Remote sensing is the process of examining and collecting data from the Earth’s surface using sensors from a distance. In this process, information is obtained from the Earth’s surface using electromagnetic radiation (e.g., visible light, infrared, microwave). Resolution refers to the level of detail in remote sensing data.
There are four different resolutions in remote sensing: spectral, radiometric, spatial, and temporal resolution. Especially when working with satellite imagery, one must be familiar with all resolutions and know which satellite has which resolution information when obtaining images from uydushop.com.tr, so that we can acquire the most suitable image for our project. In this article, we will answer the question “What is Spatial Resolution?”
Spatial resolution defines the size of an image resolution cell in the target area or the size of pixels in the focal plane. It is typically expressed in terms of ground sampling distance (GSD), footprint, pixel size, or instantaneous field of view (IFOV).
Geometric accuracy refers to an image obtained from a satellite/aircraft/UAV with a 1-meter accuracy, where each pixel corresponds to a 1×1 meter area on the ground and represents a single color tone for that pixel. These pixels come together to form the image file. The differentiation of map objects on the image is directly proportional to the spatial and radiometric resolution of the image.
High spatial resolution images do not always mean high accuracy in producing a map or orthophoto. Improvements or errors made during the processing and digitization of these images affect the accuracy of the map or orthophoto.
Deciding on which resolution to use:
Analyze the details you want to see or interpret on the image carefully. Look at the examples below to understand what can be seen at each resolution. Determine the importance of the details you want to see. Analyze the importance of seeing the details in relation to the project cost and image cost. Continuously monitor the area of interest (AOI) at a lower resolution. When a change is detected in the AOI, you can obtain more details with higher resolution images.
Consider the size of the object you want to monitor. For example, for tracking vehicles:
An average car is ~2m x 4.5m.
At a high resolution of 0.5m: the car will cover 4 x 9 pixels, which is sufficient to detect its color and general shape.
At very high resolution of 0.3m: the car covers 7 x 15 pixels, allowing you to see shapes and details like windows more clearly.
To sum up, geometric resolution satellite refers to its ability to distinguish between objects in an image captured from space. It is a crucial parameter in remote sensing, determining the level of detail visible in satellite imagery. Satellite GSD, or Ground Sampling Distance, quantifies this resolution by measuring the distance on the ground represented by each pixel in the image. The smaller the GSD, the higher the geometric resolution and the finer the details captured in the image. This plays a significant role in various applications such as urban planning, agriculture, environmental monitoring, and disaster management. As technology advances, satellites with increasingly higher geometric resolutions are being deployed, enabling more precise analysis and decision-making processes on a global scale.
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