Using Satellite and Field Data with Crop Growth Modeling to Monitor and Estimate Corn Yield in Mexico

By A. D. Báez-González, Pei-yu Chen, M. Tiscareño-López, Raghavan Srinivasan. 2002

121 citations recorded by the source corpus.

Subfields: Ecology, Environmental Engineering, Plant Science

View Paper: https://www.semanticscholar.org/paper/744cef615529044e7c60660a8f55b071b01b383c

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

In Ecology

1. Daniel P. Ames
2. Sudhanshu Sekhar Panda
3. Suranjan Panigrahi

In Plant Science

1. Daniel P. Ames
2. Sudhanshu Sekhar Panda
3. Suranjan Panigrahi

Citations in the corpus

• Application of Vegetation Indices for Agricultural Crop Yield Prediction Using Neural Network Techniques (2010, methodology): “, NDVI) are widely used in crop yield estimation [1,3,8,12,13,15,16].”
• The early explanatory power of NDVI in crop yield modelling (2008, background): “In Mexico, Báez-González et al. (2002) assessed corn yield with the NDVI.”