Summary of Data Requirements for Country Studies

For all developing countries considered in t h e AEZ study a 1:5 million scale computerized land resources --inventory is available. For a detailed country study a more refined data base is required. Technical requirements dictate a t least one observation or a s e t of colleced data for each cm2 of the resource inventory map being applied. A 1:l million scale provides an appropriate level of analysis; increasing the scale to 1:100,000 would result in up to a hundred fold increase in required data inputs. The main components of the data (in map form to be digitized) required t o compile and computerize a l q d resource inventory are:

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Soil Map (soil, texture, slope and phase)

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Administrative Area Map

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Climate (Temperature Regimes) Map

Length of Growing Period (water availability) Map

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Rainfall Pattern Map (form and variability of LGP)

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Irrigated Areas and Production

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"Other" Food and Non-Food Crop Areas and Production

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^Fish Production

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Forest Areas and Production (Fuelwood and Timber)

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National Reserves (Parks. Game Reserves, etc.)

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Urban Areas

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Industrial/Mining Areas

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Population Distribution

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Present Crop-Mix, Acreages and Inputs

All the above data may not be readily available in a compiled map or digi- tized form and the f i s t task would be t . ~ assemble all the relevant information and build up the resource inventory stage by stage.

Blair Rains, k and Kassam, AH. (1980). Land Resources and Animal Production.

In: Report on the Second FAO/UNFPA Expert Consultation on Land Resources for Populations of the Future. FAO, Rome.

Dudal, R. and Batisse, M. (1978). The Soil Map of the World. In: Nature and Resources. Vol.XIV, No. 1, January-March. United Nations Educational Scientific and Cultural Organization, Paris.

FA0 (1971-81). FAO/UNESCO Soil Map of the World, 1:5 Million, Vols.1-10.

UNESCO, Paris.

FA0 (1973). Energy and Protein Requirements. Report of a Joint FAODHO ad hoc Expert Committee, FA0 Nutrition Meetings Report Series No.52. WHO Technical Report Series No.322. FAO, Rome.

FA0 (1976a). A Framework for Land Evaluation. Soils Bull. 32. FAO, Rome.

FA0 (1978b). AGP Climate Data Bank Data held as Agro-Climatic Summaries by Plant Production and Protection Division, FAO, Rome.

FA0 (1978-1980). Report on the First and Second F.'. l/UNFPA Expert Consulta- tion on Land Resources for Populations of the Future. FAO, Rome.

FA0 (1978-81). Reports of the Agroecological Zones Project. World Soil Resources Report No.48, Vol.1

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Africa, Vo1.2

-

Southwest Asia, Vo1.3

-

^South

and Central America, Vo1.4

-

Southeast Asia. FAO, Rome.

FAO/UNEP/UNESCO (1979). A Provisional Methodology for Soil Degradation Assessment, FAO, Rome.

FA0 (198 1). Agriculture: Toward 2000. FAO, Rome.

FAO/IIASq/UNFPA (1983). G.M. Higgins, AH. Kassam, L. Naiken (FAO) and G.

Kscher, M.M. Shah (IIASA). Potential Population Supporting Capacities of Lands in the Developing World. Technical Report of Land Resources for Populations of t h e Future Project, FAO, Rome.

Kscher, G., Shah,

M.M.

and Rollinson, D.H. (1984). Agricultural Perspectives in Relation to TseTse Area Development in Africa. Report prepared for Animal Production Division, FAO, Rome.

Hyde, R.F.. Vesper.

N.J.,

Moore, RS. and Goldblatt, 1.k (1980). Measurement of Non-Agricultural Uses of Land for Nine Selected Areas in Africa by Means of Landsat MSS Data. Report on FA0 Contract No. UNFPA/INT/75/P13-2/AGL.

Holcombe Research Institute, Butler University, Indianapolis, USA

Kassam, AH., Kowal, J.M. and Sarraf, S. (1977). Climatic Adaptability of Crops.

Consultants' Report. Agro-ecological Zones Project. AGLS, FAO. Rome.

Kassam, AH. (1979a). Agro-ciimatic Suitability and Adaptability of Rainfed Crops. Consultants' Report, AGLS, FAO, Rome.

Kassam, AH. (1979b). Multiple Cropping and Rainfed Crop Productivity in Africa. Consultant's Report. AGLS, FAO, Rome.

Shah, M.M. and Kscher, G. (1980). Assessment of Population Supporting Capaci- ties. In: Report on the Second FAO/UNF'PA Expert Consultation on Land Resources for Populations of the Future. FAO, Rome.

Shah. M.M. and F'ischer, G. (1982a). Resources, Environment and Technology Options for Food Production and Self-Sufficiency in Kenya. WP-82-127.

IIASA, Laxenburg, Austria.

Shah M.M. (1982b). Economic Aspects of Soil Erosion and Conservation, Land Resources Evaluation with Emphasis on Outer Island Project. Ministry of Agricultural Development of Indonesia/UNDP/FAO, Bogor, Indonesia.

Shah. M.M., Fischer, G., Kromer, G. and Parikh. K.S. (1984). Africa's Growing Dependence on Imported Wheat: Some Implications for Agricultural Poli- cies in Africa. A Study carried out for t h e Food and Agricultural Organiza- tion of t h e United Nations. Laxenburg, Austria.

Shah. M.M.. Fischer, G.. Higgins, G.M. and Kassam,

AH.

(1985a). Estimates of Soil Erosion Losses/Productivity L.r=-e- in Agriculture: Methodology and Results for Developing Countries (forL~coming).

Shah

M.M.,

Fischer. G., Higgins, G.M., Kassam, AH. and Naiken L. (1985b). Peo- ple. Land and Food Production

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Potentials in t h e Developing World. Inter- national Institute for Applied Systems Analysis, Laxenburg, Austria (forth- coming Research Report).

Sys. C. and Riquier, J. (1980). RatGgs of FAO/UNESCO Soil Units for Specific Crop Production. Consultant's Workng Paper No. 1, Land and Water Division, FAO, Rome.

U.N.(1979). World Population Trends and Prospects by Country (1950-2000).

Summary Report of t h e 1978 Assessment, ST/ESA/Ser.R/33. United Nations, New York.

Wood, S.R (1980). The Allocation of Irrigated Areas and Production of Agro- ecological Zones. Consultant' Report. AGLS, FAO, Rome.

Young, A a n d Wright, AC.S. (1980). Rest Period Requirements of Tropical and Sub-tropical Soils under Annual Crops. Consultants' Report, AGLS. FAO.

Rome.

APPENDIX ¹

Nunierical results of the application of t h e

AEZ

methodology to an agro- ecoloical cell a r e presented; t h e computer flow diagrams of t h e methodology a r e shown in Figs. A1-A2.

Cell of total extent 18000 Hectares. The cell is situated in warm tropical climate (Ol), length of growing period: 240-269 days (05) and tesoil (Fx), slope (B, t e x t u r e (I), and phase (20) of t h e land in this cell a r e as follows:

Soil: Fx, Xanthia Ferrasols

Slope: B, slope of 8-30 cm (soil rules apply)

Texture: 1, light t e x t u r e limitations ( t e x t u r e rules apply) Phase: 20, no phase (phase rules do not apply)

Two crops, namely maize and beans, a r e considered in detail for this cell.

Table l a : Evaluation of maize as a potential crop in cell (0105 Fx 20 Bl):

results from t h e application of land productivity program (Kg. Al).

Comments: Under low level of technology, all t h e available agricultural 1 and in t h e cell falls in t h e very high productivity class. The applica- tion of t h e soil rule c a u s e s t h e total a r e a t o fall from very high t o high productivity class. The phase and the slope rules have n o effect on t h e productivity class for t h i s crop u n d e r low t e c h - nology level. The application of t h e texture rule causes t h e e x t e n t of available l a n d t o fall into t h e moderate productivity class. The expected calorie a n d protein production of maize u n d e r t h r e e technology levels a n d with and without land conser- vation measures a r e shown. If land degradation occurs, i.e., n o conservation measures, t h e n t h e total available land falls i n t o

t h e N S (not suitable) class a n d in this case t h e r e is no potential production for this crop in t h e cell. The results of t h e inter- mediate and high technology a r e similar in t h a t after t h e appli- cation of all rules. 1900 h e c t a r e s of land are available in t h e low productivity class. In t h e case of high technology, t h e slope r u l e eliminates two thirds of t h e available land from maize pro- duction whereas t h e relatively high rest period requirement limits t h e final availability of land or maize production under intermediate technology. Note t h a t , because of t h e associated yield levels in t h e intermediate a n d high technology levels, the calorie and protein production, in t h e case of both with and without conservation measures, increase a s t h e technology changes from low t o intermediate t o high level.

Table lb: Evaluation of phaselous beans as a potential crop in cell (0105 Fx 20 El): results from t h e application of land prductivity pro- gram.

Comments: The total a r e a available falls initially in the high productivity class. However. on application of all o t h e r rules, only 1200 h a a r e left in t h e low productivity class under low technology, 1900 h a under intermediate and high technology. In this example, t h e productivity, soil and t e x t u r e rule as well as degradation affect land productivity in a similar way under all t h r e e techno- loy levels. While t h e slope does not reduce productivity under low technology, 85% of t h e land h a s t o be left uncultivated (fal- low requirements). In t h e case of high technology, these per- centages a r e 66% a n d 30% respectively.

A summary of t h e results after t h e application of all t h e rules for all t h e

eighteen food crops u n d e r t h e asumption of low, intermediate and high technol- ogy for t h i s cell a r e given in Tables 2a, 2b and 2c respectively.

Table 2(a-c): Evaluation of the potential for all food crops in cell (0105 Fx 20 B l ) : results of the land productivity program, (Fig.Al) and the optimum crop-mix progam (Fig.A2). -

Table 2a: Low Technology Level

Comments: Without l a n d d e g r a d a t i o n , i . e . with land c o n s e m a t i o n m e a s u r e s . In t h i s cell, none of t h e eighteen food crops falls in very high or high productivity class. For maize, soyabean, sweet potato, cas- sava a n d upland rice 15% of t h e l a n d falls i n t o t h e moderate pro- ductivity class, whereas 85% have t o be left uncultivated ( r e s t period requirement). For millet, sorghum, beans, groundnut a n d sugar cane 15% of t h e l a n d is low productive and again 85%

fallow. Spring wheat, white potato, winter wheat, a n d winter barley a r e ruled out by t h e climate rule. All o t h e r crops do not have r e s t period requirements but p a r t of t h e land is classified a s not suitable. For t h e s e crops t h e remaining percentages and productivity classes a r e a s follows: bunded rice 33% (low), b a n a n a and plantain 100% (low), oil palm 100% (low), grassland 100% (moderate). The potential calorie and protein production is shown for each of t h e eighteen crops in Table 2a. In MODE 1, oil palm is picked as t h i s choice maximizes t h e calorie produc- tion for this cell. Note t h a t i n MODE 1 t h e protein constraint is violated in t h e zone u n d e r consideration (warm tropics, 240

-

269 LGP). Nevertheless, oil palm is also chosen in MODE 2.

When t h e present c r o p mix c o n s t r a i n t is imposed upon t h e crop choice (MODE 3). 46.3% of t h e land is allocated t o sorghum and

53.4% t o beans. Note t h a t in terms of calorie production these crops are very much inferior to oil palm.

With Land Degradation, i . e . , No Land C o n s e m a t i o n Measures.

For soyabean, beans, sweet potato, cassava, upland rice and groundnut t h e production potentail is seriously affected by degradation. Millet, sorghum a n d maize become not suitable without land conservation measures. Bunded rice, banana a n d plantain, sugar c a n e and oil palm, however, are not affected by land degradation. Potential grass land production drops roughly by 30%. In MODE 1, oil palm is, of course, chosen again.

Banana a n d plantain comes in under MODE 2, while beans a r e allocated in MODE 3.

In Tables 2b and 2c. t h e corresponding results for intermediate a d high technology a r e shown. Under both technology levels oilpalm is allocated exclusively in MODE 1 a n d MODE 2 runs. In MODE 3 t h e crop choice i s similar for both technology levels b u t markedly different when conservation i s taken into account. When no land conservation measures a r e taken, all land is given t o maize prodction. Assuming land conservation, however, t h e land allocation is 67.8% beans and 32.3% banana a n d plantain under intermediate technology while 46.6% sorghum, 21.2% beans and 32.3% banana a n d plantain a r e chosen for high technology.

Land Productivity Prqmm Total Extent

AEZ Inventory

Non- Agricultura Land Requirement

r-

^I

Agricultural Land Available

I

I

^{C h m} Technology Level

[

Figure A 1 : LAND PRODUCTIVITY PROGRAM (LPP) FOR PRODUCTION ASSESSMENT

Soil Erosion Model

Cropping Intensity Tabla

I

+

A Three levels of technology

A With and without degradation hazards ASimulation for 1975 o r (2000)

4 Pmduvtivity Lpsr Model

MCP Program

I

I

4 Input Rsquimmene At 2000 Globar

Tachnology Matrix Crop Production and lnput

Requimrnents by Cell I

3 3 S 3 S _{C C S 5}

.-

₃

-

_E

^.-

₃

c - u S ! u O O E O E O O m O m

TABLE la: Cell Example, CELL IDENTIFICATION tlajor Climate : warm tropics Length of gr. Period : E (240-269) Soil : FX Phase ; 20 Slope : B

L O 0 0 0 0

TABLE 2a : C e l l Example.

CELL IDENTIFICATION

Im Dokument Land Resources and Productivity Potential - Agro-Ecological Methodology for Agriculture Development Planning (Seite 61-73)