Open Daily: 10am - 10pm | Alley door pickup 10am - 7pm 3038 Hennepin Ave Minneapolis, MN
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  • Open Daily: 10am - 10pm
    Alley-side Pickup: 10am - 7pm

    3038 Hennepin Ave Minneapolis, MN
    612-822-4611

Open Daily: 10am - 10pm | Alley-side Pickup: 10am - 7pm
3038 Hennepin Ave Minneapolis, MN
612-822-4611
Advanced Erosion Mapping fusing GIS and Neural Networks

Advanced Erosion Mapping fusing GIS and Neural Networks

Mishra, Kartikeya
Tiwari, H. L.
Arya, Nainik

Paperback

Technology & Engineering

ISBN10: 6208425263
ISBN13: 9786208425265
Publisher: LAP Lambert Academic Publishing
Published: Feb 28 2025
Pages: 72
Weight: 0.24
Height: 0.17 Width: 6.00 Depth: 9.00
Language: English
Soil erosion, a significant environmental challenge, results from the displacement of the upper soil layer by agents such as water, wind, and human activity. This phenomenon not only diminishes soil fertility and agricultural productivity but also affects water quality and ecosystem stability. This book effectively describes the assessment and management of soil erosion by integrating Geographic Information Systems (GIS) and Artificial Neural Networks (ANN) as a powerful approach. GIS facilitates the spatial analysis and visualization of erosion patterns across extensive areas, utilizing diverse data sources like satellite imagery, soil attributes, and topographical details. ANN, with its machine learning capabilities, predicts soil erosion by identifying intricate patterns and relationships within the data. By leveraging the strengths of GIS and ANN, researchers can develop precise and comprehensive soil erosion models, enhancing decision-making for sustainable land management and soil conservation efforts.

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