Share Email Print
cover

Proceedings Paper

Options for using Landsat and RapidEye satellite images aiming the water productivity assessments in mixed agro-ecosystems
Author(s): Antônio H. de C. Teixeira; Janice F. Leivas; Gustavo Bayma-Silva
Format Member Price Non-Member Price
PDF $14.40 $18.00
cover GOOD NEWS! Your organization subscribes to the SPIE Digital Library. You may be able to download this paper for free. Check Access

Paper Abstract

For water productivity (WP) assessments, the SAFER (Surface Algorithm for Evapotranspiration Retrieving) algorithm for evapotranspiration (ET) and the Monteith’s light use efficiency (LUE) model for biomass production (BIO), were applied to Landsat and RapidEye satellite images, in the Brazilian semiarid region, inside the dry season of 2011, in a mixture of irrigated and rainfed agro-ecosystems. Firstly, with the Landsat image, the methodology from which the surface temperature (T0) is derived as a residue in the radiation balance was tested. Low differences were detected, being Landsat ET with the thermal band averaged 0.9 ± 1.5 mm d-1, while without it the mean value was 0.8 ± 1.5 mm d-1. The corresponding Landsat BIO values were respectively 28 ± 59 and 28 ± 58 kg ha-1 d-1, resulting in mean WP of 1.3 ± 1.3 kg m-3, in both cases. After having confidence on the residual methodology for retrieving T0 it was applied to the RapidEye image, resulting in average pixel values for ET, BIO and WP of 0.6 ± 1.5 mm d-1, 26 ± 58 kg ha-1 d-1 and 0.9 ± 1.3 kg m-3, representing 75%, 93% and 69% of the Landsat ones obtained without the thermal band. In addition, the Surface Resistance Algorithm (SUREAL) was used to classify the agro-ecosystems into irrigated crops and natural vegetation by using the RapidEye image. The incremental values for ET, BIO and WP in 2011 were 2.0 ± 1.3 mm d-1, 88 ± 87 kg ha d-1 and 2.5 ± 0.6 kg m-3, respectively, as a result of the replacement of the natural species by crops.

Paper Details

Date Published: 25 October 2016
PDF: 11 pages
Proc. SPIE 9998, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVIII, 99980A (25 October 2016); doi: 10.1117/12.2240119
Show Author Affiliations
Antônio H. de C. Teixeira, Embrapa Satellite Monitoring (Brazil)
Janice F. Leivas, Embrapa Satellite Monitoring (Brazil)
Gustavo Bayma-Silva, Embrapa Satellite Monitoring (Brazil)


Published in SPIE Proceedings Vol. 9998:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XVIII
Christopher M. U. Neale; Antonino Maltese, Editor(s)

© SPIE. Terms of Use
Back to Top