Performance of the interactive procedures for daytime detection of dense clouds in the MTI pipeline

Performanceoftheinteractivepro ceduresfordaytimedetectionofdensecloudsintheMTIpip elineCharlesA.Rohde,Karen LewisHirsch,AnthonyB.DavisLosAlamos National Lab oratorySpaceand Remote SensingSciencesGroup (NIS-2)P.O.Box1663 (Mail StopC-323)LosAlamos, NM,87545,USAABSTRACTPixel-scaleclouddetectionreliesonthesimplefactthatdense-enoughcloudsaregenerallybrighter,whiter,andcolder than the underlying surface.These plain-language statements are readily translated into threshold op erationsin the multisp ectral subspaces, thus providing a reasonable premise for searching data cub es for cloud signatures.Tosupplement this sp ectral input (VIS, NIR, and TIR channels), we remark that cloud tops are generally ab ove mostofthewater vap or inatmosphere column.Anextra thresholdinMTIap orpro ductcan thereforebeapplied.Thishelpsconsiderablyincaseswhereoneofthedefaultcloudsignaturesb ecomesambiguous.Theresulting cloud mask is however still sensitive to the thresholds in brightness, whiteness, temp erature, and columnwater content, esp ecially since wealso want to ag low-level clouds that are not-so-dense.Clouds are also generallyspatially large compared to pixel size.This implies that simple spatial morphological lterscan be usetoremovefalsepositives andfor expansion ofthecloudmask.Ap ositiveisindeedpreferable toa missinviewofMTI's mission in supp ort of nuclear non-proliferation; non-lo cal cloud radiative e ects can otherwise bias retrievalsin adjacent cloud-free areas.Therefore we use a data analyst to ensure builtin qualitycontrol for MTI cloud masks.Whenlo okingforlow-levelclouds,theanalystinteractswithaGUIcontaininghistograms,customizedRGBrendering of the input data, and an RGB diagnostic cloud mask for quickevaluation of all threshold values.WeuseMTI data to do cument the p erformance and analyst-sensitivity to this pro cedure.Keywords:MTI, Multisp ectral Imaging, Cloud Detection1.INTRODUCTIONThe Multisp ectral Thermal Imager (MTI) Satellite1is a state-of-the-art multisp ectral imaging platform.Its develop-ment and use are joint pro jects b etween Los Alamos National Lab oratory, Sandia National Lab oratory and SavannahRiver Technology Center.Cloud detection is an imp ortant factor in b oth MTI's primary non-proliferation mission ofaccurate surface temp erature retrieval and its secondary environmental studies mission.In the former it is imp ortanttoremovetheab errations cloudspro duceinorderachieve desiredsurfacetemp eratureaccuracy.Inthelattermission of environmental study,clouds b ecomeimp ortantintheirown right,primarily asagents of climatologicalchange.In this case a general cloud mask is useful for later classi cation schemes.MTI has 15 sp ectral bands ranging from visible wavelengths(450 nm) to longwe infrared (10m, Fig.1).2Thisselection of bands allows for a simple translation of a cloud's general characteristics into sp ectral band op erations.Cloudsare(generally):brightatvisiblewavelengths,evenlyreectivemanyelengthsfromtonear-infrared, higher in the atmosphere than most image features, and hence, colder and drier than most image features.Theselectionofathresholdonvisibleandlongwveinfraredbandcomesdirectlyfromthe rsttwocloudcharacteristics.While the creation of NVDI and CIBR like band ratios can serve as measures of the whiteness anddryness conditions.Another general characteristic of a dense cloud is a large spatial extent.There are several typ esof spatial ltering that e ectively sort large and small features.Wecho ose to implement a morphological op ening ofvariable size in order to remoe image residues of small size that pass through the sp ectral threshold ltering.We will b e discussing how these ideas have b een implementedinto the creation of MTI cloud masks.Both thealgorithm and the analyst GUI are individually describ ed.Finally a comparison of analyst resp onse is given.TheseSend corresp ondence to carohde@lanl.gov, Tel:+1-505-665-5481; Fax:+1-505-667-9208