0000000000496548

AUTHOR

Sivasathivel Kandasamy

0000-0001-9943-4535

showing 3 related works from this author

Optimization of image parameters using a hyperspectral library application to soil identification and moisture estimation

2009

The growing number of sensors raises questions about the image parameters required for the application, soil identification and moisture estimation. Hyperspectral images are also known to contain highly redundant information. Hence not all the spectral bands are needed for the satisfactory classification of the soil types. Hence, the work was aimed at obtaining these optimal spectral bands for identifying the soil types and to use these spectral bands to estimate the moisture content of the soils using the method proposed by Whiting et.al.

Identification (information)MoistureSoil waterEnvironmental scienceHyperspectral imagingFeature selectionSoil classificationSpectral bandsWater contentPhysics::GeophysicsRemote sensing2009 IEEE International Geoscience and Remote Sensing Symposium
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Quantification of LAI interannual anomalies by adjusting climatological patterns

2011

International audience; Scaling variations and shifts in the timing of seasonal phenology are central features of global change research. In this study, we propose a novel climatology fitting approach to quantify inter-annual anomalies in LAI seasonality. A consistent archive of daily LAI estimates was first derived from historical AVHRR satellite data for the 1981-2000 period over a globally representative sample of sites. The climatology values were then computed by averaging multi-year LAI profiles, gap filling and smoothing to eliminate possible high temporal frequency residual artifacts. The inter-annual variations in LAI were finally quantified by scaling and shifting the seasonal cli…

AVHRR010504 meteorology & atmospheric sciencesPhenology0211 other engineering and technologiesGlobal change02 engineering and technologyAtmospheric modelVegetationclimatology fittingSeasonalityResidualmedicine.disease01 natural sciencesLAIClimatology[SDE]Environmental SciencesmedicineEnvironmental scienceIndex Terms— inter-annual anomaliesTime seriesSmoothing021101 geological & geomatics engineering0105 earth and related environmental sciencesRemote sensing
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Optimal band selection for future satellite sensor dedicated to soil science

2009

Hyperspectral imaging systems could be used for identifying the different soil types from the satellites. However, detecting the reflectance of the soils in all the wavelengths involves the use of a large number of sensors with high accuracy and also creates a problem in transmitting the data to earth stations for processing. The current sensors can reach a bandwidth of 20 nm and hence, the reflectance obtained using the sensors are the integration of reflectance obtained in each of the wavelength present in the spectral band. Moreover, not all spectral bands contribute equally to classification and hence, identifying the bands necessary to have a good classification is necessary to reduce …

Statistical classificationContextual image classificationComputer scienceBandwidth (signal processing)Hyperspectral imagingSatelliteFeature selectionSpectral bandsData transmissionRemote sensing2009 First Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing
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