Details

Autor(en) / Beteiligte

• Sassenrath, Gretchen F
• Alarcon Calderon, Vladimir J
• Lyle Pringle, H. C
• McDonald, Miller
• Major, David
• Schepers, James
• Tarpley, Lee
• VanToai, Tara

Titel

Synthetic Imagery of Cotton Crops: Scaling from Leaf to Full Canopy

Ist Teil von

• Digital Imaging and Spectral Techniques: Applications to Precision Agriculture and Crop Physiology, 2004, p.111-133

Ort / Verlag

Madison, WI, USA: American Society of Agronomy, Crop Science Society of America, and Soil Science Society of America

Erscheinungsjahr

2004

Link zum Volltext

Quelle

Wiley Online Library All Obooks

Beschreibungen/Notizen

• Advances in sensing technology are creating the rapid development of remote imaging systems for crop monitoring. Data collected from sensors can be used to distinguish crop stress, such as that associated with low nutrient status, herbicide‐induced stress, insect pressure and poor stand establishment. Most of these systems rely on the reflectance properties of natural pigments present in leaf tissue (carotenoids and chlorophylls), and detect the production of alternate compounds under stress conditions (e.g., xanthophylls) to indicate plant stress in the visible and near‐infrared regions. While substantial progress has been made in developing spectral libraries for specific plant physiological properties at the leaf and whole plant level, limitations in the application of remote imagery to production settings arise through the need for adequate ground‐truthing of imagery to field conditions in the absence of atmospheric distortion. Field spectroradiometric measurements of individual cotton (Gossypium hirsutum L.) leaves, dry soil and wet soil were used to create hyperspectral images with known radiometric, geometric and spatial properties. Fourier series were used to interpolate the spectrum of individual leaves and soil for subsequent generation of syntheticmixed spectra. The mixtures of hyperspectral profiles were built from the randomized linear summation of soil and vegetation spectra. The resulting spectra were assigned to pixelsthat simulate a resolution of 1 m × 1 m size. The dimensions of the generated plots were 18 m × 20 m, similar to the size of the field plots from which the spectral measurements were taken. From these synthetic images, future research efforts will explore the impact of leaf angle, soil reflectance, and atmospheric distortion on canopy reflectance from aerial imagery.