Remote sensing technologies are frequently used as an effective tool in precision agriculture.  However, this research currently under study has not yet extended to California tree crops. The aim of this project is to help fill that knowledge gap by determining the technological feasibility of using remote sensing techniques to monitor peach tree fields for the management of orchard pests, in particular web-spinning spider mites (genus Tetranychus), before they reach economically damaging levels. To understand how mite damage affects stone fruit trees, spectral data was collected during the 2006 growing season.  Simultaneously, multispectral aerial images were collected to observe how mite damage is translated at the larger orchard scale.  Through the analysis of leaf and canopy level spectrometry data, it was determined that there are five major regions within the spectral curve that are the most sensitive to mite damage (400-500nm, 550-600nm, 650-710nm, 1400-1500nm, and 1900-2000nm).  These ranges, in the visible and shortwave infrared wavelengths, appear to be affected by the changes in leaf pigments and water holding capacity of the leaves as a result of mite damage.  An analysis of the multispectral images through the application of vegetation indices and supervised classification methods reveled that the Structure Intensive Pigment Index shows the greatest promise at accurately detecting mite infestations at low levels.  If these techniques are deemed to be effective by growers, there is the possibility for real-world application through inexpensive and accurate mapping of pest hotspots that can be used by farm managers to adopt variable rate technology, which enables selectively spraying of target areas, reducing the need to blanket-spray entire fields.  Key words: remote sensing, stone fruit, pest management