Characteristics of MODIS BRDF shape and its relationship with land cover classes in Australia

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1 2th Interntionl Congress on Modelling nd imultion, Adelide, Austrli, 1 6 Decemer Chrcteristics of MODI BRDF shpe nd its reltionship with lnd cover clsses in Austrli F. Li, D. L. B. Jupp, L. Lymurner, P. Tn, A. McIntyre, M. Thnkppn, A. Lewis nd A. Held Ntionl Erth Oservtion Group, Geoscience Austrli, GPO Box 378, ACT, 261, Austrli CIRO Mrine nd Atmospheric Reserch, GPO Box 323, ACT 261, Austrli Emil: Fuqin.Li@g.gov.u Astrct: urfce Bidirectionl Reflectnce Distriution Function (BRDF) correction of spectrl dt (Li et l., 21) hs importnt pplictions to time series sed nlysis nd clssifiction. However, it hs een resonly proposed tht the BRDF informtion itself cn e used directly in the time series pplictions for lnd cover mpping nd climte chnge etc. To use such dt it is importnt to understnd the chrcteristics of BRDF nd its vrition over different cover nd climte conditions nd how they relte to well-understood vritions in spectrl dt in terms of the lnd cover chrcteristics nd chnges. Mny studies hve suggested tht BRDF is relted to the chrcteristics of lnd cover types (Brown de Colstoun nd Wlthll, 26 nd Jio et l., 211), especilly to vegettion structure (height nd cover) (Lovell nd Gretz, 22; Li et l., 213) nd lso climte ptterns. In this study, 1 yers of MODI BRDF dt sets (MOD43A1) from 22 to 211 hve een used to conduct n nlysis using time series dt for lnd cover dt products ville in Austrli. The dt hve een verged over individul yers to remove the sesonl ptterns nd vrition for resons which were outlined in Li et l. (213) nd re riefly discussed lter in this pper. Using the root men squre (RM, the distnce of the shpe function from Lmertin which is mesure of its symmetry) s BRDF shpe indictor, with the inter-nnul dt series the study hs found tht: The verge RM for three nds (red, ner-infrred nd shortwve infrred) for ech yer is well correlted with Normlized Difference Vegettion Index (NDVI) if it is seprted y lnd cover clsses. Correltion coefficients R2 rnge etween The RM lso vries significntly etween lnd cover clsses. Inter-nnul vrition of RM is smll for typicl vegettion clsses, especilly for clsses with high vegettion cover. If Normlized Difference RM is used (clled NDRM, clculted using red nd ner-infrred nds nd the sme formul s NDVI), its reltionship with NDVI is much stronger thn tht of RM. Correltion coefficients R2 re close to.9 for most of the yers. Ech lnd cover clss hs well defined NDRM ptterns. The seprtion is clerer thn for the RM ptterns. NDRM seems quite sensitive to climte chnge s indicted y NDVI ut the reltionship over the 1 yers in some clsses is different from the overll reltionship etween clsses verged over ll yers. In vegetted clsses, NDRM hs tended to increse in this wy much more sensitively fter the chnge from long dry period to wet yers, nd most prticulrly fter 29. The sensitivity hs pprently incresed with clss verge NDVI. From the ove, it hs een concluded tht: Both RM nd NDRM re le to differentite lnd cover clsses defined in the Austrlin Dynmic Lnd Cover Dtset (DLCD) series well. They oth correlte well with spectrl NDVI if the ptterns re seprted y lnd cover clsses nd verged t lest over individul yers (removing intr-nnul effects). Both RM nd NDRM cn potentilly e used s dditionl fetures to mp lnd cover. However, NDRM seems to e the more sensitive of the two. However, confident nd successful use of these fetures will need dditionl understnding of the sources of the vrition nd the informtion they ring compred with trditionl spectrl dt. In prticulr, further studies re needed to understnd the rising sensitivity in NDRM compred with NDVI s cover nd greenness increse nd the previously reported (Li t l., 213) questions concerning reltive phses of intr-nnul vrition in NDRM nd RM reltive to NDVI. Keywords: MODI, BRDF shpe function, lnd cover 193

2 1. INTRODUCTION The work reported here hd its se in the prcticl choice for BRDF prmeters to correct pre-modi Lndst dt over the Austrlin continent. tudies of the MODI BRDF prmeters etween 21 nd 211 (Li et l., 213) showed tht the inter-nnul vrition ws smll compred with intr-nnul (sesonl) vrition. Therefore, the defult models were derived y verging 46 weekly sets of prmeters over the 11 yers. The vrition etween vrious sets of lnd cover clsses ws lso much higher thn the inter-nnul vrition indicting tht sptil vrition in the model ws highly significnt leding to the choice of leving the definitions t the se 5m sptil resolution. However, while the BRDF shpe nd its ptterns re importnt prmeters for correcting the BRDF effect on stellite dt (Li et l., 21, 212), they lso provide potentil independent fetures to use for lnd cover mpping. As dditionl informtion, ndmeier nd Deering (1999), Brown de Colstoun nd Wlthll (26), Hill, et l. (28) nd Jio et l. (211) hve found tht BRDF shpe fetures cn improve clssifiction ccurcy for some sprse or open lnd cover clsses tht re dominted y surfce scttering. However, the wider utilistion of this opportunity hs een limited. To use such dt it is importnt to understnd the chrcteristics of BRDF nd its vrition over different cover nd climte conditions nd how they relte to well-understood vritions in spectrl dt in terms of the lnd cover chrcteristics nd chnges. Mny studies hve found tht there is strong reltionship etween BRDF shpe, vegettion structure nd lnd cover types. For exmple, Lovell nd Gretz (22) found tht there is strong reltionship etween vegettion structure nd BRDF prmeters in Austrli sed on POLriztion nd Directionlity of the Erth's Reflectnce (POLDER) dt. Li et l. (213) lso found tht strong correltion exists etween BRDF shpe indictors (RM/NDRM) nd vegettion structure using MODI BRDF dt. Following on from the work reported y Li et l. (213), in this study, further nlysis hs een conducted using 1-yer (22-211) MODI BRDF time series nd corresponding series of lnd cover mps developed in Austrli. The ojective is to estlish reltionships etween the spectrlly derived clsses in terms of BRDF nd to investigte whether MODI BRDF prmeters cn e used s dditionl informtion to improve lnd cover clssifiction ccurcy in Austrli. 2. DATA AND METHOD 2.1. Method Models for the surfce i-directionl reflectnce fctor, ρ s (θ, θ V, φ) cn e simplified nd expressed using kernel functions s summrised in convenient context y chf et l. (22) s: F F vol geo ρ ( θ, θv, ϕ) = F iso[1 + K vol + K geo ] = FisoB( θ, θv, ϕ, α 1, α 2 ) (1) F F iso iso In this expression, θ is solr zenith ngle nd θ V is view zenith ngle, φ is reltive zimuth etween the sun nd view directions. F iso is the weight for the isotropic contriution; F vol nd F geo re the weights for volume scttering nd geometricl opticl scttering contriutions; nd K vol nd K geo re volume scttering nd geometricl opticl scttering kernel functions. K vol nd K geo re functions of θ, θ V nd φ. B(θ,θ V,φ,α 1,α 2 ) is the BRDF shpe function where α 1 is defined s F vol /F iso nd α 2 is defined s F geo /F iso. The MODI BRDF product is time series of estimtes for the coefficients (F iso, F vol nd F geo ). everl BRDF shpe indictors hve een developed nd used for nlysis (Jio et l., 211). We re ssuming (sed on simple models) tht NDVI is sensitive to lef re index (LAI), ut not structure, nd BRDF shpe is sensitive to oth LAI nd structure. The shpe of the red nd ner-infrred BRDF is oserved to chnge differently with LAI nd structure so there is spectrl effect in BRDF shpe. Bsed on these ssumption, in this study, sttistic clled the root men squre (RM) is used s the BRDF shpe indictor to nlyse nisotropy following the work done y Li et l. (213). RM etween two shpe functions ( 1 nd 2 ) is clculted s: RM 4 π π π / 2 π / 2 = 2 cosθ sinθ cosθv sinθv 1 2 dθv dθ dϕ In this pper we hve used the single shpe sttistic defined y tking 1 s the trget BRDF shpe, B, s expressed in Eq. (1) nd the second ( 2 ) s the Lmertin shpe function (equl to 1.). RM then ecomes the distnce of the shpe function from Lmertin which is mesure of its symmetry. 1/ 2 (2) 194

3 To enhnce the effect, n index (clled NDRM) which comines the red nd ner-infrred RM ws lso used. The clcultion of NDRM is similr to the NDVI, ut uses RM insted of surfce reflectnce nd is expressed s: RM NDRM = RM red red RM + RM nir nir (3) Where RM red nd RM nir re the RM sttistics for the red nd ner-infrred nds respectively MODI BRDF dt nd pre-processing The MODI BRDF group provides 5m MODI BRDF (MCD43A) model prmeters (F iso, F vol nd F geo ) t overlpping 8-dy weekly intervls sed on 7 spectrl nds. The dt selected for this study were from 22 to 211 (1 yers) for the Austrlin region nd ech yer hs 46 time periods. The product (chf et l., 22) is the result of fitting model to smples from 16 dys of tmosphericlly corrected MODI surfce reflectnce dt ut smpling t 8 dys. A comintion of the Ross Thick volume kernel nd the Lisprse Reciprocl (chf et l., 22) geometric kernel models is used to pproximte these dt. However, there is considerle extrneous sptil nd temporl vrition in these dt t their se resolution. It seems to e due to rnge of fctors, including mis-registrtion, limited ville smples in terms of numer nd distriution, shde nd occlusion effects in mountinous res, su-pixel cloud, BRDF vrince nd other residul effects. These seem to e mplified y instility in the model fitting which pprently cn occur even when the qulity flg is stisfctory. As result of these fctors, mny outliers occur in the dt tht need to e removed efore further nlysis cn e conducted. Mny, ut not ll of the effects cn e reduced y using only the est qulity dt s indicted in the MODI qulity flg metdt. These remin outliers re still need to e removed y sttisticl filtering. Tle 1. MODI nds used in this study MODI nd Bndwidth (nnometers) Bnd Bnd Bnd In this study, three MODI nds re used to clculte RM. They re MODI nd 1 (red), nd 2 (ner-infrred) nd nd 6 (shortwve infrred). To ensure gretest stility of the MODI BRDF dt, only the dt using informtion from oth Aqu nd Terr hve een used (i.e. dt processed since 22). Detils of the MODI nds used in this study nd their spectrl informtion re listed in Tle Lnd cover mps The time series of lnd cover mps for were provided y Geoscience Austrli. The first version of the se lnd cover mp (The Ntionl Dynmic Lnd Cover Dtset, DLCD) ws relesed in 211 (Lymurner, et l., 211). The products clssify Austrlin lnd cover into 33 ctegories, which conform to 27 Interntionl tndrds Orgniztion (IO) Lnd Cover tndrd ( ). They hve een sed on MODI 25m Enhnced Vegettion Index (EVI) time series dt. The lnd cover mps used in this study re the second version of the mps. It is n nnul lnd cover series nd is currently eing evluted. They comprise 1 yerly time series sed lnd cover mps. Ech mp is produced using dt from the preceding two-yer period with one-yer overlp etween mps. Three steps were used to generte the lnd cover mps. In the first step, noisy nd invlid dt points re removed from the time series. econdly, feture extrction lgorithm converts time series into set of 12 time series coefficients relted to ground phenomen such s verge greenness nd plnt phenology. In the lst step, clustering processes sed on tilored support vector clustering lgorithm re pplied to susets of the coefficients. The resultnt clusters then form the sis for further modeling process incorporting uxiliry dt to generte the finl DLCD. For further detils, see Lymurner et l. (211) nd Tn et l. (213). 3. REULT AND DICUION The F iso prmeters were extrcted nd the RM sttistics clculted for three nds using Eq. (2). The results were then verged for ech yer. Figure 1 plots RM (verge red, ner-infrred nd shortwve infrred nds) nd NDRM inter-nnul vrition for eight typicl lnd cover clsses from 22 to

4 Inter-nnul vrition of RM (Figure 1) is reltively smll, especilly for vegettion clsses with high cover. The sprse nd scttered vegettion clsses show more fluctution. For these clsses, ckground (e.g., grss, soil) chnge due to the sesonl climte vrition (minly nnul rinfll in Austrli) for ech different yer contriutes to the RM vrition (Roderick et l., 24). The NDRM provides different story. In generl NDRM lso hs little inter-nnul vrition in the first few yers, ut fter 27 nd prticulrly fter 29 it suddenly hs n incresing trend (Figure 1). The trend is not oserved y RM or NDVI. ince the climte ptterns shifted fter long dry to wet in Austrli over the sme period, it would seem possile tht NDRM is more sensitive to climte chnge effects in lnd cover. There hve certinly een significnt chnges in cover of grsses nd some shru growth in mny prts of Austrli in tht period. However, t this time it is not yet cler if these dt re displying it. The inter-nnul vrition ptterns of RM nd NDRM for the DLCD lnd cover clsses re similr to those of some older structurl vegettion structure clsses. Li et l. (213) found tht there ws strong correltion etween NDVI nd RM/NDRM if the RM nd NDRM ptterns were seprted y these vegettion structure clsses. Consequently, the sme nlysis hs een conducted in this study using the DLCD lnd RM x 1 ND RM x Yer Yer Tle 2. Correltion coefficients etween NDVI nd RM/NDRM for 1 individul yers. Where: RM/NDRM=+NDVI. R 2 is correltion coefficient. Yer RM NDRM Tree - Closed Tree - Open Tree - prse Tree - cttered hru-closed hru-open hru-sprse hru-scttered Tree - Closed Tree - Open Tree - prse Tree - cttered hru-closed hru-open hru-sprse hru-scttered Figure 1. Inter-nnul vrition for 8 typicl lnd cover clsses in Austrli for () RM nd () NDRM cover clsses. Additionl nlysis ws lso conducted for individul yers to see whether the reltionship lso hs inter-nnul vrition. Figure 2 provides xy plots for NDVI nd RM for the period for 33 lnd cover clsses in Austrli. The Figure shows tht the reltionship etween RM nd NDVI is stle lthough there is clerly independent informtion in the two vriles on se of generl correltion. The ptterns re similr in the two plots nd there is reltively smll internnul vrition during the 1-yer period. For further nlysis, the correltion coefficient hs een clculted for ech yer nd is listed in Tle 2. Tle 2 shows tht there is strong correltion etween RM nd NDVI. Although the R 2 R 2 R

5 chnged ech yer (rnging etween.5 nd.7), the intercept () nd slope () coefficients do not vry gret del for the 1-yer period. It seems tht RM is stle in regrd to inter-nnul vrition. ince Figure 1 suggests tht NDRM is quite sensitive to climte chnge nd hs stronger inter-nnul vrition compred with NDVI nd RM, the sme nlysis ws lso conducted for NDRM. The right hlf of Tle 2 shows the sttisticl results for NDVI vs NDRM. The results show tht the reltionships etween NDVI nd NDRM re much stronger thn those of NDVI nd RM. The correltion coefficients R 2 rnge etween.85 nd.92. Both intercept () nd slope () coefficients vry significntly etween the first 5 yers nd the lst five yers, prticulrly in 21 nd 211. Figure 3 provides the xy plot for NDVI nd NDRM. There re some negtive NDRM vlues, ll of which re from inlnd wter odies where NDRM is either negtive or very smll numer. It is possile tht NDRM could e used s n dditionl prmeter to improve wter ody mpping. Compred with Figures 3 nd 3, nd s indicted numericlly in Tle 2, NDRM increses significntly fter 27 nd oth the slope nd the intercept of the reltionship with NDVI etween clsses hs incresed over the lst 5 yers. RM x 1 RM x Figure 2. The reltionship etween NDVI nd RM for , seprted into erly nd lte s () nd () NDRM x NDRM x Figure 3. The reltionship etween NDVI nd NDRM for , seprted into erly nd lte s () nd () Compring Figure 3 with Figure 2, it seems tht there is strong clustering in Figure 3 when NDVI vlues re etween.15 to.25, ut this does not pper in Figure 2, nor in the other NDVI rnge in Figure 3. Ares of low NDVI re minly stle res with little vegettion such s interior nd semi-rid res. But higher NDVI res re likely to chnge much more - especilly in green grss ckground. NDRM is lso expected to 197

6 chnge with structure. Tht is the potentil difference of the NDRM reltionship of Tle 2. But so fr, we do not hve direct vlidtion nd it remins to e done. If RM nd NDRM re verged 23 over the full 1 yers, the overll reltionship etween RM/NDRM is otined s 1 shown in Figure 4 nd lst row of Tle 2. The Figure nd the tle show tht the overll reltionship 13 is persistent, with the R 2 eing.6252 nd.8868 for RM nd NDRM, respectively. The constnts () nd () re similr to those of the individul yers for 3 RM, ut for NDRM, () nd () re the verge of first 5 nd the lter five yers. They re oviously different from the lst five yers. The plot lso shows non-liner increse in sensitivity over NDVI s the cover of the clss increses. This is consistent with the results seen in Tle 2. RM/NDRM x Figure 4. XY plot for 1 yers verge of NDVI nd RM/NDRM 4. CONCLUION From the ove nlysis, we hve found tht BRDF spectrl shpe nisotropy (s expressed y RM nd NDRM) is well correlted with NDVI t yerly (inter-nnul) scle, nd BRDF shpe is significntly different etween lnd cover clsses suggesting it provides useful informtion for discriminting lnd covers. The correltion etween NDVI nd NDRM is stronger thn tht etween NDVI nd RM. NDRM hs lso significntly incresed fter 29 ut it is not yet confirmed tht the trend is relted functionlly to the lnd cover response to inter-nnul climte chnge. NDRM lso seems to e quite sensitive to wter odies nd could possily e used to distinguish their presence on the lnd surfce. NDRM s function of NDVI pprently chnges in sensitivity to chnging cover over time in vegettion clsses. However, this still needs to e independently relted to vegettion growth nd chnges in structure or dominnt vegettion types. This must occur if it is to e used with confidence for lnd cover mpping. In ddition, different ehviours of the sttistics t the sesonl or intr-nnul scle (s reported y Li et l., 213) re eing investigted. Intr-nnul spectrl dt (e.g. NDVI nd Aledo) disply sesonl cycles tht re well understood in terms of climte forcing of plnt growth, evportion nd wetting/drying phses. But t the present time, while the RM nd NDRM dt lso show sesonl reltionships they hve phse shifts tht lso need independent identifiction to e used confidently in sesonl monitoring. Our conclusions t this stge of the investigtion re: I. Both RM nd NDRM seprte different lnd cover clsses of the Austrlin DLCD series well. They lso oth correlte well with spectrl NDVI if the ptterns re seprted y lnd cover clsses nd verged t lest over individul yers (removing intr-nnul effects). II. Both RM nd NDRM cn potentilly e used s dditionl fetures to mp lnd cover. However, NDRM seems to e the more sensitive of the two. III. However, confident nd successful use of these fetures will need dditionl understnding of the sources of the vrition nd the informtion they ring compred with trditionl spectrl dt. In prticulr, further studies re needed to understnd the rising sensitivity in NDRM compred with NDVI s cover nd greenness increse in some vegetted clsses, nd the previously reported (Li t l., 213) questions concerning reltive phses of intr-nnul vrition in NDRM nd RM reltive to NDVI. ACKNOWLEDGMENT This pper is pulished with the permission of the CEO, Geoscience Austrli (GA) nd the permission of CIRO. Access to MODI BRDF dt hs een fcilitted y Edwrd King nd Mtt Pget t CIRO Mrine & Atmospheric Reserch (CMAR) who provided the MODI BRDF time series dt for Austrli on RM NDRM 198

7 n pproprite mp se. Geoscience Austrli provided series lnd cover mps. Ms Jenny Lovell of CIRO, Mr Joshu ixsmith nd Mr teven Curnow from GA reviewed the erly drft of pper. Anonymous reviewers nd editor provided mny constructive comments nd vlule suggestions tht significntly improved the pper. REFERENCE Brown de Colstoun, E.C nd Wlthll, C.L (26). Improving glol scle lnd cover clssifictions with multi-directionl POLDER dt nd decision tree clssifier. Remote ensing of Environment, 1: Hill, M.J., Averill, C., Jio, Z., chf, C.B. nd Armston, J.D. (28). Reltionship of MIR RPV prmeters nd MODI BRDF shpe indictors to surfce vegettion ptterns in n Austrlin tropicl svnnh. Cndin Journl of Remote ensing, 34, Jio, Z., Woodcock, C., chf, C.B., Tn, B., Liu, J., Go, F., trhler, A., Li, X. nd Wng, J. (211). Improving MODI lnd cover clssifiction y comining MODI spectrl nd ngulr signtures in Cndin orel forest, Cndin Journl of Remote ensing, 37 (2), 1-2. Li, F., Jupp, D.L.B., Reddy,., Lymurner, L., Mueller, N., Tn, P. nd Islm, A. (21). An evlution of the use of tmospheric nd BRDF correction to stndrdize Lndst dt. The IEEE Journl of elected Topics in Applied Erth Oservtions nd Remote ensing, 3, Li, F., Jupp, D.L.B., Thnkppn, M., Lymurner, L., Mueller, N., Lewis, A. nd Held, A. (212). A physicssed tmospheric nd BRDF correction for Lndst dt over mountinous terrin. Remote ensing of Environment, 124, Li, F., Jupp, D.L.B., Thnkppn, M., Pget, M, Lewis, A. nd Held, A. (213). The vriility of stellite derived surfce BRDF shpe over Austrli from IEEE Interntionl Geoscience nd Remote ensing ymposium, Melourne, Austrli. Lovell, J. L. nd Gretz, R.D. (22). Anlysis of POLDER-ADEO dt for the Austrlin continent: The reltionship etween BRDF nd vegettion structure. Interntionl Journl of Remote ensing, 23, Lymurner, L., Tn, P., Mueller, N., Thckwy, R., Lewis, A., Thnkppn, M., Rndll, L., Islm, A. nd enrth, U. (211). The Ntionl Dynmic Lnd Cover Dtset - Technicl report, Geoscience Austrli, Roderick, M.L., Nole, I.R. nd Cridlnd,.W. (1999). Estimting woody nd herceous vegettion cover from time series stellite oservtions. Glol Ecology nd Biogeogrphy, 8, ndmeier,. nd Deering, D.W. (1999). tructure nlysis nd clssifiction of orel forests using hyperspectrl BRDF dt from AA. Remote ensing of Environment, 69, chf, C., Go, F., trhler, A.H., Lucht, W., Li, X., Tsng, T., trugnell, N.C., Zhng, X., Jin, Y., Muller, J.P., Lewis, P., Brnsley, M., Hoson, P., Disney, M., Roerts, G., Dunderdle, M., Doll, C., d Entremont, R.P., Hu, B., Ling,., Privette, J.L. nd Roy, D. (22). First opertionl BRDF, ledo nd ndir reflectnce products from MODI. Remote ensing of Environment, 83, Tn, P., Lymurner, L., Mueller, M., Li, F., Thnkppn, M. nd Lewis, A. (213). Applying mchine lerning methods nd times series nlysis to crete ntionl dynmic lnd cover dtset for Austrli. IEEE Interntionl Geoscience nd Remote ensing ymposium, Melourne, Austrli. 199