Dados do Empregador:
Referência da Vaga: IN-2018-0802-KU
País: India
Empresa / Universidade: Karunya Institute of Technology and Sciences
Serviços / Produtos: Institute
No de Empregados: 600+
Local de Trabalho: Coimbatore
Horas Trabalhadas por Semana: 45.0
Horas Trabalhadas por Dia: 8.0
Aeroporto Internac. Mais Próximo: Coimbatore International Airport
Transporte Público Mais Próximo: Bus/Taxi
Perfil do Estudante:
Faculdade: Civil Engineering
Faculdade 2:
Faculdade 3:
Faculdade 4:
Outra faculdade:
Especialização:
Nível de Estudo: Metade do Curso
Study Level: End - (7 and more semesters), Middle - (4-6 Semesters)
Sexo Permitido:
Experiência anterior requerida:
Outros Requisitos: Knowledge of the following softwares : ArcGIS10.1 , ERDAS Imagine,ENVI softwares, Remote sensing and GIS concepts
Idioma 1: English
Nível de Idiomas: Avançado
ou: Não
Idioma 2:
Nível de Idiomas:
ou: Não
Idioma 3:
Nível de Idiomas:
Descritivo da Vaga:
Tipo de Atividade: An Investigation on irrigation performance and drought assessment of Noyyal river basin using remote sensing and GIS to be carried out. Multi temporal remote sensing (RS) data-based crop inventory and Normalized Difference Vegetation Index (NDVI), which is very sensitive to the presence of the green vegetation and is a ratio of near infrared radiation minus red radiation and near infrared ratio plus red radiation have to be generated. The NDVI will be generated from Landsat 8 and Landsat 5 imageries corresponding to 2014 and 2015. In this study, remote sensing based indicators ie., irrigation intensity( target value of 100%), water utilization index (WUI), depth of water applied, overall consumption rate (ep), relative water supply (RWS), output per unit cropped area, output per unit cultivable command and water productivity (wp) will be estimated for the command area. The command area details for verification can be collected from the department of statistics. To quantify drought, the precipitation-based Standardized Precipitation Index (SPI), the soil moisture-based Crop Moisture Index (CMI), as well as the Normalized Difference Vegetation Index (NDVI) will be used. Correlation analysis will be conducted to examine the relationships between the drought indices during the growing season and final yield, according to data collection from 2000 to 2015. This study will demonstrate how remote sensing based estimates ofcrop area and production combined with water release data from project and climatic data can provide better estimates of irrigation performance and drought assessment. This approach will allow identification of areas where agricultural performance is less than potential and thereby providing insights into how irrigation systems can be managed to improve overall performance and increase water productivity in a sustainable manner in the basin.
Semanas oferecidas (mín.): 12
Semanas oferecidas (máx.): 12
Período de: 01/08/2018
até: 01/12/2018
Categoria: Pesquisa e Desenvolvimento
Moeda: INR - Rupia indiana
Bolsa Auxílio: 8000 per month
Pago:
Refeitório na empresa ou vale refeição: Sim
Deduções Esperadas: 0%
Comentário:
Acomodação:
Será Providenciada Por: IAESTE LC KARUNYA
Custo Estimado de Acomodação: 5000 per month
Por:
Custo Estimado de Vida Incluindo Acomodação: 8000 per month
Por: