Paper
19 October 2012 Water productivity assessment by using MODIS images and agrometeorological data in the Petrolina municipality, Brazil
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Abstract
The municipality of Petrolina, located in the semi-arid region of Brazil, is highlighted as an important agricultural growing region, however the irrigated areas have cleared natural vegetation inducing a loss of biodiversity. To analyze the contrast between these two ecosystems the large scale values of biomass production (BIO), evapotranspiration (ET) and water productivity (WP) were quantified. Monteith´s equation was applied for estimating the absorbed photosynthetically active radiation (APAR), while the new SAFER (Simple Algorithm For Evapotranspiration Retrieving) algorithm was used to retrieve ET. The water productivity (WP) was analysed by the ratio of BIO by ET at monthly time scale with four bands of MODIS satellite images together with agrometeorological data for the year of 2011. The period with the highest water productivity values were from March to April in the rainy period for both irrigated and not irrigated conditions. However the largest ET rates were in November for irrigated crops and April for natural vegetation. More uniformity of the vegetation and water variables occurs in natural vegetation, evidenced by the lower values of standard deviation when comparing to irrigated crops, due to the different crop stages, cultural and irrigation managements. The models applied with MODIS satellite images on a large scale are considered to be suitable for water productivity assessments and for quantifying the effects of increasing irrigated areas over natural vegetation on regional water consumption in situations of quick changing land use pattern.
© (2012) COPYRIGHT Society of Photo-Optical Instrumentation Engineers (SPIE). Downloading of the abstract is permitted for personal use only.
Antônio H. de C. Teixeira, Morris Sherer-Warren, Fernando B. T. Hernandez, and Hélio L. Lopes "Water productivity assessment by using MODIS images and agrometeorological data in the Petrolina municipality, Brazil", Proc. SPIE 8531, Remote Sensing for Agriculture, Ecosystems, and Hydrology XIV, 85310G (19 October 2012); https://doi.org/10.1117/12.974376
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Cited by 6 scholarly publications.
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KEYWORDS
Vegetation

MODIS

Biological research

Earth observing sensors

Roentgenium

Satellites

Data modeling

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