Remote Sensing Applied to Agricultural Crops | Calculating the crop coefficient (Kc) in rice crops in southern Brazil

Diogo Silveira Kersten (u. a.)

ISBN 10: 6206623831 / ISBN 13: 9786206623830

Published by Our Knowledge Publishing, 2023

About this Item

Remote Sensing Applied to Agricultural Crops | Calculating the crop coefficient (Kc) in rice crops in southern Brazil | Diogo Silveira Kersten (u. a.) | Taschenbuch | Englisch | 2023 | Our Knowledge Publishing | EAN 9786206623830 | Verantwortliche Person für die EU: preigu GmbH & Co. KG, Lengericher Landstr. 19, 49078 Osnabrück, mail[at]preigu[dot]de | Anbieter: preigu.

Seller Inventory # 127873726

Bibliographic Details

• Title: Remote Sensing Applied to Agricultural Crops | Calculating the crop coefficient (Kc) in rice crops in southern Brazil
• Publisher: Our Knowledge Publishing
• Publication Date: 2023
• Language: English
• ISBN 10: 6206623831
• ISBN 13: 9786206623830
• Binding: Taschenbuch
• Condition: Neu
• Dimensions: 220W x 150H x 4D millimeters 220 millimeters width by 150 millimeters height by 4 millimeters depth
• Weight: 96 grams
• Seller catalogs:
  • Bücher

About this title

Synopsis

The rational use of natural resources is increasingly arousing the interest of public and private managers with regard to agricultural and industrial activities, leading to an intensification of studies that incorporate environmental planning, assessing and diagnosing the state of environments in an attempt to minimise possible impacts caused by their exploitation. This work was carried out in the municipality of Itaqui - RS, Brazil, which has large areas of floodplains where flood-irrigated rice is grown. In the 2013/14 agricultural year, the municipality had one of the largest areas planted with rice, accounting for approximately 10% of production in the state of RS. Since rice crops are irrigated by surface flooding, they have a water use efficiency of approximately 40%, which justifies the importance of knowing the qualitative and quantitative aspects of water management for the development of the crop, as well as characterising the type of soil in which it is produced. Thus, based on methodologies that use remote sensors and geographic information systems (GIS), it is possible to estimate the starting point of the crop, as well as its development until harvest.