Building Long-Term and Consistent Vegetation Index Based on Association Analysis between Different VI Products

Zong Yao Sha; Yong Fei Bai

doi:10.4028/www.scientific.net/AMR.518-523.5261

Paper Titles

The Comparison of the Community Features between the Constructed Wetland and the Natural Wetland in Nansi Lake
p.5238

The Study on the Conservation Status and Problems of Aquatic Ecosystem in Songhua River Basin
p.5244

Effect of Limited Irrigation on Growth and Water Use of Jatropha curcas L.
p.5251

Research on the Algorithm of Prevention Forest Fire Disaster in the Poyang Lake Ecological Economic Zone
p.5257

Building Long-Term and Consistent Vegetation Index Based on Association Analysis between Different VI Products
p.5261

Development and Matured Structure Variation of Ovule from Autotetraploid of Robinia pseudoacacia
p.5267

Discussion on Afforestaion Techniques in Salt-Alkaline Soil in Northern Ningxia
p.5276

Landscape Quality Evaluation on Scenic and Recreational Forest of Pinus tabulaeformis in Beijing Xi Mountain
p.5281

Palm Species on the Application of Landscape Garden in Hainan
p.5285

HomeAdvanced Materials ResearchAdvanced Materials Research Vols. 518-523Building Long-Term and Consistent Vegetation Index...

Building Long-Term and Consistent Vegetation Index Based on Association Analysis between Different VI Products

Abstract:

The dynamics of vegetation cover plays an important role in global environment evaluation. Due to the spatial, spectral and radiometric differences among different remote sensing platforms, building long-term and consistent vegetation index (VI) time series is desired to derive comparable vegetation health. In this paper, an approach called Min_Max stretch transformation (MMST) was proposed to generate long-term and consistent VI series based on spatio-temporal association analysis between AVHRR NDVI and MODIS EVI. The proposed approach intended to map AVHRR NDVI to MODIS EVI level and thus both VI products provided consistent VI series. The consistency of the transformed dataset was further evaluated.

You might also be interested in these eBooks

Advances in Environmental Science and Engineering

View Preview

Info:

Periodical:

Advanced Materials Research (Volumes 518-523)

Pages:

5261-5266

DOI:

https://doi.org/10.4028/www.scientific.net/AMR.518-523.5261

Citation:

Cite this paper

Online since:

May 2012

Authors:

Zong Yao Sha, Yong Fei Bai

Keywords:

AVHRR, EVI, MODIS, Vegetation Cover, Vegetation Index

Export:

RIS, BibTeX

Price:

Permissions CCC:

Request Permissions

Permissions PLS:

Request Permissions

Сopyright:

Citation:

References

[1] X.M. Xiao, Q. Zhang, B. Braswell, et al. Modeling gross primary production of temperate deciduous broadleaf forest using satellite images and climate data. Remote Sensing of Environment, Vol 91 (2004), 256–70.

DOI: 10.1016/j.rse.2004.03.010

Google Scholar

[2] Y. Song, M. Ma, F. Veroustraete. Comparison and conversion of AVHRR GIMMS and SPOT Vegetation NDVI data in China. International J. of Remote Sensing. Vol 31 (2010), 2377-2392.

DOI: 10.1080/01431160903002409

Google Scholar

[3] B. Matsushita, W.Yang, J. Chen, Y. Onda, G. Qiu. Sensitivity of the Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI) to topographic effects: a case study in high-density cypress forest. Sensors, Vol 7 (2007), 2636–2651.

DOI: 10.3390/s7112636

Google Scholar

[4] A. Huete, K. Didan, T. Miura, E. Rodriguez, X.Gao, L. Ferreira. Overview of the radiometric and biophysical performance of the MODIS vegetation indices. Remote Sensing of Environment, Vol 83 (2002), 195-213.

DOI: 10.1016/s0034-4257(02)00096-2

Google Scholar

[5] Z. Jiang, A. Huete, K. Didan, T.Miura. Development of a two-band enhanced vegetation index without a blue band. Remote Sensing of Environment, Vol 112 (2008), 3833-3845.

DOI: 10.1016/j.rse.2008.06.006

Google Scholar

[6] G. Li, G. Jiang, Y. Li, M. Liu. Biomass carbon storage and net primary production in different habitats of Hunshandake Sandland, China. Acta Ecologica Sinica, Vol 31 (2011), 217–224.

DOI: 10.1016/j.chnaes.2011.04.006

Google Scholar