Multispectral remote sensing for site-specific nitrogen fertilizer management

The objective of this work was to evaluate the use of multispectral remote sensing for site-specific nitrogen fertilizer management. Satellite imagery from the advanced spaceborne thermal emission and reflection radiometer (Aster) was acquired in a 23 ha corn-planted area in Iran. For the collection of field samples, a total of 53 pixels were selected by systematic randomized sampling. The total nitrogen content in corn leaf tissues in these pixels was evaluated. To predict corn canopy nitrogen content, different vegetation indices, such as normalized difference vegetation index (NDVI), soil-adjusted vegetation index (Savi), optimized soil-adjusted vegetation index (Osavi), modified chlorophyll absorption ratio index 2 (MCARI2), and modified triangle vegetation index 2 (MTVI2), were investigated. The supervised classification technique using the spectral angle mapper classifier (SAM) was performed to generate a nitrogen fertilization map. The MTVI2 presented the highest correlation (R²=0.87) and is a good predictor of corn canopy nitrogen content in the V13 stage, at 60 days after cultivating. Aster imagery can be used to predict nitrogen status in corn canopy. Classification results indicate three levels of required nitrogen per pixel: low (0-2.5 kg), medium (2.5-3 kg), and high (3-3.3 kg).

Identification of croplands of winter cereals in Rio Grande do Sul state, Brazil, through unsupervised classification of normalized difference vegetation index images

This study aimed to propose methods to identify croplands cultivated with winter cereals in the northern region of Rio Grande do Sul State, Brazil. Thus, temporal profiles of Normalized Difference Vegetation Index (NDVI) from MODIS sensor, from April to December of the 2000 to 2008, were analyzed. Firstly, crop masks were elaborated by subtracting the minimum NDVI image (April to May) from the maximum NDVI image (June to October). Then, an unsupervised classification of NDVI images was carried out (Isodata), considering the crop mask areas. According to the results, crop masks allowed the identification of pixels with greatest green biomass variation. This variation might be associated or not with winter cereals areas established to grain production. The unsupervised classification generated classes in which NDVI temporal profiles were associated with water bodies, pastures, winter cereals for grain production and for soil cover. Temporal NDVI profiles of the class winter cereals for grain production were in agree with crop patterns in the region (developmental stage, management standard and sowing dates). Therefore, unsupervised classification based on crop masks allows distinguishing and monitoring winter cereal crops, which were similar in terms of morphology and phenology.

The potential of natural regeneration of rocky outcrop vegetation on rupestrian field soils in "Serra do Cipó", Brazil

An area's innate potential to regenerate represents a crucial factor for its conservation and management. The seed rain and seed bank are important agents in the regeneration process. Seed banks are particularly important in communities where there is a high proportion of obligate seeders. Rocky outcrops are habitats where most part of the plant species depends on their seeds to reproduce and maintain viable populations. Therefore, seed banks ought to be important in this vegetation physiognomy. We test the hypotheses that the seed bank of the rocky outcrops found in the rupestrian fields of "Serra do Cipó", Brazil, is richer in species and denser than those formed on different vegetation physiognomies neighboring the outcrops. We then compared species abundance, species richness and composition in the rocky outcrops' seed banks with those of sandy and peaty bogs, forests, gallery forests, and "cerrados". Furthermore, we report on the natural regeneration potential of these soils by assessing a greenhouse study on seedling emergence. Soil samples were collected from 0 to 5 and 5 to 10 cm of depth. Rocky outcrops had the poorest in species and less dense seed bank and showed segregation in species composition. Emergence was greater in the most superficial layer. However, soils on rocky outcrops showed the greatest proportion of endemic threatened species in their seed banks, demonstrating their importance for biodiversity conservation of the "Serra do Cipó" rupestrian fields.