Ezigrade 4.2.177

We have added in an "Adaptive Grid" data thinning. Very useful for Lidar and other big data sets. Adaptive grid thinning reduces the number of points in a surface by first overlaying a regular grid across the dataset and selecting a small number of representative points within each grid cell, typically the highest, lowest, and optionally the point nearest the cell centre. Boundary and protected points are always retained. A new triangulated surface is then constructed from this reduced point set and compared with the original surface. Where the vertical difference between the two surfaces exceeds a specified tolerance, additional original points are inserted to improve the local surface representation. This process is repeated in several passes until the surface meets the required accuracy or a maximum number of iterations is reached, resulting in a significantly smaller dataset that preserves the essential geometry of the original terrain.