python获取栅格点和面值的实现

1、获取指定位置的点值：

OutputFile = open(statisticResultTXT, ’w’) cellvalue=arcpy.GetCellValue_management(inputfilepath+filenname+'.tif',staionXY, '1')OutputFile.write(stationID+'_'+filenname+''+str(cellvalue)+’n’)OutputFile.close()

2、获取区域的均值极值

utputFile = open(statisticResult, ’w’) env.workspace = (’E:loessplateauET_Splineextract_year’)rlist = arcpy.ListRasters(’*’,’tif’)for file in rlist: minValueInfo= arcpy.GetRasterProperties_management(file,’MINIMUM’)minValue = minValueInfo.getOutput(0)maxValueInfo = arcpy.GetRasterProperties_management(file,’MAXIMUM’)maxValue = maxValueInfo.getOutput(0)meanValueInfo = arcpy.GetRasterProperties_management(file,’MEAN’)meanValue = meanValueInfo.getOutput(0)print file + ’,’ + str(minValue) + ’,’ + str(maxValue) + ’,’ + str(meanValue) +’n’OutputFile.write(file + ’,’ + str(minValue) + ’,’ + str(maxValue) + ’,’ + str(meanValue) +’n’)OutputFile.close()

补充知识：python_计算格点数据降水变化斜率

我就废话不多说了，还是直接看代码吧！

import numpy as npimport pandas as pdimport codecs path=r’C:try.csv’ #读取格点数据CSVdata=pd.read_csv(path,encoding=’gbk’)outpath=r’C:rate.csv’#新建存放斜率的CSVfile_csv = codecs.open(outpath,’w+’,’utf-8’) #打开方式data1=data.T #转置n=80 #格点数m=17 #年数sl=[] #空列表for i in list(range(0,80)):#循环计算80个格点的变化斜率 print (i) sp=[] y=data1[i] y=y.values for k in range(0,m-1): for j in range(k+1,m): print(k,j) s=(y[j]-y[k])/(j-k) #计算斜率 sp.append(s) sl.append(np.median(sp)) slop= pd.DataFrame(sl)slop.to_csv(outpath,header=[’slop’]) #将SLOP写入CSV

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