Detecting and identifying marine mammals and other protected marine species (such as seabirds, sharks, and sea turtles) and collecting biological information is a singular concern for the scientific community, as well as the oil& gas, renewable energy, and fishing industries, including aquaculture. Specifically, these different sectors need information on the number, location, type of marine species, and distance to activity, vessel, or observation platform to either cease activity, collect additional data, or continue ongoing operations to satisfy monitoring requirements. Similarly, from a permitting perspective and to comply with statutory obligations, these different groups need abundance and density estimates to determine immediate and long-term impacts on marine mammals or other marine species that may be susceptible to population-level impacts in the area of operations. Understanding the abundance, distribution, and density of animals is critical for industry to evaluate where to position their activity in the short- and long-term. Traditional methods for estimating abundance, density, and distribution for multiple cetacean species rely almost exclusively on visual surveys conducted onboard ships, rigid ocean platforms, or from shore. Such surveys involve the use of “Big-Eye” 25 x 150 binoculars to manually scan for different marine species, especially marine mammals to a maximum distance of about 11-13 km from the ship. Scanning is done by trained observers who locate and identify species and estimate group sizes, which are ultimately used to estimate population abundance and in the development of habitat models. Two key measures are obtained using the binoculars, which include bearing and reticle distance to the sighted animal. While the bearing measurement is easy to obtain with accuracy, the reticle distance, however, is at best an estimate due to the motion of the vessel and sea state. In addition, reticle distance measurement errors can be compounded at distance and when the target animal is being tracked. Like theodolite readings obtained on land, automated reading of bearing and reticle distance measurements would reduce or eliminate uncertainty while recording animal sightings. Further, a second issue is the lack of any photographic or video evidence of what the observer sees through the binocular. The availability of an image or video would help to verify species identification in situations where the animal is too far to identify or close-in approaches to verify species identification is not possible. The automation of the readings from the long-range binoculars has enormous benefits for monitoring and mitigation for both the research and commercial industry. Fisheries, oil& gas, renewable energy, defense, aquaculture sectors, and scientific research groups rely on human observer data to input into mathematical and statistical models to obtain reliable abundance and density estimate for various protected marine species. By improving the ease of data collection and accuracy of readings, these different sectors can improve the quality of data collected and require fewer trained observers in the long-term, thereby reducing costs. There is a need to design, test, and make commercially available Big-Eye binoculars that can digitally show reticle measurements and bearings as the binocular is swiveled by the observer and simultaneously be recorded in a computer database. A secondary goal is the ability to obtain images or video of the observer visual field during a sighting or tracking of the animal.