def extractRaster(rasterList):
b1_List, b2_List, b3_List, b6_List = [], [], [], []
modisList = []
Rnum = 0
if not os.path.exists(raster_path):
os.makedirs(raster_path)
for in_raster in rasterList:
raster_name_b1 = in_raster[8:16] + '_b1' + '.tif'
raster_name_b2 = in_raster[8:16] + '_b2' + '.tif'
raster_name_b3 = in_raster[8:16] + '_b3' + '.tif'
raster_name_b6 = in_raster[8:16] + '_b6' + '.tif'
out_raster_b1 = raster_path + '\\' + raster_name_b1
out_raster_b2 = raster_path + '\\' + raster_name_b2
out_raster_b3 = raster_path + '\\' + raster_name_b3
out_raster_b6 = raster_path + '\\' + raster_name_b6
arcpy.ExtractSubDataset_management(in_raster, out_raster_b1, 0)
arcpy.ExtractSubDataset_management(in_raster, out_raster_b2, 1)
arcpy.ExtractSubDataset_management(in_raster, out_raster_b3, 2)
arcpy.ExtractSubDataset_management(in_raster, out_raster_b6, 5)
b1_List.append(raster_name_b1)
b2_List.append(raster_name_b2)
b3_List.append(raster_name_b3)
b6_List.append(raster_name_b6)
Rnum += 1
print 'MODIS: ' + raster_name_b1, raster_name_b2, raster_name_b3, raster_name_b6
modisList.append(b1_List)
modisList.append(b2_List)
modisList.append(b3_List)
modisList.append(b6_List)
print 'Numbers: ', Rnum
print '-' * 50
return modisList
def f1():
##########
arcpy.env.workspace = ""
rasters = arcpy.ListRasters()
mask=""
for raster in rasters:
out = ExtractByMask(raster, mask) #"按掩膜提取"
out.save("xxx/_34.tif")
arcpy.Resample_management(raster, out, "xres yres", "BILINEAR") # "NEAREST ","BILINEAR","CUBIC","MAJORITY" #"重采样"
arcpy.ExtractSubDataset_management("xxx.hdf", "outfile.tif", "2") #"提取子数据集，第三个参数是选择提取第几个子数据集（波段）"
layer=""
arcpy.MakeNetCDFRasterLayer_md(raster, "precipitation", "lon", "lat", layer) # "nc制作图层"
arcpy.CopyRaster_management(layer, out, format="TIFF") # "图层保存为栅格"
ExtractValuesToPoints(mask, raster,out, "INTERPOLATE","VALUE_ONLY") # "值提取到点"/"NONE","INTERPOLATE"/"VALUE_ONLY","ALL"
out= SetNull(raster, raster, "Value=-3000") # "将满足条件的像元值设为Nodata"
out=CellStatistics(rasters, out, "SUM", "NODATA") # "像元统计" "MEAN/MAJORITY/MAXIMUM/MEDIAN/MINIMUM/MINORITY/RANGE/STD/SUM/VARIETY " "NODATA"/"DATA"忽略nodata像元
out.save("xxx.img")
arcpy.Delete_management(raster) # "删除文件"
rasters = arcpy.ListRasters() # "数据的重命名"
for raster in rasters:
raster.save("xxx.tif")
arcpy.TableToExcel_conversion(mask, "xxx.xls")# "表转Excel"
arcpy.DirectionalDistribution_stats(raster, out, "1_STANDARD_DEVIATION", "xxx", "#")# "标准差椭圆"
arcpy.MeanCenter_stats(raster, out, "xxx", "#", "#") # "中心"
def extractHDFToTif(num):
HDFfiles = os.listdir(path + "Middle\\HDFs\\")
file = path + "Middle\\HDFs\\" + str(HDFfiles[num])
arcpy.ExtractSubDataset_management(
file, path + "Middle\\Rasters\\" + str(HDFfiles[num]).rstrip(".HDF") +
".tif", 0)
pass
def mod13a3Process(folder, index, outputFolder, product):
for filename in os.listdir(folder):
if filename.endswith(".hdf"):
print("processing "+filename)
arcpy.env.workspace = outputFolder
arcpy.CheckOutExtension("spatial")
inputRaster = os.path.join(folder,filename)
outputEVI = '{0}.{1}.tif'.format(filename, product)
if arcpy.Exists(os.path.join(outputFolder, outputEVI)):
print(outputEVI + " exists")
else:
EVIfile = arcpy.ExtractSubDataset_management(inputRaster,outputEVI,index)
arcpy.CheckInExtension("spatial")
else:
continue
def rastersPreprocessing(dates_dictionary, directory):
for keys, values in dates_dictionary.items():
arrays_withnames = [arrays for arrays in values[1]]
for hdf_file in arrays_withnames:
for folderPath, folderNames, fileNames in os.walk(directory):
for modis_images in fileNames:
if modis_images == hdf_file:
workspace = env.workspace = folderPath
raster_modis_images = arcpy.Raster(modis_images)
try:
# Extract ndvi layer from hdf multiband
ndvi_name = modis_images.split(
".hdf")[0] + "_ndvi.tif"
ndvi_path = os.path.join(workspace, ndvi_name)
ndvi_image = arcpy.ExtractSubDataset_management(
raster_modis_images, ndvi_path, "0")
print("ndvi_image {}".format(ndvi_image))
# project ndvi images
prj_name = modis_images.split(
".hdf")[0] + "_prj.tif"
prj_path = os.path.join(workspace, prj_name)
prj_ndvi = arcpy.ProjectRaster_management(
ndvi_image, prj_path,
"GEOGCS['GCS_WGS_1984',DATUM['D_WGS_1984',SPHEROID['WGS_1984',6378137.0,298.257223563]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]]",
"NEAREST",
"5.59954171587093E-03 5.59954171587093E-03",
"", "",
"PROJCS['Unknown_datum_based_upon_the_custom_spheroid_Sinusoidal',GEOGCS['GCS_Unknown_datum_based_upon_the_custom_spheroid',DATUM['D_Not_specified_based_on_custom_spheroid',SPHEROID['Custom_spheroid',6371007.181,0.0]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Sinusoidal'],PARAMETER['false_easting',0.0],PARAMETER['false_northing',0.0],PARAMETER['central_meridian',0.0],UNIT['Meter',1.0]]",
"NO_VERTICAL")
print("prj_ndvi {}".format(prj_ndvi))
except arcpy.ExecuteError:
print(arcpy.GetMessages())
continue
def lst_processing(mod11c3_file):
lst_day_name = '{0}.day.tif'.format(mod11c3_file)
lst_day = arcpy.ExtractSubDataset_management(mod11c3_file,outputEVI,0)
lst_night = 2
inPath = "R:\\NorgeIsModelling\\Indice\\MODIS\\Monthly_actEva\\Ori\\"
outPath = "R:\\NorgeIsModelling\\Indice\\MODIS\\Monthly_actEva\\Processed\\"
Database = "R:\\NorgeIsModelling\\Data\\IsModelling.gdb"
arcpy.env.scratchWorkspace = Database
for iYear in range(2001, 2015):
for iMon in range(1, 13):
MonStr = "%02d" % (iMon)
env.workspace = inPath + str(iYear) + "\\" + MonStr + "\\"
hdfList = arcpy.ListRasters('*', 'hdf')
for hdf in hdfList:
eviName = hdf[0:41]
#print("Subsetting EVI band from ....."+str(hdf))
tifFile = outPath + str(
iYear) + "\\" + MonStr + "\\" + eviName + ".tif"
#print(tifFile)
data1 = arcpy.ExtractSubDataset_management(hdf, tifFile, "0")
SetNullRaster = SetNull(tifFile, tifFile, "VALUE > 32760")
NullOut = outPath + str(
iYear) + "\\" + MonStr + "\\" + eviName + "SetNull" + ".tif"
SetNullRaster.save(NullOut)
InRaster = glob.glob(outPath + str(iYear) + "\\" + MonStr + "\\" +
"*SetNull.tif")
#print(InRaster)
arcpy.MosaicToNewRaster_management(input_rasters = InRaster, output_location = outPath + str(iYear) + "\\" + MonStr + "\\", raster_dataset_name_with_extension="merge.tif",\
coordinate_system_for_the_raster="", pixel_type="16_BIT_UNSIGNED", cellsize="", number_of_bands="1", mosaic_method="MEAN", mosaic_colormap_mode="FIRST")
print("Done" + str(iYear) + str(iMon))
print "Done"
rvals = [[0, 3], [1, 0], [2, 0], [3, 0], [4, 0], [5, 0], [6, 1], [7, 1],
[8, 1], [9, 1], [10, 1], [11, 3], [12, 2], [13, 4], [14, 2], [15, 5],
[16, 5]]
remap = arcpy.sa.RemapRange(rvals)
arcpy.env.workspace = inpath
flist = arcpy.ListFiles('*.hdf')
nfiles = len(flist)
cnt = 0
for i in flist:
cnt += 1
scene = i[:24]
outfile = outpath + scene + 'LCReclass.TIF'
extract = arcpy.ExtractSubDataset_management(i, subdataset_index='0')
reclass = arcpy.sa.Reclassify(extract, 'VALUE', remap, "NODATA")
reclass.save(outfile)
del extract
del reclass
print "Done processing file {0} of {1}".format(cnt, nfiles)
# Description: Extract and Mask NDVI from HDF based on AOI
# Purpose: Automated prediction system for vegetation cover based on MODIS- NDVI satellite data and neural networks
# Author: Sohaib K. M. Abujayyab
# Created: 11/02/2019
# Requirements: None
# -------------------------------------------------------------------------------
# Import system modules
import arcpy
import os
arcpy.env.overwriteOutput = True
arcpy.env.workspace = arcpy.GetParameterAsText(0)
rasterList = arcpy.ListRasters()
inMaskData = arcpy.GetParameterAsText(1)
OutputFolder = arcpy.GetParameterAsText(2)
#Extract NDVI from HDF
for raster in rasterList:
arcpy.AddMessage(str(raster))
OutputFolderpath = os.path.abspath(OutputFolder)
OutputFolderpath2 = os.path.join(OutputFolderpath, '')
OutputTif = str(OutputFolderpath2) + str(raster[9:-29])
arcpy.AddMessage(str(OutputTif))
Output=arcpy.ExtractSubDataset_management(raster, "in_memory/Output", "0")
# Execute ExtractByMask
arcpy.gp.ExtractByMask_sa("in_memory/Output", inMaskData, OutputTif+ ".tif")
del Output
import gc
gc.disable()
from arcpy import env
from arcpy.sa import *
arcpy.CheckOutExtension("Spatial") #Turns on Spatial Analyst Extension
env.workspace = arcpy.GetParameterAsText(0) # TO BE PARAMETER
env.overwriteOutput = True #If TRUE: when ran deletes data if it already exists. If FALSE: Does not delte data that already exists.
study_area = arcpy.GetParameterAsText(
1) # MUST BE IN GEODATABASE # TO BE PARAMETER
## HDF > RASTER TIFF
lst = arcpy.ListFiles("*.hdf")
mosaiclist = []
for filez in lst:
output_rast = filez[0:-4] + "_raster" + ".tif"
extracted = arcpy.ExtractSubDataset_management(filez, output_rast, "0")
OutExtractByMask = ExtractByMask(extracted, study_area)
OutExtractByMask.save((filez[0:-4]) + "_sa.tif")
## MOSAIC RASTERS TOGETHER
for dirname, dirnames, filenames in os.walk(env.workspace):
for subdirname in dirnames:
env.workspace = os.path.join(dirname, subdirname)
mosaiclist = arcpy.ListRasters("*sa.tif")
M_Out = env.workspace
i = 0
for raster in mosaiclist:
while i < len(lst):
currentPattern = lst[i]
arcpy.env.workspace = working_dir
#Make list of hdf files for that day
wildcard = "*A" + yd + "*"
hdfList = arcpy.ListRasters(wildcard, 'HDF')
#Test if there are HDF files for that day
if not (os.path.isfile(output_dir + "\\" + yd + 'MOD.bands.proj.tif')):
print hdfList
if len(hdfList) <> 0:
#Loop through HDF files
for hdf in hdfList:
tifname = hdf[8:23] + ".tif"
print "Extracting bands from..." + str(hdf)
data1 = arcpy.ExtractSubDataset_management(
hdf, output_dir + r'\bands.' + tifname, [11, 13, 14])
data1 = arcpy.ExtractSubDataset_management(
hdf, output_dir + r'\state.' + tifname, [1])
#Make a list of all the new tifs
arcpy.env.workspace = output_dir
tiflist = arcpy.ListRasters('bands.*', 'TIF')
tiflist_state = arcpy.ListRasters('state.*', 'TIF')
#Mosaic tifs together
print "Combining MODIS tiles..."
arcpy.MosaicToNewRaster_management(tiflist,output_dir, yd + 'bands.tif', \
"PROJCS['World_Sinusoidal',GEOGCS['GCS_WGS_1984',DATUM['D_WGS_1984',SPHEROID['WGS_1984',6378137.0,298.257223563]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Sinusoidal'],PARAMETER['False_Easting',0.0],PARAMETER['False_Northing',0.0],PARAMETER['Central_Meridian',0.0],UNIT['Meter',1.0]]", '16_BIT_SIGNED', \
number_of_bands="3")
arcpy.MosaicToNewRaster_management(tiflist_state,output_dir, yd + 'state.tif', \
"PROJCS['World_Sinusoidal',GEOGCS['GCS_WGS_1984',DATUM['D_WGS_1984',SPHEROID['WGS_1984',6378137.0,298.257223563]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Sinusoidal'],PARAMETER['False_Easting',0.0],PARAMETER['False_Northing',0.0],PARAMETER['Central_Meridian',0.0],UNIT['Meter',1.0]]", '16_BIT_SIGNED', \
for i in (0, ):
# Set the current workspace (where the hdf files are located)
env.workspace = "f:\\wtmp\hdf\\"
# Get a list of HDF files from the workspace using
#an internal GIS function "listRasters"
rasterList = arcpy.ListRasters("*", "hdf")
# Extract rasters from HDF files in the workspace
# Change "0" to the hdf layer needed
for raster in rasterList:
output = "f:\\wtmp\\hdf\\output\\layer" + str(i) + "\\" + str(
raster)[:-4] + ".tif"
layer = str(i)
arcpy.ExtractSubDataset_management(raster, output, layer)
print "Layer" + str(i) + ": 1. Extractining rasters - Finished"
## 2. Mosaic each raster to one large dataset
# glob (from iglob lib) is used to grab part of the filename (string). here we take the date part below
from glob import iglob
#set where the tif files are located
env.workspace = "f:\\wtmp\\hdf\\output\\layer" + str(i)
# Get a list of dates from file names
DateList = list() #creates an empty list for date
rasterList = arcpy.ListRasters("*", "tif") #list of all tif raster files
for raster in rasterList:
date = raster[1:8]
DateList.append(date)
def extract_from_hdf(filelist, layerlist, layernames=False, outdir=None):
"""
Extracts tifs from MODIS extract_HDF_layer files, ensures proper projection.
inputs:
filelist list of '.hdf' files from which data should be extracted (or a directory)
layerlist list of layer numbers to pull out as individual tifs should be integers
such as [0,4] for the 0th and 4th layer respectively.
layernames list of layer names to put more descriptive file suffixes to each layer
outdir directory to which tif files should be saved
if outdir is left as 'False', files are saved in the same directory as
the input file was found.
"""
if outdir is not None:
if not os.path.exists(outdir):
os.makedirs(outdir)
# enforce lists for iteration purposes and sanitize inputs
filelist = core.enf_filelist(filelist)
for filename in filelist:
if '.xml' in filename or not '.hdf' in filename:
filelist.remove(filename)
layerlist = core.enf_list(layerlist)
layernames = core.enf_list(layernames)
# ignore user input layernames if they are invalid, but print warnings
if layernames and not len(layernames) == len(layerlist):
Warning('Layernames must be the same length as layerlist!')
Warning('Ommiting user defined layernames!')
layernames = False
# create empty list to add failed file names into
failed = []
# iterate through every file in the input filelist
for infile in filelist:
# pull the filename and path apart
path, name = os.path.split(infile)
arcpy.env.workspace = path
for i, layer in enumerate(layerlist):
# specify the layer names.
if layernames:
layername = layernames[i]
else:
layername = str(layer).zfill(3)
# use the input output directory if the user input one, otherwise build one
if outdir:
outname = os.path.join(
outdir, "{0}_{1}.tif".format(name[:-4], layername))
else:
outname = os.path.join(
path, "{0}_{1}.tif".format(name[:-4], layername))
# perform the extracting and projection definition
try:
# extract the subdataset
arcpy.ExtractSubDataset_management(infile, outname, str(layer))
# define the projection as the MODIS Sinusoidal
define_projection(outname)
print("Extracted {0}".format(os.path.basename(outname)))
except:
print("Failed to extract {0} from {1}".format(
os.path.basename(outname), os.path.basename(infile)))
failed.append(infile)
print("Finished extracting all hdfs! \n")
return failed
print()
# For Loop to go through all the files and extract Bands
for hdf in hdf_list:
# Extract Band Numbers (Variables of HDFs)
MODIS_Product = os.path.basename(hdf).split(".")[0]
A = os.path.basename(hdf).split(".")[1]
modis_grid_code = os.path.basename(hdf).split(".")[2]
version = os.path.basename(hdf).split(".")[3]
B = os.path.basename(hdf).split(".")[4]
name = MODIS_Product + "_" + A + "_" + modis_grid_code + "_" + version + ".tif"
print()
print("\t - Extracting NDVI from... " + MODIS_Product + " " + B )
arcpy.ExtractSubDataset_management( hdf, outws + name , "0")
print("\t\t - Successful")
print()
print("HDF DATA EXTRACTING SUCCESSFUL...")
print()
# Rasters to same day mosaics
print("Commencing Stiching of MOODIS tiles...")
print()
extracted_NDVI = r'E:\NDVI\EXTRACTED_NDVI\\'
outws1 = r'E:\NDVI\MODIS_stiched\\'
import arcpy
arcpy.CheckOutExtension("spatial")
arcpy.gp.overwriteOutput=1
arcpy.env.workspace = "G:\\migration\\landuse\\2001"
raster_sets = arcpy.ListRasters("*", "hdf")
#ref= "G:\\pheasant\\1.maxent\\2.rasters\\LIM\\TIF\\dem1.tif"
#spref=arcpy.Describe(ref).SpatialReference
for raster_set in raster_sets:
print(raster_set)
out= "G:\\migration\\landuse\\2001\\"+raster_set+'.tif'
#arcpy.ProjectRaster_management(raster, out, ref)
arcpy.ExtractSubDataset_management (raster_set, out , '1')
print(raster_set+" has done")
print("All done")
Output_LocationGrid = outPathscrap + os.sep + str(jdate) + 'NDVIgrids'
if not os.path.exists(Output_LocationGrid):
os.makedirs(Output_LocationGrid)
env.workspace = outHdf
InputHDFs = arcpy.ListRasters()
list = []
i = 10
HDFnum = '0'
for InputHDF in InputHDFs:
OutputTIF = Output_LocationGrid + os.sep + str(jdate) + str(
i) # gridfile outHdf + "\\" +
print(OutputTIF)
# Process: Extract Subdataset...
arcpy.ExtractSubDataset_management(InputHDF, OutputTIF, HDFnum)
list.append(OutputTIF)
i = i + 1
NDVI = str(year) + str(jdate) + "." + str(product)
print(NDVI)
Coordsystem = r'C:\WaterSmart\Users\Olena\Projects\ArcGIS\WGS 1984.prj'
arcpy.CreateFileGDB_management(outPathscrap, "lst.gdb", "CURRENT")
arcpy.CreateMosaicDataset_management(outPathscrap + os.sep + "lst.gdb",
"lst2", Coordsystem, "1",
"16_BIT_SIGNED", "NONE", "")
mosimg = arcpy.AddRastersToMosaicDataset_management(
outPathscrap + os.sep + "lst.gdb" + os.sep + "lst2",
"Raster Dataset", Output_LocationGrid, "UPDATE_CELL_SIZES",
"UPDATE_BOUNDARY", "NO_OVERVIEWS", "#", "0", "1500", "#", "#",
"SUBFOLDERS", "OVERWRITE_DUPLICATES", "BUILD_PYRAMIDS",
import arcpy
import warnings
warnings.filterwarnings("ignore")
from arcpy.sa import *
arcpy.CheckOutExtension("Spatial")
arcpy.env.workspace=ras_path
#arcpy.env.snapRaster = samp
for yd in date:
extrac_tif_name=[]
extrac_tif=''
for hdf_f in hdfs:
if hdf_f.startswith(hdf_f[0:tps]+yd):
orgras=tmp_path+'\\'+hdf_f[0:len(hdf_f)-3]+"tif"
arcpy.ExtractSubDataset_management(hdf_f,orgras,str(band))
stnras = tmp_path+'\\'+hdf_f[0:len(hdf_f)-4]+"_stn.tif"
arcpy.gp.RasterCalculator_sa("SetNull(('"+orgras+"' < "+str(efrg[0])+") | ('"+orgras+"' > "+str(efrg[1])+"),'"+orgras+"'*"+str(sf)+")", stnras) # setnull
arcpy.Delete_management(orgras)
extrac_tif=extrac_tif+';'+stnras
extrac_tif_name.append(stnras)
extrac_tif=extrac_tif[1:len(extrac_tif)]
rasmosiac=hdfs[0][0:tps]+yd+".tif"
arcpy.MosaicToNewRaster_management(extrac_tif,out_path,rasmosiac,"#",valid,"#","1","LAST","FIRST")
for exfn in extrac_tif_name:
arcpy.Delete_management(exfn)
# rasprj = out_path+'\\'+rasmosiac
# arcpy.ProjectRaster_management(rasmosiac,rasprj,samp,'NEAREST',samp,'#','#','#')
# arcpy.Delete_management(rasmosiac)
#----Created by Matthew Farr-------------------#
#----------------------------------------------#
import arcpy, shutil, os, csv
from arcpy.sa import *
#Working environment within HDF folder
arcpy.env.workspace = "C:\\Users\\farrm\\Documents\\GitHub\\Ungulate\\GIS\\HDF\\"
#List of HDF files
rasterlist = arcpy.ListRasters("*" "HDF")
#UTM projection
projection = arcpy.SpatialReference(4326)
#Extract NDVI from HDF files
for raster in rasterlist:
name = raster.split('.')
filename = "..\\NDVI\\NDVI" + str(name[1][1:]) + ".tif"
arcpy.ExtractSubDataset_management(raster, filename, "0")
#Working environment within site folder
arcpy.env.workspace = "C:\\Users\\farrm\\Documents\\GitHub\\Ungulate\\GIS\\Site\\"
#List of shapefiles(i.e., sites)
shlist = arcpy.ListFeatureClasses()
#Buffer sites 650 meters
for fc in shlist:
name = fc.split('.')
filename = "C:\\Users\\farrm\\Documents\\GitHub\\Ungulate\\GIS\\SiteBuffer\\" + name[
0] + ".shp"
arcpy.Buffer_analysis(fc, filename, "1000 meters", "FULL", "FLAT")
#Working environment within sitebuffer folder
arcpy.env.workspace = "C:\\Users\\farrm\\Documents\\GitHub\\Ungulate\\GIS\\SiteBuffer\\"
#List of shapefiles(i.e., site buffers)
def HDF(filelist, layerlist, layernames = False, outdir = False):
"""
Function extracts tifs from HDFs.
Use "Extract_MODIS_HDF" in the modis module for better
handling of MODIS data with sinusoidal projections.
inputs:
filelist list of '.hdf' files from which data should be extracted
layerlist list of layer numbers to pull out as individual tifs should be integers
such as [0,4] for the 0th and 4th layer respectively.
layernames list of layer names to put more descriptive names to each layer
outdir directory to which tif files should be saved
if outdir is left as 'False', files are saved in the same directory as
the input file was found.
"""
# Set up initial arcpy modules, workspace, and parameters, and sanitize inputs.
core.Check_Spatial_Extension()
arcpy.env.overwriteOutput = True
# enforce lists for iteration purposes
filelist = core.enforce_list(filelist)
layerlist = core.enforce_list(layerlist)
layernames = core.enforce_list(layernames)
# ignore user input layernames if they are invalid, but print warnings
if layernames and not len(layernames) == len(layerlist):
print('layernames must be the same length as layerlist!')
print('ommiting user defined layernames!')
layernames=False
# create empty list to add failed file names into
failed=[]
# iterate through every file in the input filelist
for infile in filelist:
# pull the filename and path apart
path,name = os.path.split(infile)
arcpy.env.workspace = path
for i in range(len(layerlist)):
layer=layerlist[i]
# specify the layer names.
if layernames:
layername = layernames[i]
else:
layername = str(layer).zfill(3)
# use the input output directory if the user input one, otherwise build one
if outdir:
if not os.path.exists(os.path.join(outdir,layername)):
os.makedirs(os.path.join(outdir,layername))
outname=os.path.join(outdir,layername,name[:-4] +'_'+ layername +'.tif')
else:
if not os.path.exists(os.path.join(path,layername)):
os.makedirs(os.path.join(path,layername))
outname = os.path.join(path,layername,name[:-4] +'_'+ layername +'.tif')
# perform the extracting and projection definition
try:
# extract the subdataset
arcpy.ExtractSubDataset_management(infile, outname, str(layer))
print('Extracted ' + outname)
except:
print('Failed extract '+ outname + ' from ' + infile)
failed.append(infile)
return(failed)
inPath = os.path.join('I:/MODIS_CA/LAI/', str(yearn))
outPath = os.path.join('I:/MODIS_CA/LAI/TIFF/', str(yearn))
if not os.path.exists(outPath):
os.mkdir(outPath)
oway = 'I:/MODIS_CA/LAI/TIFF/' + str(yearn) + ".txt"
f = open(oway, 'a')
env.workspace = inPath
arcpy.env.scratchWorkspace = inPath
hdfList = arcpy.ListRasters('MOD15A2H.*', 'hdf')
name1 = ["name"]
num1 = 0
for hdf in hdfList:
eviName1 = hdf[9:17]
data1 = arcpy.ExtractSubDataset_management(
hdf, outPath + "/" + hdf[9:17] + "_" + str(num1) + ".tif", "1")
aa = len(name1)
# if aa > 0:
if (eviName1 != name1[aa - 1]):
name1.append(eviName1)
f.write(str(eviName1) + '\n')
print str(eviName1)
else:
print "++" + str(eviName1) + "++"
# else:
num1 = num1 + 1
print "finish "
del inPath
del outPath
del env.workspace
rasterlist = arcpy.ListRasters("*","HDF")
projection = arcpy.SpatialReference(4326)
#spliting of name MOD13A1.A2001001.h24v05.005.2008270033303.hdf
for raster in rasterlist:
name=raster.split('.')
name1=name[1]
name2=name[2]
newName="n"+str(name1[3:])+str(name2[1:3])+str(name2[4:])
newSubFolder=str(name1[5:])
filename=Result+"\\"+newSubFolder+"\\"+newName
path=Result+"\\"+newSubFolder
if os.path.exists(path):
print("Folder exists"+newSubFolder)
arcpy.ExtractSubDataset_management(raster, filename+".tif", "0")
arcpy.ProjectRaster_management(filename+".tif", filename+"p"+".tif",projection,"","","","","")
arcpy.Delete_management(filename+".tif")
else:
arcpy.CreateFolder_management(Result,newSubFolder)
print("folder made"+newSubFolder)
arcpy.ExtractSubDataset_management(raster, filename+".tif", "0")
arcpy.ProjectRaster_management(filename+".tif", filename+"p"+".tif",projection,"","","","","")
arcpy.Delete_management(filename+".tif")
arcpy.env.workspace="D:\\Shivaprakash\\TEST\\modis_uttrakanda\\TEST\\2015"
rasterlist = arcpy.ListRasters("*","HDF")
for raster in rasterlist:
delete_hdf=Result+"\\"+raster
os.remove(delete_hdf)
def Extract_MODIS_HDF(filelist,layerlist,layernames=False,outdir=False,Quiet=False):
#--------------------------------------------------------------------------------------
# Function extracts tifs from HDFs such as MODIS data.
#
# inputs:
# filelist list of '.hdf' files from which data should be extracted
# layerlist list of layer numbers to pull out as individual tifs should be integers
# such as [0,4] for the 0th and 4th layer respectively.
# layernames list of layer names to put more descriptive names to each layer
# outdir directory to which tif files should be saved
# if outdir is left as 'False', files are saved in the same directory as
# the input file was found.
#--------------------------------------------------------------------------------------
# import modules
import sys, os, arcpy, time
# Set up initial arcpy modules, workspace, and parameters, and sanitize inputs.
Check_Spatial_Extension()
arcpy.env.overwriteOutput = True
# enforce lists for iteration purposes
filelist=Enforce_List(filelist)
layerlist=Enforce_List(layerlist)
layernames=Enforce_List(layernames)
# ignore user input layernames if they are invalid, but print warnings
if layernames and not len(layernames)==len(layerlist):
print '{Extract_MODIS_HDF} layernames must be the same length as layerlist!'
print '{Extract_MODIS_HDF} ommiting user defined layernames!'
layernames=False
# create empty list to add failed file names into
failed=[]
print '{Extract_MODIS_HDF} Beginning to extract!'
# iterate through every file in the input filelist
for infile in filelist:
# pull the filename and path apart
path,name = os.path.split(infile)
arcpy.env.workspace = path
for i in range(len(layerlist)):
layer=layerlist[i]
# specify the layer names.
if layernames:
layername=layernames[i]
else:
layername=str(layer).zfill(3)
# use the input output directory if the user input one, otherwise build one
if not os.path.exists(outdir):
os.makedirs(outdir)
outname=os.path.join(outdir,name[:-4] +'_'+ layername +'.tif')
# perform the extracting and projection definition
try:
# extract the subdataset
arcpy.ExtractSubDataset_management(infile, outname, str(layer))
# define the projection as the MODIS Sinusoidal
Define_MODIS_Projection(outname)
if not Quiet:
print '{Extract_MODIS_HDF} Extracted ' + outname
except:
if not Quiet:
print '{Extract_MODIS_HDF} Failed extract '+ outname + ' from ' + infile
failed.append(infile)
if not Quiet:print '{Extract_MODIS_HDF} Finished!'
return(failed)
#Because had 100 missing days, redo it with missing data in subfolder LST_missing
arcpy.env.workspace = r"F:\Hexsim\Data\MODIS_LST_download\LST_missing\LST_raw"
arcpy.env.overwriteOutput = True
dir = "F:\Hexsim\Data\MODIS_LST_download\LST_missing\LST_raw"
ref_dataset = 'F:\\Hexsim\\Data\MODIS_LST_download\\LST_records\\ref_prof_layer\\MOD2000065.tif'
sr_out = arcpy.SpatialReference("NAD 1983")
for name in glob.glob(dir + '\\MOD11A1*'):
print(name)
base = os.path.basename(name)
file_name, file_ext = os.path.splitext(base)
if file_ext == '.hdf':
outfile = 'F:\\Hexsim\\Data\MODIS_LST_download\\LST_missing\\LST_records\\' + file_name[0:3] + file_name[9:16]
arcpy.ExtractSubDataset_management(name, outfile + ".tif", "0")
#Define projection
sr_def = arcpy.Describe(ref_dataset).spatialReference
arcpy.DefineProjection_management(name, sr_def)
#Project raster
arcpy.ProjectRaster_management(in_raster=outfile + ".tif", out_raster=outfile + "pr.tif",
out_coor_system= sr_out,
resampling_type="CUBIC",
geographic_transform = "MODIS V5 Sinusoidal to GCS NAD 1983")
####################################################################################################
################# CREATE LAYER OF POINTS WITH LOGGER LOCATIONS ##############################
days,
np.where(days == 177)[0]) # a scene was missing from the MODIS data
#extract subdatasets
arcpy.CreateFileGDB_management(datafolder, "extracts.gdb")
arcpy.CreateFileGDB_management(datafolder2, "extracts.gdb")
#Temperature
arcpy.env.workspace = datafolder
alltiles = arcpy.ListRasters('*.hdf')
for j in range(len(alltiles)):
for i in range(len(dataindices)):
theday = alltiles[j][13:16]
out_name = datafolder + 'extracts.gdb\\' + datanames[i] + "_" + theday
arcpy.ExtractSubDataset_management(datafolder + '\\' + alltiles[j],
out_name, dataindices[i])
#ET and PET
arcpy.env.workspace = datafolder2
alltiles = arcpy.ListRasters('*.hdf')
for j in range(len(alltiles)):
for i in range(len(dataindices2)):
theday = alltiles[j][13:16]
out_name = datafolder2 + 'extracts.gdb\\' + datanames2[i] + "_" + theday
arcpy.ExtractSubDataset_management(datafolder2 + '\\' + alltiles[j],
out_name, dataindices2[i])
tempdata = np.ndarray(shape=(len(dataindices), len(days)))
for i in range(len(dataindices)):
for j in range(len(days)):
lista = arcpy.ListDatasets()
hdf_files = [x for x in lista if '.hdf' in x]
fn_vars = ['a14', 'da', 'ni']
for img in hdf_files:
day = str(img.split('.')[1][5:])
for index in ['0', '4']:
outname = hdf2raster + '\\' + fn_vars[0] + day + 'lst' + '_'
if index == '0':
outname += 'da'
else:
outname += 'ni'
print img
print outname, '-----', index
arcpy.ExtractSubDataset_management(img, outname, index)
arcpy.env.workspace = hdf2raster
os.chdir(hdf2raster)
# poject
lista = arcpy.ListDatasets()
for img in lista:
raster_file = arcpy.Raster(img)
print
outname = prodata + '\\' + raster_file.name
print outname
arcpy.ProjectRaster_management(
raster_file, outname,
"PROJCS['WGS_1984_UTM_zone_24S',GEOGCS['GCS_WGS_1984',DATUM['D_WGS_1984',SPHEROID['WGS_1984',6378137.0,298.257223563]],PRIMEM['Greenwich',0.0],UNIT['Degree',0.0174532925199433]],PROJECTION['Transverse_Mercator'],PARAMETER['false_easting',500000.0],PARAMETER['false_northing',10000000.0],PARAMETER['central_meridian',-39.0],PARAMETER['scale_factor',0.9996],PARAMETER['latitude_of_origin',0.0],UNIT['Meter',1.0]]",
"NEAREST", "926.625433138333", "", "",
def extract_from_hdf(file_list, layer_list, layer_names = False, outdir = None):
"""
Extracts tifs from MODIS HDF files, ensures proper projection.
:param file_list: either a list of '.hdf' files from which data should be extracted,
or a directory containing '.hdf' files.
:param layer_list: list of layer numbers to pull out as individual tifs should be integers
such as [0,4] for the 0th and 4th layer respectively.
:param layer_names: list of layer names to put more descriptive file suffixes to each layer
:param outdir: directory to which tif files should be saved
if outdir is left as 'None', files are saved in the same directory as
the input file was found.
:return output_filelist: returns a list of all files created by this function
"""
if outdir is not None:
if not os.path.exists(outdir):
os.makedirs(outdir)
# enforce lists for iteration purposes and sanitize inputs
file_list = core.enf_filelist(file_list)
for filename in file_list:
if '.xml' in filename or '.ovr' in filename or not '.hdf' in filename:
file_list.remove(filename)
layer_list = core.enf_list(layer_list)
layer_names = core.enf_list(layer_names)
# ignore user input layer_names if they are invalid, but print warnings
if layer_names and not len(layer_names) == len(layer_list):
Warning('layer_names must be the same length as layer_list!')
Warning('Omitting user defined layer_names!')
layer_names = False
output_filelist = []
# iterate through every file in the input file_list
for infile in file_list:
# pull the filename and path apart
path,name = os.path.split(infile)
arcpy.env.workspace = path
for i, layer in enumerate(layer_list):
# specify the layer names.
if layer_names:
layername = layer_names[i]
else:
layername = str(layer).zfill(3)
# use the input output directory if the user input one, otherwise build one
if outdir:
outname = os.path.join(outdir, "{0}_{1}.tif".format(name[:-4], layername))
else:
outname = os.path.join(path, "{0}_{1}.tif".format(name[:-4], layername))
# perform the extracting and projection definition
try:
arcpy.ExtractSubDataset_management(infile, outname, str(layer))
define_projection(outname)
output_filelist.append(outname)
print("Extracted {0}".format(os.path.basename(outname)))
except:
print("Failed to extract {0} from {1}".format(os.path.basename(outname),
os.path.basename(infile)))
return output_filelist
# --------------------------------------------------------------------------- # cn002.py # Created on: 2011-04-25 13:31:26.00000 # (generated by ArcGIS/ModelBuilder) # Description: # --------------------------------------------------------------------------- # Import arcpy module import arcpy # Local variables: a2003_002 = "C:\\Users\\ekloog\\Documents\\$Doc\\3.PostDoc\\3.1.Projetcs\\3.1.3.TEMP_MODELS\\3.1.1.1.Raw_data\\MODIS_TEMP\\Night only\\a2003_002.hdf" a2003_002_tif = "C:\\Users\\ekloog\\Documents\\$Doc\\3.PostDoc\\3.1.Projetcs\\3.1.3.TEMP_MODELS\\3.1.1.4.Work\\2.Gather_data\\hdf_2_tiff\\a2003_002.tif" arcpy.ExtractSubDataset_management(a2003_002, a2003_002_tif, "0")
if len(mod44w_seltiles) > 1 or len(mod44w_seltiles) == 0:
mod44w_seltiles = get_inters_tiles(ref_extent=gladtile_extent,
tileiterator=mod44w_wgsextdict,
containsonly=False)
#Extract QA dataset
mod44w_seltilesQA = []
for tile in mod44w_seltiles:
modtileid = re.search(
'(?<=MOD44W_A2015001_)h[0-9]{2}v[0-9]{2}(?=[0-9_]{18}[.]hdf)',
os.path.split(tile)[1]).group()
outQA = os.path.join(mod44w_resgdb, "QA_{}".format(modtileid))
if not arcpy.Exists(outQA):
print(outQA)
arcpy.ExtractSubDataset_management(in_raster=tile,
out_raster=outQA,
subdataset_index=1)
mod44w_seltilesQA.append(outQA)
#If multiple MODIS tiles intersect GLAD tile, mosaick them
if len(mod44w_seltilesQA) > 1:
mod44w_gladmatch = os.path.join(
mod44w_resgdb, 'mod44wQA_gladmosaic{}'.format(gladtileid))
if not arcpy.Exists(mod44w_gladmatch):
arcpy.MosaicToNewRaster_management(
input_rasters=mod44w_seltilesQA,
output_location=os.path.split(mod44w_gladmatch)[0],
raster_dataset_name_with_extension=os.path.split(
mod44w_gladmatch)[1],
number_of_bands=1,
mosaic_method='FIRST')
