With the rapid development of the Internet, crowdsourced photos generated by mobile terminal devices can be used in many critical application scenarios, such as post earthquake recovery and emergency management. However, such applications often have resource constraints such as bandwidth, terminal device storage and processing capability, which limit the number of crowdsourced photos. Thus, it is a big challenge to use the limited resources to best reproduce the target from crowdsourced photos. In this paper, we collect and process various geographical and geometrical data of the photos to form a metaarray of photos, and propose an optimal utility selection algorithm of crowdsourced photos to achieve the best reproduction of the target under the condition of limited resources. The input of the algorithm is metadata rather than pixels, so it can efficiently analyze crowdsourcing in resourceconstrained applications. The utility of photos is used to measure the coverage degree of the target area, and an effective photo utility calculation method is proposed. Finally, we design a simulation experiment, and the results prove the effectiveness and superiority of the algorithm.