Park quality and features can contribute to more engaging places for play and recreation. However, assessing park characteristics remains a challenge. This study measured the reliability of GigaPan® as a method for assessing park characteristics as well as the validity of GigaPan® compared to Google Street View (GSV) and direct observation (DO). A total of 65 target areas (16 parks total) in Pittsburgh, PA were assessed using GigaPan®, GSV, and DO from July 2015-January 2016. For reliability and validity, 14 and 28 variables were examined, respectively. Cohen's kappa was used to assess inter-rater reliability. Sensitivity and specificity were used to measure validity. Of the 14 variables included in the inter-rater reliability analysis, five variables had almost perfect reliability (kappa > 0.80) and three variables had substantial reliability (kappa > 0.60). Of the 28 variables included in the validity analysis, GigaPan® was able to correctly classify 17 of the 28 variables and GSV was able to correctly classify 15 of the 28 variables with a sensitivity >80%. There were no significant differences between sensitivity and specificity between GSV and GigaPan®. GigaPan® performed similarly to GSV with DO being used as the gold standard. Further, GigaPan overall had high reliability among the features measured. A strength of GigaPan® is the ability to be implemented quickly in the field, making it a viable alternative to GSV particularly when temporality is an important factor.