The correct answer is option 'A', which includes techniques such as remote sensing, GIS, and GPS.

Remote sensing is the process of acquiring information about the Earth's surface without physically being in contact with it. It involves the use of various sensors, such as satellites or aircraft, to collect data about the Earth's surface and atmosphere. Remote sensing data can be in the form of images or other measurements, and it provides valuable information for a wide range of applications, including land cover mapping, environmental monitoring, and disaster management.

GIS (Geographic Information System) is a system designed to capture, store, manipulate, analyze, manage, and present spatial or geographic data. It combines both the data and the software tools required to work with that data, allowing users to visualize, analyze, and interpret geospatial information. GIS enables the integration and analysis of different types of data, including remote sensing data, GPS data, and other sources, to support decision-making processes in various fields, such as urban planning, natural resource management, and transportation.

GPS (Global Positioning System) is a satellite-based navigation system that allows users to determine their precise location on the Earth's surface. It relies on a network of satellites that continuously transmit signals to GPS receivers on the ground. By calculating the time it takes for the signals to reach the receiver, the GPS receiver can determine the distance to each satellite and use the information to triangulate the user's position. GPS has become an essential tool in various applications, including navigation, surveying, and mapping.

These techniques (remote sensing, GIS, GPS) are closely interconnected and often used together in geoinformatics. Remote sensing provides the data source, GIS is used for data integration, analysis, and visualization, and GPS provides accurate location information. Together, they enable the collection, processing, and analysis of geospatial data for a wide range of applications, such as land use planning, environmental monitoring, disaster management, and natural resource management. These techniques have revolutionized the way geographers and other professionals work with spatial data, making it easier and more efficient to analyze and understand complex geospatial phenomena.

Answer is a here