scholarly journals Soil loss estimation using geographic information system in enfraz watershed for soil conservation planning in highlands of Ethiopia

2016 ◽  
Vol 5 (2) ◽  
pp. 21-30 ◽  
Author(s):  
Gizachew Tiruneh ◽  
Mersha Ayalew
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Soil Loss ◽  
Satellite Images ◽  
Geographic Information ◽  
Rainfall Erosivity ◽  
Gis And Remote Sensing ◽  
Digital Elevation ◽  
Elevation Model ◽  
Soil Loss Rate

Accelerated soil erosion is a worldwide problem because of its economic and environmental impacts. Enfraz watershed is one of the most erosion-prone watersheds in the highlands of Ethiopia, which received little attention. This study was, therefore, carried out to spatially predict the soil loss rate of the watershed with a Geographic Information System (GIS) and Remote Sensing (RS). Revised Universal Soil Loss Equation (RUSLE) adapted to Ethiopian conditions was used to estimate potential soil losses by utilizing information on rainfall erosivity (R) using interpolation of rainfall data, soil erodibility (K) using soil map, vegetation cover (C) using satellite images, topography (LS) using Digital Elevation Model (DEM) and conservation practices (P ) using satellite images. Based on the analysis, about 92.31% (5914.34 ha) of the watershed was categorized none to slight class which under soil loss tolerance (SLT) values ranging from 5 to 11 tons ha-1 year-1. The remaining 7.68% (492.21 ha) of land was classified under moderate to high class about several times the maximum tolerable soil loss. The total and an average amount of soil loss estimated by RUSLE from the watershed was 30,836.41 ton year-1 and 4.81 tons ha-1year-1, respectively.Int. J. Agril. Res. Innov. & Tech. 5 (2): 21-30, December, 2015

scholarly journals Spatial Estimation of Soil Erosion Using RUSLE Modeling: the Case of kaffa Zone, South western Ethiopia

2021 ◽  
Author(s):  
Mesfin Anteneh ◽  
Dereje Biru
Keyword(s):  
Soil Loss ◽  
Satellite Images ◽  
Sustainable Land Use ◽  
Rainfall Erosivity ◽  
Model Estimate ◽  
Digital Elevation ◽  
Gis And Rs ◽  
Sentinel 2A ◽  
Elevation Model ◽  
Land Use And Management

Abstract This research was administered to spatially predict the soil loss rate of kaffa zone using model estimate and GIS. Revised Universal Soil Loss Equation (RUSLE) adapted to Ethiopian conditions was accustomed estimate potential soil losses by utilizing information on rainfall erosivity (R) using interpolation of rainfall data, soil erodibility (K) using DSMW soil map, vegetation cover (C) using Sentinel-2A satellite images, topography (LS) using Digital Elevation Model (DEM) and conservation practices (P ) using DEM and satellite images. supported the analysis, the mean and total annual soil loss potential of the study area was 30 tons ha-1 year-1 and 36264.5tons ha-1 year-1, respectively. The result also showed that about 2.89, 8.02, 15.31 and 73.78% of the study area were classified a slight, moderate, high and very high with values ranging 0 to 15 ,15 to50,50 to 200, and > 200 tons ha-1 year-1, respectively. The study demonstrates that the RUSLE using GIS and RS provides great advantage to spatially analyze multi-layer of knowledge. The expected amount of soil loss and its spatial distribution could facilitate sustainable land use and management.

scholarly journals Emerging cross-disciplinary profiles: The Geomatic Epidemiologist

2020 ◽  
Vol 30 (Supplement_5) ◽  
Author(s):  
M Recchioni ◽  
V Castello ◽  
S Del Vecchio ◽  
V Ciaccio ◽  
A M Donia ◽  
...  
Keyword(s):  
Public Health ◽  
Information System ◽  
Geographic Information System ◽  
Relevant Literature ◽  
Holistic Approach ◽  
Geographic Information ◽  
Health Study ◽  
Gis And Remote Sensing ◽  
Public Health Epidemiology ◽  
And Training

Abstract Issue Geographic information systems (GIS) and remote sensing technologies are increasingly used in Public Health epidemiology, showing a great potential in anticipating and responding to actual and future challenges for the public health system and in improving health services' excellence. According to the evidences collected within a wide meta-research carried on of relevant literature (”GIS geographic information system” and “GIS geographic information system and training” on Pubmed; “epidemiologist use of GIS and training” and “epidemiologist use of gis” on Google Scholar),GIS and new sensing technologies are mostly used to: map air and water pollution, map diseases prevalence, predict infection diseases and vector-spread diseases in big areas, study health service coverage and preparedness in emergencies, map cities and study urban health, study climate changes for decision making. Description of the Problem Specific skills and training are required to address the use of GIS and new sensing technologies.The specific aim of our study is to identify the professional profile of a new figure, called 'Geomatic Epidemiologist' and to define its professional and educational standards, as well as the relevant training programs. Results Data collection and analysis of INAPP and ESCO databases about existing professional profiles (starting from 2016) has allowed drafting a first qualification schema and profile. The profile has been defined according to the 4C model (elaborated by Univaq) distinguishing between Hard Skills (technical knowledge and skills),Soft Skills (cognitive, individual and social) and interpersonal behaviors. Conclusions Profile will be validated with relevant stakeholders and Public Health professionals in order to deepen the understanding of the main competences required to study health issues with GIS and related technologies; to this extent, a questionnaire has been elaborated to evaluate relevance, frequency and complexity of each component of the profile Key messages Developing cross-disciplinary profiles, (i.e. the Geomatic Epidemiologist) integrating clusters of competences (holistic approach). Public health research challenges and excellence.

Delineating soil landscape facets from digital elevation models using compound topographic index in a geographic information system

Soil Research ◽  
2007 ◽  
Vol 45 (8) ◽  
pp. 569 ◽  
Author(s):  
X. Yang ◽  
G. A. Chapman ◽  
J. M. Gray ◽  
M. A. Young
Keyword(s):  
Information System ◽  
Geographic Information System ◽  
Land Use Planning ◽  
Digital Elevation Models ◽  
Geographic Information ◽  
Coastal Areas ◽  
Topographic Index ◽  
Digital Elevation ◽  
Soil Landscape ◽  
Compound Topographic Index

Soil landscapes and their component facets (or sub-units) are fundamental information for land capability assessment and land use planning. The aim of the study was to delineate soil landscape facets from readily available digital elevation models (DEM) to assist soil constraint assessment for urban and regional planning in the coastal areas of New South Wales (NSW), Australia. The Compound Topographic Index (CTI) surfaces were computed from 25 m DEM using a D-infinity algorithm. The cumulative frequency distribution of CTI values within each soil landscape was examined to identify the values corresponding to the area specified for each unmapped facet within the soil landscape map unit. Then these threshold values and CTI surfaces were used to generate soil landscape facet maps for the entire coastal areas of NSW. Specific programs were developed for the above processes in a geographic information system so that they are automated, fast, and repeatable. The modelled facets were assessed by field validation and the overall accuracy reached 93%. The methodology developed in this study has been proven to be efficient in delineating soil landscape facets, and allowing for the identification of land constraints at levels of unprecedented detail for the coast of NSW.

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