예제 #1
0
파일: load.py 프로젝트: mci/mpatlas
def wdpapoly2mpa():
    wpolys = WdpaPolygon.objects.all().defer(*WdpaPolygon.get_geom_fields()).order_by("wdpaid")
    count = 0
    for wpoly in wpolys:
        mpa, created = Mpa.objects.get_or_create(wdpa_id=wpoly.wdpaid)
        count += 1
        print count
        mpa.name = wpoly.name
        mpa.wdpa_id = wpoly.wdpaid
        mpa.country = wpoly.country
        mpa.sub_location = wpoly.sub_loc
        mpa.designation = wpoly.desig
        mpa.designation_eng = wpoly.desig_eng
        mpa.designation_type = wpoly.desig_type
        mpa.iucn_category = wpoly.iucn_cat
        mpa.int_criteria = wpoly.int_crit
        mpa.marine = wpoly.marine
        mpa.status = wpoly.status
        mpa.status_year = wpoly.status_yr
        mpa.area_notes = wpoly.area_notes
        mpa.rep_m_area = wpoly.rep_m_area
        mpa.calc_m_area = wpoly.gis_m_area
        mpa.rep_area = wpoly.rep_area
        mpa.calc_area = wpoly.gis_area
        mpa.gov_type = wpoly.gov_type
        mpa.mgmt_auth = wpoly.mang_auth
        mpa.mgmt_plan_ref = wpoly.mang_plan

        # mpa.geom_smerc = wpoly.geom_smerc
        # mpa.geom = wpoly.geom
        # mpa.geog = wpoly.geog

        mpa.save()

    # SQL update all geometry rows, much faster than through django
    print "UPDATE geometry columns"
    cursor = connection.cursor()
    cursor.execute("UPDATE mpa_mpa SET geog = w.geog FROM wdpa_wdpapolygon as w WHERE mpa_mpa.wdpa_id = w.wdpaid")
    transaction.commit_unless_managed()
    print "UPDATE complete"

    Mpa.set_all_geom_from_geog()
예제 #2
0
파일: views.py 프로젝트: mci/mpatlas
def lookup_point(request):
    """Find nearby polygons with a point and search radius.
    Three lookup methods are supported:
        sphericalmercator: radius (in km) is applied to search buffer in
            900913 (aka Google Spherical Mercator) projection.  This method
            is appropriate when used in conjuction with web maps.
        greatcircle: uses PostGIS ST_DWithin spatial query on a geography
            column, using great circle distances.
        point: simple test if point is inside polygons (e.g., radius=0)
    These methods assume the geometries are in a Geography column.  Edge
    cases across the dateline are handled correctly.
    Different methods are needed if a regular Geometry column is used
    in order to handle cases across the dateline."""
    mpa_list = ()
    default_method = 'webmercator'
    try:
        lon = float(request.GET['lon'])
        lat = float(request.GET['lat'])
        try:
            radius = float(request.GET['radius'])
        except:
            radius = 225.0 # km
        try:
            method = request.GET['method'] or default_method # set default if empty string passed
        except (KeyError):
            method = default_method
        if method not in ('point', 'greatcircle', 'webmercator', 'webmercator_buffer', 'webmercator_box', 'webmercator_simple'):
            raise LookupMethodError('Unknown or malformed lookup method passed in GET query string.')
        if (radius == 0):
            method = 'point'
    except:
        # Bad input, return empty list
        return render(request, 'wdpa/mpalookup.json', {
            'mpa_list': mpa_list,
        }, content_type='application/json; charset=utf-8')
    else:
        # We need to normalize the longitude into the range -180 to 180 so we don't
        # make the cast to PostGIS Geography type complain
        point = geos.Point(normalize_lon(lon), lat, srid=gdal.SpatialReference('WGS84').srid) # srid=4326 , WGS84 geographic
        if (method == 'webmercator'):
            if (normalize_lon(lon) < 0):
                lon360 = normalize_lon(lon) + 360
            else:
                lon360 = normalize_lon(lon) - 360
            point360 = geos.Point(lon360, lat, srid=gdal.SpatialReference('WGS84').srid)
            point.transform(900913) # Google Spherical Mercator srid
            point360.transform(900913)
            #mpa_list = WdpaPolygon.objects.filter(geom_smerc__dwithin=(point, Distance(km=radius))).defer(*WdpaPolygon.get_geom_fields())
            mpa_list = WdpaPolygon.objects.filter(Q(geom_smerc__dwithin=(point, Distance(km=radius))) | Q(geom_smerc__dwithin=(point360, Distance(km=radius)))).defer(*WdpaPolygon.get_geom_fields())
            search = point
        elif (method == 'webmercator_buffer'):
            point.transform(900913) # Google Spherical Mercator srid
            searchbuffer = point.buffer(radius * 1000) # convert km to m, create buffer
            mpa_list = WdpaPolygon.objects.filter(geog__intersects=searchbuffer).defer(*WdpaPolygon.get_geom_fields())
            search = searchbuffer
        elif (method == 'webmercator_box'):
            point.transform(900913) # Google Spherical Mercator srid
            searchbuffer = point.buffer(radius * 1000)
            mpa_list = WdpaPolygon.objects.filter(geog__intersects=searchbuffer.envelope).defer(*WdpaPolygon.get_geom_fields()) # use simple bounding box instead
            search = searchbuffer.envelope
        elif (method == 'webmercator_simple'):
            point.transform(900913) # Google Spherical Mercator srid
            searchbuffer = point.buffer(radius * 1000, quadsegs=2) # simple buffer with 2 segs per quarter circle
            mpa_list = WdpaPolygon.objects.filter(geog__intersects=searchbuffer).defer(*WdpaPolygon.get_geom_fields())
            search = searchbuffer
        elif (method == 'greatcircle'):
            mpa_list = WdpaPolygon.objects.filter(geog__dwithin=(point, Distance(km=radius))).defer(*WdpaPolygon.get_geom_fields())
            search = point
        elif (method == 'point'):
            mpa_list = WdpaPolygon.objects.filter(geog__intersects=point).defer(*WdpaPolygon.get_geom_fields())
            search = point
        candidate_radius = radius * 2.2 # We're using big icons on a point, this let's us catch it better
        mpa_candidate_list = MpaCandidate.objects.filter(geog__dwithin=(point, Distance(km=candidate_radius))).defer(*MpaCandidate.get_geom_fields())
        search.transform(4326)
        return render(request, 'wdpa/mpalookup.json', {
            'search': search.coords,
            'mpa_list': mpa_list,
            'mpa_candidate_list': mpa_candidate_list,
        }, content_type='application/json; charset=utf-8')