Rice Crop Monitoring with Unmanned Helicopter Remote Sensing Images

Agricultural crop, one of the biological entities, is sensitive to its environmental condition including various soil and crop inputs. Alteration in environmental condition causes reduction in crop productivity (such as crop yield and total biomass etc.). Ultra-modern technology such as, precision agriculture (PA) is capable to prevent crop damage and maintain crop productivity. PA is the technology of applying correct amount of crop input at the exact place and time of requirement. Application of PA technology has become increasingly prevalent among the farmers from developed countries as well as developing countries due to its capability for optimizing crop yield by facilitating sound crop status monitoring (Zhang and Taylor, 2001). Mostly, satellite images have been used as the primary source of information for analyzing crop status in precision agriculture. However, obtaining up-to-date aerial photography is very expensive, the quality is variable, and data processing is also intensive and complicated. Innovative new technologies to acquire timely and accurate crop information are required for the success of PA technology. Assessment of leaf radiation has the potential to detect nitrogen (N) deficiency and is a promising tool for N management and monitoring. Moreover, over-fertilization may result in surface runoff and pollute subsurface water (Wood et al., 1993; Auernhammer et al., 1999; Daughtry et al., 2000; Zaman et al., 2006). Chlorophyll is an indirect indicator of nitrogen status and is used in optical reflectance-based variable-rate nitrogen application technology (Lee and Searcy, 2000; Jones et al., 2004; Alchanatis et al., 2005; Kim and Reid, 2006; Min et al., 2008). Biermacher et al. (2006) used sensor-based systems to determine crop nitrogen requirements and estimated that the variable-rate system had the potential to achieve a net profit of about $22 to $31 per ha. The ability to accurately estimate plant chlorophyll concentration can provide growers with valuable information to estimate crop yield potential and to make decisions regarding N management (Kahabka et al., 2004; Reyniers and Vrindts, 2006; Zaman and Schumann, 2006). Spectroradiometry has been useful in the research environment for determining principal wavebands and spectral patterns that relate to nutrient stress (Noh et al., 2004; Tumbo et al. 2001). High spectral resolution and the ability to account for temporal changes are distinct