Correction: Rembold, F.; Atzberger, C.; Savin, I.; Rojas, O. Using Low Resolution Satellite Imagery for Yield Prediction and Yield Anomaly Detection. RemoteSens 2013, 5, 1704-1733

Using Low Resolution Satellite Imagery for Yield Prediction and Yield Anomaly Detection

Low resolution satellite imagery has been extensively used for crop monitoring and yield forecasting for over 30 years and plays an important role in a growing number of operational systems. The combination of their high temporal frequency with their extended geographical coverage generally associated with low costs per area unit makes these images a convenient choice at both national and regio...

Assessing drought probability for agricultural areas in Africa with coarse resolution remote sensing imagery

Comparison of Satellite Imagery and Ground-Based Active Optical Sensors as Yield Predictors in Sugar Beet, Spring Wheat, Corn, and Sunflower

1 The original use of remote sensing using infrared photography for yield variation was conducted by Colwell (1956). Since the launch of the Landsat 1 imaging satellite in 1972 (Mulla, 2013), satellite imagery has been widely used in agriculture for yield prediction and most lately for site-specific N management. Bhatti et al. (1991) used Landsat imagery and auxiliary data to estimate wheat yie...

Correction: Atzberger, C. Advances in Remote Sensing of Agriculture: Context Description, Existing Operational Monitoring Systems and Major Information Needs. Remote Sens 2013, 5, 949-981

I would like to devote this review to my teachers and colleagues, Nadine Brisson and Gilbert Saint, who passed away too early. I am also grateful to a number of people who contributed directly and indirectly to this paper: Antonio Formaggio and Yosio Shimabokuro and their team from INPE (Sao Jose dos Campos) for shared drafting of a related research proposal for a Brazilian monitoring system; F...

Mid-Season High-Resolution Satellite Imagery for Forecasting Site-Specific Corn Yield

A timely and accurate crop yield forecast is crucial to make better decisions on crop management, marketing, and storage by assessing ahead and implementing based on expected crop performance. The objective of this study was to investigate the potential of high-resolution satellite imagery data collected at mid-growing season for identification of within-field variability and to forecast corn y...