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• The developement of red mud flood environmental information system and the methodology for the spatial analysis of the degraded area

  1-11

  Gábor Bakó

  Gábor Kovács

  Zsolt Molnár

  Judit Kirisics

  Eszter Góber

  András Ambrus

  Views:

  174

  The red mud disaster occurred on 4th October 2010 in Hungary has raised the necessity of rapid intervention and drew attention to the long-term monitoring of such threat. Both the condition assessment and the change monitoring indispensably required the prompt and detailed spatial survey of the impact area. It was conducted by several research groups - independently - with different recent surveying methods. The high spatial resolution multispectral aerial photogrammetry is the spatially detailed (high resolution) and accurate type of remote sensing. The hyperspectral remote sensing provides more information about material quality of pollutants, with less spatial details and lower spatial accuracy, while LIDAR ensures the three-dimensional shape and terrain models. The article focuses on the high spatial resolution, multispectral electrooptical method and the evaluation methodology of the deriving high spatial resolution ortho image map, presenting the derived environmental information database.

• Spatial pattern of soil erosion using RUSLE model and GIS software at the Saf Saf watershed, Algeria

  31-47

  Kamel Khanchoul

  Zine El Abidine Boukhrissa

  Ouafa Othmani

  Views:

  102

  Soil erosion is one of the problems threatening the Algerian environment. In agriculture, soil erosion leads to the thinning of the topsoil under the effect of the natural erosive forces of water, or under the effect of agricultural activities. The present study aims to estimate average soil loss rate and to identify vulnerable zones. Through the integration of RUSLE model at the Saf Saf watershed, various parameters are utilized such as the rainfall erosivity factor (R), soil erodibility factor (K), slope length - slope factor (LS), crop management factor (C) and practice management factor (P). All these parameters are prepared and processed through a geographic information system (GIS) and remote sensing using various database sources. The results reveal that the river basin has an average annual soil loss of 3.9 t ha⁻¹ yr⁻¹, and annual soil loss of 4.53 million tonnes for the period 1975-2017. Meanwhile, eighty five percent of the study area is experiencing acceptable rate of soil erosion loss, which is ranging between 0 to 5 t ha⁻¹ yr⁻¹. The present study of risk assessment can contribute to understand the spatial pattern of soil erosion in order to use appropriate conservation practices for sustainable soil management.