5 resultados para International assessment
Resumo:
2015
Resumo:
Clomazone (2-(2-chlorophenyl)methyl-4.4-dimethyl-3-isoxazolidinone) is a post emergence herbicide widely used in rice fields in Rio Grande do Sul (Brazil) with high activity against Gramineae at the recommended application rate(AR).of 700g/ha. The herbicide input into the aquatic ecosystem may occur by aerial application or water drainage. The presence of this chemical in the water may affect non-target organisms leading to impairments in the aquatic food chain. Studies were conducted in this work to evaluate the risk of Clomazone using the estimated mean affective concentration (EC50) for the microalgae Selenastrum capricornutum(96h), the duckweed Lemna valdiviana(96h) and the crustacean Daphnia similis(48h). The EC50 values were 11.2; 31.7 and 13.8 mg/l, respectively. According to the obtained data, and considering a direct input of the herbicide in a 10cm column water, the estimated maximum application rate that doesn't cause acute effects is 5.3 AR for S. capricornutum, 6.5 AR for D. similis and 15.0 AR for L. valdiviana. The estimated maximum application rate that doesn't cause chronic effects is 2.0 AR for D. similis, 1.6 AR for S. capricornutum and 4.5 AR for L. valviana.
Resumo:
2008
Resumo:
2016
Resumo:
Monitoring agricultural crops constitutes a vital task for the general understanding of land use spatio-temporal dynamics. This paper presents an approach for the enhancement of current crop monitoring capabilities on a regional scale, in order to allow for the analysis of environmental and socio-economic drivers and impacts of agricultural land use. This work discusses the advantages and current limitations of using 250m VI data from the Moderate Resolution Imaging Spectroradiometer (MODIS) for this purpose, with emphasis in the difficulty of correctly analyzing pixels whose temporal responses are disturbed due to certain sources of interference such as mixed or heterogeneous land cover. It is shown that the influence of noisy or disturbed pixels can be minimized, and a much more consistent and useful result can be attained, if individual agricultural fields are identified and each field's pixels are analyzed in a collective manner. As such, a method is proposed that makes use of image segmentation techniques based on MODIS temporal information in order to identify portions of the study area that agree with actual agricultural field borders. The pixels of each portion or segment are then analyzed individually in order to estimate the reliability of the temporal signal observed and the consequent relevance of any estimation of land use from that data. The proposed method was applied in the state of Mato Grosso, in mid-western Brazil, where extensive ground truth data was available. Experiments were carried out using several supervised classification algorithms as well as different subsets of land cover classes, in order to test the methodology in a comprehensive way. Results show that the proposed method is capable of consistently improving classification results not only in terms of overall accuracy but also qualitatively by allowing a better understanding of the land use patterns detected. It thus provides a practical and straightforward procedure for enhancing crop-mapping capabilities using temporal series of moderate resolution remote sensing data.