Teodoro Isnard Ribeiro de Almeida

ASTER and landsat ETM + images applied to sugarcane yield forecast

This paper proposes a method to support sugarcane yield forecast using vegetation spectral indices, principal component analysis and historic yield data. The study area is located in the State of São Paulo, Brazil, and is divided into 11 production plots (108.75 ha), where sugarcane of the RB85 5536 variety is cultivated on red latossol (oxissol‐type) soil and flat topography. The data employed in the study include radiometrically and geometrically corrected enhanced thermatic mapper Plus (ETM+)/Landsat‐7 and ASTER/Terra images, acquired in June and April 2001, respectively, and historic harvest data measured in 2000 and 2001. The method comprises several steps: (a) enhancement of specific spectral responses of vegetation constituents; (b) reduction of spectral dimensions with prioritization of information and weighing of parameters related to foliar area; the data processed through these steps are reduced to a single image (the synthesis image), from which the mean DN (digital number) per cultivated area is calculated; (c) the image DNs are subsequently transformed into ton of stalk per hectare (t ha−1) through normalization, which requires knowledge of the previous years yield for the cultivated production plots under analysis. Yield estimates using the method showed greater precision in comparison to the ubiquitous visual methods employed by the sugarcane agro‐industry in Brazil. Using factual productivity data of the year 2000 harvest only, the method achieved estimate errors varying between 2.57% and 5.65%, compared with 9.06% expected by the sugar factory; whereas using data from the year 2001 harvest, error margins were remarkably lower, around 1%.

Biogeochemical processes and the diversity of Nhecolândia lakes, Brazil

The Pantanal of Nhecolândia, the worlds largest and most diversified field of tropical lakes, comprises approximately 10,000 lakes, which cover an area of 24,000 km(2) and vary greatly in salinity, pH, alkalinity, colour, physiography and biological activity. The hyposaline lakes have variable pHs, low alkalinity, macrophytes and low phytoplankton densities. The saline lakes have pHs above 9 or 10, high alkalinity, a high density of phytoplankton and sand beaches. The cause of the diversity of these lakes has been an open question, which we have addressed in our research. Here we propose a hybrid process, both geochemical and biological, as the main cause, including (1) a climate with an important water deficit and poverty in Ca(2+) in both superficial and phreatic waters; and (2) an elevation of pH during cyanobacteria blooms. These two aspects destabilise the general tendency of Earths surface waters towards a neutral pH. This imbalance results in an increase in the pH and dissolution of previously precipitated amorphous silica and quartzose sand. During extreme droughts, amorphous silica precipitates in the inter-granular spaces of the lake bottom sediment, increasing the isolation of the lake from the phreatic level. This paper discusses this biogeochemical problem in the light of physicochemical, chemical, altimetric and phytoplankton data.

Correlation between the variations of clay content in soils and sediments and the spectral behavior of superjacent vegetation using spectir hyperspectral images

This work approaches geobotany in southeastern Brazil within terrains comprising Forested Savannas, Gallery and Riparian Atlantic forests developed over fluvial-lacustrine sediments and rocks. The notion was to test the ability of SpecTIR V-S hyperspectral imagery (357 VNIR-SWIR channels; spatial resolution of 1m) to identify the variation of clay content in soils/sediments based on spectral patters yielded by the overlying vegetation. Samples were collected for granulometric analysis in the center of 30 plots with 20x20m each. Vegetation was grouped by floristic similarity. Tailored spectral indices were applied to the SpecTIR V-S data. Different indices were needed to extract parameters of the physical environment from varying vegetation. Results indicate that the physiognomies investigated are influenced differently by clay content in soils and that the vegetation also responds distinctly due to subtle textural variations in the subjacent terrains.