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 Regional Centre for Mapping of Resources for Development International Institute for Geo Information and Earth Observation  Kenyatta University


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Regional Centre for Mapping of Resources for Development

International Institute for Geo-

Information and Earth Observation





Kenyatta University




Course Description of a Joint IT-Course by RCMRD, KU, and ITC






Quantifying Environmental Processes at Regional Scale in Support of Food Security

-

with emphasis on RS-based crop-simulation techniques, and


RS/GIS-based agro-ecosystem mapping methods




Duration:

  • 2 Modules of 3 weeks each
    (you can also opt to attend only module-1)


Period:

  • 15 May - 30 June 2006


Number of participants:

  • 15 to 30


Entry level:

  • Basic training in RS/GIS skills

  • Basic understanding of plant-soil-water concepts.


Target Group:

  • IT-Researchers in Food Security

  • Mid-career Professionals

  • BSc, MSc, PhD Students

  • Higher National Diploma Holders (+3 yrs)

  • University staff





Course Coordinators:

  • Dr.Tesfaye Korme (RCMRD)

  • Dr.Simon M. Onywere (KU)

  • Valentijn Venus (ITC)


Lecturing staff:

  • Dr.Tesfaye Korme (RCMRD)

  • Dr.Hussein O.Farah (RCMRD)

  • Eric Khamala (RCMRD)

  • Dr.Simon M. Onywere (KU)

  • Dr.Godfrey A. Olukoye (KU)

  • Dr.Joy A. Obando (KU)

  • Dr.Gitonga N. Mburugu (KU)

  • Prof.Chris Shisanya (KU)

  • Dr.Alexander Njue (KU)

  • Valentijn Venus (ITC)

  • Dr.Kees de Bie (ITC)



All exercises are based on
data from sub-sahara Africa.


This is a certificate course jointly awarded by Kenyatta University, ITC, and RCMRD.



Introduction


Growing concerns on the productivity and sustainability of agricultural land uses have increased the demand for more detailed and timely information on current and future production levels of food and fibre crops at regional scales. Indeed, decision makers in Food Security, require more-and-more detailed and spatial explicit information on what is happening where, coupled with timely quantitative production forecasts. The quantitative methods introduced in this course provide researchers and IT-professionals the tools and skills to apply and further explore the latest Geo-Information techniques to generate more detailed, more accurate and more quantitative assessments of the state of the agricultural production environment. Using satelite data interpretation, data mining, crop simulation, modelling, and statistical techniques, course participants are taught new insights in how to estimate timely and quantitatively current food and fiber production levels at regional scale.

Aim

The course aims to transfer knowledge and skills in applying quantitative RS/GIS and IT-techniques to generate more detailed, accurate, spatial explicit, timely, and quantitative production forecasts for food and fibre crops at regional scales, and to stimulate participants to engage in development oriented research for enhanced food security in Sub-Saharan Africa.



Content



1. How to derive Agro-Ecosystem Parameters from Satellite Data? (week 1,2; VV&SO)


  • Approaches and methods for quantifying environmental processes from earth observation systems: an illustrated historical overview.

  • Considerations for selecting an appropriate satellite platform, and acquisition dates.

  • Obtaining and pre-processing RS-data.

  • Techniques to infer crop, land and weather parameters (e.g. NDVI, ETa, PREC, LAI, aPAR, PAR, Tcanopy, Tair) from space-born sensors.


2. What is grown Where and When ? (week 3; KdB,TK,GO)


  • Land use mapping concepts.

  • Use of spectral vs. temporal satellite image signatures for crop identification.

  • Segmentation of multi-temporal NDVI-images to map Vegetation Index profiles (VIPs).

  • Disaggregate agricultural statistics on cropped areas using mapped VIPs.

  • Match VIPs to known crop calendars practiced.

  • Use of VIPs to monitor land use conversions, modifications, and anomalies.


3. How Much is Produced ? (week 4,5; VV,CS,AN, FH,JO)


  • Agro-Meteorological production models: Index value techniques, semi-empirical regression techniques, seasonal integration techniques (e.g. Monteith efficiency equation), crop growth simulation techniques, and techniques based on satellite-derived parameter values.

  • Estimate how much is produced using RS-based crop-simulation techniques.

  • Season forecasts: estimation, validation, use of weather forecast models, aspects of concern.

  • Use of spectral and temporal satellite image signatures to detect epidemic pests.

  • Estimate how much is lost/destroyed using RS-based techniques.

  • Long term forecasts: estimate consequences of climate change projections.


4. Kenyan Case Study (week 6 SO,VV,CS,EK)


  • Group project: combining the What, Where, When, and How Much questions using a real-world example (includes a 1-day field visit).


Objectives


By the end of each topic, participants should be able to:


1.

  • Compare and select for given objectives suitable approaches, methods, and materials for the quantification of threads to food productivity at regional scale through hazard analysis.

  • xxx

2.

  • Map crop types by integrating crop calendar information with multi-temporal satellite observations to quantify acreages under different land use types

  • Xxx

3.

  • Quantify yields/hectare for different crop types

  • Apply quantitative remote sensing techniques for estimating environmental parameter values

  • Monitor drought and insect induced hazards on food and fibber production levels

  • Understand how such information may contribute to enhanced food security

  • Extend the applications of these environmental monitoring techniques to prepare projections for the future

  • Xxx

4.

  • xxx



Hardware and software requirements


Software and data will be provided through the RCMRD network.

Hardware facilities, a computer cluster and lecture space will be provided by RCMRD.


Teaching Materials


Various lecture notes, presentations (PPT), manuals, handouts, datasets, software and assignments will be provided to each of the participants (also in digital format).

Allocated time per teaching / learning method








Time (hours)

Topic:

1

2

3

4

Total

Le

Lectures

24

8

16

0

48

SP

Supervised Practical

46

24

54

0

124

GA

Group Assignment

0

0

0

24

24

FW

Fieldwork

0

0

0

8

8

SS

Self Study

10

5

10

5

30

Ex

Exams

0

3

0

3

6

Total:

80

40

80

40

240

Assessment


By module:

  • Performance during group and individual assignments (30%).

  • A written exam (open book) with questions from all topics covered (70%).


For Time Management, Commitments, Budget Preparation, and calculation of Course Fees:


Quantifying Environmental Processes at Regional Scale in Support of Food Security


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