Forward Byline Resolution with airSlate SignNow

Forward byline resolution

hey everybody in this video we're going to look at some trade-offs between spatial spectral and temporal resolution in satellite imagery so there's four types of resolution we might think about in remote sensing radiometric resolution is essentially the range of energy or radiance that is recorded by any given digital number or that's mapped into any given digital number and this really amounts to what levels of brightness can i resolve right if if a large range of brightness has been mapped into a single digital number you can never resolve anything below that increment of brightness then we have spatial resolution essentially the pixel size of the image really amounts to what is the smallest object i can resolve in my image right smaller pixels are going to let us resolve smaller things and spectral resolution this is the width of each spectral band measured usually in nanometers in other words this is the range of wavelengths within which uh a given band was collected right so for you know red the red band it might be you know 600 to 700 nanometers or something like that and obviously if you have smaller bandwidths a more narrow range of nanometers you can more easily discern materials that have similar spectral signatures and then finally we have temporal resolution how long does it take to collect repeat images of the same location on earth how often does the satellite pass overhead and this essentially boils down to how frequently can i monitor some process for example for agricultural crop health you might need every two weeks for wildfires you might need every two hours for weather you might need continuous temporal updates so those are the four types of resolution and let's start by digging into spatial resolution so i'm going to show you three examples of the exact same image here's landsat band 6 it's a 60 meter pixel size so each of these square cells is 60 meters in width if we step up to band 3 which is a 30 meter pixel size notice how much detail we can start to resolve we can resolve some linear things probably roads this curvy black thing here what could that be well if we go to 15 meter pixel size suddenly it's clear that that actually is a river that's otter creek so the advantage of spatial resolution is quite clear it really lets us pick out a lot more detail in the images so what determines spatial resolution to to talk about this and to use this as a launch point towards understanding trade-offs i want us to start by considering a simple camera geometry this is called a framing geometry a framing camera so essentially the way this works is you have some detector chip back here actually let's start on the ground you have some ground element called the instantaneous field of view that might be square but it doesn't have to be light reflecting...