(一社)日本リモートセンシング学会 第57回学術講演会論文集 2014年11月 A7 㧗ゎീᗘᖸ΅ SAR ⏬ീ GIS ࢹ࣮ࢱࢆ⏝࠸ࡓ㧗ᒙᘓ≀ࡢ㧗ࡉᢳฟ Detection of high-rise building’s heights using high-resolution InSAR images and GIS data ۑ㕥ᮌ ㈼ኴ㑻 1࣭ ࣜࣗ࢘ ࢙࢘ࣥ 2࣭ ᒣᓮ ᩥ㞝 2 Kentaro Suzuki, Wen Liu and Fumio Yamazaki Abstract : The detection techniques of building heights using remote sensing data have been proposed in previous researches. In this study, a detection method for high-rise building heights using high-resolution InSAR images and GIS data was proposed and a case study was conducted. Specifically, an interferometric image was made from a pair of TerraSAR-X complex images and layover areas were detected by an InSAR analysis. Then, building heights were measured using the detected layover areas and GIS building footprints. Finally, detected heights were compared with the reference heights from Lidar data. Keywords : high-rise building, height detection, TerraSAR-X, InSAR analysis 1. ࡣࡌࡵ ᘓ≀ࡢࣔࢽࢱࣜࣥࢢࡸࣔࢹࣜࣥࢢࡣ㸪㒔ᕷィ⏬ࡸ ⅏ᐖᑐ⟇ࡢ❧㸪⎔ቃᙳ㡪ホ౯࡞ࢆ⾜࠺ࡓࡵ㔜 せ࡛࠶ࡿ㸬ࡇࡢࡁྛࠎࡢᘓ≀ࡢᙧ≧ࢆᢕᥱࡍࡿ᪉ ἲ㸪ࡃᘓ≀㧗ࡉࡢᢳฟ᪉ἲࡀࡁ࡞ㄢ㢟࡞ࡗ ࡚࠸ࡿ㸬 ࣮ࣜࣔࢺࢭࣥࢩࣥࢢࡼࡿᘓ≀㧗ࡉࡢᢳฟࡣ㸪ග Ꮫ⏬ീࡢ❧యどࡸ࣮ࣞࢨ 㔞ࡶࡼࡃ⏝࠸ࡽࢀࡿࡀ㸪 ኳೃࡸኪ㛫㛵ࢃࡽࡎほ ࡛ࡁࡿྜᡂ㛤ཱྀ࣮ࣞ ࢲ (SAR) ࡀ ᭷ ຠ ࡞ ᡭ ẁ ࡛ ࠶ ࡿ 㸬 ࡉ ࡽ 㸪 ㏆ ᖺ TerraSAR-X (TSX)ࡸ COSMO-SkyMed ࡞ࡢ㧗ゎീ ⾨ᫍ SAR ⏬ീࡀ⏝࡛ࡁࡿࡼ࠺࡞ࡾ㸪ᗈᇦ࣭ᐃ ᮇⓗヲ⣽࡞ᆅ⾲㠃ࡢほ ࡀྍ⬟࡞ࡗࡓ㸬SAR ࡼࡿᘓ≀㧗ࡉࡢᢳฟᡭἲࡣࡇࢀࡲ࡛ከࡃᥦࡉࢀ ࡚࠸ࡿࡀ 1)㸪㒔ᕷࡢ㧗ᒙᘓ≀ࡢ㧗ࡉᢳฟ࠾࠸࡚ࡣ ᘓ≀ࡢࠕಽࢀ㎸ࡳࠖࠕᖸ΅┦ࠖࢆ⏝࠸ࡓᡭἲࡀ ᭷⏝࡛࠶ࡿ⪃࠼ࡽࢀࡿ㸬SAR ⏬ീ࡛ࡣ㸪ᗄఱᏛⓗ ࡞ṍࡳࡼࡗ࡚ᘓ≀ࡀ⏬ീୖಽࢀ㎸ࡴࡓࡵ㸪ࡇࡢ ಽࢀ㎸ࡳ⠊ᅖࢆ≉ᐃࡋ㸪ᘓ≀ࡢ GIS ࢹ࣮ࢱ⤌ࡳྜ ࢃࡏࡿࡇ࡛ྛࠎࡢᘓ≀ࡢ㧗ࡉࢆᢳฟࡀྍ⬟࡛࠶ ࡿ 2)㸬ࡲࡓ㸪ᚲせ࡞ฎ⌮ࢆࡋࡓᖸ΅⏬ീ࡛ࡣᘓ≀ ࡼࡗ࡚ᖸ΅⦤ࡀⓎ⏕ࡋ㸪⌮ㄽ್ࢆ⏝࠸ࡿࡇ࡛ᘓ ≀ࡢಽࢀ㎸ࡳ⠊ᅖࢆ≉ᐃࡍࡿࡇࡀ࡛ࡁࡿ 3)㸬ࡇࡢ ࡁ㸪㧗ᒙᘓ≀ࡣ┦ࡢኚ㔞ࡀࡁ࠸ࡓࡵ㸪ಽࢀ ㎸ࡳ⠊ᅖᖸ΅⦤ࡀⓎ⏕ࡋࡸࡍࡃ㸪ಽࢀ㎸ࡳ⠊ᅖࡢ ≉ᐃࡀࡋࡸࡍ࠸≉ᚩࡀ࠶ࡿ㸬 ᮏ◊✲࡛ࡣ㸪㧗ゎീᗘᖸ΅ SAR ⏬ീ GIS ᘓ≀ ㍯㒌ࢆ⏝࠸࡚㧗ᒙᘓ≀ࡢ㧗ࡉᢳฟࡍࡿࡇࢆ┠ⓗ ࡍࡿ㸬ࡲࡎ TSX ࡢᖸ΅⏬ീࢆసᡂࡋ㸪ᖸ΅⦤ࡢ ⌮ㄽᘧࡽᘓ≀ࡢಽࢀ㎸ࡳ⠊ᅖࢆᢳฟࡍࡿ㸬ࡉࡽ㸪 ᢳฟࡋࡓಽࢀ㎸ࡳ⠊ᅖ GIS ᘓ≀㍯㒌ࢹ࣮ࢱࢆ⏝ ࠸࡚ᘓ≀㧗ࡉࢆᢳฟࡋ㸪Lidar ࡽồࡵࡓ㧗ࡉẚ ㍑ࡍࡿ㸬 1 Ꮫ⏕ဨ ༓ⴥᏛᏛ㝔 ᕤᏛ◊✲⛉ ᘓ⠏࣭㒔ᕷ⛉Ꮫᑓᨷ ṇဨ ༓ⴥᏛᏛ㝔 ᕤᏛ◊✲⛉ ᘓ⠏࣭㒔ᕷ⛉Ꮫᑓᨷ ( ᡤᅾᆅ ࠛ263-8522 ༓ⴥᕷ✄ẟ༊ᘺ⏕⏫1-33 ᕤᏛ⣔⥲ྜ◊✲Ჷ4F) (㐃⤡ඛ Tel; 043-290-3528, E-mail; [email protected]) 2 2. ᑐ㇟ᆅᇦ⏝ࢹ࣮ࢱ ᮏ◊✲࡛ࡣ㸪࣓ࣜ࢝ྜ⾗ᅜࡢ࢝ࣜࣇ࢛ࣝࢽᕞ ࢧࣥࣇࣛࣥࢩࢫࢥᕷࡢ㧗ᒙࣅࣝ⩌ࢆᑐ㇟ᆅᇦࡋ ࡓ(Fig.1)㸬⏝ࡍࡿ TSX ⏬ീࡣ 2007/12/05 ྠᖺ 12/27 ྲྀᚓࡉࢀࡓ HS ࣮ࣔࢻࡢ SLC ⏬ീ࡛࠶ࡿ㸬 ࡇࡢ⏬ീࡣࡶࢪ࣐ࢫ᪉ྥࡢゎീᗘࡀ 1.10 (m/pixel) 㸪 ࢫ ࣛ ࣥ ࢺ ࣞ ࣥ ࢪ ᪉ ྥ ࡢ ゎ ീ ᗘ ࡀ 0.92 (m/pixel)࡛࠶ࡾ㸪༡ྥ㌶㐨ࡼࡾྲྀᚓࡉࢀࡓ㸬ࡲࡓ㸪 Lidar ࡢ DEM DSM ࢆᖸ΅⏬ീࡢᆅᙧ┦ࡢ⿵ṇ ᘓ≀㧗ࡉࡢ᳨ド⏝ࢹ࣮ࢱࡋ࡚⏝࠸ࡓ㸬ࡇࡢࢹ࣮ ࢱࡢỈᖹ᪉ྥศゎ⬟ࡣ 2.0m㸪ᆶ┤ศゎ⬟ࡣ 0.06m ࡛ ࠶ࡿ㸬⏝ࡍࡿ GIS ᘓ≀㍯㒌ࢹ࣮ࢱࡣ㸪ࢧࣥࣇࣛࣥ ࢩࢫࢥᕷࡀ HP ୖ࡛බ㛤ࡋ࡚࠸ࡿࡶࡢࢆ⏝ࡋࡓ 4)㸬 Fig.2(a)ᑐ㇟ᆅᇦࡢᘓ≀㍯㒌 Lidar ࡽồࡵࡓᆅ ⾲㠃㧗ࡉࢆ♧ࡍ㸬ᮏ◊✲࡛ࡣ㸪㧗ࡉ 50m ௨ୖ࡛ಽࢀ ㎸ࡳ⠊ᅖࡀࡢᘓ≀ࡢᙳධࡽ࡞࠸ࡼ࠺࡞ᘓ≀ 12 Ჷࢆᑐ㇟㧗ࡉࡢᢳฟࢆ⾜࠺㸬ᑐ㇟ᘓ≀ࢆ Fig.2(b) ♧ࡍ㸬 Fig.1. The study area in San Francisco, CA, U.S.A. and shooting areas of TerraSAR-X (TSX) and Lidar data. 3. ᖸ΅⦤ࢆ⏝࠸ࡓᘓ≀ಽࢀ㎸ࡳ⠊ᅖᢳฟࡢᢳฟ 3-1. ᖸ΅⏬ീࡢసᡂ ᘓ≀ࡢಽࢀ㎸ࡳ⠊ᅖࢆᢳฟࡍࡿ➨୍ẁ㝵ࡋ࡚㸪 TSX ࡢᖸ΅⏬ീࢆసᡂࡋࡓ㸬12/05 ⏬ീࢆ࣐ࢫࢱ࣮ ⏬ീࡋ࡚㸪ࣝࢵࢡᩘ 2:2 ࡢึᮇᖸ΅⏬ീࢆసᡂࡍ ࡿ㸬㌶㐨⿵ṇ Lidar ࡢ DEM ࢆ⏝࠸ࡓᆅᙧ┦ࡢ 㝖ཤࢆ⾜ࡗࡓᚋ㸪GoldStein ࣇࣝࢱ࣮ࢆ㐺⏝ࡋࡓ㸬 ̶ 17 ̶ Range Azimuth a c d e f g h i k 0 b j l 100m Building Height Fig.4. Schematic image of the InSAR observation. (a) (b) Fig.2. Geocoded image of building heights measured by Lidar data (a); slant-range phase image and target buildings (b). h a R cos T (2) a : ࢫࣛࣥࢺࣞࣥࢪศゎ⬟ (m/pixel) a ᮏ⏬ീ࡛ࡣ a = 0.92 ࡞ࡢ࡛㸪h = 1.2R ࡞ࡿ㸬 ᘧ(1)(2)ࡽ㸪ࢫࣛࣥࢺࣞࣥࢪ᪉ྥࡢ㞄᥋ࡍࡿࣆ ࢡࢭࣝࡢ┦ᕪ ǻ( rad/pixel)ࡣ௨ୗࡢᘧ࡛⾲ࡉࢀࡿ㸬 b c 'I Building footprint Fig.3. A close up of the phase image within the yellow frame in Fig.2 (b). Fig.2(b)ࡣᙉᗘ⏬ീᖸ΅⏬ീࢆ㔜ࡡࡓࢫࣛࣥࢺࣞ ࣥࢪ⏬ീ࡛࠶ࡾ㸪୍㒊ᣑࡋࡓᅗࢆ Fig. 3 ♧ࡍ㸬 ࡇࡢ⏬ീࡽᘓ≀ࡢಽࢀ㎸ࡳ᪉ྥᖸ΅⦤ࡀⓎ⏕ ࡋ࡚࠸ࡿᵝᏊࡀ☜ㄆ࡛ࡁࡿ㸬 3-2. ᖸ΅⦤ࡢ⌮ㄽᘧ ḟᘓ≀㧗ࡉᖸ΅┦ࡢ㛵ಀᘧࢆ⏝࠸࡚ಽࢀ ㎸ࡳ⠊ᅖࢆᢳฟࡍࡿ㸬SAR ࡼࡿᘓ≀ࡢほ ࡢᵝᏊ ࢆ Fig. 4 ♧ࡍ㸬ࡲࡎ㸪㧗ࡉ h (m)ࡢᘓ≀ࡼࡿ┦ ࡢኚ㔞 ( rad)ࡀ௨ୗࡢᘧ࡛⾲ࡉࢀࡿ㸬 I 4SBA h OH tan T Bԋ : ⏬ീ㛫ࡢᆶ┤㌶㐨㛫㊥㞳 (m) Ȝ : ࣮ࣞࢲࡢἼ㛗 (m) H : ࣐ࢫࢱ࣮⏬ീྲྀᚓࡢ⾨ᫍ㧗ࡉ (m) ș : ධᑕゅ (rad) (1) 4SaBA OH sin T (3) ᮏ⏬ീ࡛ࡣ ǻ = 0.65 rad/pixel ࡞ࡿ㸬 ࡲࡓ㸪ᖸ΅⦤ࡣ┦ࡀ ʌ ࡽ-ʌ ኚࡍࡿ┦ ࣛࢵࣉ(PW)ⅬࡀᏑᅾࡍࡿ㸬PW Ⅼ࡛ࡢ ǻ⌮ࡣ ㄽୖ -2ʌ ࡛࠶ࡾ㸪PW Ⅼࡣ୍ᐃ㛫㝸 T (pixel)࡛⌧ࢀࡿ㸬T ࡣᘧ(1)(2)ࡽ௨ୗࡢᘧ࡛⾲ࡉࢀࡿ㸬 T OH sin T 2aBA (4) ᮏ⏬ീ࡛ࡣ T = 9.66 pixels ࡞ࡿ㸬 3-3. ಽࢀ㎸ࡳ⠊ᅖᢳฟ᪉ἲ ᖸ΅⏬ീࡘ࠸࡚㸪ᘧ(3)ࢆ⏝ࡋࡓ┦ᕪࡼࡿ ಽࢀ㎸ࡳ⠊ᅖᢳฟ㸪ᘧ(4)ࢆ⏝ࡋࡓ PW Ⅼ㛫㝸 ࡼࡿᢳฟࢆ⾜࠺㸬๓ฎ⌮ࡋ࡚㸪ᖸ΅⏬ീࡽࢫࣛ ࣥࢺࣞࣥࢪ᪉ྥࡢ┦ᕪ⏬ീࢆసᡂࡋ㸪ǻ < -ʌ ࢆ ‶ࡓࡍࣆࢡࢭࣝࢆ PW Ⅼࡋ࡚ᢳฟࡋࡓ㸬Fig.3 ࡢ ┦⏬ീࡽᢳฟࡉࢀࡓ PW Ⅼࢆ Fig.5(a)♧ࡍ㸬 ࡲࡎ㸪┦ᕪࡼࡿᢳฟࢆ⾜࠺㸬┦ᕪ⏬ീࡢ PW Ⅼ 2ʌ ࢆຍ࠼࡚┦ࣥࣛࢵࣆࣥࢢࢆ⾜࠸㸪ࡑ ࡢ⏬ീࡢ┦ᕪࡀ 0.325 < ǻ < 0.975 ࢆ‶ࡓࡍⅬࢆ ᮏ⏬ീ࡛ࡣ㸪Bԋ = 561.6㸪Ȝ = 3.1×10-2㸪H = 5.01×105㸪 ᢳฟࡋࡓ㸬ࡑࡋ࡚㸪ᢳฟࡋࡓࣆࢡࢭࣝࢆࢭࢢ࣓ࣥࢸ ࣮ࢩࣙࣥࡉࡏ㸪⤖ྜᚋࡢࣆࢡࢭࣝᩘࡀ 35 ௨ୗࡢࢭ ș = 0.70 ࡛࠶ࡾ㸪 = 0.54h ࡞ࡿ㸬 ḟ㸪㧗ࡉ h ࡢᘓ≀ࡀࢫࣛࣥࢺࣞࣥࢪ⏬ീୖ࠾ ࢢ࣓ࣥࢺࢆࣀࢬࡋ࡚㝖ཤࡋࡓ㸬᭱⤊ⓗᢳฟࡋ ࡅࡿಽࢀ㎸ࡳ㔞 R (pixel)ࡢ㛵ಀࡣ௨ୗࡢᘧ࡛⾲ࡏࡿ㸬 ࡓ⠊ᅖࢆ Fig. 5(b)♧ࡍ㸬┦ᕪࡼࡿᢳฟࡣ㸪1 ̶ 18 ̶ a b Per 1 pixel c c Fig.6. Illustration of detecting layover length. 0 PW point 1.3 ࣆࢡࢭࣝࡈ⠊ᅖࢆᢳฟࡍࡿࡓࡵ㸪⣽࠸⠊ᅖࡲ ࡛ಽࢀ㎸ࡳࢆ᥎ᐃ࡛ࡁࡿ୍᪉㸪ࣀࢬࡼࡗ࡚ಽࢀ ㎸ࡳ⠊ᅖ࡛ࡶᢳฟ࡛ࡁ࡞࠸ࣆࢡࢭࣝࡶከ࠸㸬 (a) a Detected area ࡑࡇ࡛㸪┦ᕪࡀࡁࡃ≉ᐃࡋࡸࡍ࠸ PW Ⅼὀ ┠ࡋࡓᢳฟࡶヨࡳࡓ㸬ࡇࡢᡭἲ࡛ࡣ PW Ⅼ㛫㝸ࡼ ࡗ࡚ಽࢀ㎸ࡳ⠊ᅖࢆᢳฟࡍࡿ㸬๓ฎ⌮࡛ᢳฟࡋࡓ PW Ⅼࡘ࠸࡚㸪ࣞࣥࢪ᪉ྥࡢḟࡢ PW Ⅼࡲ࡛ࡢ㛫 㝸 T ࢆ⟬ฟࡋ㸪8 < T < 12 ࢆ‶ࡓࡍሙྜ㸪⮬㌟ࡢ PW Ⅼࡽḟࡢ PW Ⅼࡲ࡛ࡢࣆࢡࢭࣝࢆᢳฟࡍࡿ㸬ࡑࡋ ࡚㸪ྠࡌࡃࢭࢢ࣓ࣥࢸ࣮ࢩࣙࣥࢆ⾜ࡗ࡚㸪ࣆࢡࢭࣝ ᩘ 35 ௨ୗࡢࢭࢢ࣓ࣥࢺࢆ㝖ཤࡋࡓ㸬ࡇࡢฎ⌮ࡼ ࡿᢳฟ⠊ᅖࢆ Fig. 5(c)♧ࡍ㸬ࡇࡢᡭἲ࡛ࡣ㸪PW Ⅼࡢࡳὀ┠ࡍࡿࡓࡵ㸪PW Ⅼ㛫ࡢࣀࢬࡢᙳ㡪ࢆ ཷࡅࡎಽࢀ㎸ࡳ⠊ᅖࢆᢳฟࡍࡿࡇࡀ࡛ࡁࡿ㸬୍ ᪉㸪1 ᖸ΅⦤࠶ࡓࡾࡢᢳฟ࡞ࡿࡓࡵ㸪ᐇ㝿ࡢಽࢀ ㎸ࡳ⠊ᅖࢆ࡚ᢳฟ࡛ࡁࡿࢃࡅ࡛ࡣ࡞࠸㸬 b c (b) a Detected area b c 3-4. ᢳฟ⠊ᅖࡢ⤖ྜ ࡑࡇ࡛㸪┦ᕪ PW Ⅼ㛫㝸ࡼࡾᢳฟࡋࡓ⠊ᅖ ࢆ⤖ྜࡍࡿࡇ࡛᪉ࡢᢳฟ₃ࢀࢆ⿵ࡋࡓ㸬Fig. 5(d)ࡣ୧ᡭἲࡼࡿᢳฟ⠊ᅖࡢ࣮࢝ࣛྜᡂᅗ࡛࠶ࡾ㸪 ⓑࡣ୧ᡭἲ࡛ᢳฟ࡛ࡁࡓ⠊ᅖ㸪㯤Ⰽࡣ┦ᕪࡼࡗ ࡚⿵ࡉࢀࡓ⠊ᅖ㸪㟷ࡣ PW 㛫㝸ࡼࡗ࡚⿵ࡉࢀ ࡓ⠊ᅖࢆ♧ࡍ㸬ࡇࡢᅗࡽ㸪┦ᢳฟ₃ࢀࢆ⿵ ࡋ࡚࠸ࡿᵝᏊࡀࢃࡿ㸬ᮏ◊✲࡛ࡣ㸪ᢳฟࡉࢀࡓࡍ ࡚ࡢ⠊ᅖࢆᘓ≀ࡢಽࢀ㎸ࡳぢ࡞ࡋ㸪㧗ࡉࡢᢳฟ ⏝࠸ࡿ㸬 (c) a b c R:PD G:PD B:PW (d) Fig.5. Phase difference image with phase wrap points (yellow pixel) (a); Detected layover area from phase difference analysis (b); Detected layover area from PW analysis (c); Color composite of two detected areas by phase difference (PD) and phase wrap (PW) analysis (d). 4. ಽࢀ㎸ࡳ GIS ࢹ࣮ࢱࢆ⏝࠸ࡓᘓ≀㧗ࡉࡢᢳฟ 4-1. ᘓ≀㧗ࡉᢳฟ᪉ἲ ᢳฟࡋࡓಽࢀ㎸ࡳ⠊ᅖ GIS ᘓ≀㍯㒌ࢆ⏝࠸ࡓ ᘓ≀㧗ࡉࡢᢳฟࡢᡭ㡰ࢆ௨ୗ♧ࡍ㸬Fig.6 ࡢࡼ࠺ ᘓ≀㍯㒌ࢆ 1 ࣆࢡࢭࣝẖ⾨ᫍ᪉ྥ⛣ືࡋ㸪 SAR ࡢධᑕഃࡢ㍯㒌ୖࣆࢡࢭࣝྵࡲࢀࡿಽࢀ㎸ ࡳ⠊ᅖࡢྜࢆồࡵࡿ㸬ࡑࡋ࡚ࡇࡢྜࡀ 25%ࢆୗ ᅇࡗࡓࡽࡑࡢ⛣ື⠊ᅖࡲ࡛ࢆಽࢀ㎸ࡳ㔞 R ࡋ㸪ᘧ (2)ࡽᘓ≀㧗ࡉࢆồࡵࡓ㸬 ̶ 19 ̶ Table 1. Comparison table of the detected heights vs. the Lidar heights. Building ID a b c d e f Detected Height (m) 71.8 51.4 113.6 108.8 49.0 89.7 Lidar Height (m) 77.0 67.0 116.0 115.0 55.0 90.0 Error (m) -5.2 -15.6 -2.4 -6.2 -6.0 -0.3 Building ID g h i j k l Detected Height (m) 102.9 88.5 143.5 102.9 65.8 74.2 Lidar Height (m) 106.0 90.0 125.0 99.0 67.0 84.0 -3.1 -1.5 18.5 3.9 -1.2 -9.8 Error (m) Lidar height (m) 150 130 Average error: 6.1m RMS error : 8.3m 110 ᖸ΅⏬ീࢆసᡂࡋ࡚㸪ᖸ΅⦤ࡢ⌮ㄽᘧࡽ┦ᕪ ┦ࣛࢵࣉⅬࡢ㛫㝸ὀ┠ࡋࡓᘓ≀ࡢಽࢀ㎸ࡳ⠊ ᅖࡢᢳฟࢆ⾜ࡗࡓ㸬ࡉࡽ㸪GIS ᘓ≀㍯㒌ࢆ⏝࠸࡚ ᘓ≀ࡢಽࢀ㎸ࡳ㔞ࢆỴᐃࡋ㸪ᘓ≀㧗ࡉࢆồࡵࡓ㸬᭱ ᚋᮏᡭἲࡢᘓ≀㧗ࡉ Lidar ࡼࡾồࡵࡓᘓ≀㧗ࡉ ࢆẚ㍑᳨ウࡋࡓ㸬 ᢳฟ⤖ᯝࡣᖹᆒㄗᕪ 6.1m ࡛࠶ࡾ㸪㧗ᒙᘓ≀ࡢ㧗 ࡉ᥎ᐃࡋ࡚ࡣ㧗࠸⢭ᗘ࡛࠶ࡗࡓ㸬୍᪉㸪࿘㎶ࡢᵓ 㐀≀ࡸᘓ≀ࡢᙧ≧ࡼࡗ࡚ᢳฟㄗᕪࡀࡁࡃ࡞ࡿ ࡇࡶ☜ㄆࡉࢀࡓ㸬 ᚋࡣ㸪࿘㎶ࡢᘓ≀❧ᆅ≧ἣࢆ⪃៖ࡋࡓᡭἲࡸ㸪 ᘓ≀ࡢᙧ≧ࡶ␃ពࡋࡓᡭἲࢆ⪃࠼ࡿᚲせࡀ࠶ࡿ㸬 ࡲࡓ㸪ᙳ᮲௳ࡀ␗࡞ࡿ⏬ീࢆ⏝ࡍࡿࡇ࡛㸪ᖸ ΅⦤ࡢ⌮ㄽ್ࡀኚືࡋࡓሙྜ࡛ࡶᮏᡭἲࡢᢳฟࣇ ࣮ࣟࡀ᭷⏝࡛࠶ࡿࢆ᳨ドࡍࡿணᐃ࡛࠶ࡿ㸬 ㅰ㎡ ᮏ◊✲࡛⏝࠸ࡓ TSX ⏬ീ Lidar ࢹ࣮ࢱࡣ 2012 IEEE Geoscience and Remote Sensing Society Data Fusion Contest ࡼࡾᥦ౪ࡉࡏ࡚࠸ࡓࡔ࠸ࡓ㸬ࡇࡇㅰ ពࢆ⾲ࡍࡿ㸬 90 70 ࠙ཧ⪃ᩥ⊩ࠚ 1) T. Toutin and L. Gray, : State-of-the-art of elevation 50 70 90 110 130 150 extraction from satellite SAR data, ISPRS Journal of Detected height (m) Photogrammetry and Remote Sensing, Volume 55, Issue 1, pp. 13–33, 2000. Fig.7. Comparison of the detected heights vs. the 2) W. Liu, F. Yamazaki, : Building height detection Lidar heights. from high-resolution TerraSAR-X imagery and GIS data, Proceedings of 2013 Joint Urban Remote 4-2. ᢳฟ⤖ᯝ᳨ドࢹ࣮ࢱࡢẚ㍑ Sensing Event, IEEE, Sao Paulo, Brazil, CD-ROM, ᢳฟࡋࡓᘓ≀㧗ࡉࢆ Lidar ࡽồࡵࡓ㧗ࡉࢆṇゎ 33-36, 2013. ࡋ࡚ẚ㍑ࡋࡓ⤖ᯝࢆ Table1 Fig. 7 ♧ࡍ㸬ᮏᡭ ἲࡼࡿᖹᆒㄗᕪࡣ 6.1m㸪RMS ࡣ 8.3m ࡞ࡾ㸪 50% 3) ୖᮏ⣧ᖹ࣭ᑠᯘ㐩࣭బ➉ㄔ࣭ඣᓥṇ୍㑻࣭ᱵ ࡢᘓ≀ࢆ 5m ௨ෆࡢㄗᕪ࡛㧗ࡉࡢ᥎ᐃࡀ࡛ࡁࡓ㸬㧗 ཎಇᙪ࣭ᯇᒸᘓᚿ࣭ᾆሯΎᓠ㸸SAR ࣥࢱ࣮ࣇ ࡉ 50m ௨ୖࡢᘓ≀ࡀᑐ㇟࡛࠶ࡿࡇࢆ⪃៖ࡍࡿ㸪 ࢙ࣟࢢ࣒ࣛࡽࡢᆶ┤ᵓ㐀≀ࡢ⮬ືᢳฟ᪉ἲ㸪 ⢭ᗘࡼࡃᘓ≀㧗ࡉࡀᢳฟ࡛ࡁࡓ⪃࠼ࡽࢀࡿ㸬 ᪥ᮏ࣮ࣜࣔࢺࢭࣥࢩࣥࢢᏛ➨ 56 ᅇᏛ⾡ㅮ₇ ୍᪉ᢳฟㄗᕪࡢࡁ࠸ᘓ≀ὀ┠ࡋ࡚ࡳࡿ㸪ᘓ ㄽᩥ㞟㸪pp.139-140, 2014. ≀ i ࡣ 18.5m 㐣㧗ࡉࢆᢳฟࡋ㸪ᘓ≀ b ࡣ 15.6m 4) City and County of San Francisco WEB ࣮࣌ࢪ: https://data.sfgov.org/Facilities-and-Structures/Build 㐣ᑠ㧗ࡉࢆᢳฟࡋ࡚࠸ࡿ㸬ᘓ≀ i ࡢㄗᕪࡘ࠸࡚ ing-Footprints-Zipped-Shapefile-Format-/jezr-5bxm ᳨ウࡋࡓ⤖ᯝ㸪ࡇࡢᘓ≀ࡢಽࢀ㎸ࡳ᪉ྥ࠶ࡿࡢ ᘓ≀ࡢಽࢀ㎸ࡳ⠊ᅖࡀΰྜࡋ࡚㧗ࡉࢆᢳฟࡋ࡚࠸ ࡓࡇࡀศࡗࡓ㸬ᘓ≀ b ࡘ࠸࡚ࡣ㸪࿘㎶ࡢᆅୖ ᵓ㐀≀ࡸ✵ㄪᶵ࡞ࡢᒇ᰿ୖᵓ㐀≀ࡼࡿᙳ㡪 ࡼࡾ㸪Ᏻᐃࡋࡓᖸ΅ࡀᚓࡽࢀ࡞ࡗࡓࡇࡀཎᅉ ⪃࠼ࡽࢀࡿ㸬 50 4. ࡲࡵ ᮏ◊✲࡛ࡣ㸪㒔ᕷᇦࡢ㧗ᒙᘓ≀ࡢ㧗ࡉࢆ㧗ゎീᗘ ᖸ΅ SAR ⏬ീ GIS ᘓ≀㍯㒌ࢹ࣮ࢱࢆ⏝࠸࡚ᢳฟ ࡍࡿᡭἲࢆᥦࡋࡓ㸬ලయⓗࡣ㸪TerraSAR-X ࡢ ̶ 20 ̶
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