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An Assessment of Soil Erosion Potential in the Klipriviersberg Nature Reserve Using GIS and Remote Sensing Techniques.

紀錄類型:	書目-電子資源 : Monograph/item
正題名/作者:	An Assessment of Soil Erosion Potential in the Klipriviersberg Nature Reserve Using GIS and Remote Sensing Techniques./
作者:	Akinseye, Samuel Akintayo.
出版者:	Ann Arbor : ProQuest Dissertations & Theses, : 2018,
面頁冊數:	89 p.
附註:	Source: Masters Abstracts International, Volume: 82-11.
Contained By:	Masters Abstracts International82-11.
標題:	Surface water. -
電子資源:	http://pqdd.sinica.edu.tw/twdaoapp/servlet/advanced?query=28284386
ISBN:	9798708792310

An Assessment of Soil Erosion Potential in the Klipriviersberg Nature Reserve Using GIS and Remote Sensing Techniques.
Akinseye, Samuel Akintayo.

An Assessment of Soil Erosion Potential in the Klipriviersberg Nature Reserve Using GIS and Remote Sensing Techniques. - Ann Arbor : ProQuest Dissertations & Theses, 2018 - 89 p.

Source: Masters Abstracts International, Volume: 82-11.

Thesis (M.Sc.)--University of Johannesburg (South Africa), 2018.

This item must not be sold to any third party vendors.

To guarantee the sustainability of South African nature reserves, there is a need to pay attention to the threats faced by soils in nature reserves. Soil, which makes up part of the natural environment, needs to be protected. Given these environmental management concerns, this study aimed at quantifying the amount of soil loss and maps the soil erosion potential risk in one of the South African nature reserves - Klipriviersberg Nature Reserve.In order to achieve this, the Revised Universal Soil Loss Equation (RUSLE) model was used. The RUSLE model preparation, data management, evaluation of result and its visualization were carried out using the software ArcGIS 10.1. RUSLE parameters were integrated and evaluated in the ArcGIS 10.1 environment using a raster calculator in order to estimate the annual soil loss within the KNR. This study recorded the final quantitative RUSLE values by showing the potential annual soil loss with a minimum and maximum value of 0 and 206tons ha-1 year-1 respectively, and a potential mean soil loss of 6tons ha-1 year-1 over the studied period. The outcome of this study reveals that the risk of soil losses in the KNR ranged from low to high over the studied period. This study further demonstrates that remote sensing can be used successfully to quantify soil erosion in the KNR by revealing the critical areas of its occurrence.

ISBN: 9798708792310Subjects--Topical Terms:

3685235
Surface water.
Subjects--Index Terms:

River ecology

An Assessment of Soil Erosion Potential in the Klipriviersberg Nature Reserve Using GIS and Remote Sensing Techniques.
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300 $a 89 p.
500 $a Source: Masters Abstracts International, Volume: 82-11.
500 $a Advisor: Ahmed, Fethi ;Elbasit, Mohamed Abd.
502 $a Thesis (M.Sc.)--University of Johannesburg (South Africa), 2018.
506 $a This item must not be sold to any third party vendors.
520 $a To guarantee the sustainability of South African nature reserves, there is a need to pay attention to the threats faced by soils in nature reserves. Soil, which makes up part of the natural environment, needs to be protected. Given these environmental management concerns, this study aimed at quantifying the amount of soil loss and maps the soil erosion potential risk in one of the South African nature reserves - Klipriviersberg Nature Reserve.In order to achieve this, the Revised Universal Soil Loss Equation (RUSLE) model was used. The RUSLE model preparation, data management, evaluation of result and its visualization were carried out using the software ArcGIS 10.1. RUSLE parameters were integrated and evaluated in the ArcGIS 10.1 environment using a raster calculator in order to estimate the annual soil loss within the KNR. This study recorded the final quantitative RUSLE values by showing the potential annual soil loss with a minimum and maximum value of 0 and 206tons ha-1 year-1 respectively, and a potential mean soil loss of 6tons ha-1 year-1 over the studied period. The outcome of this study reveals that the risk of soil losses in the KNR ranged from low to high over the studied period. This study further demonstrates that remote sensing can be used successfully to quantify soil erosion in the KNR by revealing the critical areas of its occurrence.
590 $a School code: 2140.
650 4 $a Surface water. $3 3685235
650 4 $a Topography. $3 3561794
650 4 $a Soil erosion. $3 602940
650 4 $a Provinces. $3 3549414
650 4 $a Environmental impact. $3 3564810
650 4 $a Energy. $3 876794
650 4 $a Reforestation. $3 612282
650 4 $a Land degradation. $3 2054631
650 4 $a Objectives. $3 3561496
650 4 $a Ecosystems. $3 595401
650 4 $a Climate change. $2 bicssc $3 2079509
650 4 $a Wildlife conservation. $2 fast $3 542165
650 4 $a Agriculture. $3 518588
650 4 $a Vegetation. $3 3560047
650 4 $a Geography. $3 524010
650 4 $a Precipitation. $3 3680799
650 4 $a Remote sensing. $3 535394
650 4 $a Creeks & streams. $3 3685269
650 4 $a Permeability. $3 915594
650 4 $a River ecology. $3 3685237
650 4 $a Mapping. $3 3355992
650 4 $a Runoff. $3 696138
650 4 $a Geographic information systems. $3 542758
650 4 $a Geographic information science. $3 3432445
653 $a River ecology
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