MAPPING DETAILED DISTRIBUTION OF TREE CANOPIES BY HIGH-RESOLUTION SATELLITE IMAGES INTRODUCTION

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1 MAPPING DETAILED DISTRIBUTION OF TREE CANOPIES BY HIGH-RESOLUTION SATELLITE IMAGES Hideki Hashiba, Assistant Professor Nihon Univ., College of Sci. and Tech., Department of Civil. Engrg. Chiyoda-ku Tokyo JAPAN, Sotaro Tanaka, General Manager Toshiro Sugimura, Senior Research Scientist Remote Sensing Technology Center of Japan, Minato-ku Tokyo JAPAN, ABSTRACT Surveying the condition of individual trees and the plants growing densely in detail is important for the environmental conservation and the maintenance of vegetation and forest area. The authors have verified a possibility of vegetation investigation by high-resolution satellite image as IKONOS and Quickbird. Two-dimensional distribution of small-scale vegetation in Tokyo can be known from these satellite images. Digital Roof Model (DRM) to display the height of building s roof is developed from the image observed by the IKONOS satellite. This model enables us to give the position of tree canopy shape three dimensionally in a case of using the IKONOS image. A tree canopy map of the forest in a city park in the outline was studied from DRM used the IKONOS image three dimensionally. Capability of depiction of canopy pattern influenced by the difference of performance of two satellite images in the overcrowded tree region where the tree crown parts overlapped was investigated. The array configuration of the trees was extracted accurately for City Wildlife Park INTRODUCTION Surveying the canopy height of an independent tree or the crown heights of dense forest is important in assessing the natural environment. The exact ascertainment of the volume of trees and forests is especially desired in the assessment of a vegetation environment. Authors have already proposed the Digital Roof Model (DRM), which expresses the roof heights of buildings in urban areas, using high-resolution satellite images (H.Hashiba et al 2003a, 2003b, 2004b). This model has been shown to be capable of generating a three-dimensional ascertainment and rendering of buildings, derived only from image data observed by high-resolution satellite. Moreover, the possibility of a vegetation distribution investigation that uses high resolution multispectral image data, as observed by the high resolution satellite IKONOS, has also been suggested (T.Sugimura 2002, H.Hashiba et al 2000,2001). Recently, remote sensing has begun to be observed by satellite (Quickbird), where the ground resolution has a high-resolution, or more, performance of 2.4m~2.4m with multi-spectral (visible red, blue, green, and near-infrared), or 0.6m~0.6m with panchromatic. Using high-resolution, or more, satellite observation images for tree and vegetation investigation, an interpretation change detection from the past can be achieved (Hahsiba et al 2004a). In this study both the IKONOS image and the Quickbird high resolution satellite images were used, and the extraction of information on tree crown distribution of forest was attempted. DRM was applied to trees in city region to know the shape of the forest, and the height of the tree crown were plotted by 3D lines. A bird's-eye view of tree garden was made as a result, and situations of the tree canopy were displayed three dimensionally. In addition, the edge was emphasized by a filtering process for IKONOS and Quickbird satellite images with different ground resolution Separability of trees at overcrowded area is one target of this work.

2 MODEL FOR MAPPING THE SURFACE OF TREE CANOPY IN THREE DIMENTION BY USING IKONOS IMAGE DATA Satellite image and test site Panchromatic images were used as data observed stereoscopically by IKONOS satellite on March 10 and 13, of the year Two images were taken at an observation angle of approximately 10 from southeast and northwest respectively. The B/H ratio becomes about 0.4. The test area was Kitanomaru Park, which is located near the Imperial Palace. This area is a natural park in which trees and woods are maintained. The tree is afforested by a variety of levels of overcrowding (Figure 1, 2). Figure 1. Test area a) IKONOS image b) QuickBird Image Figure 2. IKONOS Image and QuickBird image of test area

3 Extraction Image of Tree and Vegetation Area Based on the multispectral images, a maximum likelihood classification method and an extraction method using the NDVIi value were combined to extract only the vegetation areas. A representative vegetation index was calculated from visible radiation red and near-infrared radiation observation data in multispectral images and designated as the Normalized Vegetation Index (NDVI). Here NDVIi was calculated by using equation (1). In addition, the K value was the scale parameter, which can change the scale width of the calculation results. In this study, examination was added with K=100. Parts showing positive values in the processed results were judged to be vegetation. NDVIi=[{DN Eh (IR)-DN Eh (VI-Red)}/{DN Eh (IR)+DN Eh (VI-Red)}] K (1) Here, DN Eh : Digital number of multispectral image enhanced to 1m 1m space resolution VI-Red: Visible radiation red IR: Near-infrared radiation Training data was sampled from image data in the area, and a maximum likelihood classification method was used to classify the land covering. For the classification process, statistic values in all four bands of the high-resolution multispectral image were used (visible radiation blue, green, red and near-infrared radiation). Unlike the conventional satellite image data, this is high-resolution, multi-spectral image data, which allows reading of various land covering types from the image and setting of many classification items. Artificial structures such as buildings especially tend to lend themselves to classification according to many items, such as roof types or colors. Thirteen categories were set for roofs, with consideration of materials and colors. Furthermore, since trees, bare land, asphalt, etc., can be distinguished by slight differences in spectral properties, depending on their position, several categories were set. The field was investigated for the training areas of all items to confirm the similarity between the setting item and the actual land covering. By superimposing 1) the results obtained from the ratio processing of spectral properties contained by the above pixels and 2) the results obtained from statistical characteristics, and by using the AND operation, only sections extracted as vegetation in both were re-extracted to be displayed as the vegetation area. Overlapping of Stereo Pair Image First, strict position matching was conducted for the stereo pair images. GCP (Ground Control Point) is a reference point on the street for which altitude is stated on a 1:10000 topographic map, and points with altitude of 23m-24m are used. Supposing the image coordinates of one of the stereo pair images to be (X, Y) and those of the other image to be (U, V), the affine conversion formula between these images is as shown in equation (2), and there is a shift of 2m (2 pixels) in the pixel direction and 1m (1 pixel) in the line direction at a point 10km (10000 pixels) away. Thus it is nearly equivalent to the parallel movement in localized areas such as this subject area. X= U V Y= U V (2) When strict position matching is completed, corresponding point coordinates for the identical ground objects are measured on the stereo pair images to determine the deviation (D) over the image based on the results. The obtained value is generated due to the effect of the building's height. Here, each image has been observed from satellite positions S1 and S2, as shown in Figure 2, and equation (3) can be obtained by applying the theorem of cosines to P 1 P H P 2. Here, h indicates the height from the reference surface to the tree crown top. In addition, the position of PH on the reference surface is unknown. h 2 =D 2 /(tan 2 i 1 +tan 2 i 2-2tani 1 *tani 2 *cosθ) (3) Principle of height measurement of building top from satellite positions S 1 and S 2 (i 1 and i 2 indicate the incident angle from each satellite position respectively, and θ indicates the difference in the azimuth angles of observation.

4 Automatic making of DRM (Digital Roof Model) for Tree region To find out if it is possible to automatically search the corresponding points between the two paired images, a window of a small area (11x11 pixels in size) was designed. The correlation coefficient for the pixels in each of the reference image and search image windows for judgment, and the point at which it was the largest, was decided as the point of correspondence. The distance between corresponding points represents distortion D, and altitude H can be calculated by using Equation (3). Based on the generated DRM and satellite images only for the vegetation areas, a three-dimensional birdseye view was created. Values automatically generated by DRM were used as data for height direction, and natural color images with 1m resolution generated by processing panchromatic and multispectral images were used as the images for rendering. TWO DIMETIONAL MAPPING OF TREE CANOPY DISTRIBUTION BY THE HIGH RESOLUTION MULTISPECTRAL IMAGE Outline Emphasis Filtering The image data used is a panchromatic image because it makes a comparative study of the effect of filtering observed by the Quickbird satellite on February 1, The observation wavelength band is from 0.45μm to 0.6m~0.6m in this image for the ground resolution, and 0.90μm. Moreover, the panchromatic image that had been observed as a comparison by the IKONOS satellite on March 10, 2000, was used. The outline of the trees in the IKONOS panchromatic image and the Quickbird panchromatic image were emphasized by a Prewitt Edge Detector filter in the area of Kitanomaru Park. By using these images, the extraction of shape and the numbers of the tree canopy on the image were examined in two cases. In the first case, the tree canopy had not come into contact with the tree canopy in the vicinity to become completely independent, and in the second case two or more trees were adjacent and some tree crowns were overlapped. Mapping of Tree Crown Distribution by Uuniting Shape Information and Color Information To display the distribution situations of tree canopies in two dimensional and more in detail, shape information and color information on the tree canopy were united. That is, the summation of Digital Number of the outline emphasis image and each band images was operated. And, the effect of the extraction of the tree canopy distribution was examined as a result by each the IKONOS image and the Quickbird image. The image data used to calculate are observed by IKONOS satellite on March 10, 2000 and observed by Quickbird satellite on February 1, Afterwards, the threshold was decided the calculation result of NDVIq value as extracting only the tree parts, and accordingly the only tree area was extracted from the summation of outline emphasis image and each band images. The calculation of the NDVIq value was calculated from the digital number of images that had been observed by the Quickbird satellite on February 1, The NDVIq value was examined to calculate by equation (4) as seen below. Here, the scale parameter was examined as K=300. NDVIq=[{DN Eh (IR)-DN Eh (VI-Red)}/{DN Eh (IR)+DN Eh (VI-Red)}] K (4) Here, DN Eh : Digital number of Multispectral image enhanced to ground resolution of Quickbird panchromatic image VI-Red: Visible radiation red IR: Near-infrared radiation RESULT IN TREE HIGHT DISTRIBUTION MAP FROM DRM BY IKONOS IMAGE. Figure 3 shows the created DRM image. Ranging of the height of the tree canopy in the tree part in the test area was displayed as shown in the figure. Moreover, the situation in which the trees in the test area were overcrowded was three-dimensionally understood by both display forms when the multispectral image was combined with the DRM image and also when only the DRM image was displayed. (Figure 3 and Figure 4). The altitude shown here is above the sea from the mean sea level of Tokyo Bay. The situation in which the top part of the tree ranged as shown in figure was reflected. Especially, the overcrowded situation of the tree woods was able to be understood

5 three-dimensionally. Moreover, the height distribution of the tree woods was able to be displayed in detail by seeing DRM level slice picture three-dimensionally. The possibility that information to presume the volume of the tree woods is obtained only from the high resolution satellite observation was able to be verified. This is thought to be an effective result for the biomass presumption of the tree woods. Altitude 50m Altitude 0m Figure 3. Altitude of trees top distribution by level slice DRM (Digital Roof Model) Image a) Extraction of vegetation area only in three dimensional Altitude0m Altitude 50m b) Display of level slice of DRM in three dimensional Figure 4. Display of ranging situations of the tree canopies in three dimensional by using DRM

6 RESULT IN TWO DIMENSIONAL DISTRIBUTION MAP OF TREE CANOPIES Outline Extraction Characteristic of Each Level of Overcrowding of Trees The filtering image of the test site by two kinds of high resolution satellite images is shown in Figures 5. Because the image of the Quickbird satellite became a high resolution as compared with the IKONOS satellite image, the outline of an individual tree is admitted to have been extracted more accurately. Moreover, a complex outline is a complicated situation for the IKONOS image to render, as in the places where the trees were overcrowded. However, it is thought that a plain structure is extracted a little by Quickbird. As for both the IKONOS and Quickbird satellites, the outline of the trees is plainly extracted for the independent tree, if not for the next tree coming in succession ( Figure Case 1 in 5C and 5D, and Figure 6b). However, both images get to the shadow part and the main body of the tree in the extraction of both outlines, and the judgment of the tree or the shadow part is difficult only in this filtering image. It has been extracted for the condition of overcrowding of several trees (Figure - 5C, in D(50m~50m area), and a local photograph (Figure 6a) like the mass of one tree that overlaps a complex outline structure of two that are adjacent is extracted in the IKONOS satellite image. In many cases, the outline of the tree is extracted by filtering, and the improvement of resolution has been effective because of a little shadow of the borderline where the tree canopy comes in succession in the Quickbird satellite image (Figure 7). a) IKONOS image b) QuickBird image Figure 5. c) Edge enhanced IKONOS image d) Edge enhanced QuickBird image (Panchromatic image) (Panchromatic image) Comparison between IKONOS and QuickBird in effect of separation of tree crowns by Edge enhanced panchromatic images

7 a) Ground photographs of Case 1. b) Ground photograph of Case 2. Figure 6. Ground photographs in Case1 and Case2 a) IKONOS image b) QuickBird image c) Edge enhanced IKONOS image d) Edge enhanced QuickBird image (Panchromatic image) (Panchromatic image) Figure 7. The separability of the tree crowns in over crowded tree area

8 Canopy Mapping by Uniting the Outline Emphasis Image and High Resolution Multispectral Image The distribution maps of tree canopy both for the IKONOS and the Quickbird image were shown in Figure 9. As for both images, the positions and the shape of the tree canopies are displayed in detail, as shown in the figure. Especially, it is understood that one tree effect of an outline emphasis has remarkably acted on one extraction display in the Quickbird image in the place where the trees were overcrowded. As mentioned above, the possibility was able to be verified that the tree canopy map can ascertain the situation of the tree distribution easily by uniting the outline emphasis image and multispectral image of the high resolution satellite image. Figure 8. Extraction area of Tree canopies calculated by NDVIq value (The parameter of this case is K=300, threshold value was judged that the tree between from the calculation result of NDVIq) swhite area: Tree canopies BBlack area: The other land covers a) Case of IKONOS image b) Case of Quickbird image Figure 9. Tree canopy distribution obtained from uniting of outline emphasis image and multispectral image

9 SUMMARY A DRM retrieved from high resolution satellite image data was applied to three-dimensional display of trees in a garden park, and a bird s-eye view of the scenery was created. This bird s-eye view can serve to environmental evaluation or to environmental design with focusing on tree distribution. Separability of individual trees at overcrowded tree cover was examined in two cases of high resolution satellite images taken by IKONOS and Quickbird, from two points of view, number of trees and the shape of trees. As a result, a shadow effect separating the overcrowded tree canopies rises by the improvement of spatial resolution from 1m~1m to 0.6m~0.6m at two sensor systems. A fused image of multispectral image and the outline emphasis image of tree crown has a function to show crowns separating individually. The greater spatial resolution makes the better separability of canopies as well. Detailed tree shape corresponding to various tree sizes of overcrowded area will be studied in future. An automatic counting the number of trees using multispectral image in which the tree crown outline is emphasized will be another subject. ACKNOWLEDGEMENT This research received the grant of the science research of the Ministry of Education, Science and Technology in JAPAN (Research No ). REFERENCES T.Sugimura, S.Tanaka, H.Hashiba, and K.Kameda (2002). Three dimensional measurement by using IKONOS image, RESTEC, Vol.49, pp.12-16, (in Janapanese). H.Hashiba, K.Kameda, S.Tanaka, T.Sugimura (2000). Possibility of Mapping Small Trees and Plants Distribution in Urban Area Using High Resolution Satellite Image. Journal of Map: Science of spatial representation, Japan Cartographers Association Vol.38, No.4, p H.Hashiba, K.Kameda, S.Tanaka, T.Sugimura (2001). Extraction of distribution for small-scale vegetation in urban area using high-resolution satellite data. Journal of Environmental Systems and Engineering, Japan Society of Civil Engineer, No.685/Ⅶ-20,pp (in Japanese). H.Hashiba, K.Kameda, S.Tanaka, T.Sugimura (2003a). Digital Roof Model (DRM) using High Resolution Satellite Image and Its Application for 3D Mapping of City Region. IEEE International Geoscience and Remote Sensing Society, IGARSS2003, Vol.III: pp H.Hashiba, K.Kameda, S.Tanaka, T.Sugimura (2003b). An Application of Digital Roof Model (DRM) for Height Measurement of Trees.IEEE, International Geoscience and Remote Sensing Society, IGARSS2003, Vol. IV: pp H.Hashiba, T.Sugimura, S.Tanaka (2004a). Evaluation of Small-scale Vegetation in City Region from Highresolution Satellite Images with Different Ground Resolution. IEEE, International Geoscience and Remote Sensing Society, IGARSS2003, Vol. V: pp H.Hashiba, S.Tanaka, T.Sugimura (2004b). Detection of Three-dimensional position of vegetation in the city using high-resolution satellite image and GIS. ASPRS 2004 Fall Conference Proceedings (ASPRS Images to Decision:Remote Sensing Foundation for GIS Applications), No.12.

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