多边形重叠的Shapefile：计算平均值

Question

我有一个非常大的多边形shapefile，其中包含数百个要素，通常彼此重叠。 这些功能中的每一个都有一个存储在属性表中的值。 我只需要计算重叠区域的平均值。 我可以想象这个任务需要几个复杂的步骤：我想知道是否有一个简单的方法。 我愿意接受各种建议，我可以使用ArcMap，QGis，arcpy脚本，PostGis，GDAL ...我只需要一些想法。 谢谢！

Answer 1

您应该使用ArcGIS中的联合工具 。 它将在多边形重叠的地方创建新的多边形。 为了保留两个多边形的属性，请两次添加多边形shapefile作为输入，并使用ALL作为join_attributes参数，这也会创建与它们相交的多边形，您可以轻松选择和删除它们，因为它们具有相同的FID。 然后，只需将一个新字段添加到属性表，然后根据输入多边形中的两个原始值字段对其进行计算。 这可以在脚本中完成，也可以直接使用工具箱的工具完成。

Answer 2

您能否将多边形栅格化为多个图层，每个像素可能包含您的属性值。 然后通过平均属性值合并图层？

Answer 3

经过几次尝试，我找到了一种解决方案，将所有特征栅格化，然后执行像元统计以计算平均值。 请参阅下面我编写的脚本，请随时评论和改进它！ 谢谢！

    #This script processes a shapefile of snow persistence (area of interest: Afghanistan).
    #the input shapefile represents a month of snow cover and contains several features.
    #each feature represents a particular day and a particular snow persistence (low,medium,high,nodata)
    #these features are polygons multiparts, often overlapping.
    #a feature of a particular day can overlap a feature of another one, but features of the same day and with
    #different snow persistence can not overlap each other.
    #(potentially, each shapefile contains 31*4 feature).
    #the script takes the features singularly and exports each feature in a temporary shapefile
    #which contains only one feature.
    #Then, each feature is converted to raster, and after
    #a logical conditional expression gives a value to the pixel according the intensity (high=3,medium=2,low=1,nodata=skipped).
    #Finally, all these rasters are summed and divided by the number of days, in order to
    #calculate an average value.
    #The result is a raster with the average snow persistence in a particular month.
    #This output raster ranges from 0 (no snow) to 3 (persistent snow for the whole month)
    #and values outside this range should be considered as small errors in pixel overlapping.
    #This script needs a particular folder structure. The folder C:\TEMP\Afgh_snow_cover contains 3 subfolders
    #input, temp and outputs. The script takes care automatically of the cleaning of temporary data


    import arcpy, numpy, os
    from arcpy.sa import *
    from arcpy import env

    #function for finding unique values of a field in a FC
    def unique_values_in_table(table, field):
            data = arcpy.da.TableToNumPyArray(table, [field])
            return numpy.unique(data[field])

    #check extensions
    try:
        if arcpy.CheckExtension("Spatial") == "Available":
            arcpy.CheckOutExtension("Spatial")
        else:
            # Raise a custom exception
            #
            raise LicenseError
    except LicenseError:
        print "spatial Analyst license is unavailable"  
    except:
        print arcpy.GetMessages(2)
    finally:
        # Check in the 3D Analyst extension
        #
        arcpy.CheckInExtension("Spatial")

    # parameters and environment
    temp_folder = r"C:\TEMP\Afgh_snow_cover\temp_rasters"
    output_folder = r"C:\TEMP\Afgh_snow_cover\output_rasters"
    env.workspace = temp_folder
    unique_field = "FID"
    field_Date = "DATE"
    field_Type = "Type"
    cellSize = 0.02


    fc = r"C:\TEMP\Afgh_snow_cover\input_shapefiles\snow_cover_Dec2007.shp"

    stat_output_name = fc[-11:-4] + ".tif"

    #print stat_output_name
    arcpy.env.extent = "MAXOF"

    #find all the uniquesID of the FC
    uniqueIDs = unique_values_in_table(fc, "FID")

    #make layer for selecting
    arcpy.MakeFeatureLayer_management (fc, "lyr")
    #uniqueIDs = uniqueIDs[-5:]
    totFeatures = len(uniqueIDs)
    #for each feature, get the date and the type of snow persistence(type can be high, medium, low and nodata)
    for i in uniqueIDs:
        SC = arcpy.SearchCursor(fc)
        for row in SC:
            if row.getValue(unique_field) == i:
                datestring = row.getValue(field_Date)
                typestring = row.getValue(field_Type)

        month = str(datestring.month)
        day = str(datestring.day)
        year = str(datestring.year)

    #format month and year string
        if len(month) == 1:
            month = '0' + month

        if len(day) == 1:
            day = '0' + day

    #convert snow persistence to numerical value
        if typestring == 'high':
            typestring2 = 3
        if typestring == 'medium':
            typestring2 = 2
        if typestring == 'low':
            typestring2 = 1
        if typestring == 'nodata':
            typestring2 = 0
    #skip the NoData features, and repeat the following for each feature (a feature is a day and a persistence value)
        if typestring2 > 0:
                #create expression for selecting the feature
                expression = ' "FID" = ' + str(i) + ' '
                #select the feature
                arcpy.SelectLayerByAttribute_management("lyr", "NEW_SELECTION", expression)
                #create 
                #outFeatureClass = os.path.join(temp_folder, ("M_Y_" + str(i)))
                #create faeture class name, writing the snow persistence value at the end of the name
                outFeatureClass = "Afg_" + str(year) + str(month) + str(day) + "_" + str(typestring2) + '.shp'
                #export the feature
                arcpy.FeatureClassToFeatureClass_conversion("lyr", temp_folder, outFeatureClass)
                print "exported FID " + str(i) + " \ " + str(totFeatures)
                #create name of the raster and convert the newly created feature to raster
                outRaster = outFeatureClass[4:-4] + ".tif"
                arcpy.FeatureToRaster_conversion(outFeatureClass, field_Type, outRaster, cellSize)
                #remove the temporary fc
                arcpy.Delete_management(outFeatureClass)
        del SC, row
    #now many rasters are created, representing the snow persistence types of each day. 
    #list all the rasters created 
    rasterList = arcpy.ListRasters("*", "All")
    print rasterList

    #now the rasters have values 1 and 0. the following loop will
    #perform CON expressions in order to assign the value of snow persistence
    for i in rasterList:
            print i + ":"
            inRaster = Raster(i)
            #set the value of snow persistence, stored in the raster name
            value_to_set = i[-5]
            inTrueRaster = int(value_to_set)
            inFalseConstant = 0
            whereClause = "Value > 0"


            # Check out the ArcGIS Spatial Analyst extension license
            arcpy.CheckOutExtension("Spatial")
            print 'Executing CON expression and deleting input'
            # Execute Con , in order to assign to each pixel the value of snow persistence
            print str(inTrueRaster)
            try:
                    outCon = Con(inRaster, inTrueRaster, inFalseConstant, whereClause)
            except:
                    print 'CON expression failed (probably empty raster!)'

            nameoutput = i[:-4] + "_c.tif"
            outCon.save(nameoutput)
            #delete the temp rasters with values 0 and 1
            arcpy.Delete_management(i)
    #list the raster with values of snow persistence
    rasterList = arcpy.ListRasters("*_c.tif", "All")
    #sum the rasters
    print "Caclulating SUM"
    outCellStats = CellStatistics(rasterList, "SUM", "DATA")
    #calculate the number of days (num of rasters/3)
    print "Calculating day ratio"
    num_of_rasters = len(rasterList)
    print 'Num of rasters : ' + str(num_of_rasters)
    num_of_days = num_of_rasters / 3
    print 'Num of days : ' + str(num_of_days)
    #in order to store decimal values, multiplicate the raster by 1000 before dividing
    outCellStats = outCellStats * 1000 / num_of_days
    #save the output raster
    print "saving output " + stat_output_name
    stat_output_name = os.path.join(output_folder,stat_output_name)
    outCellStats.save(stat_output_name)
    #delete the remaining temporary rasters
    print "deleting CON rasters"
    for i in rasterList:
            print "deleting " + i
            arcpy.Delete_management(i)
    arcpy.Delete_management("lyr")