
 SRID and other MoFA STAFF trained in
RS/GIS applications and remote sensingbased agricultural field survey techniques.
OTHER APPLICATIONS
 Land suitability analysis and land use
planning
 Rapid location of particular crops and
livestock activities
 Determination of onset and end of the
rains
 Rapid zonation of natural disasters
(e.g. drought, floods) affecting
agriculture
 Identification of surface water
resources
 Rangeland monitoring and
management
 Pest threat monitoring (e.g. Locust)
APPROACH(METHOD)
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IDENTIFICATION OF CROP TYPES AND AREA ESTIMATION

o
Studies will be conducted to map individual crop types and estimate crop areas using a combination of optical and
microwave remote sensors (Landsat, SPOT, MODIS, NOAA , AVHRR, Radarsat, ERS, Envisat, JERS, Nigeria
sat-X)
DEVELOPMENT OF CROP YIELD AND PRODUCTION MODEL

o
Multispectral, multi-temporal and/or multi-scale approaches that commonly use remote sensing information derived
from satellites like SPOT, Landsat, NOAA-AVHRR, MODIS, Radarsat, ERS-1 would be used jointly with Agrometeorological plant production models or statistical correlations to develop a Crop Yield and Production
Model to predict yields of crops.
IDENTIFICATION OF CROP PHYSIOLOGICAL PARAMETERS FOR CROP GROWTH AND YIELD
MODELLING

o
Crop Biophysical characteristics and physiological parameters derived from remotely sensed data would be
selected to develop crop yield models.
FIELD TESTING, REFINEMENT AND VALIDATION OF MODEL

o
Yield simulation model established would be validated in the field based on its accuracy for crop classification and
for retrieval of crop specific parameters form Remote Sensed data
PILOT STUDY LOCATION - GHANA
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 DISTRICTS WILL BE
USED TO DESIGN,
IMPLEMENT AND
CALIBRATE A
METHODOLOGY FOR
REMOTE SENSINGBASED WATER
RESOURCE AND CROP
IDENTIFICATION AND
AREA ESTIMATION
SELECTION OF PILOT
AREAS ARE BASED ON
AGRO-ECOLOGICAL
ZONES OF GHANA
PROJECT SCHEDULE & COST
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 FIVE (5) YEARS @ US$3,785,143
Year 1
DESCRIPTION
Apppointment of Research Associate
Inventory of ancillary data
Definition of field data collection methodology
Decision on remote sensing platforms to be used
Software/hardware acquisition
Other field equipment acquisition
Selection of University for PhD Training Mr Ohemeng
Objective 1
Objective 2
Objective 3
Progress reports
Final report
Year 2
Year 3
Year 4
Year 5
United Nations / Pakistan International
Workshop
INTEGRATED USE OF SPACE
TECHNOLOGIES FOR FOOD - AND
WATER SECURITY13
PAKISTAN SPACE AND UPPER
ATMOSPHERE RESEARCH
COMMISSION (SUPARCO)
11 – 15 March 2013
Islamabad, Pakistan