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Yield mapping techniques are beginning to cross over into orchard crop production. Perennial orchard/tree crops are high dollar commodities that can greatly benefit from precision agriculture applications. Tree crops introduce new challenges with creating yield maps as well as any management map because accurate positional data cannot be obtained by the use of Global Positioning Systems (GPS) when a clear view of the sky does not exist under the tree canopy. External to the canopy a GPS can yield accurate positional data whereas underneath the canopy it cannot. This research focuses on the development of a system that can effectively detect every tree inside a given field/orchard inspired by the interpoint method used in forestry. An encoder based system and a DGPS based system collected data concurrently in an open canopy orchard and a dense canopy orchard. The accuracy of each system was analyzed using a stress value. The encoder based system had an average stress value of 2.3 in the open canopy and 0.9 in the dense canopy orchards. The DGPS based system had an average stress value of 138.3 in the open canopy and 128.8 in the dense canopy orchards. The encoder based system in association with the snap method successfully detected all trees in both orchard configurations whereas the DGPS system did not.