def produceTotal(obs):
"""
Set up rios to apply images
"""
controls = applier.ApplierControls()
controls.setReferenceImage(obs.inputImages[0])
controls.setOutputDriverName('HFA')
infiles = applier.FilenameAssociations()
infiles.images = obs.inputImages
outfiles = applier.FilenameAssociations()
if obs.stage == 'dix':
if obs.fraction == 'bare':
outStage = 'djl'
elif obs.fraction == 'green':
outStage = 'djm'
elif obs.fraction == 'dry':
outStage = 'djn'
outfiles.image = qvf.changestage(qvf.changedate(os.path.basename(obs.inputImages[0]),obs.era),outStage)
obs.outfile = outfiles.image
otherargs = applier.OtherInputs()
imginfo = fileinfo.ImageInfo(obs.inputImages[0])
otherargs.coverNull = imginfo.nodataval[0]
controls.setStatsIgnore(otherargs.coverNull)
applier.apply(model, infiles, outfiles, otherargs, controls=controls)
addHistory(obs)
def recallList(sceneListTemp, recallStage):
"""
Define and recall landsat images with stage
"""
recallList = []
for scene in sceneListTemp:
scene = qvf.changestage(scene, recallStage)
if not os.path.exists(scene) and qv.existsonfilestore(scene):
recallList.append(scene)
qv.recallToHere(recallList)
def getStatVal(imageFile,longitude,latitude,winsize,statistic,site):
"""
Caculates the statistics on the pixels in the window array
"""
band1,band2,band3,band4,band5,band6,count = 'None','None','None','None','None','None','None'
if imageFile != 'None' and imageFile != None:
imageFile=qvf.changestage(imageFile,'tmp')
temp = '%s_%s_%spix.tif' % (imageFile.split('.')[0],site.strip(),winsize)
if not os.path.exists(temp):
subsetRaster = getWindow(imageFile,longitude,latitude,winsize,site)
else:
subsetRaster = temp
try:
imgInfo = gdalcommon.info(subsetRaster)
handle = gdal.Open(subsetRaster)
for band in [1,2,3,4,5,6]:
if handle != None:
bandHandle = handle.GetRasterBand(band)
bandArray = bandHandle.ReadAsArray()
maskedBand = ma.masked_values(bandArray, 0)
count = ma.count(maskedBand)
if statistic == 'mean': statVal = maskedBand.mean()
elif statistic == 'std': statVal = maskedBand.std()
else:
statVal = None
if band == 1:
band1 = statVal
elif band == 2:
band2 = statVal
elif band == 3:
band3 = statVal
elif band == 4:
band4 = statVal
elif band == 5:
band5 = statVal
elif band == 6:
band6 = statVal
except:
pass
return band1, band2, band3, band4, band5, band6, count
def applyMasks(processedList):
"""
Do masking of output - create generic model to be used for all seasonal products.
Uses cloud and shadow masks to mask image. Uses RSC derived masks if available
and fmask if not.
"""
cloudList = []
shadowList = []
sceneList =[]
maskImageList = []
processedListClipped = []
for scene in processedList:
processedListClipped.append(qvf.changestage(scene, 'tmp'))
if not os.path.exists(qvf.changestage(scene, 'tmp')):
fMaskCloudImage = qvf.changestage(scene, 'dgr')
fMaskShadowImage = qvf.changestage(scene, 'dgs')
if qv.existsonfilestore(fMaskCloudImage):
cloudMaskImage = fMaskCloudImage
if qv.existsonfilestore(fMaskShadowImage):
shadowMaskImage = fMaskShadowImage
if qv.existsonfilestore(cloudMaskImage) and qv.existsonfilestore(shadowMaskImage) and qv.existsonfilestore(scene):
cloudList.append(cloudMaskImage)
shadowList.append(shadowMaskImage)
sceneList.append(scene)
maskImageList.append([scene,cloudMaskImage,shadowMaskImage])
if len(maskImageList)!=0:
recallList(cloudList, qvf.stage(cloudList[0]))
recallList(shadowList, qvf.stage(shadowList[0]))
recallList(sceneList, qvf.stage(sceneList[0]))
print 'Applying masks...'
controls = applier.ApplierControls()
controls.setStatsIgnore(0)
for (image1,image2,image3) in maskImageList:
tmpscene = qvf.changestage(image1, 'tmp')
print tmpscene
if not os.path.exists(tmpscene) and os.path.exists(image1) and os.path.exists(image2):
infiles = applier.FilenameAssociations()
infiles.image1 = image1
infiles.image2 = image2
infiles.image3 = image3
outfiles = applier.FilenameAssociations()
outfiles.outimage = tmpscene
if not os.path.exists(outfiles.outimage):
applier.apply(createMaskedImage, infiles, outfiles, controls=controls)
if os.path.exists(outfiles.outimage):
os.remove(image1)
os.remove(image2)
os.remove(image3)
return processedListClipped
def searchDatabaseScenes(pointDict,timeLag,defStage,winsize):
"""
Search database to find scenes which intersect field data points and were acquired
within specified number of days of field work
"""
keys = pointDict.keys()
for key in keys:
pointDict[key].image[1] = ImageDict()
pointDict[key].image[2] = ImageDict()
pointDict[key].image[3] = ImageDict()
pointDict[key].image[4] = ImageDict()
pointDict[key].image[5] = ImageDict()
pointDict[key].image[6] = ImageDict()
pointDict[key].image[7] = ImageDict()
pointDict[key].image[8] = ImageDict()
for stage in ['d%s' % defStage]:
if stage == 'd%s' % defStage:
print defStage
recallStage = 'd%s' % defStage
data_source = 'usgs'
for key in keys:
fieldDate = pointDict[key].obs_time.split(' ')[0]
fieldDate = fieldDate.replace('-','')
fieldDate = '%s-%s-%s' % (fieldDate[:4],fieldDate[4:6],fieldDate[6:])
pointDict[key].obs_time = fieldDate
con = metadb.connect(api=metadb.DB_API)
cursor = con.cursor()
query = """
SELECT abs(cast('%s' as date) - f.cal_date),SLATSFilename(f.sat_type,f.scene_date)
FROM FindFootprintsByPoint(%s, %s) as f, landsat_list
WHERE landsat_list.scene_date = f.scene_date
AND abs(cast('%s' as date) - f.cal_date) < %s
AND landsat_list.product = 're'
AND data_source ='%s'
""" % (fieldDate,pointDict[key].longitude,pointDict[key].latitude,fieldDate,timeLag,data_source)
try:
cursor.execute(query)
results = cursor.fetchall()
results.sort()
index=[1,2,3,4,5,6,7,8]
if len(results) > 0:
for i in index:
try:
result = results[i-1]
image = qvf.changestage(result[1], '%s' % stage)
if qv.existsonfilestore(image) and pointDict[key].image[i].imageName is None:
pointDict[key].image[i].imageName = image
pointDict[key].image[i].timeLag = result[0]
pointDict[key].image[i].tmp3pix = qvf.changestage('%s_%s_%spix.tif' % (image.split('.')[0],pointDict[key].site.strip(),winsize),'tmp')
else:
pointDict[key].image[i].imageName = 'None'
pointDict[key].image[i].timeLag = 'None'
pointDict[key].image[i].tmp3pix = 'None'
except IndexError:
pointDict[key].image[i].imageName = 'None'
pointDict[key].image[i].timeLag = 'None'
pointDict[key].image[i].tmp3pix = 'None'
image='None'
elif len(results) == 0:
image = 'None'
print pointDict[key].site,fieldDate,pointDict[key].longitude,pointDict[key].latitude
else:
print 'Really bad problem.'
except:
print 'failed', query, pointDict[key].site
return pointDict
