Remote sensing is the small- or large-scaleacquisition of information of an object or phenomenon, by the use of either recording or real-time sensing device(s) to collect data in inaccessible areas etc.
data dictionary
A validation error occurs when a model's predictions on a validation dataset significantly differ from the actual outcomes, indicating that the model may not generalize well to unseen data. This type of error can arise from overfitting, where the model learns the training data too closely, or from underfitting, where the model fails to capture the underlying patterns. In essence, validation errors highlight the model's limitations in accurately predicting future data.
A boolean is not a validation rule itself; rather, it is a data type that can hold one of two values: true or false. In the context of validation rules, boolean values can be used to determine whether certain conditions are met, thereby validating input or data. For example, a validation rule might check if a field is required (true) or optional (false).
Data validation is a process that ensures the accuracy and quality of data by checking it against predefined rules or criteria before it is processed or stored. By implementing validation checks—such as format, range, and consistency—errors can be identified and corrected at the point of entry, thereby preventing incorrect or incomplete data from being used. This proactive approach minimizes the risk of mistakes, enhances data integrity, and improves overall decision-making. Ultimately, it helps maintain reliability and trust in data-driven processes.
The opposite of remote sensing is close-up sensing, where data is collected from objects or phenomena in close proximity to the sensor or observer. This type of sensing involves direct contact or nearness to the subject being observed, as opposed to remote sensing which involves collecting data from a distance.
Hakil Kim has written: 'A method of classification for multisource data in remote sensing based on interval-valued probabilities' -- subject(s): Interval analysis (Mathematics), Remote sensing 'A method of classification for multisource data in remote sensing based on interval-valued probabilties' -- subject(s): Remote sensing
gps
A mapmaker might use active remote sensing over passive remote sensing because active remote sensing provides its own source of energy to illuminate the target, allowing for more control over the data collected. This can result in better resolution and accuracy in mapping features of interest.
by ground truthing
remote sensing
The National Remote Sensing Agency (NRSA) is located in Hyderabad, India. It is an autonomous organization under the Department of Space, Government of India, and is responsible for remote sensing satellite data acquisition and processing.
Remote sensing.
remote sensing
In addition to remote sensing data, cartographers also use ground surveys, GPS technology, aerial photography, and geographic information systems (GIS) to collect data for making maps. These methods help ensure accuracy and provide additional layers of information that can be used for mapping purposes.
Remote sensing provides valuable data for GIS by allowing for the collection of information from a distance using sensors on satellites or aircraft. This data can be used to create detailed maps, monitor changes in the environment, assess land cover and land use, and analyze spatial patterns. Remote sensing helps to enhance the accuracy, efficiency, and scope of GIS applications.
In remote sensing, a platform refers to the vehicle or instrument used to collect data from above the Earth's surface. This can include satellites, aircraft, drones, or ground-based sensors. The choice of platform depends on the specific needs of the remote sensing application and the type of data being collected.