PS 86-118: Electronic data collection methods for tree and seedling census data in forest dynamics plots
Kehauwealani K. Nelson-Kaula1, Faith Inman-Narahari1, Rebecca Ostertag1, Christian Giardina2, Susan Cordell2, and Lawren Sack3. (1) University of Hawaii, (2) USDA Forest Service, (3) UCLA
Field electronic data collection has increased in use due to its ease and time savings in data entry. The ability to map and collect measurement data in one operation in situ is particularly useful for collecting spatially explicit data. In addition, the ability to pre-set default field values, required fields, automated in-field data checking, and drop-down menus built into customized forms (e.g., species lists) have the potential to reduce error in the field during data collection. In two Center for Tropical Forest Science (CTFS) plots in Hawaii, we have developed easy to use electronic data collection tools using ESRI products including ArcMap and ArcPad to collect data on Juniper Systems field computers. Our data is stored within geodatabases and can be easily transferred to and from field computers. The seamless integration of mapping and tree demography data collection removes the need for data entry and digitizing maps from paper copies. Instead, data collected on field computers can be automatically integrated into the main database from the field copies. Lists of errors, such as suspect and missing values, can be quickly generated along with maps for locating trees to be checked. Field crews typically find field computers easy to use and simpler than multiple paper data sheets. Most field computers are ruggedized and waterproof and can be less problematic than paper data sheets in inclement weather.
Based on published estimates of time needed for data entry, in person months per hectare, we estimate that we save 0.3 mo/ha of time in data entry, 0.16 mo/ha in digitizing maps, and 0.14 mo/ha in other miscellaneous data tasks, saving an average of 2.4 mo for each of our 4-ha plots. Electronic data collection is a cost-effective and efficient method of data collection that may be valuable for other research projects.