The Correlation between LAI and Vegetation Index of Masson Pine
FU Yin-Zhen, WANG Xiao-Qin, JIANG Hong
Key Laboratory of Spatial Data Mining & Information Sharing of Ministry of Education，
Spatial Information Research Center of Fujian Province， Fuzhou University， Fuzhou 350002， China
With Yongan City of Fujian Province as the study area, the authors investigated the best VIs for estimating LAI of masson pine. Several VIs were calculated from the IRS-P6(LISS-III) image, which included DVI， EVI2，MSAVI， NDVI， RDVI， RVI and TNDVI. The correlation between the measured LAI of masson pine using LI-COR LAI-2000 and VIs was established， and the effects on the LAI of masson pine were studied. The LAI estimation models based on different VIs were quantitatively analyzed with both R2 and standard error. The estimation models included linear model， quadratic curve model，exponential curve model and power curve model. The results show that there exists curvilinear correlation (exponential correlation or power correlation) between selected VIs and LAI of masson pine. The exponential curve model and the power curve model constitute the best inversion models， and TNDVI， NDVI and RVI are fairly good for inversing LAI of masson pine， in which the R2 of the exponential curve model and the power curve model are all larger than 0.76 and their verification R2 are all larger than 0.84， but the standard errors of RVI's inversion models are much larger than those of the other two models. In general，both the exponential curve model and the power curve model of TNDVI and NDVI can yield good results in estimating LAI of masson pine.
LIU Yang,LIU Shu-bin,LU Zhong-jun, et al. The Correlation between LAI and Vegetation Index of Masson Pine[J]. REMOTE SENSING FOR LAND & RESOURCES,
2010, 22(3): 41-46.
［2］Chen J M，Pavlic G，Brown L，et al. Derivation and Validation of Canada-wide Coarse-resolution Leaf Area Index Maps Using High-resolution Satellite Imagery and Ground Measurements［J］.Remote Sensing of Environment，2001（8）：165-184.
［3］Colombo R，Bellingeri D，Fasolini D，et al. Retrieval of Leaf Area Index in Different Vegetation Types Using High-resolution Satellite Data［J］.Remote Sensing of Environment，2003，86（1）：120-131.
［4］Pandya M R，Singh R P，Chaudhari K N，et al.Leaf Area Index Retrieval Using IRS LISS-III Sensor Data and Validation of the MODIS LAI Product Over Central India［J］. Geoscience and Remote Sensing，2006，44(7)：1858-1865.
［5］Turner D P，Warren B C，Robert E K，et al. Relationships Between Leaf Area Index and Landsat TM Spectral Vegetation Indices Across Three Temperate Zone Sites［J］.Remote Sensing of Environment，1999，70(1)：52-68.
［6］González-Sanpedro M C， Toan T L， Moreno J，et al. Seasonal Variations of Leaf Area Index of Agricultural Fields Rretrieved from Landsat Data［J］. Remote Sensing of Environment，2008，112(3)：810-824.
［7］Eklundh，Lars. Estimating Leaf Area Index in Coniferous and Deciduous Forests in Sweden Using Landsat Optical Sensor Data［C］// Proceedings of SPIE - The International Society for Optical Engineering.2002，4879：379-390.
［13］Wu Jindong，Wang Dong， Bauer M E. Assessing Broadband Vegetation Indices and QuickBird Data in Estimating Leaf Area Index of Corn and Potato Canopies［J］. Field Crops Research，2007，102(1)：33-42.
［17］Zhangyan Jiang，Alfredo R, Huete，et al.Development of a Two-band Enhanced Vegetation Index without a Blue Band［J］.Remote Sensing of Environment，2008，112(10)：3833-3845.
［18］Roujean J L，Breon F M. Estimating PAR Absorbed by Vegetation from Bidirectional Reflectance Measurements［J］. Remote Sensing of Environment，1995，51(3)：375-384.
2010,
Vol. 22
