نتایج جستجو برای: agrometeorological indices

تعداد نتایج: 83123  

2007
Paul C. Doraiswamy Paul W. Cook

A potential application of the normalized difference vegetation index (NDVI) is to monitor crop yields over large areas. The study concentrated on the spring Mheat areas of North Dakota and South Dakota for several years (1989-1992). The NOAA AVHRR data was carefully analyzed to minimize processing and sampling errors. Sums of biweekly NDVI county averages over an eight week period from heading...

2015
Nikolaos Malamos Ioannis L. Tsirogiannis Antonis Christofides Stavros Anastasiadis Silvia Vanino

Agriculture plays a key role in the management of water use. Especially in Greece, irrigation is an essential element of agricultural production and agricultural water use has a substantial share in total water use. The presented study illustrates the key features of the IRMA_SYSTEM, a regional, user-friendly computer/mobile-based, open and free modular software for estimating site specific cro...

Journal: :Revista Brasileira de Ciências Agrárias - Brazilian Journal of Agricultural Sciences 2019

Journal: :International Journal of Enviornment and Climate Change 2023

A study was conducted in April 2020 to assess the impact and usefulness of agrometeorological Advisory Services increasing production wheat crops under DAMU KVK, Kushinagar. The two villages were selected for this study, groups farmers selected, namely, a group adopting Advisories (50 farmers), regularly their operations (AAS Farmers), another not aware (Non AAS Farmers) during rabi season. dat...

Journal: :Korean Journal of Agricultural and Forest Meteorology 2013

Journal: :Remote Sensing 2021

Timely and reliable estimations of crop yield are essential for management successful food trade. In previous studies, remote sensing data or climate often used alone in statistical estimation models. this study, we synthetically agrometeorological indicators vegetation parameters to estimate maize Jilin Liaoning Provinces China. We applied two methods select input variables, the random forest ...

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