977 resultados para Normalize different vegetation indices


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Dissertation submitted in partial fulfillment of the requirements for the Degree of Master of Science in Geospatial Technologies.

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

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This paper analyses the associations between Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) on the prevalence of schistosomiasis and the presence of Biomphalaria glabrata in the state of Minas Gerais (MG), Brazil. Additionally, vegetation, soil and shade fraction images were created using a Linear Spectral Mixture Model (LSMM) from the blue, red and infrared channels of the Moderate Resolution Imaging Spectroradiometer spaceborne sensor and the relationship between these images and the prevalence of schistosomiasis and the presence of B. glabrata was analysed. First, we found a high correlation between the vegetation fraction image and EVI and second, a high correlation between soil fraction image and NDVI. The results also indicate that there was a positive correlation between prevalence and the vegetation fraction image (July 2002), a negative correlation between prevalence and the soil fraction image (July 2002) and a positive correlation between B. glabrata and the shade fraction image (July 2002). This paper demonstrates that the LSMM variables can be used as a substitute for the standard vegetation indices (EVI and NDVI) to determine and delimit risk areas for B. glabrata and schistosomiasis in MG, which can be used to improve the allocation of resources for disease control.

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In unfertilized, highly weathered tropical soils, phosphorus (P) availability to plants is dependent on the mineralization of organic P (Po) compounds. The objective of this study was to estimate the mineralization of total and labile Po in soil size fractions of > 2.0, 2.0-0.25 and < 0.25 mm under leguminous forest tree species, pasture and "capoeira" (secondary forest) in the 0-10 cm layer of a Red-Yellow Latosol after 90 d of incubation. The type of vegetation cover, soil incubation time and soil size fractions had a significant effect on total P and labile P (Pi and Po) fraction contents. The total average Po content decreased in soil macroaggregates by 25 and 15 % in the > 2.0 and 2.0-0.25 mm fractions, respectively. In contrast, there was an average increase of 90 % of total Po in microaggregates of < 0.25 mm. Labile Po was significantly reduced by incubation in the > 2.0 (-50 %) and < 0.25 mm (-76 %) fractions, but labile Po increased by 35 % in the 2.0-0.25 mm fraction. The Po fraction relative to total extracted P and total labile P within the soil size fractions varied with the vegetation cover and incubation time. Therefore, the distribution of P fractions (Pi and Po) in the soil size fraction revealed the distinctive ability of the cover species to recycle soil P. Consequently, the potential of Po mineralization varied with the size fraction and vegetation cover. Because Po accounted for most of the total labile P, the P availability to plants was closely related to the mineralization of this P fraction.

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Surveys were carried out in terra firme' forest, successional forest, buritirana' (palm vegetation) and shrub canga' (savanna). Extrafloral nectaries (EFNs) were present in 30 plant species belonging to 22 genera and 14 families. Nectary species represented 17.6-53.3% of the species samples in different areas, with local abundances varying from 19.1-50.0%. The percentage of species with EFNs was greater in the flora of the shrub canga than in the terra firme and successional forests. Nectary plants were more abundant in the shrub canga and successional forest. The high abundance of EFNs may be the result of intense foraging activity by ants on plants, leading to the formation of facultative mutualism. -from Authors

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The carbon (C) sink strength of arctic tundra is under pressure from increasing populations of arctic breeding geese. In this study we examined how CO2 and CH4 fluxes, plant biomass and soil C responded to the removal of vertebrate herbivores in a high arctic wet moss meadow that has been intensively used by barnacle geese (Branta leucopsis) for ca. 20 years. We used 4 and 9 years old grazing exclosures to investigate the potential for recovery of ecosystem function during the growing season (July 2007). The results show greater above- and below-ground vascular plant biomass within the grazing exclosures with graminoid biomass being most responsive to the removal of herbivory whilst moss biomass remained unchanged. The changes in biomass switched the system from net emission to net uptake of CO2 (0.47 and -0.77 µmol/m**2/s in grazed and exclosure plots, respectively) during the growing season and doubled the C storage in live biomass. In contrast, the treatment had no impact on the CH4 fluxes, the total litter C pool or the soil C concentration. The rapid recovery of the above ground biomass and CO2 fluxes demonstrates the plasticity of this high arctic ecosystem in terms of response to changing herbivore pressure.

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The Iberian pig valued natural resources of the pasture when fattened in mountain. The variability of acorn production is not contained in any line of Spanish agricultural insurance. However, the production of arable pasture is covered by line insurance number 133 for loss of pasture compensation. This scenario is only contemplated for breeding cows and brave bulls, sheep, goats and horses, although pigs are not included. This insurance is established by monitoring ten-day composites Normalized Difference Vegetation Index (NDVI) measured by satellite over treeless pastures, using MODIS TERRA satellite. The aim of this work is to check if we can use a satellite vegetation index to estimate the production of acorns.

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Resources created at the University of Southampton for the module Remote Sensing for Earth Observation

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Remote sensing is a promising approach for above ground biomass estimation, as forest parameters can be obtained indirectly. The analysis in space and time is quite straight forward due to the flexibility of the method to determine forest crown parameters with remote sensing. It can be used to evaluate and monitoring for example the development of a forest area in time and the impact of disturbances, such as silvicultural practices or deforestation. The vegetation indices, which condense data in a quantitative numeric manner, have been used to estimate several forest parameters, such as the volume, basal area and above ground biomass. The objective of this study was the development of allometric functions to estimate above ground biomass using vegetation indices as independent variables. The vegetation indices used were the Normalized Difference Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Simple Ratio (SR) and Soil-Adjusted Vegetation Index (SAVI). QuickBird satellite data, with 0.70 m of spatial resolution, was orthorectified, geometrically and atmospheric corrected, and the digital number were converted to top of atmosphere reflectance (ToA). Forest inventory data and published allometric functions at tree level were used to estimate above ground biomass per plot. Linear functions were fitted for the monospecies and multispecies stands of two evergreen oaks (Quercus suber and Quercus rotundifolia) in multiple use systems, montados. The allometric above ground biomass functions were fitted considering the mean and the median of each vegetation index per grid as independent variable. Species composition as a dummy variable was also considered as an independent variable. The linear functions with better performance are those with mean NDVI or mean SR as independent variable. Noteworthy is that the two better functions for monospecies cork oak stands have median NDVI or median SR as independent variable. When species composition dummy variables are included in the function (with stepwise regression) the best model has median NDVI as independent variable. The vegetation indices with the worse model performance were EVI and SAVI.

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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).

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The aim of this study was to use digital images acquired by cameras attached to a helium balloon to detect variation of the nutritional status in Brachiaria decumbens. The treatments consisted of five doses of nitrogen (0, 50, 100, 150 e 200kg ha-1) with six replications each, evaluated in a completely randomized statistical design. A remote sensing system composed of digital cameras and microcomputers was used for image acquisition, and a helium balloon lifted the cameras to the heights of 15, 20, 25 and 30m. A portable chlorophyll meter and analyses of leaf nitrogen content were used to make comparisons with data obtained by the remote sensing system. Data was acquired in two phases, in different climatic conditions. At the end of each phase, dry matter production was measured. Three vegetation indices were used to evaluate the detection of different nutritional status. The three indices were able to detect the effects of N doses. The indices constructed with the Green spectral band showed to be more efficient.

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Pós-graduação em Agronomia (Energia na Agricultura) - FCA

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The mean transit time (MTT) of water in a catchment gives information about storage, flow paths, sources of water and thus also about retention and release of solutes in a catchment. To our knowledge there are only a few catchment studies on the influence of vegetation cover changes on base flow MTTs. The main changes in vegetation cover in the Swiss Alps are massive shrub encroachment and forest expansion into formerly open habitats. Four small and relatively steep headwater catchments in the Swiss Alps (Ursern Valley) were investigated to relate different vegetation cover to water transit times. Time series of water stable isotopes were used to calculate MTTs. The high temporal variation of the stable isotope signals in precipitation was strongly dampened in stream base flow samples. MTTs of the four catchments were 70 to 102 weeks. The strong dampening of the stable isotope input signal as well as stream water geochemistry points to deeper flow paths and mixing of waters of different ages at the catchments' outlets. MTTs were neither related to topographic indices nor vegetation cover. The major part of the quickly infiltrating precipitation likely percolates through fractured and partially karstified deeper rock zones, which increases the control of bedrock flow paths on MTT. Snow accumulation and the timing of its melt play an important role for stable isotope dynamics during spring and early summer. We conclude that, in mountainous headwater catchments with relatively shallow soil layers, the hydrogeological and geochemical patterns (i.e. geochemistry, porosity and hydraulic conductivity of rocks) and snow dynamics influence storage, mixing and release of water in a stronger way than vegetation cover or topography do.