2006 5 10
1. 1.1. 1.2. HASM 1.3. HASM 2. HASM 2.1. 2.2. 2.3. 2.4. 2.5. 2.6.
1.
1. 1.1.
1. 20
1. 1.1.1.
1. overlay
1. 1.1.2. real-time
1. 1.1.3. 90
1. 1.1.4.
1. 1.2. HASM
1. earth surface system surface surface modelling
x y f, HASM 8 HASM, { } ), ( j i y x Ω ( ) ( ) + + + Γ + + Γ = + + + + Γ + + Γ = + + + + + + + + + + + + + + + + + + + + + + + 1 ) ( ) 0.5( 1 ) ( ) 0.5(,,, 1 1, 1,, 2 22 1 1, 1,, 1 22 1 1 1, 1, 1 1, 1 1,,,, 1 1, 1,, 2 11 1 1, 1,, 1 11 1 1 1, 1, 1 1, 1 1, n j i n j i n j i i i n j i n j i n j i j j n j i n j i n j i i i i n j i n j i i n j i n j i n j i n j i n j i j j n j i n j i n j i i i n j i n j i n j i i i i n j i n j i i n j i n j i G E N hy hy f f hx hx f f hy hy hy f f hy f f G E L hy hy f f hx hx f f hx hx hx f f hx f f 1 = i i i x x hx 1 = j j j y y hy j i f, ~ j i f, ~ ), ( j x i y ) Φ,, (, j i j i f y x 1.
1. HASM 1.2.1. 450530 449520 2746 4941 47470 64 320683 318592 2016 4130 37445 56 178418 180849 1396 2710 24716 48 97169 101156 1613 1732 14761 40 31539 31468 714 846 6511 32 8994 8925 255 377 2345 24 1229 1227 66 110 495 16 Kriging IDW Spline Cubic TIN N 1.
2. HASM 575049 573252 3707 6206 52170 64 453571 450702 3271 5984 47064 56 264262 268259 2280 4000 25737 48 137840 143656 2133 2495 17986 40 39796 39713 875 1118 7195 32 9980 10004 304 469 2432 24 1433 1437 83 137 524 16 Kriging IDW Spline Cubic TIN N 1.
1. 1.2.2. 1.
1. 2. HASM Kriging
1. 4. HASM IDW
1. 5. HASM TIN
1. 1.2.3. HASM HASM, HASM a) b) HASM : a), b) ( o, *, V4 )
1. HASM, 15 15π f ( 1, y) = 1 f (, y) = 2sin sin( πy) + 1 16 16 a) b) Kriging Spline IDW, a), b) ( * IDW, Kriging, Spline, TIN, o )
1. HASM HASM HASM HASM, IDW IDW HASM HASM IDW ( IDW, HASM 1, HASM 2, * HASM 20, o )
1. HASM TIN HASM ( TIN, HASM 10, HASM 20, * HASM 25, o )
1. ( ) HASM a) b) HASM Kriging Spline TIN, a) b) ( o HASM, * Spline, Kriging, TIN )
1. HASM a) b), a), b) ( * IDW, Kriging, o Spline, HASM )
1. 1.2.4. HASM HASM5 T T n+ 1 H C H C 0 F λ = H T G Q n
[ ] G C : z = Z C C ~ ws z R Z = = T a T T c T T T w a c w T c T T w c w T T L S L W K L L S W L K L L K L L K L C C H H 0 0 0 ~ 0 ~ ~ ~ 0 0 ~ ~ 1.
1. f ( x, y) = 2sin( πx) sin( πy) + 1 1 h = [0 1] [0 1] N 20 21 20
1. 21 4.76753e-2 4.76753e-2 2.97206e-2 2.97206e-2 41 1.56250e-2 9.98871e-3 9.23565e-3 5.98132e-3 61 5.89601e-3 1.83831e-3 3.50763e-3 1.08183e-3 81 4.29238e-3 4.93060e-4 2.55741e-3 2.68031e-4 101 3.04702e-3 9.28704e-5 1.99478e-3 5.69623e-5 121 1.84728e-3 2.16574e-5 1.13616e-3 1.07885e-5
1. 121 20 121
1. 121 1.81623e-3 1.81623e-3 1.20496e-3 1.20496e-3 101 3.39212e-3 1.88143e-3 2.22039e-3 1.15091e-3 81 5.14755e-3 1.89467e-3 3.22334e-3 1.15991e-3 61 6.84850e-3 1.90230e-3 4.33931e-3 1.16291e-3 41 1.15486e-2 1.91734e-3 6.79527e-3 1.17100e-3 21 4.86356e-2 1.93625e-3 3.17408e-2 1.17976e-3
1. HASM5 HASM
1. 1.2.5. HASM GIS HASM, Mercator HASM x y = = a a λ ln tan π 4 + 1 2 1+ ϕ e e sin sin x ; y 1 ; ϕ ; λ ; a 2 2 2 ; a b, e = 2 a b ; C ϕ ϕ e 2 + C
1. : HASM GIS HASM (GIS) HASM
1. HASM HASM, HASM
1. 1.3.
1. 1.3.1.
1. 1.3.2. HASM HASM
1. 1.3.3. GIS
2.1.
HASM ' N35 o 05
771
3085
a) b) c) d) a HASM b TIN c SPLINE d IDW
a b c d a HASM b TIN c SPLINE d IDW
HASM TIN SPLINE IDW 3085 3085 3085 3085 (m) 6.347 7.266 7.431 10.903 (%) 0.3017 0.3526 0.3631 0.4543
HASM TIN SPLINE IDW HASM
1 2 3
2.2.
SMPD SMPD
DEM NPP GDP
E2 E3 ( t) SMPDij = G n, p ij p ( t) ij () t p ij M ( ) ( ) ( ) a5 a4 a S 3 k NPP DEM ( Tran ) = Wij ij ij ij k = 1 d ijk a 1 a 2
2.2.1 WA ( ) -- Grid (1km) Dem ( )----Grid (1km) NPP ( ) -----Grid(10km) City ( )--Point Coverage Rail ( ) -----Arc Coverage Road ( )-----Arc Coverage Boundary ( )--Polygon Coverage
1930
1949
2000
2020
1949
2000
2020
NPP ( ) 2 MNPP() t 760 500 ij ij () t = exp 6 demij () t 3700m 2 Tranij () t 10 ( ()) demij t 500 DEMij () t = 500m demij () t 3700m demij () t 1 dem () t 500m ij = ra Max i, j ij ( t) + roij ( t) () t + ro () t { ra } ij ij p ij () t W () t NPP () t 0.0001 0.7 ( ) ( DEM () t ) ( Tran () t M 1.3 = ) ij ij ij ij k = 1 () t ( S k () t ) d () t ijk 1.2 ( n t) SMPD ij = G, p ij p ( t) () t ij
p ij () t W () t NPP () t 0.0001 0.7 ( ) ( DEM () t ) ( Tran () t M 1.3 = ) ij ij ij ij k = 1 ( n t ) SMPD ij = G, p ij p () t () t ij () t ( S k () t ) d () t ijk 1.2
1km 6 1) 2) 3) 200 4) 5) 6)
1930 ( / )
SMPD SMPD SMPD ( / )
1949 ( / )
2000 ( / )
2010 I / )
2020 I / )
1930 2000 1930 1949, 3% 0.4% 0.5% 1949 2000, 2% 3.1% 2.5%
52% 33% 16%
2.2.2. 2000 DEM 80 80m DEM ij = 80 DEM 2000 1 ij DEM 2000 DEM 2000 ij ij > 80 80
NPP 760 gc m-2 yr-1 NPP NPP = e ij ( ( NPP ij 10 760) 6 2 )
1km 1km 10km 10km = = l k ijk k ij D N Ro 1 1.5 = = l k ijk k ij D N Ra 1 1.2 + + = ) ( ) ( ) ( ) ( ij ij ij ij ij ij ij ij ij Ro Max Ro Ra Max Ra Max Ro Max Ro Ra Max Ra Tran 2. HASM
i, j 20km CT ij = l k = 1 ( S k D 1.2 ) ijk p ij = W ij ( ) 0.0024 ( ) 2.7 1.8 2. 3 NPP DEM Tran ) ( CT ) ij ij ( ij ij SMPDij = G2000 p ( n) ij p ij
a) DEM DEM b) NPP c) d) 1 2000 SMPD
2000 SMPD
a) b) c) 2020 ( 2050 ) ( 2020 )
d) e)
4660 3020 2260 2020 I
2020 II 1800 1170 260
2020 III 1800 850 190
2020 IV 1800 850 110
2.3.
Holdridge MAB TAP PER 1 365 365 ( x, y, t) = TEM ( j, x, y, t) 365 j= 1 ( x, y, t) = P( j, x, y, t) ( x y, t), = j = 1 58.93MAB( x, y, t) TAP( x, y, t) ( j, x, y t) P ( j, x, y, t) TEM, j 0 o C 30 o C ; j MAB TAP PER
( x, y, t) = ln MAB( x, y t) M, ( x, y, t) = lntap( x, y t) T, ( x, y, t) = ln PER( x, y t) P, d i 2 2 ( x y, t) = ( M ( x, y, t) M ) + ( T ( x, y, t) T ) + ( P( x, y t) P ) 2, i0 i0, i0 ( M i0, Ti 0, Pi 0 ) i dk ( x, y, t) = min{ di ( x, y, t) } ( x, y) i i
Mean center model x y j () t j () t = = s () t X () t I j ij ij i= 1 S j ( t) I j i= 1 s ij () t Y () t S j ij () t I j ( t) t j s () ij t j i S j () t j ( X ij ( t), Yij ( t) ) j i ( x ( ) ( )) j t, y j t j
735
Da Hingg an Moun tains Xiao Hinggan Mountains Junggar Basin Tianshan Mountains Turpan Basin Inner Mongolia Plateau Changbai Mountains Yanshan Mountains Tarim Basin Alashan Plateau Altun Mountains Kunlun Mountains Qaidam Basin Qilian Mountains Lvliang-Taihang Mountains Qinghai-Xizang Plateau Loess Plateau Qinling Mountains North China Plain Sichuan Basin Himalaya Mountains Hengduan Mountains Wuling Mountains Jiangnan Hills Wuyi Mountains Yunnan-Guizhou Plateau Nanling Mountains
Changbai mountains Da-Xiao Hinggan mountains Hengduan mountains Temperature 15.00 10.00 5.00 0.00 T = -0.0028E + 9.3481 R 2 = 0.927 0 1000 2000 3000 Temperature 10.00 8.00 6.00 4.00 T = -0.004E + 8.3638 2.00 R 2 = 0.7104 0.00 0 200 400 600 800 Temperature 25.00 20.00 15.00 10.00 5.00 0.00 T = -0.0054E + 24.542 R 2 = 0.91 0 1000 2000 3000 4000 5000 Elevation Elevation Elevation Loess plateau Nanling mountains Qilian mountains Temperature 12.00 10.00 8.00 6.00 4.00 T = -0.0036E + 14.111 R 2 = 0.7579 Temperature 25.00 20.00 15.00 10.00 5.00 0.00 T = -0.006E + 18.996 R 2 = 0.8273 Temperature 12.00 10.00 8.00 6.00 4.00 2.00 0.00 T = -0.0037E + 14.787 R 2 = 0.9875 600 800 1000 1200 1400 1600 0 500 1000 1500 0 1000 2000 3000 4000 Elevation Qinghai-Xizang Plateau 10.00 T = -0.0029E + 14.442 8.00 R 2 = 0.9086 6.00 4.00 2.00 0.00 1500 2500 3500 4500 5500 Elevation Temperature Temperature Elevation Qinling mountains 20.00 15.00 10.00 T = -0.004E + 15.681 R 2 = 0.5844 5.00 0.00 0 200 400 600 800 1000 1200 Elevation Temperature Elevation Taihang and Lvliang mountains 15.00 T = -0.005E + 14.53 10.00 R 2 = 0.9573 5.00 0.00 0 500 1000 1500 2000 2500 Elevation Tianshan mountains Wuling mountains Wuyi mountains 20.00 Temperature 20.00 T = - 0.0038E + 13.858 15.00 R 2 = 0.7238 10.00 5.00 0.00 0 500 1000 1500 2000 2500 3000 Temperature 15.00 10.00 T= -0.0055E + 18.112 5.00 R 2 = 0.8932 0.00 0 500 1000 1500 2000 Temperature 30.00 T= -0.0044E + 18.848 20.00 R 2 = 0.8199 10.00 0.00 0 500 1000 1500 2000 Elevation Elevation Elevation Yanshan mountains Himalaya mountains Yunnan-Guizhou Plateau Temperature 12.00 10.00 8.00 6.00 T= -0.0046E + 12.258 4.00 R 2 = 0.9701 2.00 0.00 100 600 1100 1600 Temperature 10.00 5.00 T = -0.0064E + 30.978 R 2 = 0.7276 0.00 3000 3250 3500 3750 4000 4250 4500 Temperature 25.00 20.00 15.00 10.00 5.00 T = -0.0045E+ 19.979 R 2 = 0.7305 0 500 1000 1500 2000 2500 Elevation Elevation Elevation
1960-2002
60 70 80 90
60 70 80 90
HadCM2 T1, T2, T3 T4 1961-1990 2010-2039 2040-2069 2070-2099
HadCM3 T1, T2, T3 T4 1961-1990 2010-2039 2040-2069 2070-2099
HadCM2 T1, T2, T3 T4 1961-1990 2010-2039 2040-2069 2070-2099 T4
HadCM3 T1, T2, T3 T4 1961-1990 2010-2039 2040-2069 2070-2099
HadCM2 T1, T2, T3 T4 1961-1990 2010-2039 2040-2069 2070-2099
HadCM3 T1, T2, T3 T4 1961-1990 2010-2039 2040-2069 2070-2099
HadCM2d1 552 HadCM3A1FI 204 50% HadCM2 HadCM3
HadCM3 HadCM2 HadCM3 HadCM2 HLZ 21
2.4.
Odum K 50%
1 [0.5K K] 2 3 4?
: : : ( ) ( ) ( ) ( ) J X J X J X X X J X X X J X X J X X = + + + = + + 0 0 0 2 2 0 0 2 0 2 2 2 1 2 1 2 ( ) J X J X X = 0 ( ) P V X J t S X k k k δ d δ δ d δ 2 1 d 2 = = 2. HASM
logistic dn dt ( t) n () = rn t 1 K ( t)
(dn(t) /dt ) 0.30 0.25 0.20 0.15 0.10 0.05 0.00 n = 0. 5K = K 0.00 0.00 0.01 0.05 0.27 0.73 0.95 0.99 1.00 1.00 (n(t)/k) n
(n(t) /K ) 2. HASM 1.0 0.8 0.6 0.4 0.2 n = 0. 5K 0.0 1 6 11 16 (t)
(dn(t) /dt ) 0.30 0.25 0.20 0.15 0.10 0.05 n = 0. 211K n = 0. 788K 0.00 0.00 0.00 0.01 0.05 0.27 0.73 0.95 0.99 1.00 1.00 (n(t) /K )
2. HASM (n(t) /K ) 1.0 0.8 0.6 0.4 0.2 n = 0. 788K n = 0. 211K 0.0 1 6 11 16 (t)
[0.5K K], 0.289K [0.5K K]
[0.211K 0.788K]
2.5.
( / )
( 1km )
kg kg kg kg kg
2.6.
2.6.1. change detection process
CAV SAV CD t v ( x, t) ( x, y, t) λ NDVI = λ λ 1 Y = Y = RED. 1 X NIR NIR 1 Y 1+ Y v ( x, y + 2, t) 2v( x, y + 1, t) 3 y= 1 2 λ + λ NDVI 2 RED RED ( + ( v( x y + t) v( x y t) ) ) 2 1, 1,,, ( y, t) = ABS( v( x + 1, y, t) v( x, y, t) ) 2 2 2 () = SAV ( y, t) + CAV ( y, t) + AV ( y, t) y= 1 X x= 1 ( x, y, t) λ + v( x, y, t) ( )( 2 1 + SAV ( y, t) ), NIR 1 2
1976 12 1 Landsat
1988 12 3 Landsat
0.03 0.025 0.02 0.015 0.01 0.005 0 1 156 311 466 621 776 931 1086 1241 1396 1551 1706 1861 2016 2171 2326 2481 2636 2791 2946 SAV(y,1) Column number of pixel in the visualized matrix (y) 1976 NDVI SAV
0.018 0.016 0.014 0.012 0.01 0.008 0.006 0.004 0.002 0 1 155 309 463 617 771 925 1079 1233 1387 1541 1695 1849 2003 2157 2311 2465 2619 2773 2927 SAV(y,2) Column number of pixel in the visualized matrix (y) 1988 NDVI SAV
0.000015 0.00001 0.000005 0-0.000005-0.00001-0.000015-0.00002 1 156 311 466 621 776 931 1086 1241 1396 1551 1706 1861 2016 2171 2326 2481 2636 2791 2946 CAV1(y,2) Column number of pixel in the visualized matrixes (y) 1988 NDVI CAV
CD SAV CAV
2.6.2. 2000 Multi-resolution Land Characteristics Program 2002
4 C = df p S ij ij () t m i= 1 n i ln = j= 1 ( ε ) ( p i () t ) i= 1 d m ln m( t ) ( ε ) HU () t = pi () t hi () t () t I j i= 1 s ( t) X ( t) ij ij x j = i= 1 S j ( t) ( ) ( ) () I j sij t Yij t y j t = i= 1 S j () t 1 2 2 ij
1
1984
1991
1996
3 4 5 C t () = 2.3584d( t) + 0. 6306 t C(t) d(t) 0.9298 C () t = 1.5134HU( t) + 0. 5522 t C(t) HU(t) 0.9411
Tischendorf Fahrig model based on dispersal success model based on search time
Roberts Malanson Gramer Gustafson Gardner
2: 1983 1990 1997
1983 1990 1997 0.7870 0.8815 0.8937 ( / ) 221.1 47.1 45 (%) 0.224 0.166 0.146 ( / ) 120.4 144.5 1270 ( / ) 18.3 1839.9 3148.5