Assessing of Soil Erosion Risk Through Geoinformation Sciences and
  Remote Sensing -- A Review
Lachezar Filchev Vasil Kolev
During past decades a marked manifestation of widespread erosion phenomena
was studied worldwide. Global conservation community has launched campaigns at
local, regional and continental level in developing countries for preservation
of soil resources in order not only to stop or mitigate human impact on nature
but also to improve life in rural areas introducing new approaches for soil
cultivation. After the adoption of Sustainable Development Goals of UNs and
launching several world initiatives such as the Land Degradation Neutrality
(LDN) the world came to realize the very importance of the soil resources on
which the biosphere relies for its existence. The main goal of the chapter is
to review different types and structures erosion models as well as their
applications. Several methods using spatial analysis capabilities of geographic
information systems (GIS) are in operation for soil erosion risk assessment,
such as Universal Soil Loss Equation (USLE), Revised Universal Soil Loss
Equation (RUSLE) in operation worldwide and in the USA and MESALES model. These
and more models are being discussed in the present work alongside more
experimental models and methods for assessing soil erosion risk such as
Artificial Intelligence (AI), Machine and Deep Learning, etc. At the end of
this work, a prospectus for the future development of soil erosion risk
assessment is drawn.