Paper
2 October 2008 Estimating irrigation demand using satellite remote sensing: a case study of Paphos District area in Cyprus
Author Affiliations +
Proceedings Volume 7104, Remote Sensing for Agriculture, Ecosystems, and Hydrology X; 71040I (2008) https://doi.org/10.1117/12.800366
Event: SPIE Remote Sensing, 2008, Cardiff, Wales, United Kingdom
Abstract
The monitoring of agricultural areas in Cyprus provides important data for efficient water supply plans and for avoiding unnecessary water lost due to inefficient irrigation. In this context, satellite remote sensing techniques may be useful as an efficient tool for monitoring agricultural areas. The objective of this study is to present the overall methodology for monitoring agricultural areas and estimating the irrigation demand in Cyprus using satellite remote sensing, irrigation models and other auxiliary data. Field spectro-radiometric measurements using SVC-HR 1024 and GER 1500 were undertaken to determine the spectral signature of different types of crops so as to assist our classification techniques. Final crop maps using Landsat TM and ETM+ can be produced and the optimal amount of irrigation demand required for certain types of crops can be determined in order to avoid any non-effective water management. This paper presents the overall methodology of the proposed research study designed to enable the implementation of an integrated approach by combining satellite remote sensing, irrigation models, micro-sensor technology and in-situ spectroradiometric measurements to determine the irrigation demand and finally to validate our results.
© (2008) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Diofantos G. Hadjimitsis, Giorgos Papadavid, Kyriacos Themistokleous, Anastasis Kounoudes, and Leonidas Toulios "Estimating irrigation demand using satellite remote sensing: a case study of Paphos District area in Cyprus", Proc. SPIE 7104, Remote Sensing for Agriculture, Ecosystems, and Hydrology X, 71040I (2 October 2008); https://doi.org/10.1117/12.800366
Lens.org Logo
CITATIONS
Cited by 10 scholarly publications.
Advertisement
Advertisement
RIGHTS & PERMISSIONS
Get copyright permission  Get copyright permission on Copyright Marketplace
KEYWORDS
Remote sensing

Satellites

Agriculture

Earth observing sensors

Reflectivity

Data modeling

Sensor networks

Back to Top