A Multi-Criteria Evaluation approach to Delineation of Suitable Areas for Planting Trees (Case Study: Juglans regia in Gharnaveh Watershed of Golestan Province)

Document Type : Research and Full Length Article

Authors

1 Gorgan university

2 Department of the Environmental Sciences. Gorgan University

Abstract

For the successful tree establishment, an evaluation of land suitability is necessary.
In this paper, we demonstrate how to implement fuzzy classification of land suitability in a
GIS environment for afforestation with Juglans regia in Gharnaveh Watershed of Golestan
Province in Iran. Juglans regia is one of the most important agro-forestry species in many
rural parts of Iran. Relevant criteria for Juglans regia and suitability levels were defined using
literature review and expert knowledge and layers were prepared and incorporated into a GIS
database. We also defined the fuzzy membership functions for the criteria and assigned some
important weights through expert knowledge and Analytical Hierarchy Process. This
information was used as input to the weighted linear combination of MCE method. Our
results indicate that a low percentage of area is classed as very highly suitable comprising
some 645 ha or 11% of area for afforestation with Juglans regia. Results of the study also
indicate the usefulness of fuzzy modeling of land suitability which provides some information
for optimum land-use planning.

Keywords


Aronoff, S. 1989. GIS a Management
Perspective. WDL Publications, Ottawa,
Canada. Asgar Lotfizadeh, L., (1965).
Fuzzy sets. Information and Contro, l 8:
338–353.
Baja, S.; Chapman D. M.; and Dragovich
D. 2002. Fuzzy modeling of
environmental suitability index for rural
land use systems: An assessment using
GIS. Environment and Planning, 29: 3–
20.
Barbour, M. G. 1987. Community ecology
and distribution of California hardwood
forests and woodlands. In: Plumb,
Timothy R.; Pillsbury, Norman H.,
technical coordinators. Proceedings of the
symposium on multiple-use management
of California's hardwood resources; 1986
November 12-14; San Luis Obispo, CA.
Gen. Tech. Rep. PSW-100.Berkeley, CA:
U.S. Department of Agriculture, Forest
Service, Pacific Southwest Forest and
Range Experiment Station: 18-25.
[5356]. Booklet of forestry plan.
Braimoh, A. K.; Vlek, P. L. G.; Stein, A.,
2004. Land evaluation for maize based on
fuzzy set and interpolation.
Environmental Management, 33(2): 226–
238.
Brown, D. E. 1982. Californian evergreen
forest and woodland. In: Brown, David
E., ed. Biotic communities of the
American Southwest United States and
Mexico. Desert Plants. 4(1-4): 66-69.
Burrough, P. A., 1989. Fuzzy
mathematical methods for soil survey and
land evaluation. J. of Soil Science, 40:
477–492.
Burrough, P. A.; MacMillan, R. A.; van
Deursen, W. 1992. Fuzzy classification
methods for determining land suitability
from soil profile observations and
topography. J. of Soil Science, 43: 193–
210.
Ceballos-Silva, A and Lopez-Blanco, J.
2003. Delineation of suitable areas for
This is trial version
www.adultpdf.com
Journal of Rangeland Science, 2011, Vol. 1, No. 2 A. Mashayekhan and A. Salman Mahiny / 233
crops using a Multi-Criteria Evaluation
approach and landuse/cover mapping: a
case study in Central Mexico.
Agricultural Systems., 77: 117-136.
Chang, L.; Burrough, P. A. 1987. Fuzzy
reasoning: A new quantitative aid for
land evaluation. Soil Survey and Land
Evaluation, 7: 69–80.
Chirici G., C. P.; Marchetti M.; Travaglini
D.; Wolf U., 2002. Modello di
valutazione dell’attitudine fisica del
territorio per la realizzazione di
piantagioni di noce comune e di
douglasia in Italia meridionale. Monti e
Boschi, 6: 25-31. Clark Labs News,
2004.
Conrad O. 2002. Digitales Gel¨andeModell (DiGeM) Terrain Analysis
Software. http://www.geogr.unigoettingen.de/pg/saga/digem/
Dull., H. E. H. and Edvorte E. W. R. 1992.
Indicator values of plants in central
Europe. Cabi press.
Eastman J R, J. W., Kyem P A K,
Toledano J, 1995. Raster procedures for
multi-criteria/multi-objective decisions
Photogrammetric Engineering & Remote
Sensing. 61(5): 539-547 .
Eastman, J. R., 1999. IDRISI 32. Guide to
GIS and Image Processing. Clark Labs,
Clark University, Worcester, MA, USA.
IIIGEC, 1993. Atlas General del Estado
de México. Secretaria de Finanzas,
México.
Eastman, J. R.; Jiang, H.; Toledano, J.
1998. Multi-criteria and multi-objective
decision making for land allocation using
GIS. In Multicriteria Analysis for LandUse Management (Beinat, E., Nijkamp,
P. (Eds): Kluwer Academic Publishers),
227-251.
Farajzadeh, M.; Miraza Bayati, R.; Rahimi,
M., 2007. Preparation of Saffron
Cultivation Suitability Map Based on the
Comparison of Different Weighting
Methods in GIS Environment.
Heywood, I.; Oliver, J.; Tomlinson, S.
1995. Building an exploratory multicriteria modeling environment for spatial
decision support. In: Fisher, P. (Ed.),
Innovations of GIS 2. Taylor and Francis,
Leicester, UK, pp. 127–136.
Iless, J. 1999. Community tree planting
and care guide. Iowa urban and
community forestry council.
Janssen, R.; Rietved, P. 1990. Multicriteria
analysis and GIS: an application to
agriculture land use in the Netherlands.
In: Scholten, H., Stilwell, J. (Eds.),
Geographical Information Systems for
Urban and Regional Planning. Kluwer,
Dordrecht, The Netherlands, pp. 129–
138.
Joerin, F., The´riault, M., Musy, A. 2001.
Using GIS and outranking multi criteria
analysis for land-use suitability
assessment. International Journal of
Geographical Information Science 10 8:
321–339.
Kollias, V. J.; Kalivas, D. P. 1998. The
enhancement of a commercial
geographical information system
(ARC/INFO) with fuzzy processing
capabilities for the evaluation of land
resources. Computers and Electronics in
Agriculture 20: 79–95.
Lexer M J, H.; K., Vacik, H., 2000.
Modelling the effect of forest site
conditions on the ecophysiological
suitability of tree species: An approach
based on fuzzy set theory. Computers and
Electronics in Agriculture, 27: 393–399.
Malczewski, J., 1999. GIS and Multicriteria Decision Analysis. Wiley, New
York, USA.
Malczewski, J. A.,1996. GIS-based
approach to multiple criteria group
decision-making. International Journal
of Geographical Information Science,
10(8): 321–339.
Mosaddegh, A. 1980. Afforestation and
forest nursery. Negar press.
This is trial version
www.adultpdf.com
234 / J. of Range. Sci., 2011, Vol. 1, No. 3 A Multi-Criteria Evaluation…
Oberthur, T., Dobermann, A., Aylward,
M., 2000. Using auxiliary information to
adjust fuzzy membership functions for
improved mapping of soil qualities.
International Journal of Geographical
Information Science, 14(5): 431–454.
Pereira, J. M. C., Duckstein, L. 1993. A
multiple criteria decision-making
approach to GIS- based land suitability
evaluation. International J. of
Geographical Information Science, 7(5):
407–424.
Perveen, F., Nagasawa, R., Uddin, I,.
Delowar Hossain, K.M, 2007. Crop- land
suitability analysis using multicriteria
evaluation and GIS approach. 5th
international symposium on digital earth.
Quinn, R. D. 1990. The status of walnut
forests and woodlands (Juglans
californica) in southern California. In:
Schoenherr, Allan A., ed. Endangered
plant communities of southern California:
Proceedings, 15th annual symposium;
1989 October 28; Fullerton, CA. Special
Publication No.
Ruger, N.; Schluter, M.; Matthies, M.,
2005. A fuzzy habitat suitability index for
Populus euphratica in the Northern
Amudarya delta (Uzbekistan). Ecological
Modeling, 184: 313–328.
Sicat R S. C., E. J. M., Nidumolu, U. B.
2005. Fuzzy modeling of farmers’
knowledge for land
Tang, H. J., and Van Ranst, E., 1992.
Testing of fuzzy set theory in land
suitability assessment for rainfed grain
maize production. Pedologie, 42: 129–
147.
The booklet of forestry plan. 2006. The
forest and rangeland of Iran. Tirageh
press.
Van Ranst, E., Tang, H., Groenemans, R.,
Sinthurahat, S., 1996. Application of
fuzzy logic to land suitability for rubber
production in peninsular Thailand.
Geoderma, 70: 1–19.