Journal of Geographical Sciences ›› 2017, Vol. 27 ›› Issue (1): 79-94.doi: 10.1007/s11442-017-1365-9

• Orginal Article • Previous Articles     Next Articles

An automated method for mapping physical soil and water conservation structures on cultivated land using GIS and remote sensing techniques

MEKURIAW Asnake1,2(), HEINIMANN Andreas3, ZELEKE Gete4, HURNI Hans3(), HURNI Kaspar3   

  1. 1. Natural Resources Management Department, Bahir Dar University, Bahir Dar, Ethiopia
    2. Geospatial Data and Technology Center, Bahir Dar University, Bahir Dar, Ethiopia
    3. Center for Development and Environment, University of Bern, Switzerland
    4. Water and Land Resource Center, Addis Ababa, Ethiopia
  • Received:2015-07-11 Accepted:2015-09-08 Online:2017-02-10 Published:2017-02-10
  • About author:

    Author: Asnake Mekuriaw, PhD, E-mail: asnie12@yahoo.com

    *Corresponding author: Hans Hurni, Professor, E-mail: hans.hurni@cde.unibe.ch

Abstract:

An efficient and reliable automated model that can map physical Soil and Water Conservation (SWC) structures on cultivated land was developed using very high spatial resolution imagery obtained from Google Earth and ArcGIS?, ERDAS IMAGINE?, and SDC Morphology Toolbox for MATLAB and statistical techniques. The model was developed using the following procedures: (1) a high-pass spatial filter algorithm was applied to detect linear features, (2) morphological processing was used to remove unwanted linear features, (3) the raster format was vectorized, (4) the vectorized linear features were split per hectare (ha) and each line was then classified according to its compass direction, and (5) the sum of all vector lengths per class of direction per ha was calculated. Finally, the direction class with the greatest length was selected from each ha to predict the physical SWC structures. The model was calibrated and validated on the Ethiopian Highlands. The model correctly mapped 80% of the existing structures. The developed model was then tested at different sites with different topography. The results show that the developed model is feasible for automated mapping of physical SWC structures. Therefore, the model is useful for predicting and mapping physical SWC structures areas across diverse areas.

Key words: physical SWC structure mapping, automated, mathematical morphology, GIS and remote sensing