Evaluation of remote sensing data for moorland erosion

Evaluation of remote sensing data for moorland erosion by Mohamed S. Alam Download PDF EPUB FB2

REMOTE SENSING BASED DETECTION OF FORESTED WETLANDS: AN EVALUATION OF LIDAR, AERIAL IMAGERY, AND THEIR DATA FUSION by Ashley Elizabeth Suiter B.S., Central Michigan University, A Thesis Submitted in Partial Fulfillment of the Requirements for the Master of Science Department of Geography and Environmental Resources in the Graduate School.

This book focuses on grassland ecosystem evaluation including vegetation coverage, net primary productivity, carbon sink accounting, and grassland degradation evaluation based on mutual data resource, ecosystem model simulation, remote sensing monitoring and driving mechanism exploration.

In the group of active remote sensing methods, the best method is a backscatter empirical model, which gives a %GSM RMSE and a % correlation between the estimated and the field soil by: Remote sensing (RS) data are used for estimating bio-physical parameters and indices besides cropping systems analysis, and land-use and land-cover estimations during different seasons5,6.

However, RS data alone cannot sug-gest crop suitability for an area unless the data are inte-grated with the site-specific soil and climate data.

erosion occurred in the beach of Kalaignanapuram during and the minimum erosion rate at Pachayapuram with magnitudes of m3/year and m3/year respectively. In the yearKalaignanapuram beach showed a high erosion rate of m3/year and Vembar beach had endured the Management of coastal erosion using remote sensing.

was calculated for estimating the cost of soil erosion. Two basic data sources were used for evaluating thecost of soil erosion: (1) soil mapping units with the respective composition of Nitrogen, Phosphorus and Potassium and (2) annual soil erosion rate in each soil mapping units.

A flowchart describing the methodology for estimation of cost. This research studies the quantification of soil erosion under different levels of data availability in Wadi Yalamlam.

Remote Sensing (RS) and Geographic Information Systems (GIS) techniques have been implemented for the assessment of the data, applying the Revised Universal Soil Loss Equation (RUSLE) for the calculation of the risk of by:   The present study was undertaken to assess the annual rate of soil erosion from the study watershed using distributed information for topography, land use, soil, etc.

using remote sensing (RS) and geographic information system (GIS) techniques and to compare the simulated sediment loss with observed sediment by: 8. Traditionally, remote sensing has been used for soil erosion research through aerial photo interpretation both for detecting erosion features (e.g.

Bergsma,Jones and Keech, ) and obtaining model input data (e.g. Morgan and Napela,Stephens et al., ). Starting in with the launch of Landsat-1, satellite imagery has Cited by: Another popular proxy is the intersection of a tidal datum with the coastal profile, known as mean high water (MHW).

Potential data sources for investigating shorelines include historical and aerial photographs, coastal maps, beach surveys, in situ GPS, and a range of remote sensing data. The process of identifying a shoreline involves first selecting and defining an indicator feature, and then detecting the chosen features from the available Size: KB.

Remote sensing and GIS based assessment of soil erosion and soil loss risk around hill top surface mines situated in Saranda Forest, Jharkhand Mali Vijay Kisan 1 Department of Agricultural and Food Engineering, Indian Institute of Technology, KharagpurIndiaCited by: 3. • Soils and erosion sensitivity in Nigeria • Forest fires in Syria • Roll call Remote Sensing • Collect data about • Visible –Invisible Collect evaluation data 8.

Calculate map accuracy 9. Produce final results and reports. 45 Interpretation. Remote sensing and geographic information system (GIS) were used to reduce the time and costs needed for rapid assessment of gully erosion.

Firstly, a gully erosion inventory map (GEIM) with gully locations was obtained from various sources and randomly divided into two groups: A training dataset (70% of the data) and a validation dataset (30% of the data).

Various proximal and remote sensing disciplines such as laboratory and field sensors, unmanned aerial vehicles, and airborne and spaceborne sensors are essential tools, well-suited for surveying large areas and monitoring soil degradation at a high temporal and spatial interval.

erosion lossin other regions of the world (Millward and Mersey, ; Reusing et al., ; Angima et al.,Ma et al.,). In general, RUSLE is used for estimating average annual soil erosion loss based on sample plot data.

Theuse of remote sensing and GIS allows us to map the spatial distribution of soil erosion risk. However,File Size: KB.

Spatial Techniques for Soil Erosion Estimation Remote Sensing and GIS Approach Rupesh Jayaram Patil Abstract Soil erosion is a global threat to the natural resources and is particularly responsible for reduction in crop yield due to reduction in land productivity and storage capacity of multipurpose reservoirs due to continuous siltation.

From mineral deposits, to remote sensing, to sampling and analysis, Essentials of Mineral Exploration and Evaluation offers an extensive look at this rapidly changing field. Key Features Covers the complete spectrum of all aspects of ore deposits and mining them, providing a.

The main conceptual features of the book are: To combine various aspects of geological remote sensing, ranging from the laboratory spectra of minerals and rocks to aerial and space-borne remote sensmg. - To integrate photogeology into remote sensing.

- To promote remote sensing as a tool in integrated geoexploration. System (GIS), Remote Sensing (RS) and Multi-Criteria Evaluation (MCE) techniques to quantify and map erosion vulnerable areas using RUSLE model. Slope gradient, slope length, soil type, soil con-File Size: 3MB.

Although a variety of rainfall-runoff models are available, selection of a suitable rainfall-runoff model for a given watershed is essential to ensure efficient planning and management of watersheds. Such studies are relatively limited in developing nations, including India.

In this study, rainfall-runoff modeling was carried out using HEC-HMS and WEPP hydrologic models, and remote sensing Cited by:. The Third Edition of this book retains the basic principles of remote sensing, introduced in the earlier editions. It covers all aspects of the subject from electromagnetic radiation, its.Available remote sensing data for the Dubračina River Basin were stereopairs of aerial photographs from and high resolution DEM derived from the airborne LiDAR survey conducted in March Remote Sensing & Assessment of Soil Resources [A.K.

Kolay] on *FREE* shipping on qualifying offers. Remote Sensing & Assessment of Soil Resources.