Crop Disease Detection Using Remote Sensing Image Analysis

ISBN 10: 3036556052 / ISBN 13: 9783036556055

Published by MDPI AG, 2022

About this Item

Crop Disease Detection Using Remote Sensing Image Analysis | Buch | Gebunden | Englisch | 2022 | MDPI AG | EAN 9783036556055 | Verantwortliche Person für die EU: Libri GmbH, Europaallee 1, 36244 Bad Hersfeld, gpsr[at]libri[dot]de | Anbieter: preigu Print on Demand.

Seller Inventory # 126080490

Bibliographic Details

• Title: Crop Disease Detection Using Remote Sensing Image Analysis
• Publisher: MDPI AG
• Publication Date: 2022
• Language: English
• ISBN 10: 3036556052
• ISBN 13: 9783036556055
• Binding: Buch
• Condition: Neu
• Dimensions: 250W x 175H x 18D millimeters 250 millimeters width by 175 millimeters height by 18 millimeters depth
• Weight: 705 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

Pest and crop disease threats are often estimated by complex changes in crops and the applied agricultural practices that result mainly from the increasing food demand and climate change at global level. In an attempt to explore high-end and sustainable solutions for both pest and crop disease management, remote sensing technologies have been employed, taking advantages of possible changes deriving from relative alterations in the metabolic activity of infected crops which in turn are highly associated to crop spectral reflectance properties. Recent developments applied to high resolution data acquired with remote sensing tools, offer an additional tool which is the opportunity of mapping the infected field areas in the form of patchy land areas or those areas that are susceptible to diseases. This makes easier the discrimination between healthy and diseased crops, providing an additional tool to crop monitoring. The current book brings together recent research work comprising of innovative applications that involve novel remote sensing approaches and their applications oriented to crop disease detection. The book provides an in-depth view of the developments in remote sensing and explores its potential to assess health status in crops.