The U.S. Department of Agriculture, Forest Service, Southcm Research Station, appointed a remote-sensing team to develop an image-processing methodology for mapping forest lands over large geographic areds. The team has presented a repeatable methodology, which is based on regression modeling of Advanced Very High Resolution Radiometer (AVHRR) and Landsat Thematic Mapper (TM) data. It is a methodology that Forest inventory and Analysis (FIA) survey personnel can implement in any region or area. The term repeatable implies objectivity. Studies in the conterminous United States, Central America and Mexico, and west Texas and Oklahoma have provided valuable insights that address the subjective nature of some of the steps taken in mapping large forest areas. The team has identified seven such steps. They have reduced or eliminated subjectivity in four of the steps and identified two steps in which objectivity can be enhanced.

Carbon neutrality refers to net-zero carbon emissions. It can be achieved by reducing carbon emissions or increasing carbon adsorption. The popularity of social media including Twitter, YouTube, and LinkedIn provides good channels for sharing relevant information and promoting sustainable carbon-neutral living styles. For example, a motor company has launched social media challenges with Korean pop stars to raise awareness of carbon neutrality. Social media provides real-time information. In Jakarta, flood-related tweet intensity during a flood peaked at about 900 tweets a minute during the floods of 2015. The tweets created real-time maps that people sent a minute before. Regarding government policies, identification of problem areas is needed to help policymakers to resolve problems. Machine learning can monitor these events by studying past records to know how countries and governments performed in a high-risk event or environmental crisis and this data can be used to provide future recommendations to governments for policy making. Additionally, AI can analyze online unstructured data, and predict various scenarios of carbon emissions and adsorptions using structured data. The world of social media is a huge data source still yet to be fully optimized in science.