Remote sensing methods as a base for landform and soil maps of the Iranian loess plateau
Geodesy, Photogrammetry, Remote Sensing, Geoinformatics, Cartography
Final Report Abstract
This project was dedicated to analyse remote sensing methods for landform and digital soil mapping of the Iranian loess plateau. This region is a unique landscape, which has a size of about 2500 km², covered by mineral dust, up to at least 70 m thick. Sedimentological and geochronologcial investigations show that these loess deposits have high value as records of Quaternary landscape evolution and climate change, as these provide a link between loess deposits in south-eastern Europe and Central Asia. In accordance with the research proposal, we investigated landform derivation by geomorphometric analysis on different scales and started to apply geomorphometric results regarding the scorpan approach (s: soil; c: climate; o: organisms and vegetation, r: topography; p: parent material; a: age; n: space), which allows to establish empirical relations between the soil and the denoted attributes. Our results show that for this landscape high-resolution digital elevation models (< 10 m geometric resolution) are necessary to automatically achieve geomorphometric features and landform units with an accuracy >70%. Furthermore, first results show that the topographic aspect is in combination with vegetation cover an important factor for soil organic carbon and should be incorporated in according modelling approaches and erosion estimates for this region.
Publications
- (2016): Comparison of different landform classification methods for digital landform and soil mapping of the Iranian loess plateau. Geophysical Research Abstracts, Vol. 18, EGU2016-12248 -1, EGU General Assembly 2016, Vienna, Austria
Hoffmeister, D., Kramm, T., Curdt, C., Maleki, S., Khormali, F., Kehl, M.
- (2017): A comparison of different landform classifications for the Iranian Loess Plateau. LoessFest 2017, 8.-12.10.2017, Gorgan, Iran
Hoffmeister, D., Kramm, T., Curdt, C., Maleki, S., Khormali, F., Kehl, M.
- (2017): Accuracy assessment of landform classification approaches on different spatial scales for the Iranian Loess Plateau. International Journal of Geoinformation 6 (11), 366
Kramm, T., Hoffmeister, D., Curdt, C., Maleki, S., Khormali, F., Kehl, M.
(See online at https://doi.org/10.3390/ijgi6110366) - (2017): Geological controlling soil organic carbon and nitrogen density in a hillslope landscape, semiarid area of Golestan province, Iran. Desert 22(2), 221-228
Maleki, S.,Khormali, F., Bagheri Bodaghabadi, M., Mohammadi, J., Kehl, M., Hoffmeister, D.
- (2017): Relationships between vegetation, soil and slope aspect in the Iranian loess plateau, Golestan province, Northern Iran. LoessFest 2017, 8.-12.10.2017, Gorgan, Iran
Maleki, S, Khormali, F, Bagheri, M, Kehl, M, Hoffmeister, D and Mohammadi, J.
