关于空间分析JTS的总结——筛点
筛点:往往库里返回的数据的点非常密集,筛点后会甩掉大量的较小偏移的临近点,并根据点与点之前距离的设定(例如:距离50米以内的点甩掉)和最大甩点数(例如:最多甩到10000个点就不甩了),减小精度来增加空间运算速度。
实例代码:
distanceToleranceMeter:50 --最小甩点距离
maxCoordinateCount:10000 --最大甩点数
@Override public <T> List<Coordinate> simplify(List<T> lngLatList, Function<T, Coordinate> transformer) { // 地图匹配最小距离 100m double distanceTolerance = GeometryUtil.getEarthArcDistance(distanceToleranceMeter); List<Coordinate> coordinates = Lists.newArrayList(); Coordinate lastCoordinate = null; for (T lonLat : lngLatList) { // Longitude;Latitude;z, Coordinate coordinate = transformer.apply(lonLat); if (coordinate == null) { continue; } if (lastCoordinate == null || !coordinate.equals2D(lastCoordinate, 0.000001)) { coordinates.add(coordinate); lastCoordinate = coordinate; } } if (coordinates.isEmpty()) { return coordinates; } Coordinate[] pts = coordinates.toArray(new Coordinate[coordinates.size()]); coordinates.clear(); double currentDistanceTolerance = distanceTolerance; do { // 精简点算法在参数【distanceTolerance】定值情况下,点不会再减少,故增加距离,避免死循环 pts = DouglasPeuckerLineSimplifier.simplify(pts, currentDistanceTolerance); currentDistanceTolerance += GeometryUtil.getEarthArcDistance(10D); } while (pts.length > maxCoordinateCount); return Lists.newArrayList(pts); }
@Override public List<Coordinate> buildCoordinates(List<String> lngLatList, boolean inverseGeo) { List<Coordinate> coordinates = simplify(lngLatList, new Function<String, Coordinate>() { public Coordinate apply(String coord) { try { String[] arr = StringUtils.split(coord,";"); String longitude = arr[0]; String latitude = arr[1]; if (longitude != null && latitude != null) { return new Coordinate(Double.parseDouble(longitude), Double.parseDouble(latitude)); } } catch (NumberFormatException e) { logger.error(e.getMessage(), e); } return null; } }); if(inverseGeo){//是否批量转偏移 List<String[]> stringList = coordinates.stream().map(t -> new String[]{t.getX() + "", t.getY() + ""}).collect(Collectors.toList()); List<String> result = mapService.inverseGeoConvert(stringList); coordinates = result.stream().map(t -> new Coordinate(Double.parseDouble(t.split(",")[0]), Double.parseDouble(t.split(",")[1]))).collect(Collectors.toList()); } return coordinates; }