Abstract
Soil is a natural body that delivers important ecosystem services apart from being a medium for plant growth. Soil mapping can be time-consuming and expensive. During the 1960s and 1970s, the introduction of air photointerpretation in soil survey through element analysis, physiognomic and physiographic analysis, helped increase mapping efficiency. In the late 1980s, the geopedologic approach to soil mapping amplified the role of geomorphology. It helps understand soil variation in the landscape which increases mapping efficiency. In the present study, the adequacy of soil data resulting from geopedology-based predictive soil mapping for assessing land degradation is applied in two contrasting climatic regions: in humid tropics in Thailand and in dry and hot arid climate in Iran. The result shows that the geopedologic approach helps map soil in inaccessible mountain areas. However, for application in land degradation studies all the required soil properties may not be available in a soil map. The effect of land cover and land use management practices on soil properties, such as porosity and compaction affecting hydraulic conductivity, a parameter used in modelling rainfall-runoff-soil erosion, is usually not reported in soil surveys. These data have to be collected separately. For mapping areas susceptible to frequent floods, the geomorphic understanding of the river valley and soil characterization (Fluventic and Aquic) helps identify susceptible areas. Similarly, the study shows how the geopedologic approach in combination with digital image processing and/or the application of simple decision rules applied in a Geographic Information System (GIS) help in mapping soil salinity trends.
| Original language | English |
|---|---|
| Title of host publication | Geopedology |
| Subtitle of host publication | An Integration of Geomorphology and Pedology for Soil and Landscape Studies: Second Edition |
| Editors | Joseph Alfred Zinck, Graciela Metternicht, Hector Francisco del Valle, Marcos Anjelini |
| Publisher | Springer |
| Pages | 413-435 |
| Number of pages | 23 |
| ISBN (Electronic) | 9783031206672 |
| ISBN (Print) | 9783031206665 |
| DOIs | |
| Publication status | Published - 1 Jan 2023 |
Keywords
- Decision tree
- Erosion modelling
- Flood-prone area
- Remote sensing
- Soil salinity trends
- Surface runoff
- 2024 OA procedure