免费文献传递   相关文献

Characteristics and Application of GF-1 Image in Grassland Monitoring

高分一号卫星影像特征及其在草地监测中的应用



全 文 :!23" !5#
 Vol.23  No.5
! " # $
ACTA AGRESTIA SINICA
   2015$  9%
  Sep.  2015
犱狅犻:10.11733/j.issn.10070435.2015.05.029
#;0=pq r./¥àû(¬sf90¸Æ
/ ²1,2,³  1´,èµµ1,œ3¶1,è· 1´,= 1
(1.¥*+¬<ñÁAÀ°+˜™],n} ¥210093;
2.°Þ*+34,<:AÀ’M8Cð–T¤C:=Vº,°Þ Ù}750021)
45

G¥ôìzŠ™Çîp½BNñÏjâç

•z{¢‰~àæZ

)*z‰5=±†7žAp!RSB‡
Â

}NñG˜™K_

ÎxNñzÎȶ

Á.WX8 «p

l@ñ/XŒ°jBNñ±†

ñ‚:9ë

æ
ç¨=©/«p!=jp½

LJ犚2 =–N¼0D§ŒÃð„vãÞ.éQ。lmPJ:~àæZ8¤zn¥
¢‰ûüHšïBŠXg

6“z‰5BÎì

ñ›Hñ9yQB‚Æâç

)*z‰5BÎì

ñ›Hp½B
æüg

±†7žApšïBðçHWXNñyQB±†KmRS

©/«p=:9ëBvzÞ.éQ–G‡
¦Èõ8 «pBÙü‹²ÂéQ

æç¨vzÞ.éQG‡¦8Š<8 «pB«©péQ

ÃÕÅHšïB
L×im

678

ìzŠ™

8 «p

NñÏj

ê¢Þ.

6RRS
9:;<=
:TP79    >?@AB:A     >CD=:10070435(2015)05109308
犆犺犪狉犪犮狋犲狉犻狊狋犻犮狊犪狀犱犃狆狆犾犻犮犪狋犻狅狀狅犳犌犉1犐犿犪犵犲犻狀犌狉犪狊狊犾犪狀犱犕狅狀犻狋狅狉犻狀犵
WANGLei1,2,GENGJun1,YANGRanran1,TIANQingjiu1,YANGYanjun1,ZHOUYang1
(1.InternationalInstituteforEarthSystemScience,NanjingUniversity,Nanjing,JiangsuProvince210093,China;
2.KeyLaboratoryforRestorationandReconstructionofDegradedEcosysteminNorthwesternChinaofMinistryofEducation,
NingxiaUniversity,Yinchuan,Ningxia750021,China)
犃犫狊狋狉犪犮狋:InordertoevaluatethemonitoringabilityofGF1imageingrassland,onthebasisofanalysisof
thecharacteristicsofthebandsetting,radiometricandspectralresponsecoefficientofsensor,thedistribu
tedinformationwasextracted,andthevegetationindexofgrasslandwascalculated.Withthecombination
offieldmeasuredspectrum,vegetationcoverage,leafareaindexandabovegroundbiomassdata,thebest
vegetationindexforgrasslandparameterswasestimated.Theoptimalmodelwasdeterminedaccordingto
犚2and犚犕犛犈 (rootmeansquareerror).TheresultsshowedthatGF1sensorskeptconsistencyinband
setcomparingwithothersensors.Theimprovementofspatialresolutionenhancedtheidentificationability
ofobjecttypes,andtheimprovementofradiationresolutionenhancedthelevelsofdata.Thespectralre
sponsecoefficientscoveredbetterthespectralcurvesofdifferenttypesofgrassland.Thecorrelationofdif
ferentgrasslandvegetationparametersandGF1vegetationindexreachedahighlevel,andmettheneeds
ofremotesensingestimationorinversion.Theregressionanalysesshowedthatthebestestimationmodel
for犔犃犐andthebiomassofthegrasslandwerecubicpolynomialregressionmodelbasedon犚犞犐(ratioveg
etationindex),andthebestestimationmodelforthevegetationcoverageofthegrasslandwerepower
functionmodelbasedon犖犇犞犐(normalizeddifferencevegetationindex),andthegoodmappingeffectof
theresearchregionwasobtained.
犓犲狔狑狅狉犱狊:GF1sensor;Vegetationindex;Grasslandmonitoring;Remotesensingestimation;Image
characteristics
EFGH
:20140902;IJGH:20141211
KLMN

¬­°•C*IJ
(30Y20A01900312/13);|Án<˜™¬­C*°+˜™Áز³[’(2010CB951503);¬­C:‡Ã
˜™@kÁØ
(973ÁØ)[’(2012CB723206);¬­“rÛÈ”°•ÉÊÁØ[’(2011BAC07B03)´ µ
OPQR

;:
(1980),¸ ,°ÞÙ}»,ƽ,¤˜,¾D¿À8 8:ê¢˜™,Email:WL8999@163.com;ÇÈÅÆ Authorfor
correspondence,Email:tianqj@nju.edu.cn
  +¬ð•=!B“ìz‰5Kñ°j”AÀC*
IJ+

ìzAÄÇî+B\DZ+áRÇîìz
Š™©Sá•ñjU

;lp½ž¥ðà

¦•ñP
æ n<

®¯´†Ïj

FŽùë¥Þ†:FŽ
! " # $ !23"
n
W•Ýܸ¨ø5
|Á¸¨‚

ê¢[ŠÓ5Þ.8 Ùæšp†Ò
Qn[14]。
NñÅG_…‚zÎv
G./B8 yQ’Š

•|ÁƽF+ŒCD
Å¥=ñY
[5],
0¬¢c¯Nñ#4òha,6_
…!2Y,5Še«ÇÒ=BNñ´†*¬[6],Nñ
:úç†Ò@qšpBé:8Þ.5ÝÜÆL¼Ï
j

OúG|RÖB•–‡Ã



Nñ8 š
pŒš›B6“oùg=““Qg

j¦áG
ìzŠ™ÇîCDBž¥@Ü

8 «p5KñP8 h>B”œ

i=(
VB¨ë

 ./ž¥•|Á8ÝÜñPšp˜™
+
[7],Tueler[8]¦1989$AÀñˆHꢕ–
•NñX+Bž¥
。B.F.Taylor[9]KZ3 N
ñ,N:uBîà=$
NOAA´‘↓;*/ÂNñ,N:uBî
à=$
8,N%:uëBƒ@ApÄ
Å0.81。¶|![10]¥ NOAA/AVHRR´‘K
Zbž„2BNÞ;iHÏj





Þú

Ã
Kîà,–†Oë;iHL¼z{

Öð0!
[11]
zÆKZb4¤ñÝ=‚œc·ÚçñÝNÞ;i
Hê¢Þú

ö{Ž
[12]
*¥NOAAp½8ñ/X
ŒjëB±†8:ú紑

;i*/ÂNñê¢
ÞúB•–

Ã}‚œcÃóNÞGÊ

;iHž
¥

P=H3•–B|¥g=|6Åg

#$…

*
ë+ÆUkHWX¢‰B8 Ïjâç¥ô˜
™

ÖR!
[13]
‡¦ HJ1Çîp½Þ.H2010$Å
kçNñB8 :úç

PJH HJ1Çîp½G
Nñ:úçÏjΏH쓓=ì6“z‰5Bp
½†
。LiP[14]!KÈz{H LandsatETM+=
OLI2e¢‰B~àDog,lmPJK¦8 
yQˆÎ
,OLI•#as~àBõì¦ETM+。;
a«!
[15]
}¥ôïô†ÝBNñG˜™K_


KÈH4¥Š™

FŽî=LandsatTM ¢‰•
Nñæç¨

©/«p=ñ‚:9ëÞ.N/B
Do=âç

ìzŠ™ÅG+¬ìzAÄÇî+B
\DZ+¢‰

¬Fz{Ò¢‰RgÃ¥ôÒ
•NñÏj@ÜBž¥Ýç

}ìzŠ™6RGp½†

z{Ò~àæZ

±
†7ž©p=)*z‰5!RS

ÎxNñzÎh
>

Á.WX8 «p

l@ñ/XŒ°jBNñ±
†

:9ë

æç¨

Ùæì¨=©/«p
(leaf
areaindex,LAI)!=jp½,LJƒ@z{§Œv
z8 «p

ð„78éQ

Þ.ÃôL˜™Ý1N
ñšpB6“zÎ×

ƒ•¥ôìzŠ™Â¢‰B
NñÏjâç

Ã%ðNñšpBê¢Þ.éQ

G
ìzŠ™Â¢‰•NñÏj@ÜBž¥Îš>

ÐK¦Nñ:uh>Ïj

Nñ,XŒCDVÛ

1 STYUV
1.1 ”•–—˜
˜™Ý
(N43°26′,E116°40′ ,L – 3 4
1236m)Y¦+¬‚œc®@ÝB+4¤ñÝ,
£Š¶O‡O£¨Ž‚BÄ{kNÞ

5+¬°
+0ê¢8pBñÁ˜™]¦2006$µkB‚
œc•ñk¬8:=gIVê¢UV–ñ
[16],
ñ
PLK

Ãz΍‚œc!Ù*©äÄ<©

K
Ü/Â240km2,}1QNÞG¾\,¼½2012
$8%=2013$8%B2üNñR¦p½—
ó

8 ¾DOPDp
(犛狋犻狆犪犽狉狔犾狅狏犻犻)、*D
p
(犛狋犻狆犪犵狉犪狀犱犻狊)、RN(犔犲狔犿狌狊犮犺犻狀犲狀狊犻狊)、T^
QN
(犃犵狉狅狆狔狉狅狀犮狉犻狊狋犪狋狌犿)= B 2 (犃狉狋犲犿犻狊犻犪
犳狉犻犵犻犱犪)!àá。
1.2 [¬›R
¼½CËJxB˜™Ý HJ1CCDp½B8Š
<8 «p
(normalizeddifferencevegetationin
dex,NDVI)Á.lm,ŒxWX:uh>BNñÏ
j&ñ

Ïj&ñ*wG16m×16m,”e&ñ‚
?KãmNL

!žŸæZ3e1m×1mBÏj
&N

Uk±†*5
、LAI、æç¨、:9ë!«¬
B°j

Ñ¥ MobileMapperCXÐՀ GPS±²
GPS{¬:。°j““G2013$7%31+—8%
6+,¼½Ì#86RR®B˜¹=p½BS(g,
ƒµki&ñ50e¥¦p½z{。
1.3 (¬ÍZtmƒÍf°
”c10∶30—14∶30ŒcðÂô“à‚,B
§”e&ñ‚1m×1m&T:B±†p½,B¥
ASDªe(AnalyticalSpectralDevices)BÁí±
†ð Fieldspec4;ijë,±†qr325~2500
nm,±†z‰5•~u350~700nmG3nm,700
~1400nmG10nm,U–ãG25°。•”ü°j0
Ë;iêh—ð

°jIE]Óñ/Z¦&:+5
:‚N1.5mYZ,”e&T:±²5±†p½
xL–õ

4901
!5# ; :!:ìzŠ™Çî6RRS†Ò•NñÏj+Bž¥
:1 ”•–uR、犌犉1犠犉犞4 r¥sf[¬µ;™
Fig.1 Locationsofstudyareaandsampleplots
1.4 (¬uh0Îf
Nñ:9ëB¥ÜÇÌ]CBNÓJx


æç¨Bjë8±†XŒ;i

B¥pŠƒ›T}
Ó

•ñPòZ1m×1m&NÏ,¦pŠƒ›]Ó
LšZ¦&N+5:‚N

R(ƒ›ì¨

}|¤—
ó&NÏG»

}&NÏG¡…KJxBƒ®;i
õ˜

¥ê¢×RzyBNÓ

Jxæç¨p½

NñLAIBjëB¥LiCORªeB89Ù
æz{ðLAI2000;i,Eð‰jë‡/+Wâ
E(àÓ*±67BKL

Œx÷c

+

+—!
“à;ijë

ÃûP8±†j듓“•WЇ
48h。Œx270°öçQ,”e&T:jë0,Ëjë
c6±±²G犃õ,¯ ̕NñÙæšjë3ü±
²G犅õ,LJ¿‘FV22001.0;iLAIj.。
1.5 vw rhi0ñZYjk
]ŒxBìzŠ™p½GGF1WFV4¢‰


Jx““G2013$7%30+,K¦Nñ8 
ˆÎ

|UGXŒp½

©üȶCP1]ó,â^
è͘™³¬BFD

\1 vw rhi
Table1 Theimageacquisitioninformation
¢‰
Sensor
+#
Data
““
Time/UTC
(àctã
Solarzenithangle/°
(àNYã
Solarazimuthangle/°
°jctã
Sensorzenithangle/°
°jNYã
Sensorazimuthangle/°
GF1WFV4 2013730 03h42m 26.1747 158.4 54.0402 286.6640
  *ð—ðB¥ENVI5.0+BFLAASHéŠ,
Ò*ð—ð.Ó5‡¦ MODTRAN4+)*Âê
éQU@B

O‡¦RF€B—ð

B¥k¬Ap
KÞÎ×R;i)*k¬ÌNlFLAASH éQ,
]FB‡Tšp…†¦6RE˜‘=+¬´†Çî
+5
[17],
Ò+

*ðéQŒB+i¨Þî

ðk{
éQŒBRural(:Ä),ë¦p½5•Â¢‰õ
ǏâšJxB

E£æZHctã=NYãȶ

K(‡*ð—ðÌB˜™Ý6R

B¥"s=
jGPSÖL:;iÔ±´—ð,ÖL:B§Ñ¥
MobileMapperCXì´¨ßüGPSSá,|Ώ=
“ÐՀBkY´¨

B¥Ûü‹²ÂéQ

K6
Rp½;iÔ±´—ð

—ð0DÖL•1eR®


ÃKÔ±—ðÌB×R

;iH"s=ñ´¨
VP

}ûP&ñ6“ȶ=6RWEÔ±YZ0
DB67

1.6 *^4h
8 «p
(vegetationindex,VI)5ë‹~àp
½(mg]mmgà@ˆá

|¥¦K8 ©/
«p
(LAI)、æç¨、:9ë、±@i)*ÏÐ
A p
(absorbed photosynthetic active radiation,
APAR)!ŠAÄ8 šp;iÞj8©Bê¢
šp
[18]。
¼½ƒ@˜™˜§

ŒxH6Yn¥8
 «p¥¦¥ôìzŠ™ê¢p½BNñÏ
jâç

5901
! " # $ !23"
\2 xyÆ*^4h0œôzØ
Table2 Vegetationindexformula
«]
Name
Á.ªÂ
Formula
…†
Origin
犇犞犐 犖犐犚-犚犈犇 [19]
犚犞犐 犖犐犚/犚犈犇 [20]
犚犇犞犐 (犖犐犚-犚犈犇)/ (犖犐犚+犚犈犇槡 ) [21]
犖犇犞犐 (犖犐犚-犚犈犇)/(犖犐犚+犚犈犇) [22]
犛犃犞犐 (1+犔)(犖犐犚-犚犈犇)/(犖犐犚+犚犈犇+犔)犔=0.5 [23]
犕犛犃犞犐 (2犖犐犚+1- (2犖犐犚+1)2-8(犖犐犚-犚犈犇槡 ))/2 [24]
  ò:犇犞犐Dõ8 «p;犚犞犐Èõ8 «p;犚犇犞犐C8Š<8 «p;犖犇犞犐8Š<8 «p;犛犃犞犐ËÌRà8 «p;犕犛犃犞犐~¿
QËÌR(8 «p
;犖犐犚#as~à;犚犈犇a±~à
Note:犇犞犐differencevegetationindex,犚犞犐ratiovegetationindex,犚犇犞犐renormalizeddifferencevegetationindex,犖犇犞犐normalized
differencevegetationindex,犛犃犞犐soiladjustedvegetationindex,犕犛犃犞犐modifiedsoiladjustedvegetationindex,犖犐犚nearinfraredband,
犚犈犇redband
2 lmY;n
2.1 #;0=pq rhi0KR./
GF1ÇîL†H2Â2mz‰5|Þ/8mz
‰5‹±†ƒ›
,4Â16mz‰5‹±†ƒ›。•
ì6“z‰5

‹±†8쓓z‰5l@B±+
ꢕ–

‹†J×RöAu@•–

ì´¨ìÇk
¨÷ÖL•–!N/BÎì
[8],
Gp½ùëBÇ
k†Òž¥ÎH‡Ã
。GF1WFV4‹±†Â¢
‰8 HJ1B CCD1,Landsat8OLI = Landsat7
ETM+¾Dšp†ƒž~àBKÈ,lmCP3


\3 犌犉1犠犉犞4,犎犑1犅犆犆犇1,犔犪狀犱狊犪狋8犗犔犐,犔犪狀犱狊犪狋7犈犜犕+ r%¸{(uh%.
Table3 ThekeypropertyofGF1WFV4,HJ1BCCD1,Landsat8OLIandLandsat7ETM+
¢‰
Sensor
Cøu#
Return
period/d
6“z‰5
Spatial
resolution/m
~àp
Numberof
bands
)*z‰5
Radiometric
resolution/bit
3
Blue
´
Green
a
Red
#as
NIR
GF1WFV4 4 16 4 10 0.45~0.52 0.52~0.59 0.63~0.69 0.77~0.89
HJ1BCCD1 4 30 4 8 0.41~0.52 0.52~0.60 0.63~0.69 0.76~0.90
Landsat8OLI 16 30 9 12 0.45~0.51 0.53~0.59 0.64~0.67 0.85~0.88
Landsat7ETM+ 16 30 8 8 0.45~0.52 0.52~0.60 0.63~0.69 0.77~0.90
2.1.1 ^êи GF1WFV4‹±†Â¢‰B~
àæZ8Ò~®¾Çy„

C HJ1A/B
CCD,ZY3MUX,CBERSCCD!,–G4e~à(î
3
、´ 、
a=#as
),
8Landsat7ETM+Kž~à‡
TŠX

ø•´±=#as~àüœDÆ

ˆ8
Landsat8OLIƒÈ,•a±=#as~àDƚ*,
¾Dë¦OLI¢‰*ÚÐõH~àB±†qr。
2.1.2 ¹º»»" •)*z‰5N/,GF1
WFV4¢‰BÈùÈÕŊk/¨B¿“,ÑÕ
Ò)*z‰5ÎìÅH10bit,ì¦ HJ1A/BCCD
=Landsat7ETM+B8bit,ñ›H6RB³¨ë


wÚ¦Landsat8OLI¢‰B12bit。
2.1.3 >¼$K½‘ ¢‰1~àE®‰‘R
gB67

•Rk±†Ý“K±†)*B7žâç
WX

|¥±†7žAp;ikë¾s

±†7žA
pK8 «pŒWX/¨B67

GHz{
GF1WFV4±†7ž©pRg,¦Ò8 HJ1B
CCD1,Landsat7ETM+=Landsat8OLI¢‰
;iKÈ

Ãl@˜™Ý¾DNñyQ=j±†K
m;iz{

ë×2|ì,Nñ8 šp©+CD
BÔe~àYZ–ÕÅHšïB\A

¾DPA
•
,´
±~àB+5~uîY¦â^CïPS8 
©®‚¤©´F*B0.55μm ­#;•a±~
à

J—ñ H7žApìõÝÜBqr

ɕ©
´FB›óÏÐ$0.68μm­#ÑÕ7ž/¨Ä
Åv*

ƒK¦Landsat7ETM+,a±~àB‚K
J—ß#

ƒK¦ HJ1BCCD,‚KYZ7ž/¨
‡TŠX

wñ H¤z



ÝÜ;la±~à

B2NñÙæ*5B



ÝÜ;lÅa±~à
Bqrw¦Dp=RN

Éҩ´FBÏÐ$Y
6901
!5# ; :!:ìzŠ™Çî6RRS†Ò•NñÏj+Bž¥
ZŸA#¦a±~àB7žApŠõ

•#as~
à

ƒK¦Landsat8OLIDoC*,ƒK¦Land
sat7ETM+,Ò7žApBìõqrJ—‘w,¾
D§+•0.79~0.82μm­#,8 HJ1BCCD1B
‚šK‡TŠX

w7žApìõÝÜqrzœñ
*

wF¦3YNñyQÙæ•0.75~0.95μmq
r‚*5fLÂh



•WX¢‰“ÃW*
Aë7žApNXBJ—Do

:2 øw|ÍZ¡¸./¥15(¬+0™fÍZ4q
Fig.2 Spectralresponsesfunctionofdifferentsensorsandthemeasuredcurveofspectrumofmajorgrasslandcommunity
2.2 #;0=pq rhi0(¬sf*tþÿ
2.2.1 «Ž¾ú“”€¶·“‘¿À»¼ G
H§Œ1Nñ«¬Þ.Bvz8 «p

¦Nñ
犔犃犐、æç¨=:9ë3eNñh>«¬8 GF1
WFV46R8 «p;iƒ@z{,lm—ó

P4),1Nñ«¬“88 «p“ƒ@gŒ
š*Do

w–”•â^èÍê¢Þ.B8 «
p

PJGF1WFV48 «pŒš›BNñ«
¬Þjâç
。3eNñÏj«¬+,æç¨81
8 «pBƒ@g`\vì

ƒ@gAp¦
0.53~0.83’“,8 犖犇犞犐Bƒ@Apv*G
0.83,:9ë818 «pBƒ@g`\ƒKš
Ú

ƒ@Ap¦0.35~0.66’“,8犚犞犐B
ƒ@gv*G0.66,犔犃犐818 «pBƒ@A
p¦0.43~0.80’“,v*õG8 犚犞犐B
0.80。
\4 (¬犔犃犐、}ð$ab+°Y犌犉1犠犉犞4 r*^4h0|6‚h
Table4 ThecorrelationcoefficientofGF1WFV4vegetationindexandgrassland犔犃犐,coverageorbiomass
  犖犇犞犐 犇犞犐 犚犞犐 犚犇犞犐 犛犃犞犐 犕犛犃犞犐
©/«p
犔犃犐
0.71 0.50 0.80 0.62 0.43 0.57
æç¨
Coverage
0.83 0.61 0.82 0.74 0.53 0.67
:9ë
Biomass
0.55 0.40 0.66 0.49 0.35 0.46
2.2.2 «Ž¾ú­q•Á1 ¼½ƒ@z{lm,
Œx81Nñ«¬ƒ@gv*B8 «p;i78
z{

zÆð„8 «p8犔犃犐、æç¨、:9ë’
“B78éQ

P5),Ô½Mƒ@ApBLN犚2 =
犚犕犛犈µkvzÞ.éQ。Nñ犔犃犐BvzÞ.
éQG‡¦ GF1WFV4RVIBÙü‹²ÂéQ,
Ò犚2 G0.708,犚犕犛犈 G0.369;Nñæç¨B1
éQ犚2 õmnA#,v*õG‡¦ GF1 WFV4
NDVIB«©péQ,Ò 犚2 G0.699,犚犕犛犈 G
8.877;Nñ:9ëB1éQ犚2 õƒKšÚ,w‡
¦GF1WFV4RVI:@BÙüN/´¨vì,犚2
G0.689,犚犕犛犈G948.46kg·ha-1。
7901
! " # $ !23"
\5 犌犉1犠犉犞4 r*^4hY(¬犔犃犐、}ð$ab+°0Jr×o
Table5 TheregressionmodelofGF1WFV4vegetationindextograssland犔犃犐,coverageorbiomass
Þ.«¬
Estimate
index
8 «p
Vegetation
index
éQ
Model
ÈkAp
犚2
–N¼0D
犚犕犛犈
©/«p
犔犃犐
犚犞犐
狔=0.3908狓-0.9109 0.636 0.412
狔=0.0662狓2-0.341x+0.9843 0.703 0.372
狔=0.0108狓3-0.1258x2+0.7258x-0.8594 0.708 0.369
狔=0.1658e0.3357狓 0.595 0.376
狔=0.0603狓1.7113 0.588 0.403
狔=1.8788ln(狓)-1.9003 0.559 0.453
æç¨
Coverage
犖犇犞犐
狔=172.63狓-47.837 0.690 8.912
狔=178.65狓2-56.52狓+24.388 0.695 8.844
狔=2108.6狓3-3955.6狓2+2616.1狓-544.46 0.698 8.883
狔=9.471e2.8879狓 0.698 8.874
狔=138.37狓1.8303 0.699 8.877
狔=108.58ln(狓)+112.13 0.681 9.041
:9ë
Biomass
犚犞犐
狔=808.72狓-355.68 0.438 1275.07
狔=272.31狓2-2203.5狓+7445.1 0.621 1047.30
狔=100.82狓3-1512狓2+7715.8狓-9697.1 0.689 948.46
狔=1383.2e0.1825狓 0.385 1194.89
狔=855.18狓0.8887 0.347 1326.86
狔=3710.9ln(狓)-2108.4 0.351 1370.63
2.3 K@#;0=pq r0(¬*^uh~ô
YÔ:
B¥/LK_zÇBNÓ

‡¦ GF1WFV4
6RÕؙÝנȶ

LJ»›öJ

¿l˜
™ÝæçyQ

×3a),ëNñ、µñ、K\、6®:
=¦ñ!5YËñæçyQ。ë¦ìzŠ™Çî6
R6“z‰5=)*z‰5BÎì

1Ëñæçy
Q× ŒÞŒDoJ—

UXRS"†¡…<
‹!¿lãä



‡ !mhñ9B‚Æâçq
*Ú¨Îì

PAG}ø•30m=19.5mz‰5
‚šù‚ÆBNñ× ‚Bò,LJ

•ìzŠ™
6R‚lâÕŚïB‚Æ=ô×

¦(‡*ð—ð!C^XÌBìzŠ™6Ra
±=#as~àRlENVI5.0,zÆÁ.犖犇犞犐
=犚犞犐,Œx%ðB1NñÏj«¬BvãÞ.
éQ

pµBandmath.Œ,Þ.(e˜™ÝB
Nñ犔犃犐、æç¨=:9ë(×3b,3c,3d)。l
m—ó

1Ïj«¬”•J—B6“oùg

LJK
1Ïj«¬;iz€ÀÁ

Nñ犔犃犐BõÜqr¾
Dz Î • 0~3 ’ “,Ò +,犔犃犐 • 0~1 Ù
24.07%,1~2Ù45.46%,2~3Ù9.50%,æç¨
KLšì

I@1QNñBæçRS

õÜqr¾D
zΕ40~100’“,Ò+,æ稕40~60Ù
12.72%,60~80Ù47.29%,80~100Ù17.88%,
Nñ:9ëBõÜqr¾DzΕ2000~6000
kg·ha-1’“,Ò+,:9ë• 2000~4000 Ù
34.53%,4000~6000Ù35.62%。X“,1Ïj«
¬lm×B6“KÈ

|}~

Nñ:9ë=
犔犃犐•6“‚BzÎRSŠXgšì,ˆNñæç
¨8Ûƒ“B6“zÎRSŠXgƒKšÚ

Ð
¾D5ëNñÙæì¨BDogNX

3 ~
  *¥GF1WFV46Rð„BNñšpÞ.é
Q

҃@Ap–*¦0.6,Ð8©Xy¢‰B
Þ.âçA#
[15,30],
GNñê¢ÏjBΏHZB
p½†
,¯
ˆ

WX¢‰ñ‡ì¨

6“z‰5

±
†z‰5

±†7ž©p!Do†Jxp½B““
=6“WX

Òp½BŠXg=ƒ@gPAW
Š
[26],
•*¥‹†p½ÂXUkXŠÝÜNñ:u
h>78Ïj“

FDKWX¢‰p½;iŠX
gz{

ÃVPéQB´¨

•ìzŠ™Çp½B^X‡/+


5*ðúðFà

ŒxH¬»*ðéÂ

Ðäj*&
…WX““Jxp½BWµkg



ìzŠ™Ç
õÇáRâ

*Ú¨ÎìHp½æçâç=
"@À‘Bž¬âç

wõǽêB°jã¨n<

ŠN/

ñ HÔ±´—ðBù¨

½êéQz{p
½B0D

hŠN/

WX“#JxƒXñ9p½B
8901
!5# ; :!:ìzŠ™Çî6RRS†Ò•NñÏj+Bž¥
ŠXg*d°jã¨Bn<ˆÊÚ
[3132],
NXéQB Ç¥g*ÚÊÚ

FDUkã¨8Š<^X

:3 ”•–(¬;™、犔犃犐、}ð$、b+°lmÔ:
Fig.3 Theimageshowinggrasslanddistribution,LAI,coverageandbiomassinthestudyarea
  T˜™ŒxH˜™ÝNñŠ$+:uvG"Ì
B“#ÅG““à:

UkHñ/XŒ°j

z{H
ìzŠ™Â¢‰BNñÏjâç

Qù†NñB
9ñn[33],
d–ìzŠ™ÇîB•ñ¾i“
“Bñ 

žUkWX9ñ“#BNñšpÞ.8
¢‰Ïjâç¥ô

4 l
ìzŠ™Â¢‰~àæZ8³0•ñ¾iB¤
z¢‰ûüHš›BŠXg

$•a±=#as
~à8Landsat8OLIŠkDÆs,8 HJ1A/B
CCD,ZY3MUX,CBERSCCD,LandsatTM/
ETM+!¢‰B~àæZ‡TŠX;6“z‰5
BÎì

ÑÕËñæçyQBUXRSJ—ñ›

×
 ¡…Ÿ <‹

)*z‰5BÎì

ÑÕp½Bæ
ügJ—ñ›

@á×RBތŸ $%‰Dog
ñ›

â^ÎìNñÏj«¬Þ.B´¨

±†7ž
Ap8¾DNñ8 yQ=j±†KmB:@lm
…~

â^CïñðçWXNñyQ±†KmBn

*¦NñÏjBꢞ¥

w8Ò~¢
‰“l”•WX/¨BDo

•8WX¢‰ƒX
UkNñÏj“

Dz{Ò67/¨

WXNñÏj
«¬8GF1WFV48 «pBƒ@gÄÅHšì
KL

â^èÍê¢Þ.]©BFD

Ɍš
ïBL×im

9901
! " # $ !23"
u>?
[1] ChenJM,CihlarJ.Retrievingleafareaindexofborealconifer
forestsusingLandsatTMimages[J].RemoteSensingofEnvi
ronment,1996,55(2):153162
[2] PuRL,GongP.HyperspectralremotesensinganditsAppli
cation[M].Beijing:HighEducationPress,2000:70
[3] FangH,LiangS.Retrievingleafareaindexwithaneuralnet
workmethod:Simulationandvalidation[J].IEEETransac
tionsonGeoscienceandRemoteSensing,2003,41(9):2052
2062
[4] AnayaJA,ChuviecoE,PalaciosOruetaA.Abovegroundbi
omassassessmentinColombia:Aremotesensingapproach
[J].ForestEcologyand Management,2009,257(4):1237
1246
[5] ScurlockJ,HalD.Theglobalcarbonsink:agrasslandPer
spective[J].GlobalChangeBiology,1998,4(2):229233
[6] N´ì,f®@,٘a,!.+¬Nñ:AÀƆÒn<
[J].+¬°+·:¼°+,2010,53(7):757765
[7] ڛ*,Öw˜,;Lñ,!.këê¢XÍ8.Ó[M].4¥:
°+¡¢
,2013:321322
[8] TuelerPT.Remotesensingtechnologyforrangelandman
agementapplications[J].JournalofRangeManage,1989,42
(6):442453
[9] TaylorBF,DiniPW,KidsonJW.Determinationofseasonal
andinterannualvariationinNewZealandpasturegrowthfrom
NOAA7data[J].RemoteSensingofEnvironment,1985,18
(2):177192
[10]¶|,ÇÐî,Úcz.NOAA/AVHRR´‘¥¦NÞÏj
B˜™
[J].+¬()´†8ÝØ,1998,5(5):2933
[11]Öð0,yL.*¥ê¢FŽ´‘;iNÞ*/ÂÞú˜™
[J].N)°+,1996,13(2):1420
[12]ö{Ž,ÖÆ,֍H.*/ÂNñê¢Þú•–˜™[J].N
ñ+w
,1994,2(1):913
[13]ÖR,;Xø,Y˜,!.} HJ1Çîê¢p½Þ.ìæNñ
8 S!Šg:úçBÝç¥Þ

}ÅkçNñGÊ
[J].+
¬ôx
,2013,33(4):12501255
[14]LiP,JiangLG,FengZM.Crosscomparisonofvegetation
Indicesderivedfrom Landsat7enhancedThematic Mapper
Plus(ETM+)andLandsat8OperationalLandImager(OLI)
sensors[J].RemoteSensing,2014,6(1):310329
[15];a«,ÖÔé,Hê,!.4¥Š™,FŽî,LandsatTM Â
¢‰Þ.Nñæç¨

©/«p

ñ‚:9ëȚ˜™
[J].
±†+8±†z{
,2013,33(10):28032808
[16]ì3[,mi@,-ø,!.‡¦‚œUV–ñBk¬Ap:=
gIVNӘ™8Wµkgz{
[J].+¬°+:ñÁ°+,
2013,43(2):287294
[17]+¬Çž¥+5.ÑñÇîˆ[EB/OL].http://
www.cresda.com/n16/n1130/index.html,2014/1/6
[18]õRJ,ûˆŽ.8 «p˜™;kñÁ°+;k[J].ñÁ°
+;k
,1998,13(4):327333
[19]RichardsonAJ,WiegandCL.Distinguishingvegetationfrom
soilbackgroundinformation[J].PhotogrammetricEngineering
andRemoteSensing,1977,43(12):15411552
[20]JordanCF.Derivationofleafareaindexfromqualityoflight
ontheforestfloor[J].Ecology,1969,50(4):663666
[21]RoujeanJL,BreonFM.EstimatingPARabsorbedbyvege
tationfrombidirectionalreflectancemeasurements[J].Remote
SensingofEnvironment,1995,51(3):375384
[22]RouseJW,HaasRH,DeeringDW,犲狋犪犾.Monitoringthe
vernaladvancementandretrogradation(greenwaveeffect)of
naturalvegetation[R].ProgressReportRSC19731,Remote
SensingCenter,TexasA&MUniversity,1973:7576
[23]HueteAR.Asoiladjustedvegetationindex(SAVI)[J].Re
moteSensingofEnvironment,1988,25(3):295309
[24]QiJ,ChehbouniA,HueteAR,犲狋犪犾.Amodifiedsoiladjus
tedvegetationindex[J].RemoteSensingofEnvironment,
1994,48(2):119126
[26]fâ,;"â,¶3â,!.HJ1ACCD8 TM p½†ÒÞ.
NñLAI=e:9ëimȚz{[J].ê¢+w,2012,16
(5):10001023
[27];¸0,Öp9,âZ¬,!. NOAA18/AVHRR8FY3A/
VIRRBOLRúGŠXg=Dogz{[J].ê¢+w,2013,
17(5):13111323
[28]Öd,mi@,©ùõ,!.WXÇî†JIjNDVIgâDo
z{†n3špµk
[J].+¬°+:ñÁ°+,2012,42(2):
238245
[29]¶Ú,n°Š,;‰=.WX¢‰Bé:8 «pKK:©
/«pBÞj´¨=¡¢gz{
[J].ê¢+w,2008,12
(1):143151
[30]ÖFH,ÖÔB,ßÌ,!.‡¦8 «pB1QNÞÝ:9ë
éQ

}‚œcãµR¶GÊ
[J].8 :+w,2007,31
(1):2331
[31]GaoF,SchaafCB,StrahlerAH,犲狋犪犾.Detectingvegetation
structureusingakernelbasedBRDFModel[J].RemoteSens
ingofEnvironment,2003,86(2):198205
[32]MÔJ,’H“.ëÜýN–B‹ã¨‹~à*5ê¢éQ
[J].ê¢+w,2005,9(4):337342
[33]HmiminaaG,DufrêneaE,PontaileraJY,犲狋犪犾.Evaluation
ofthepotentialofMODISsatelitedatatopredictvegetation
phenologyindifferentbiomes:Aninvestigationusingground
basedNDVImeasurements[J].RemoteSensingofEnviron
ment,2013,132:145158

%&( , -)
0011