Control Extension and Orthorectification Procedures for Compiling Vegetation Databases of National Parks in the Southeastern United States

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1 Contol Extension and Othoectification Pocedues fo Compiling Vegetation Databases of National Paks in the Southeasten United States Thomas R. Jodan Cente fo Remote Sensing and Mapping Science (CRMS) Depatment of Geogaphy, The Univesity of Geogia thens, G US tombob@uga.edu Commission IV, WG IV/6 KEYWORDS: vegetation mapping; softcopy photogammety; GIS; mountainous teain; national paks BSTRCT: Vegetation mapping of national pak units in the southeasten United States is being undetaken by the Cente fo Remote Sensing and Mapping Science at the Univesity of Geogia. Because of the unique chaacteistics of the individual paks, including size, elief, numbe of photos and availability of gound contol, diffeent appoaches ae employed fo conveting vegetation polygons intepeted fom lage-scale colo infaed aeial photogaphs and delineated on plastic ovelays into accuately geoefeenced GIS database layes. Using steamlined softcopy photogammety and aeotiangulation pocedues, it is possible to diffeentially ectify ovelays to compensate fo elief displacements and ceate detailed vegetation maps that confom to defined mapping standads. This pape discusses the issues of gound contol extension and othoectification of photo ovelays and descibes the pocedues employed in this poject fo building the vegetation GIS databases. INTRODUCTION The Cente fo Remote Sensing and Mapping Science (CRMS) at The Univesity of Geogia has been engaged fo seveal yeas in mapping vegetation communities in national paks in southeasten United States (Welch, et al., 2002). In this poject, vegetation polygons delineated on ovelays egisteed to lage-scale (1:12,000 to 1:16,000 scale) colo-infaed (CIR) aeial photogaphs ae conveted to digital fomat and integated into a GIS database. To maximize vegetation discimination, the aeial photogaphs ae acquied duing the autumn (leaf-on) season when the changing colos of the leaves povide additional indicatos fo species and vegetation community identification. It is citical that the polygons tansfeed fom ovelay to GIS database be accuate in tems of position, shape and size to ensue that analyses that depend on the inteaction of layeed data sets, such as fie fuel modelling and data visualization, can be pefomed with confidence (Madden, 2004). s many of these paks ae located in emote and ugged aeas whee conventional souces of gound contol ae lacking, steamlined aeotiangulation pocedues have been developed to extend the existing gound contol and pemit the poduction of othophotos and coected ovelays fo incopoation into the GIS database. STUDY RE ND METHODOLOGY The oveall poject aea encompasses much of the southeasten United States and includes U.S. National Pak units located in the states of Kentucky, Tennessee, Noth Caolina, South Caolina, Viginia and labama (Figue 1). The paks diffe geatly in size, location, elief and oigin. Some of the smalle ( ha) histoical battlefield paks and national home sites in the poject ae located in o nea uban aeas with little elief and ample oads, field boundaies and othe featues that can be used fo gound contol. In these cases, gound contol coodinates ae extacted fom U.S. Geological Suvey (USGS) Digital Othophoto Quate Quadangles (DOQQ) and simple polynomial techniques ae applied to ceate coected photos. Intepetation is then pefomed diectly on the ectified CIR photogaphs and the polygons tansfeed into the GIS. FODO labama STRI BLI MC Tennessee LIRI -85 Kent ucky BISO OBRI Geogia CUG GRSM West Viginia CRL COWP Viginia BLRI Noth Caolina NISI South Caolina GUCO Kilometes -85 Figue 1. U.S. National Pak units being mapped by the UG- CRMS. See Table 1 below fo pak name abbeviations. Many of the paks, howeve, ae set aside to potect natual aeas anging fom 80 to ove 2000 sq. km in size and equie a lage numbe of aeial photogaphs fo complete coveage (Table 1). In the moe emote aeas, a ecuing poblem is the lack of cultual featues suitable fo use as the gound contol equied to estitute the aeial photogaphs and associated ovelays. This issue is fequently exacebated by the pesence of extensive foest cove and high elief. The esult is that the locations and shapes of vegetation polygons intepeted fo N

2 Table 1: U.S. National Paks being mapped by the UG-CRMS bbeviation Pak Name Location Size (Ha) # Photos Photo Scale baham Lincoln National Histoic Site BLI Kentucky ,000 Big South Fok National Receation ea BISO Kentucky/Tennessee 50, ,000 Blue Ridge Pakway BLRI Noth Caolina/Viginia 37, ,000 Cal Sandbug Home National Histoic Site CRL Noth Caolina ,000 Cowpens National Battlefield COWP South Caolina ,000 Cumbeland Gap National Histoical Pak CUG Kentucky 8, ,000 Fot Donelson National Histoic Site FODO Tennessee ,000 Geat Smoky Mountains National Pak GRSM Tennessee/Noth Caolina 209,000 1,200 12,000 Guilfod Couthouse National Militay Pak GUCO Noth Caolina ,000 Little Rive Canyon National Peseve LIRI labama 5, ,000 Mammoth Cave National Pak MC Kentucky 21, ,000 Ninety-Six National Histoic Site NISI South Caolina ,000 Obed Wild and Scenic Rive OBRI Tennessee 2, ,000 Stones Rive National Battlefield STRI Kentucky ,000 these aeas tend to be moe highly influenced by geometic eos caused by impope ectification techniques o poo contol. full photogammetic solutio n and othoectification is equied in these instances. Contol Extension Extension and simplification of gound contol identification and aeotiangulation pocedues developed fo mapping Geat Smoky Mountains National Pak has damatically impoved the speed and accuacy with which aeial photogaphs and ovelays can be pepaed fo use in building the GIS database (Jodan, 2002). These methods pemit the use of non-taditional featues such as tee tops to be used fo gound contol. In addition, the pocedues can be undetaken by nonphotogammetists to achieve accuacies equied to meet the poject goals and deadlines that would be difficult unde nomal cicumstances. Using low cost softcopy photogammety tools povided by the DMS Softcopy 5.0 softwae package and standad aeotiangulation point distibution and numbeing pactises, pass points ae identified on scanned (42 µm) colo infaed aeial photogaphs (R-WEL, Inc., 2004). lthough well-defined cultual featues ae chosen as pass points wheneve possible, it is fequently the case that natual featues such as cones of cleaings o even tee tops must be employed when the tee canopy is extemely dense. Well-defined featues suitable fo use as gound contol points (GCPs) ae identified on USGS DOQQs and the scanned aeial photos. Thei X,Y Univesal Tansvese Mecato (UTM) planimetic coodinates ae measued diectly fom the DOQQ. Elevation values fo GCPs ae extacted fom USGS digital elevation models (DEMs) using a bilinea intepolation algoithm. In geneal, the accuacy of the GCP coodinates ecoveed fom these data sets is on the ode of ± 3-5 m in XY and ±4-7 m in Z. Photo coodinates ae oganized into flight line stips within DMS Softcopy 5.0 and automatically employed with the eosys 5.0 fo Windows aeotiangulation (T) package to compute map coodinates fo the pass points (Stevens, 2002). The pocess is quick and typical eos ae compaable in magnitude to the GCP coodinate eos. Expeience has shown that a peson familia with aeial photogaphs and the fundamental concepts of photogammety quickly can be tained to do poductive aeotiangulation wok with this system in just one o two days. This is a vast impovement on pevious T softwae which equied weeks of expeience and a stong photogammetic backgound to achieve adequate esults. Rectification of Ovelays Ovelays fist must be scanned and ectified to the map coodinate system befoe the vegetation polygons can be incopoated into the GIS database. It is difficult, howeve, to accuately tansfe gound and image coodinates diectly fom the aeial photogaphs to the ovelays using manual methods. Theefoe, the fiducial maks on the photos and scanned ovelays ae employed as egistation points. Image coodinates identified duing the T pocess ae tansfomed into the ovelay coodinate system and used with an appopiate ectification algoithm to ceate a coected ovelay that is in egiste with the undelying GIS database. The aste polygons ae conveted to vecto fo mat using R2V pogam fom ble Softwae, Inc. (Cambidge, Massachusetts, US) and impoted to ESRI cgis fo editing. In aeas of little elief, it is appopiate to apply simple polynomial coection techniques to ceate ectified photogaphs. Fo sma lle paks, these ectified photos ae tiled, ovelaid with coodinate gids and pinted on a high quality colo pinte fo use in the field. Intepetation is pefomed on ovelays egisteed to the had copy pints. The ovelays ae scanned and conveted to vecto fomat fo input to the GIS. Thee the polygons epesenting vegetation communities ae edited and assigned attibutes. The vegetation map of Guilfod Couthouse National Militay Pak was ceated in this manne (Figue 2). In the Guilfod Couthouse map poduct, the top potion in a ectified colo infaed aeial photogaph annotated with the pak bounday. In the bottom section of the poduct, the detailed vegetation map is pesented at the same scale and aea coveage as the aeial photogaph.

3 Figue 2. The vegetation map poduct o Guilfod Couthouse National Militay Pak.

4 Fo aeas of high elief such as Geat Smoky Mountains National Pak, Blue Ridge Pakway and Cumbeland Gap, the ovelays must be diffeentially ectified using a DEM to emove the effects of elief displacement, which at times can be quite significant (see Jodan, 2002). Impope coections can lead to majo difficulties in edge matching detail in the ovelap aeas of adjacent photogaphs along a flight line. The mountainous teain in Geat Smoky Mountains National Pak is the souce of majo elief displacements in the lage (1:12,000) scale aeial photogaphs. These elief effects geatly influence the appaent shapes of objects appeaing on adjacent photos as well as thei map positions and aeas. Thus, it is impotant that the polygons ae coected popely in shape and position to facilitate edge matching duing its incopoation into the GIS database. Fo example, a distinct aea appeaing on the aeial photogaphs in the Thundehead Mountain aea in the cental potion of the pak nea the ppalachian Tail occus on a steeply sloping mountainside. Elevation anges fom 1549 m in the lowe left cone of the image chip to 1214 m in the uppe ight a ange of 335 m ove a distance of about 600 m. When viewed on the thee ovelapping photogaphs, the aea appeas to be vastly diffeent sizes and shapes (Figue 3). Thus, mapping the aea fom each of the thee uncoected photos would potentially give diffeent esults. (a) (b) (c) Figue 3. The dak shadowed aea in the above image chips appeas to be vey diffeent in shape and size in these thee ovelapping photogaphs. The image chip (a) is fom the lowe ight cone of Photo 10063; b) nea the bottom cente of Photo 10062; and c) lowe left edge of Photo COMPRISON OF RECTIFICTION METHODS Thee ae a numbe of well-known image ectification methods available that can be used fo conveting vegetation ovelays in aste fomat to a vecto map base. Thee of these ae 1) polynomial (affine) based on a least-squaes fit to twodimensional GCPs; 2) single -photo pojective ectification efeenced to a mean datum elevation using a photogammetic solution and 3-D GCP coodinates; and 3) igoous diffeential coection (othocoection) using the photogammetic solution and a DEM (Novak, 1992; Welch and Jodan, 1996). To compae the effectiveness of the techniques, Photo fom Thundehead Mountain was ectified using each of the thee methods and then ovelaid with the completed vegetation map (Figues 4a-d). In the following examples, the dake shadowed aea and coesponding vegetation polygon indicated by the black aow in Figue 4a will be used to illustate the effects of the diffeent ectification methods. In the GIS database, this polygon has an aea of 5.97 ha (Table 2). fte aeotiangulation, 14 GCPs wee available fo Photo The affine tansfomation coefficients wee computed using the method of least squaes and esulted in an RMSE at the 14 GCPs of 106 pixels o 53 m. Most of this eo is due to elief displacements in the image. The aeial photogaph was then ectified using the polynomial method. The esulting image is appoximately in the coect geogaphical location but elief displacements have not been coected (Figue 4a). lthough the geneal coespondence between the vegetation polygons and the undelying image can be seen (point on the photo), it is clea that the oveall egistation accuacy is poo: the lines fom the vegetation coveage do not fit this ectified ai photo well and the shape distotions in the image ae clealy visible. In this case, the dak shadowed aea in the photo coesponding to the polygon (indicated by the aow) appeas to be longe, wide and in a diffeent position than the actual polygon in the vegetation coveage. In this figue, the polygon measued diectly fom the image has an aea of 8.34 ha, which is 2.4 ha (40 pe cent) geate than the actual aea of the polygon taken fom the GIS database. The oveall geomety of the image ectified using the single photo pojective tansfomation was not impoved significantly ove the polynomial ectification (Figue 4b). The photogammetic solution used to detemine the exteio oientation paametes, howeve, was excellent and yielded a RMSE of 3.34 pixels o 1.67 m at the 14 GCPs. The image was then ectified to an elevation datum value of 1380 m using a method which enfoces the scale at the datum and coects fo tilt but does not coect fo elief effects. Note that although the vegetation polygons geneally do not fit the image exactly, thee is a good fit in the aeas nea the 1380 m contou (shown in yellow) whee scaling is exact using the photogammetic solution. Oveall, the shapes of the taget polygon and othe featues ae still distoted and this solution is not satisfactoy. The aea of the sample polygon measued fom this image is 7.9 ha. Othocoection was pefomed on the photo using the same exteio oientation paametes computed above, but this time using the USGS DEM to povide elevation values to coect fo elief displacement at each pixel location (Figue 4c). Polygons in the completed vegetation coveage ae aligned pefectly with the undelying othophoto (see point ) and the shadowed aea indicated by the aow has an aea of 5.98 ha which coesponds well with the value in the GIS database fo the polygon. This high level of coespondence clealy demonstates the equiement fo a full softcopy photogammetic solution to ectifying vegetation ovelays. Finally, as a logic check, the vegetation vectos wee ovelaid on the USGS DOQQ (Figue 4d). It is eassuing to see that the GIS database ceated by othocoection techniques descibed in this pape lines up vey well with the USGS DOQQ poduct of the same aea.

5 Table 2. Results of diffeent image ectification methods on Photo (Geat Smoky Mountains: Thundehead Mountain Quadangle). Rectification Method # GCPs RMSE (pix) RMSE (m) ea of Taget Polygon (ha) Diffeence DOQQ (Refeence Image) N/ N/ N/ ffine Polynomial % Single Photo Pojective % Othocoection % Figue 4a. Potion of Photo esulting fom the polynomial ectification. Polygons in the completed vegetation coveage ae shown in geen. The sample polygon in the lowe ight potion of the photo (indicated by the black aow) has an aea of 5.97 ha accoding to the GIS database but 8.34 ha when measued diectly fom the image. Figue 4b. Photo ectified using the single photo pojective tansfomation. In this image, the contou epesenting the datum elevation of 1380 m employed fo the ectification is shown in yellow. Figue 4c. The digital othophoto ceated by fom Photo and the USGS DEM. Figue 4d. potion of the USGS DOQQ coesponding to the aea coveed by Photo

6 CONCLUSION Expeience with mapping vegetation communities in national paks units in the southeasten United States has led to the development of steamlined methods fo the extension of gound contol in emote aeas using softcopy photogammety and analytical aeotiangulation techniques. Basic gound contol extacted fom standad USGS digital othophoto quatequads (DOQQs) and digital elevation models (DEMs) povide the famewok with which a lage numbe of aeial photogaphs of aeas that have nealy continuous tee canopy cove can be contolled. lthough a numbe of ectification methods ae available, it was found that fo aeas of high elief, ovelays delineating vegetation polygons ae moe accuately tansfeed to a GIS database if they ae fist othocoected using photogammetic diffeential ectification techniques. This method impoves not only positional accuacy but also ease of editing and edge matching polygons fom adjacent photogaphs. In a test polygon, aea calculation was in eo by as much as 40% when simple polynomial ectification was pefomed on an aea with vey high elief. REFERENCES Jodan, T.R., Softcopy Photogammetic Techniques fo Mapping Mountainous Teain: Geat Smoky Mountains National Pak. Doctoal Dissetation, The Univesity of Geogia, thens, Geogia, 193 pp. Madden, M., Vegetation Modeling, nalysis and Visualization in U.S. National Paks and Histoical Sites. chives of the ISPRS 20 th Congess, Istanbul, Tukey, July 12-23, 2004 (in pess). Novak, K., Rectification of Digital Imagey, Photogammetic Engineeing and Remote Sensing, 58(3): R-WEL, Inc., DMS Softcopy 5.0 Uses Guide, thens, G, US, 191 pp. Stevens, M., eosys fo Windows Uses Manual, St. Paul, Minnesota, 207 pp. Welch, R. and T.R. Jodan, Using Scanned i Photogaphs. In Raste Imagey in Geogaphic Infomation Systems, (S. Moain and S.L. Baos, eds), Onwad Pess, pp Welch, R., M. Madden and T. Jodan, Photogammetic and GIS techniques fo the development of vegetation databases of mountainous aeas: Geat Smoky Mountains National Pak, ISPRS Jounal of Photogammety and Remote Sensing, 57(1-2):