Multiscale Analysis of Landscape Spatial Heterogeneity Using Vegetation Indexes

DOI

10.2991/rsete.2013.147How to use a DOI?

Keywords

Spatial heterogeneity, variogram, spatial resolution, NDVI, DVI

Abstract

Remote sensing provides multiscale image data to monitoring the earth surface. The spatial heterogeneity of the surface is a function of image scales. It is also affected by various remote sensing variables. This work uses variogram to assess the abilities of NDVI (normalized difference vegetation index) and DVI (difference vegetation index) to exploit the surface spatial heterogeneity. The decay of spatial heterogeneity as pixel size increases is measured and the spatial variability within coarse spatial resolution pixel is calculated. The results show that: 1) NDVI and DVI display a similar ability in detecting the spatial structure. NDVI variogram modeling outperforms DVI modeling in characterizing the spatial variability of the surface; 2)the spatial variability and the spatial structure both follow logarithmic relationships with stronger fits as the spatial resolution decreases; 3) the loss of spatial variability within pixel increases as spatial resolution decreases. Simple aggregation of fine resolution pixels to a coarse resolution engenders loss of image variability.

Copyright

© 2013, the Authors. Published by Atlantis Press.

Open Access

This is an open access article distributed under the CC BY-NC license (http://creativecommons.org/licenses/by-nc/4.0/).

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TY  - CONF
AU  - Ding Yanling
AU  - Zhao Kai
AU  - Zheng Xing-ming
PY  - 2013/08
DA  - 2013/08
TI  - Multiscale Analysis of Landscape Spatial Heterogeneity Using Vegetation Indexes
BT  - Proceedings of the 2013 the International Conference on Remote Sensing, Environment and Transportation Engineering (RSETE 2013)
PB  - Atlantis Press
SP  - 607
EP  - 610
SN  - 1951-6851
UR  - https://doi.org/10.2991/rsete.2013.147
DO  - 10.2991/rsete.2013.147
ID  - Yanling2013/08
ER  -