Applications of Ground-Based Remote Sensing for Precision Agriculture in Korea

摘要

Leaf color and plant vigor are key indicators of crop health. These visual plant attributes are frequently used by greenhouse managers, producers, and consultants to make water, nutrient, and disease management decisions. Remote sensing techniques can quickly quantify soil and plant attributes, but it requires humans to translate such data into meaningful information. Over time, scientists have used reflectance data from individual wavebands to develop a series of indices that attempt to quantify things like soil organic matter content, leaf chlorophyll concentration, leaf area index, vegetative cover, amount of living biomass, and grain yield. The recent introduction of active sensors that function independent of natural light has greatly expanded the capabilities of scientists and managers to obtain useful information. Characteristics and limitations of active sensors need to be understood to optimize their use for making improved management decisions. Pot experiments involving sand culture were conducted in 2003 and 2004 in a green house to evaluate corn. Another pot experiments using sand culture were conducted in 2004 and 2005 to estimate the recommendation model for top dressing rate of N fertilizer on red pepper using ground-based remote sensing under greenhouse conditions. Also field experiments were conducted for ten fields of red pepper in 2005 and 2006, respectively to estimate the N fertilizer efficiency on red pepper treated with the top dressing rate recommended by remote sensing test developed in former pot experiment. And field experiments were conducted in 2006 to evaluate nitrogen status and yield of rice as well as application rate of N fertilizer. The rNDVI, gNDVI and aNDVI by ground-based remote sensors were used for evaluation of corn, red pepper, and rice biomass. The result obtained from the case study was shown that ground remote sensing as a non-destructive real-time assessment of plant nitrogen status was thought to be a useful tool for in season crop nitrogen management providing both spatial and temporal information.