Integration of Remote Sensing, GIS and MCDM for Land Capability Classification in Andit Tid Watershed, Ethiopia

  • Hamere YohannesEmail author
  • Teshome Soromessa
Research Article


Land evaluation is the core component of land-use planning process, particularly where resource is limited and degraded, like Ethiopian Highland. Thus, evaluation of land in terms of its capability is important. The aim of land capability is to identify the physical inherent capacity of the land for different uses to avoid further degradation. Relevant data such as soil depth, soil texture, soil drainage, erosion hazard, altitude, slope and slope direction have been utilized for land capability evaluation in Andit Tid watershed. The integration of remote sensed data, geographical information system and multicriteria evaluation approach was used to obtain spatial information of land capability. The result revealed that the largest part of the watershed was occupied by class III 122.44 ha (25.87%) and the smallest part occupied by class VIII 3.6 ha (0.76%), characterized by very steep slope and rocky and used only as natural reserves. Class I, which claimed only few limiting factors, occupied only 7.65 ha (1.62%). The first four classes (I–IV), which have a capability for agricultural purpose, occupied 63%, class V and class VI occupied 119.2 ha (25.19%), capable for grazing, and class VII holds 51.63 ha (10.91%), capable for forestry. The main limiting factors for land capability classification were soil texture, soil depth, soil drainage and slope. As compared to the current land use, with the current land use, most of the lands are used against the capability classification of the land.


Criteria GIS Remote sensing Multicriteria Land capability classes 



We acknowledge Addis Ababa University for financial and facility support. The authors are also grateful to the contribution of Water and Land Resource Center who provide major soil data and all participants during field survey.

Compliance with Ethical Standards

Conflict of interest

The authors declare that they have no conflict of interest.


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Copyright information

© Indian Society of Remote Sensing 2019

Authors and Affiliations

  1. 1.Center for Environmental Science, College of Natural and Computational SciencesAddis Ababa UniversityAddis AbabaEthiopia
  2. 2.Natural Resource Management Department, College of Agriculture and Environmental ScienceDebre Berhan UniversityDebre BerhanEthiopia

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