2023
DOI: 10.12912/27197050/154994
|View full text |Cite
|
Sign up to set email alerts
|

Contribution of Geomatics, Priority Activity Program Guidelines, and Remote Sensing to Environmental Study in the Cretaceous Basin of Errachidia-Boudenib, Morocco

Abstract: The present study aims at mapping areas vulnerable to water erosion based on the Priority Activity Program/ Regional Activity Center (PAP/CAR) model guidelines, geomatics, remote sensing, and GIS in the Errachidia-Boudenib Cretaceous basin. This basin is located in south-eastern Morocco and covers an area of 13 000 km 2 , the basin is 320 km long and 75 km wide. The method of estimating water erosion is composed of three phases; a predictive phase consisting of a mapping of predisposing factors such as slope, … Show more

Help me understand this report

Search citation statements

Order By: Relevance

Paper Sections

Select...
1

Citation Types

0
0
0

Year Published

2023
2023
2024
2024

Publication Types

Select...
2
1

Relationship

0
3

Authors

Journals

citations
Cited by 3 publications
(1 citation statement)
references
References 6 publications
0
0
0
Order By: Relevance
“…The integration of remote sensing data with predictive models enables the identification of areas vulnerable to environmental risks such as water erosion. This methodology highlights the potential of predictive analytics in environmental risk assessment, providing a framework that can be adapted to various geological contexts, including those in the U.S. (Mehdaoui et al, 2023).…”
Section: Effectiveness Of Predictive Analytics In Risk Identificationmentioning
confidence: 99%
“…The integration of remote sensing data with predictive models enables the identification of areas vulnerable to environmental risks such as water erosion. This methodology highlights the potential of predictive analytics in environmental risk assessment, providing a framework that can be adapted to various geological contexts, including those in the U.S. (Mehdaoui et al, 2023).…”
Section: Effectiveness Of Predictive Analytics In Risk Identificationmentioning
confidence: 99%