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The Kathmandu Valley Case Study

Dalam dokumen Geospatial monitoring and modeling system (Halaman 150-153)

EXERCISE 2-12 MCE: CONFLICT RESOLUTION OF COMPETING OBJECTIVES 149

In this exercise, we will consider the case of the expansion of the carpet industry in Nepal and its urbanizing effects on areas traditionally devoted to valley agriculture. After the flight of the Tibetans into Nepal in 1949, efforts were undertaken, largely by the Swiss, to promote traditional carpet-producing technologies as a means of generating local income and export revenues. Today the industry employs over 300,000 workers in approximately 5000 registered factories. Most of these are sited within the Kathmandu Valley. The carpets produced are sold locally as well as in bulk to European suppliers.

In recent years, considerable concern has been expressed about the expansion of the carpet industry. While it is recognized that the

production of carpets represents a major economic resource, the Kathmandu Valley is an area that has traditionally been of major importance as an agricultural region. The Kathmandu Valley is a major rice growing region during the monsoon months, with significant winter crops of wheat and mustard (for the production of cooking oil). The region also provides a significant amount of the vegetables for the Kathmandu urban area. In addition, there is concern that urbanization will force the loss of a very traditional lifestyle in the cultural heritage of Nepal.

In an attempt to limit the degree of urban expansion within the Kathmandu area, the Planning Commission of Nepal has stopped granting permission for the development of new carpet factories within the ring road of Nepal, promoting instead the area outside the Kathmandu Valley for such developments. However, there still remains significant growth within the valley.

A

Display the image KVLANDU with the KVLANDU palette. The Kathmandu urban area is clearly evident in this image as the large purplish area to the west. The smaller urban region of Bakhtipur can be seen to the east. Agricultural areas show up either as light green (fallow or recently planted) or greenish (young crops). The deep green areas are forested.

The focus of this exercise is the development of a planning map for the Kathmandu Valley, setting aside 1500 hectares outside the

Kathmandu ring road in which further development by the carpet industry will be permitted and 6000 hectares in which agriculture will be specially protected. The land set aside for specific protection of agriculture needs to be the best land for cultivation within the valley, while those zoned for further development of the carpet industry should be well-suited for that activity. Remaining areas, after the land is set aside, will be allowed to develop in whatever manner arises.

The development of a planning zone map is a multi-objective/multi-criteria decision problem. In this case, we have two objectives: the need to protect land that is best for agriculture and the need to find other land that is best suited for the carpet industry. Since land can only be allocated to one of these uses at any one time, the objectives are viewed as conflicting -- i.e., they may potentially compete for the same land.

Furthermore, each of these objectives require a number of criteria. For example, suitability for agriculture can be seen to relate to such factors as soil quality, slope, distance to water, and so on. In this exercise, a solution to the multi-objective/multi-criteria problem is presented as it was developed with a group of Nepalese government officials as part of an advanced seminar in GIS.1 While the scenario was developed purely for the purpose of demonstrating decision support techniques and the result does not represent an actual policy decision, it is one that incorporates substantial field work and well-established perspectives.

Each of the two objectives is dealt with as a separate multi-criteria evaluation problem and two separate suitability maps are created. They are then compared to arrive at a single solution that balances the needs of the two competing objectives.

The data available for the development of this solution are as follows:

i. Land use map derived from Landsat imagery named KVLANDU ii. Digital elevation model (DEM) named KVDEM

1 The seminar was hosted by UNITAR at the International Center for Integrated Mountain Development (ICIMOD) in Nepal, September 28-October 2, 1992.

EXERCISE 2-12 MCE: CONFLICT RESOLUTION OF COMPETING OBJECTIVES 150

iii. 50 meter contour vector file named DEMCONTOURS iv. Vector file of roads named KVROADS

v. Vector file of the ring road area named KVRING vi. Vector file of rivers named KVRIVERS

vii. Land capability map named KVLANDC

The Landsat TM imagery dates from October 12, 1988. The DEM is derived from the USGS Seamless Data Distribution System at http://seamless.usgs.gov/. All other maps were digitized by the United Nations Environment Program Global Resources Information Database (UNEP/GRID). The roads data are quite generalized and were digitized from a 1:125,000 scale map. The river data are somewhat less generalized and also derived from a 1:125,000 map. The land capability map KVLANDC was digitized from a 1:50,000 scale map with the following legend categories:

IIBh2st Class II soils (slopes 1-5 degrees / deep and well drained). Warm temperate (B = 15-20 degrees) humid (h) climate. Moderately suitable for irrigation (2).

IIIBh Class III soils (slopes 5-30 degrees / 50-100cm deep and well drained). Warm temperate and humid climate.

IIICp Class III soils and cool temperate (C = 10-15 degrees) perhumid climate.

IVBh Class IV soils (slope >30 degrees and thus too steep to be cultivated) and a warm temperate humid climate.

IBh1 Class I soils (slopes <1 degree and deep) / warm temperate humid climate / suitable for irrigation for diversified crops.

IBh1R Class I soils / warm temperate humid climate / suitable for irrigation for wetland rice.

EXERCISE 2-12 MCE: CONFLICT RESOLUTION OF COMPETING OBJECTIVES 151

The Multi-Criteria Evaluation for the Carpet

Dalam dokumen Geospatial monitoring and modeling system (Halaman 150-153)