Abstract
To the soil conservationalist, remote sensing methodologies provide profuse and updated information about soil properties, rock exposure, vegetation attributes, and built infrastructure characteristics. This chapter provides an overview of the main characteristics of remotely sensed images, and their use in map** spatial properties of agricultural catchments. It offers several spectral indices for quantifying soil and vegetation properties, using visible and near-infrared data, by means of algebraic band-ratio methods. Next, it describes soft and hard classification techniques, including pixel-based and object-based classification. Another useful application suggests the use of classified remotely sensed data as a tool for computing and map** runoff coefficients, as well as channel network data for guiding drainage determination. Finally, in the past decade, the use of high-resolution drones for land use/land cover classification has become common in soil erosion studies. Extracting DEMs and topographic properties has also become an important part in soil degradation analyses; in particular, change detection of soil loss and soil deposition can be used to estimate sediment budgets. The tools reviewed in this chapter further expand the notion that remotely sensed data can be used to provide evidence of the state and dynamics of a given catchment—thereby providing a general framework for depicting and simulating the mechanisms of water erosion in agricultural catchments.
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Svoray, T. (2022). Earth Observations. In: A Geoinformatics Approach to Water Erosion. Springer, Cham. https://doi.org/10.1007/978-3-030-91536-0_5
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