Automatic Speech Recognition (ASR) by machine is an attractive research topic in signal processing domain and has attracted many researchers to contribute in this area. In recent year, there have been many advances in automatic speech reading system with the inclusion of audio and visual speech features to recognize words under noisy conditions. The objective of audio-visual speech recognition system is to improve recognition accuracy. In this paper we computed visual features using Zernike moments and audio feature using Mel Frequency Cepstral Coefficients (MFCC) on 'vVISWa' (Visual Vocabulary of Independent Standard Words) dataset which contains collection of isolated set of city names of 10 speakers. The visual features were normalized and dimension of features set was reduced by Principal Component Analysis (PCA) in order to recognize the isolated word utterance on PCA space.The performance of recognition of isolated words based on visual only and audio only features results in 63.88% and 100% respectively.

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Drought is natural hazard which is caused due to shortage of rainfall. Among the natural hazards, drought is hard to find out because it grows gradually and have huge impact on nature, human habitat and economy. Many satellite based drought indices have so far been suggested for regional and national levels. Meteorological and satellite based indices are used to detect different types of drought, including meteorological, agricultural and hydrological drought. NOAA-AVHRR, MODIS data are used in worldwide for vegetation analysis and drought monitoring and drought assessment. The several meteorological variables (indicators) such as precipitation, temperature, humidity and evapotranspiration are required to calculate drought severity level. The nature of drought indices shows different climate dryness, precipitation deficit or correspond to delayed hydrological impacts such as lowered water level in reservoir, lake, river streams, soil moisture level and agriculture crop health. The long term historical records of satellite imagery and climatic data are essential to calculate drought severity level and to determine drought risk prone area. The agriculture sector is vulnerable to the drought. Now day's satellite imagery has been used in agriculture drought assessment. The government agencies and district based municipal department can create drought mitigation plan based on drought monitoring model. This review paper has discussed the use of remotely sensed data for agriculture drought assessment.

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