From blood zone to school zone an analysis of educational industry restructuring requirement after war-ridden decades

Any attack to normal life is not good for individuals and for nations that derail the activities of development It is not only derailing the developments, it forced the decision makers to rearrange the activities and rectify the damages which need additional requirements such as time, skill and knowledge, capital, technology and materials. When a short time attack itself requires such a huge requirements, a war that too consumed more than two decades need huge requirements and some other aspects such as building confidence in domestic as well in international arena. Particularly in educational service, high dropout rate, few education providers, little options to choose in higher education, higher age groups back to education, motivational factors for bring them back to education are few issues that need to be addressed. As informed by UNESCO (United Nations Educational, Scientific and Cultural Organization) Education helps people to develop the attitudes, skills and knowledge to make informed decisions that will improve individuals and nations, now and in the future. For any post conflict development, education becomes higher priority than immediate material needs which has been considered as priority by affected communities, development authorities and Governments. Because Education can provide physical, cognitive and psychological supports and restore the routine and gives hope for the future. It can also serve as a channel for communicating vital messages for trust building, wound healing and base for sustainable development. After 25 years of conflict, Government of Sri Lanka and educational service providers both from domestic and foreign, consumers and other stakeholders can come closer to provide good education to improve economic situation and business environment for sustainable development in Sri Lanka. This study intends to analyze education system restructuring requirement after the war for sustainable development in Sri Lanka

Agricultural drought monitoring in Tamil Nadu in India using Satellite-based multi vegetation indices

Drought being an insidious hazard, is considered to have one of the most complex phenomenons. The proposed study identifies remote sensing-based indices that could act as a proxy indicator in monitoring agricultural drought over Tamil Nadu's region India. The satellite data products were downloaded from 2000 to 2013 from MODIS, GLDAS – NOAH, and TRMM. The intensity of agricultural drought was studied using indices viz., NDVI, NDWI, NMDI, and NDDI. The satellite-derived spectral indices include raw, scaled, and combined indices. Comparing satellite-derived indices with in-situ rainfall data and 1-month SPI data was performed to identify exceptional drought to no drought conditions for September month. The additive combination of NDDI showed a positive correlation of 0.25 with rainfall and 0.23 with SPI, while the scaled NDDI and raw NDDI were negatively correlated with rainfall and SPI. Similar cases were noticed with raw LST and raw NMDI. Indices viz., LST, NDVI, and NDWI performed well; however, it was clear that NDWI performed better than NDVI while LST was crucial in deciding NDVI coverage over the study area. These results showed that no single index could be put forward to detect agricultural drought accurately; however, an additive combination of indices could be a successful proxy to vegetation stress identification.

Effect of different herbicide spray volumes on weed control efficiency of a battery-operated Unmanned aerial vehicle sprayer in transplanted rice (Oryza sativa L.)

The effect of spray volume on weed control in transplanted rice ecosystems using the Unmanned aerial vehicle (UAV) needs to be better understood for management in the advancements of UAV-based spraying technology. The present study aimed to find out the influence of varied spray volumes of 15 L/ha, 20 L/ha and 25 L/ha using the UAV and 500 L/ha using a Knapsack sprayer (KS) to compare the weed density, weed dry matter and weed control efficiency and yield in transplanted rice (Oryza sativa L.). Pre-emergence (PE) application of Pyrazosulfuron-ethyl at 25 g a.i./ha at three days after transplanting (DAT) and post-emergence (PoE) application of Bis-pyribac sodium at 25 g a.i./ha at 25 DAT were used as herbicide treatments. The results revealed that varied spray volumes significantly influenced the weed density, dry matter, and weed control efficiency of the UAV and KS. Application of herbicides using KS (500 L/ha) and UAV (25 L/ha) had better control on the weeds by reducing weed density and dry matter at 20, 40, and 60 DAT, with no significant difference. Higher grain yield and straw yield were recorded in KS (500 L/ha) and UAV (25 L/ha), with no significant difference. However, applying 25 L/ha had better weed control efficiency and higher yield, possibly due to optimum deposition. Considering the low volume application of UAV (25 L/ha) as compared with KS (500 L/ha), it is better to go for the optimal application of 25 L/ha, which is an energy-efficient and cost-effective, labour-saving approach compared to KS

IMPACT OF TSUNAMI 2004 IN COASTAL VILLAGES OF NAGAPATTINAM DISTRICT, INDIA

ABSTRACTA quake-triggered tsunami lashed the Nagapattinam coast of southern India on December 26, 2004 at around 9.00 am (IST). The tsunami caused heavy damage to houses, tourist resorts, fishing boats, prawn culture ponds, soil and crops, and consequently affected the livelihood of large numbers of the coastal communities. The study was carried out in the Tsunami affected villages in the coastal Nagapattinam with the help of remote sensing and geographical information science tools. Through the use of the IRS 1D PAN and LISS 3 merged data and quick bird images, it was found that 1,320 ha of agricultural and non-agricultural lands were affected by the tsunami. The lands were affected by soil erosion, salt deposition, water logging and other deposited sediments and debris. The maximum run-up height of 6.1 m and the maximum seawater inundation distance of 2.2 km were observed at Vadakkupoyyur village in coastal Nagapattinam.Pre and Post Tsunami survey on soil quality showed an increase in pH and EC values, irrespectiveof distance from the sea. The water reaction was found to be in alkaline range (> 8.00) in most of the -1wells. Salinity levels are greater than 4 dS m in all the wells except the ring well. The effect of summer rainfall on soil and water quality showed the dilution of soluble salts. Pumping of water has reduced the salinity levels in the well water samples and as well as in the open ponds. Following the 2004 event, it has become apparent to know the relative tsunami hazard for this coastal Nagapattinam. So, the Tsunami hazard maps are generated using a geographical information systems (GIS) approach and the results showed 20.6 per cent, 63.7 per cent and 15.2 per cent of the study area fall under high hazard, medium hazard and low hazard category respectively

Monitoring vegetation dynamics using multi-temporal Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) images of Tamil Nadu

Vegetation indices serve as an essential tool in monitoring variations in vegetation. The vegetation indices used often, viz., normalized difference vegetation index (NDVI) and enhanced vegetation index (EVI) were computed from MODIS vegetation index products. The present study aimed to monitor vegetation's seasonal dynamics by using time series NDVI and EVI indices in Tamil Nadu from 2011 to 2021. Two products characterize the global range of vegetation states and processes more effectively. The data sources were processed and the values of NDVI and EVI were extracted using ArcGIS software. There was a significant difference in vegetation intensity and status of vegetation over time, with NDVI having a larger value than EVI, indicating that biomass intensity varies over time in Tamil Nadu. Among the land cover classes, the deciduous forest showed the highest mean values for NDVI (0.83) and EVI (0.38), followed by cropland mean values of NDVI (0.71) and EVI (0.31) and the lowest NDVI (0.68) and EVI (0.29) was recorded in the scrubland. The study demonstrated that vegetation indices extracted from MODIS offered valuable information on vegetation status and condition at a short temporal time period

Comparative Analysis of Aerosol Optical Properties over High Altitude Region of Western Ghats in Southern India

Observations of aerosols and Black Carbon (BC) were carried out at Ooty, high altitude region in Western Ghats using Multi wavelength solar radiometer (MWR) and Aethalometer. For the years 2018 and 2021, the Optical Characteristics of Aerosols and Clouds (OPAC) model was used to estimate monthly, seasonal, and spectral variations of aerosol optical properties such as Aerosol Optical Depth (AOD), Single Scattering Albedo (SSA), and Asymmetry Parameter (ASY). The dominance of fine anthropogenic aerosols was shown by higher AOD during the pre-monsoon period. The maximum and minimum seasonal variation of AOD occurred during pre-monsoon (1.1 ± 0.02) and winter (0.21 ± 0.001) respectively. The significant spectral variation of AOD occurred during March to May as it decreases with the increase in wavelength .The SSA increases as the wavelength increases, ranged between 0.83 ± 0.02 and 0.77 ± 0.01.The variability of SSA is significant during January and February which is a characteristic of coarse type aerosols. Asymmetry Parameter with the monthly mean of 0.75 ± 0.01 indicated the forward scattering of aerosols and there is no significant difference in them over the years

Identification of 'Start of Season' in Major Rainfed Crops of Tamil Nadu, India Using Remote Sensing Technology

Cropping seasons are the seasons in which a particular crop is grown. Identification of cropping seasons is crucial for successful cropping in rainfed areas. This research study focuses on the identification of major rainfed crop growing seasons in rainfed areas of Tamil Nadu using remote sensing technology. The MODIS (Moderate-Resolution Image Spectroradiometer) satellite product MOD13Q1 is utilized to produce NDVI (Normalized Difference Vegetation Index) of the study region. Then the NDVI values for each rainfed ground truth point were extracted and the value was used to produce a line graph representing the crop growing period. Likewise, multiple lines were produced for major rainfed crops: Rice, Maize, Pearl millet, Sorghum, Groundnut, Moth bean, Cotton and Chilli. The result reveals that the Maize and Cotton growing season starts in June-July, mostly single crop per year. Rice, Pearl millet, Sorghum and Chilli are also grown as a single crop per year, sowing by the month of October-November. Besides, there was a double-cropping area of Groundnut- Black gram and Groundnut-Moth Bean raised during June-July and October-November respectively

Area Assessment for Rice Crop in Thiruvarur District Assimilating Sentinel 1A Satellite Data

This study proposes an effective method to map rice area using the Sentinel-1A SAR (Synthetic Aperture Radar) time series data over the Thiruvarur district during samba 2021. Fully automated MAPscape-Rice software was used to pre-process the SAR data and extraction of multi-temporal features. The rice-growing area was estimated based on the extracted multi-temporal features and statistics were derived at district and block level in Thiruvarur district. The study area registered a total rice area of 127027 ha; among the blocks, the Kottur block recorded the largest area of 16615 ha and the lowest area of 6865 ha was recorded in the Thiruvarur block. The estimated rice area was validated with the observed rice area in the Thiruvarur district using accuracy assessment, which indicates an overall accuracy of 92.0 per cent and 0.84 kappa co-efficient

Quantification of Biophysical Parameters and Economic Yield in Cotton and Rice Using Drone Technology

New agronomic opportunities for more informed agricultural decisions and enhanced crop management have been made possible by drone-based near-ground remote sensing. Obtaining precise non-destructive information regarding crop biophysical characteristics at spatial and temporal scales is now possible. Drone-mounted multispectral and thermal sensors were used to assess crop phenology, condition, and stress by profiling spectral vegetation indices in crop fields. In this study, vegetation indices, viz., Atmospherically Resistant Vegetation Index (ARVI), Modified Chlorophyll Absorption Ratio Index (MCARI), Wide Dynamic Range Vegetation Index (WDRVI), Normalized Red–Green Difference Index (NGRDI), Excess Green Index (ExG), Red–Green Blue Vegetation Index (RGBVI), and Visible Atmospherically Resistant Index (VARI) were generated. Furthermore, Pearson correlation analysis showed a better correlation between WDRVI and VARI with LAI (R = 0.955 and R = 0.982) ground truth data. In contrast, a strong correlation (R = 0.931 and R = 0.844) was recorded with MCARI and NGRDI with SPAD chlorophyll ground truth data. Then, the best-performing indices, WDRVI and MCARI in cotton, and VARI and NGRDI in rice, were further used to generate the yield model. This study for determining LAI and chlorophyll shows that high spatial resolution drone imageries are accurate and fast. As a result, finding out the LAI and chlorophyll and how they affect crop yield at a regional scale is helpful. The widespread use of unmanned aerial vehicles (UAV) and yield prediction were technical components of large-scale precision agriculture