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A field experiment was conducted at the B A College of Agriculture, Anand Agricultural University, Anand (India)(22°35’N, 72°55’E; 45.1 m MSL)during rabi (winter) season of 2003-2004 on a sandy loam soil to study the effect of row orientation and row spacing on radiation interception, Leaf Area Index and Light extinction coefficient in Wheat (Triticum aestivum L.) cv. GW-496 under two dates of sowing. The PAR values in terms of incident/incoming PAR and transmitted PAR at the field were measured after canopy development (i.e. 23 Days after sowing) at 10 day intervals at 0900-1000 h, 1200-1300 h and 1500-1600 h in a day with a Sun San Canopy Analysis System (Delta-T Devices, UK). LAI was also measured directly by the Sun Scan Canopy Analysis System at noon. The instantaneous values were averaged for that day and were converted to MJm-2 day-1. Solar radiation was recorded by a Pyranometer. The conversion of the daily solar radiation to PAR was made by employing a 0.5 fraction. Narrow NS (North-South) rows in general produced higher LAI throughout the growing season. NS row with narrow spacing was the most effective treatment in relation to the accumulated IPAR values, although the differences in the values corresponding to other treatments were not remarkable. The fluctuations in extinction coefficient (k) values were less random in NS rows than those corresponding ones for EW rows.

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Drought is a complex hazard which directly affects the water balance of any region. It impacts agricultural, ecological and socioeconomical spheres. It is a global concern. The occurrence of drought is triggered by climatic phenomena which cannot be eliminated. However, its effect can be well managed if actual spatio-temporal information related to crop status influenced by drought is available to decision-makers. This study attempted to assess the efficiency of remote sensing products from space sensors for monitoring the spatio-temporal status of meteorological drought in conjunction with impact on vegetation condition and crop yield. Time series (2000–2019) datasets of TRMM were used to compute SPI and MODIS was used to compute VCI. Association between SPI and VCI was explored. YAI was calculated from the statistical data records. Final observations are that the agricultural crop yield changed as per the climate variability specific to location. The study indicates drought indices derived from remote sensing give a synoptic view because of the course resolution of the satellite images. It does not reveal the precise relationship to the small-scale crop yield. Remote sensing can be an effective way to monitor and understand the dynamics of the drought and agriculture pattern over any region.