Soil greenhouse gas emissions and their relations to soil attributes in a sugarcane area

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Plantas de cobertura em pré-safra e adubação nitrogenada no milho em plantio direto

Pós-graduação em Agronomia (Ciência do Solo) - FCAV

Assessing the dynamic of structural changes in Cerrado vegetation of protected and non-protected areas using NDVI

The structure of Brazilian savannah, named locally as “cerrado”, tends to change if the human pressures, such as pasture and intensive fire, are suppressed showing a densification of the physiognomies throughout the time. Vegetation Index acquired from remotely sensed data has been a proper way to study and monitoring large areas, and the Normalized Difference Vegetation Index (NDVI) is one of the most used for this purpose. The aim of this study was to assess the dynamic of structural changes in protected and non-protected areas of cerrado vegetation using NDVI. For this purpose, three cerrado fragments in the state of São Paulo, Brazil, were evaluated for a 26 year time span from 1985 and 2011, being two of them protected against anthropogenic interference. Landsat 5 –Thematic Mapper images were used and processed in ArcGIS. In the protected areas NDVI indicated that the vegetation followed the expected trend of changes for cerrado, with more open physiognomies tending to be denser throughout this period of 26 years, whereas in the non-protected fragment the NDVI evidences human pressure, showing lower phytomass in 2011. NDVI showed to be efficient in detecting and monitoring changes in cerrado vegetation structure, and can be useful to study both, the natural dynamics of cerrado vegetation and the anthropogenic interference in protected areas.

Índices bióticos mono e multimétricos de avaliação da qualidade da água em riachos da Mata Atlântica

Protocols for rapid habitat evaluation and the biotic indices used in biomonitoring of streams in Brazil provide useful information about water quality and modifications in the ecosystem. However, the interpretation of their results is limited. Previous studies pointed out the low sensitivity of those indices to measure the quality of low-order streams, since they only measure organic impacts. Environmental degradation of these streams is mainly related to impacts caused by landscape change, such as erosion, siltation, channel change, loss of riparian vegetation, and reduction in water flow. The streams of the Serra do Japi are under some of these impacts, caused by agricultural activities. In this study, we evaluated whether the reduction of natural characteristics in these environments would decrease water quality. The Protocol of Habitat Diversity was affected by the impacts of agricultural activities. However, the other three biotic indices: Biological Monitoring Working Party Score System, Average Score Per Taxon, and Index of Benthic Community were not as sensitive to those impacts, since they all indicated a high water quality. An adaptation of the attributes and the scoring system is suggested for defining better policies for the conservation of this area.

Discriminação de classes de cobertura vegetal utilizando técnicas de classificação digital de imagens de sensoriamento remoto

The aim of this work is to discriminate vegetation classes throught remote sensing images from the satellite CBERS-2, related to winter and summer seasons in the Campos Gerais region Paraná State, Brazil. The vegetation cover of the region presents different kinds of vegetations: summer and winter cultures, reforestation areas, natural areas and pasture. Supervised classification techniques like Maximum Likelihood Classifier (MLC) and Decision Tree were evaluated, considering a set of attributes from images, composed by bands of the CCD sensor (1, 2, 3, 4), vegetation indices (CTVI, DVI, GEMI, NDVI, SR, SAVI, TVI), mixture models (soil, shadow, vegetation) and the two first main components. The evaluation of the classifications accuracy was made using the classification error matrix and the kappa coefficient. It was defined a high discriminatory level during the classes definition, in order to allow separation of different kinds of winter and summer crops. The classification accuracy by decision tree was 94.5% and the kappa coefficient was 0.9389 for the scene 157/128. For the scene 158/127, the values were 88% and 0.8667, respectively. The classification accuracy by MLC was 84.86% and the kappa coefficient was 0.8099 for the scene 157/128. For the scene 158/127, the values were 77.90% and 0.7476, respectively. The results showed a better performance of the Decision Tree classifier than MLC, especially to the classes related to cultivated crops, indicating the use of the Decision Tree classifier to the vegetation cover mapping including different kinds of crops.

Análise Espacial Multivariada Aplicada na Avaliação da Fertilidade do Solo

Fundação de Amparo à Pesquisa do Estado de São Paulo (FAPESP)

Condicionamento de um subsolo exposto no cerrado por meio de resíduos e da revegetação

Pós-graduação em Agronomia - FEIS