Integration of high-resolution multispectral and coarse-resolution multitemporal imagery of Mediterranean forested area

Agustin Lobo; Nicolau Pineda

doi:10.1117/12.413949

23 January 2001 Integration of high-resolution multispectral and coarse-resolution multitemporal imagery of Mediterranean forested area

Agustin Lobo, Nicolau Pineda

Author Affiliations +

Proceedings Volume 4171, Remote Sensing for Agriculture, Ecosystems, and Hydrology II; (2001) https://doi.org/10.1117/12.413949
Event: Europto Remote Sensing, 2000, Barcelona, Spain

Abstract

Annual cycles of vegetation index calculated from time sequences of satellite images at resolutions ranging from 1 to 8 km. are a useful proxy of the phenology of light interception, and are being used as an input for bio-geospheric models and landcover charts at global, continental and regional scales. Measuring the annual course of light intercepted by vegetation at a finer scale would have important practical consequences. The core of human action on the environment is undertaken at the landscape and district scales and an important part of the spatial variance is within resolutions finer than the coarse (~1 km2) pixels of cunent multi-temporal imagery. Time series of vegetation index at landscape and district scales would provide dynamic information on vegetation at the scale that is required for management. High-resolution images have an appropriate spatial scale but do not offer the required acquisition frequency. The integration of coarse but frequent imagery and the highresolution imagery is necessary. We have approached the integration of multi-temporal VEGETATION images into products derived from the high spatial resolution images in a forested Mediterranean landscape. Our results show that high-resolution imagery and frequent, coarse-resolution imagery provide complementary information.

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Agustin Lobo and Nicolau Pineda "Integration of high-resolution multispectral and coarse-resolution multitemporal imagery of Mediterranean forested area", Proc. SPIE 4171, Remote Sensing for Agriculture, Ecosystems, and Hydrology II, (23 January 2001); https://doi.org/10.1117/12.413949

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KEYWORDS

Vegetation

Spatial resolution

Image resolution

Image segmentation

Composites

Atmospheric corrections

Earth observing sensors

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