Predicting maize yield in Zimbabwe using dry dekads derived from remotely sensed Vegetation Condition Index

Monitoring Meteorological Drought in Iran Using Remote Sensing and Drought Indices

Drought is a major environmental disaster in many parts of the world. Knowledge about the timing, severity and extentof drought can aid planning and decision-making. Drought indices derived from in-situ meteorological data have coarsespatial and temporal resolutions, thus, obtaining a real-time drought condition over a large area is difficult. This studyused advanced very high resolution radiom...

Testing the Contribution of Stress Factors to Improve Wheat and Maize Yield Estimations Derived from Remotely-Sensed Dry Matter Productivity

According to Monteith’s theory, crop biomass is linearly correlated with the amount of absorbed photosynthetically active radiation (APAR) and a constant radiation use efficiency (RUE) down-regulated by stress factors such as CO2 fertilisation, temperature and water stress. The objective was to investigate the relative importance of these stress factors in relation to regional biomass productio...

Remotely Sensed Rice Yield Prediction Using Multi-Temporal NDVI Data Derived from NOAA's-AVHRR

Grain-yield prediction using remotely sensed data have been intensively studied in wheat and maize, but such information is limited in rice, barley, oats and soybeans. The present study proposes a new framework for rice-yield prediction, which eliminates the influence of the technology development, fertilizer application, and management improvement and can be used for the development and implem...

Assimilation of remotely sensed soil moisture and vegetation with a crop simulation model for maize yield prediction

Predicting Spatial Distribution of Key Honeybee Pests in Kenya Using Remotely Sensed and Bioclimatic Variables: Key Honeybee Pests Distribution Models

Bee keeping is indispensable to global food production. It is an alternate income source, especially in rural underdeveloped African settlements, and an important forest conservation incentive. However, dwindling honeybee colonies around the world are attributed to pests and diseases whose spatial distribution and influences are not well established. In this study, we used remotely sensed data ...