fn classify_points(points: &mut Vec<Point>, starting_point: [f64; 3]) {
    // Create a 3D KdTree
    let dimensions = 3;
    let mut kdtree: KdTree<TreePoint, _> = KdTree::new(dimensions);

    // add all the points to the tree
    for point in points.iter() {
        // TODO: find top_left most point
        if point.x == 438000.12 && point.y == 4462999.95 {
            kdtree.add([point.x, point.y, point.z], TreePoint(point, true)).unwrap();
        }
        kdtree.add([point.x, point.y, point.z], TreePoint(point, false)).unwrap();
    }

    // study from one point to the next, classifying what we can as we go
    classify_ground(kdtree, starting_point);
}

fn classify_ground<T, U>(kdtree: KdTree<U,U>, starting_point: [f64; 3]) where U: std::convert::AsRef<[f64]> {
    // find all points within proper slope to be considered "ground"
    let nearest = kdtree.nearest(&starting_point, 15, &squared_euclidean).unwrap();
    // only take interest in the points that are within 1.5m and have yet to be classified
    for n in &nearest {
        if n.0 <= 1.5 && (n.1).1 {
            // check point slope from "starting_point", if under a value, it is a new ground;
            // add it to the list of "recursive calls to make"
        }
    }
    // store those point values
    unsafe {
        GROUND_CLASSIFIED_COUNT += 1;
    }
}