Remote sensing is widely applied in the study of terrestrial primary production and the global carbon cycle. The
researches on the spatial heterogeneity in images with different sensors and resolutions would improve the application of
remote sensing. In this study two sites on alpine meadow grassland in Qinghai, China, which have distinct fractal
vegetation cover, were used to test and analyze differences between Normalized Difference Vegetation Index (NDVI)
and enhanced vegetation index (EVI) derived from the Huanjing (HJ) and Landsat Thematic Mapper (TM) sensors. The
results showed that: 1) NDVI estimated from HJ were smaller than the corresponding values from TM at the two sites
whereas EVI were almost the same for the two sensors. 2) The overall variance represented by HJ data was consistently
about half of that of Landsat TM although their nominal pixel size is approximately 30m for both sensors. The overall
variance from EVI is greater than that from NDVI. The difference of the range between the two sensors is about 6 pixels
at 30m resolution. The difference of the range in which there is not more corrective between two vegetation indices is
about 1 pixel. 3) The sill decreased when pixel size increased from 30m to 1km, and then decreased very quickly when
pixel size is changed to 250m from 30m or 90m but slowly when changed from 250m to 500m. HJ can capture this
spatial heterogeneity to some extent and this study provides foundations for the use of the sensor for validation of net
primary productivity estimates obtained from ecosystem process models.
The spatial scaling of satellite data is faced widely and inevitably in remote sensing applications for the spatial
heterogeneity of ecosystems. In this study variogram analysis was used to evaluate the spatial variability and the scale
effects of the Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) from Huanjing
(that is, environment satellite sensor in Chinese, HJ-1A/B), Landsat-5 Thematic Mapper (TM), Moderate Resolution
Imaging Spectroradiometer (MODIS) 250 m, 500 m, 1 km, and the field sampled above-ground biomass (AGB). Results
show that the overall spatial variance decreased when pixel size increased from 30 m (HJ and TM) to 1 km (MODIS) at
the area of 10 km × 10 km. The value of 1 or 3×3 pixels approximately represent the above-ground biomass from the
cyclic sampling design. This indicates that the HJ data can be used to retrieve the biomass and its scaling-up for its
performance comparable with Landsat TM data, though both sensors were applicable than that of MODIS. Further the
method to scale-up is a fundament approach to the validation and application of MODIS products and ecosystem
model’s outputs on regional scale.
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