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Copy pathDRIP.py
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347 lines (321 loc) · 14.4 KB
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'''
Module: SLIP - DRIP Landslide Detection Package
Program: DRIP.py
==========================================================================================
Authors: Justin Roberts-Pierel, Aakash Ahamed, Jessica Fayne, Amanda Rumsey, 2015
Organization: NASA DEVELOP
The DRIP and SLIP Landslide Detection Package, developed by the Himalaya Disasters Team at
Goddard Space Flight Center, was created to identify landslide events in Nepal in a near real-time capacity.
This product will be used to develop accurate landslide prediction models, and will be used for future disaster management.
See the README associated with this program for more information.
==========================================================================================
'''
import os,urllib,csv,time,datetime,h5py,csv,sys,gdal,ogr,,osr,smtplib,socket,glob,copy
from urllib.request import urlretrieve
from urllib.parse import urlparse
from numpy import loadtxt
import numpy as np
from osgeo import gdal, gdalconst
from email.mime.multipart import MIMEMultipart
from email.mime.base import MIMEBase
from email.mime.text import MIMEText
from email.mime.image import MIMEImage
from email import encoders
from natsort import natsorted,ns
#returns the current directory as a string
def getCurrentDirectory():
return(os.path.dirname(os.path.realpath(__file__)))
#reads a text file "filename", and returns the contents
def readStrTextFile(filename):
text_file=open(filename,'r')
fileString=text_file.read()
text_file.close()
return(fileString)
#returns current time as a timestamp
def getTimeStamp():
return(time.strftime("%Y%m%d-%H%M%S"))
#creates a GPM download URL...Should be updated to use ftplib
def getDownloadURL(downloadString):
return('ftp://'+userString+'@jsimpson.pps.eosdis.nasa.gov/NRTPUB/imerg/early/' + downloadString + '/')
#gets the most recent file list
def getFileList(timeString,downloadTime):
urlretrieve(getDownloadURL(downloadTime),os.path.join(getCurrentDirectory(),'txtFiles',timeString + '.txt'))
#converts an array to a raster
def array2raster(newRasterFilename,rasterOrigin,pixelWidth,pixelHeight,array,dataType):
array=array.astype(float)
cols=array.shape[1]
rows=array.shape[0]
originX=rasterOrigin[0]
originY=rasterOrigin[1]
driver=gdal.GetDriverByName('GTiff')
outRaster = driver.Create(newRasterFilename, cols, rows, 1, dataType)
outRaster.SetGeoTransform((originX, pixelWidth, 0, originY, 0, pixelHeight))
outband = outRaster.GetRasterBand(1)
outband.WriteArray(array)
outRasterSRS = osr.SpatialReference()
outRasterSRS.ImportFromEPSG(4326)#EPSG code for Nepal only
outRaster.SetProjection(outRasterSRS.ExportToWkt())
outband.FlushCache()
#gets the lat/lon extent of a raster
def getRasterExtent(input):
geoTransform = input.GetGeoTransform()
minx = geoTransform[0]
maxy = geoTransform[3]
maxx = minx + geoTransform[1]*input.RasterXSize
miny = maxy + geoTransform[5]*input.RasterYSize
pixelX=geoTransform[1]
pixelY=geoTransform[5]
extent=[minx,maxx,miny,maxy,pixelX,pixelY]
return(extent)
#downloads most recent data via getFileList. It will download multiple new files if they exist, or just the most recent, or none if up to date
def downloadMostRecent():
getFileList(timeStr,time.strftime('%Y%m'))
fileList = loadtxt(os.path.join(getCurrentDirectory(),'txtFiles',timeStr + '.txt'),'str',',')
date=-1
newFileName=str(fileList[-1][8][-(fileNameLength+1):-1])
lastFileName = readStrTextFile(os.path.join(getCurrentDirectory(),'mostRecent.txt'))
if lastFileName == newFileName:
print('No new file to analyze. Quitting...')
sys.exit()
fileName=copy.deepcopy(newFileName)
tempTime=copy.deepcopy(timeStr)[0:6]
numFiles=0
while lastFileName != fileName:
date-=1
fileName=str(fileList[date][8][-(fileNameLength+1):-1])
if np.abs(date)>=len(fileList):
numFiles=numFiles-date-1
date=0
month=str(int(tempTime[4:6])-1)
if month==0:
month=12
year=str(int(tempTime[0:4]-1))
else:
if len(month)==1:
month='0'+month
year=tempTime[0:4]
getFileList(year+month,year+month)
fileList = loadtxt(os.path.join(getCurrentDirectory(),'txtFiles',year+month + '.txt'),'str',',')
tempTime=year+month
numFiles=numFiles-date-1
print('Found ',numFiles,' new files!')
fileName=copy.deepcopy(newFileName)
date=-1
percent=0
sys.stdout.write("\rDownloading...%d%%" % percent)
sys.stdout.flush()
fileList = loadtxt(os.path.join(getCurrentDirectory(),'txtFiles',timeStr + '.txt'),'str',',')
downloadString=time.strftime('%Y%m')
fileNum=1
#loops through the file list and downloads all new files
while lastFileName != fileName:
try:
urlretrieve(getDownloadURL(downloadString)+fileName, os.path.join(getCurrentDirectory(),'h5Files',fileName + '.h5'))
except:
print('\nError downloading file: ',fileName)
sys.exit()
percent=((fileNum/numFiles))*100
sys.stdout.write("\rDownloading...%d%%" % percent)
sys.stdout.flush()
date-=1
if np.abs(date)>=len(fileList):
date=-1
month=str(int(timeStr[4:6])-1)
if month==0:
month=12
year=str(int(timeStr[0:4]-1))
else:
if len(month)==1:
month='0' + month
year=timeStr[0:4]
getFileList(year+month,year+month)
fileList = loadtxt(os.path.join(getCurrentDirectory(),'txtFiles',year+month + '.txt'),'str',',')
downloadString=year+month
fileName=str(fileList[date][8][-(fileNameLength+1):-1])
fileNum+=1
text_file=open(os.path.join(getCurrentDirectory(),'mostRecent.txt'),'w')
text_file.write(newFileName)
text_file.close()
txtFiles=glob.glob(os.path.join(getCurrentDirectory(),'txtFiles','*.txt'))
for file in txtFiles:
os.remove(file)
return(numFiles)
#reads an HDF5 file and saves the relevant data as text files, then sums data
def readHDF5Variables(numFiles):
h5Files=sorted(glob.glob(os.path.join(getCurrentDirectory(),'h5Files','*.h5')))
gpmhdf = h5py.File(h5Files[0], 'r')
#these lat/lon values are specific to Nepal, they are the rows/columns corresponding to the study region
lat = gpmhdf['Grid']['lat'][1163:1205]
lon = gpmhdf['Grid']['lon'][2600:2683]
max_lat=lat[lat.shape[0]-1]
min_lat=lat[0]
max_lon=lon[lon.shape[0]-1]
min_lon=lon[0]
ysize=(max_lat-min_lat)/lat.shape[0]
xsize=(max_lon-min_lon)/lon.shape[0]
gpmhdf.close()
extent=getRasterExtent(gdal.Open(os.path.join(getCurrentDirectory(),'referenceFile','reference.TIF'),gdalconst.GA_ReadOnly))
extent[4]=xsize
extent[5]=-ysize
print('')
percent=0
sys.stdout.write("\rProcessing...%d%%" % percent)
sys.stdout.flush()
fileNum=1
for file in h5Files:
gpmhdf = h5py.File(file, 'r')
precipitationCal = gpmhdf['Grid']['precipitationCal'][2600:2683,1163:1205]
precipitationCal=precipitationCal/2
gpmhdf.close()
np.savetxt(os.path.join(getCurrentDirectory(),'Sum24','Files',file[-(fileNameLength+3):-3] + '.txt'),precipitationCal,delimiter=',')
np.savetxt(os.path.join(getCurrentDirectory(),'Sum48','Files',file[-(fileNameLength+3):-3] + '.txt'),precipitationCal,delimiter=',')
np.savetxt(os.path.join(getCurrentDirectory(),'Sum72','Files',file[-(fileNameLength+3):-3] + '.txt'),precipitationCal,delimiter=',')
np.savetxt(os.path.join(getCurrentDirectory(),'max16','Files',file[-(fileNameLength+3):-3] + '.txt'),precipitationCal,delimiter=',')
try:
dailySum(precipitationCal,file,extent)
except:
np.savetxt(os.path.join(getCurrentDirectory(),'DailySums',timeStr[-15:-7] + '.txt'),precipitationCal,delimiter=',')
#the summing functions
sum24(precipitationCal,extent)
sum48(precipitationCal,extent)
sum72(precipitationCal,extent)
max16(precipitationCal,extent)
os.remove(os.path.join(getCurrentDirectory(),'h5Files',file))
percent=(fileNum/numFiles)*100
sys.stdout.write("\rProcessing...%d%%" % percent)
sys.stdout.flush()
fileNum+=1
#finds one metric, a max value in the past 16 days
def max16(newFile,extent):
historicFiles=sorted(glob.glob(os.path.join(getCurrentDirectory(),'max16','Files','*txt')))
os.remove(historicFiles[0])
#sums the past 24 hours of rainfall, sends an email if exceeds threshold
def sum24(newFile,extent):
currentSum=loadtxt(os.path.join(getCurrentDirectory(),'Sum24','sum24.txt'),dtype='float',delimiter=',')
historicFiles=sorted(glob.glob(os.path.join(getCurrentDirectory(),'Sum24','Files','*txt')))
lastFile=loadtxt(os.path.join(getCurrentDirectory(),'Sum24','Files',historicFiles[0]),dtype='float',delimiter=',')
currentSum=currentSum-lastFile
currentSum=currentSum+newFile
np.savetxt(os.path.join(getCurrentDirectory(),'Sum24','sum24.txt'),currentSum,delimiter=',')
sumToSave=copy.deepcopy(currentSum)
rotatedSum = np.rot90(sumToSave)
tiffFiles=glob.glob(os.path.join(getCurrentDirectory(),'Sum24','Tiffs','*.TIF'))
if not tiffFiles:
lastTifNum='1'
else:
tiffFiles=natsorted(tiffFiles,alg=ns.IC)
lastTif=tiffFiles[-1]
lastTifNum=str(int(lastTif[lastTif.rfind('_')+1:lastTif.rfind('.')])+1)
array2raster(os.path.join(getCurrentDirectory(),'Sum24','Tiffs',timeStr[-11:-7]) + '_24HourSum_' + lastTifNum + '.TIF',[extent[0],extent[3]],extent[4],extent[5],rotatedSum,gdalconst.GDT_Float32)
while len(tiffFiles)>48:
os.remove(tiffFiles[0])
tiffFiles=natsorted(glob.glob(os.path.join(getCurrentDirectory(),'Sum24','Tiffs','*.TIF')),alg=ns.IC)
os.remove(historicFiles[0])
try:
sumMask = loadtxt(os.path.join(getCurrentDirectory(),'Sum24','sumMask.txt'),dtype='float',delimiter=',')
except:
sumMask=np.ones((currentSum.shape[0],currentSum.shape[1]))
newMask=copy.deepcopy(currentSum)
newMask[newMask<144]=1
newMask[newMask>=144]=0
maskChange=sumMask-newMask
sumMask[maskChange==-1]=1
sumMask=np.multiply(sumMask,currentSum)
if np.max(sumMask)>=144:
sumMask[sumMask<144]=1
sumMask[sumMask>=144]=0
tiffFiles=natsorted(glob.glob(os.path.join(getCurrentDirectory(),'Sum24','Tiffs','*.TIF')),alg=ns.IC)
sendEmail(tiffFiles[-1])
np.savetxt(os.path.join(getCurrentDirectory(),'Sum24','sumMask.txt'),sumMask,delimiter=',')
percentIncrease=pctChange(currentSum)
if np.max(percentIncrease) > 1000:
array2raster(os.path.join(getCurrentDirectory(),'DailySums','Tiffs',timeStr[-11:-7]) +'.TIF',[extent[0],extent[3]],extent[4],extent[5],percentIncrease,gdalconst.GDT_Float32)
#sums the past 48 hours of rainfall, sends an email if exceeds threshold
def sum48(newFile,extent):
currentSum=loadtxt(os.path.join(getCurrentDirectory(),'Sum48','sum48.txt'),dtype='float',delimiter=',')
historicFiles=sorted(glob.glob(os.path.join(getCurrentDirectory(),'Sum48','Files','*txt')))
lastFile=loadtxt(os.path.join(getCurrentDirectory(),'Sum48','Files',historicFiles[0]),dtype='float',delimiter=',')
currentSum=currentSum-lastFile
currentSum=currentSum+newFile
np.savetxt(os.path.join(getCurrentDirectory(),'Sum48','sum48.txt'),currentSum,delimiter=',')
rotatedSum = np.rot90(currentSum)
tiffFiles=glob.glob(os.path.join(getCurrentDirectory(),'Sum48','Tiffs','*.TIF'))
if not tiffFiles:
lastTifNum='1'
else:
tiffFiles=natsorted(tiffFiles,alg=ns.IC)
lastTif=tiffFiles[-1]
lastTifNum=str(int(lastTif[lastTif.rfind('_')+1:lastTif.rfind('.')])+1)
array2raster(os.path.join(getCurrentDirectory(),'Sum48','Tiffs',timeStr[-11:-7]) + '_48HourSum_' + lastTifNum + '.TIF',[extent[0],extent[3]],extent[4],extent[5],rotatedSum,gdalconst.GDT_Float32)
while len(tiffFiles)>48:
os.remove(tiffFiles[0])
tiffFiles=natsorted(glob.glob(os.path.join(getCurrentDirectory(),'Sum48','Tiffs','*.TIF')),alg=ns.IC)
os.remove(historicFiles[0])
#sums the past 72 hours of rainfall, sends an email if exceeds threshold
def sum72(newFile,extent):
currentSum=loadtxt(os.path.join(getCurrentDirectory(),'Sum72','sum72.txt'),dtype='float',delimiter=',')
historicFiles=sorted(glob.glob(os.path.join(getCurrentDirectory(),'Sum72','Files','*txt')))
lastFile=loadtxt(os.path.join(getCurrentDirectory(),'Sum72','Files',historicFiles[0]),dtype='float',delimiter=',')
currentSum=currentSum-lastFile
currentSum=currentSum+newFile
np.savetxt(os.path.join(getCurrentDirectory(),'Sum72','sum72.txt'),currentSum,delimiter=',')
rotatedSum = np.rot90(currentSum)
tiffFiles=glob.glob(os.path.join(getCurrentDirectory(),'Sum72','Tiffs','*.TIF'))
if not tiffFiles:
lastTifNum='1'
else:
tiffFiles=natsorted(tiffFiles,alg=ns.IC)
lastTif=tiffFiles[-1]
lastTifNum=str(int(lastTif[lastTif.rfind('_')+1:lastTif.rfind('.')])+1)
array2raster(os.path.join(getCurrentDirectory(),'Sum72','Tiffs',timeStr[-11:-7]) + '_72HourSum_' + lastTifNum + '.TIF',[extent[0],extent[3]],extent[4],extent[5],rotatedSum,gdalconst.GDT_Float32)
while len(tiffFiles)>48:
os.remove(tiffFiles[0])
tiffFiles=natsorted(glob.glob(os.path.join(getCurrentDirectory(),'Sum72','Tiffs','*.TIF')),alg=ns.IC)
os.remove(historicFiles[0])
#sends an e-mail containing "attachment", currently to the authors
def sendEmail(attachment):
gmail_user = "YOUR EMAIL"
gmail_pwd = "YOUR Password"
to=['jpierel14@gmail.com','ahamednasa@gmail.com']
subject = 'DRIP Alert'
text='Current precipitation levels are significantly higher than historical averages (see attachment)'
msg = MIMEMultipart()
msg['From'] = gmail_user
msg['To'] = ", ".join(to)
msg['Subject'] = subject
msg.attach(MIMEText(text))
img = MIMEImage(open(attachment, 'rb').read())
img.add_header('Content-Disposition', 'attachment', filename=attachment[attachment.rfind('/'):-6] + '.TIF')
msg.attach(img)
mailServer = smtplib.SMTP("smtp.gmail.com", 587)
mailServer.ehlo()
mailServer.starttls()
mailServer.ehlo()
mailServer.login(gmail_user, gmail_pwd)
mailServer.sendmail(gmail_user, to, msg.as_string())
mailServer.close()
#creates a file containing a daily sum
def dailySum(newData,fileName,extent):
todayData = loadtxt(os.path.join(getCurrentDirectory(),'DailySums',timeStr[-15:-7]),'float',delimiter =',')
summedData=todayData + newData
if '-S233000-' in fileName:
rotatedSum = np.rot90(summedData)
array2raster(os.path.join(getCurrentDirectory(),'DailySums','Tiffs',timeStr[-11:-7]) + '.TIF',[extent[0],extent[3]],extent[4],extent[5],rotatedSum,gdalconst.GDT_Float32)
np.savetxt(os.path.join(getCurrentDirectory(),'DailySums',timeStr[-15:-7] + '.txt'),summedData,delimiter=',')
#calculates a percent change between an array and a reference threshold array
def pctChange(newData):
thresholds=loadtxt(os.path.join(getCurrentDirectory(),'Annual_Thresholds.txt'),'float',delimiter='\t')
P_change=((np.subtract(newData,thresholds))/thresholds)*100
return(P_change)
#main, calls all other functions
def main():
global timeStr
timeStr=getTimeStamp()
global fileNameLength
fileNameLength=len(readStrTextFile('mostRecent.txt'))
global userString
userString='anonymous:anonymous'#change this to be your email:email, once registered with GPM FTP site
numNewFiles=downloadMostRecent()
readHDF5Variables(numNewFiles)
if __name__ == "__main__":
main()