What does resampling mean in GIS?

What does resampling mean in GIS?

Resampling is the process of interpolating the pixel values while transforming your raster dataset. This is used when the input and output do not line up exactly, when the pixel size changes, when the data is shifted, or a combination of these.

When projecting elevation data What is the appropriate choice for the resampling technique?

Elevation is also a phenomenon that is a continuous variable, i.e. 10.432467533 m is perfectly legitimate as an elevation (darn those integer valued DEMs!). Therefore, you should be using bilinear (BL) or cubic convolution (CC) resampling methods when dealing with these data.

When to use resampling instead of reprojection?

Suppose that instead of resampling during reprojection, your goal is to aggregate pixels to larger pixels in a different projection. This is useful when comparing image datasets at different scales, for example 30-meter pixels from a Landsat-based product to coarse pixels (higher scale) from a MODIS-based product.

How are Datacube and raster data reprojected?

We pass raster.geobox to the function to request that the data gets reprojected to match the spatial grid of our low resolution raster. To control how the data is reprojected, we can specify a custom resampling method that will control how our high resolution pixels will be transformed into lower resolution pixels.

How does resampling work in Google Earth Engine?

Specifically, when one of these methods is applied to an input image, any required reprojection of the input will be done using the indicated resampling or aggregation method. resample () causes the indicated resampling method ( ‘bilinear’ or ‘bicubic’) to be used at the next reprojection.

When to use resampling to reduce image resolution?

Reduce Resolution Suppose that instead of resampling during reprojection, your goal is to aggregate pixels to larger pixels in a different projection. This is useful when comparing image datasets at different scales, for example 30-meter pixels from a Landsat-based product to coarse pixels (higher scale) from a MODIS-based product.