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Proceedings Paper

Detecting subtle environmental change: a multi-temporal airborne imaging spectroscopy approach
Author(s): Ian J. Yule; Reddy R. Pullanagari; G. Kereszturi
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Paper Abstract

Airborne and satellite hyperspectral remote sensing is a key technology to observe finite change in ecosystems and environments. The role of such sensors will improve our ability to monitor and mitigate natural and agricultural environments on a much larger spatial scale than can be achieved using field measurements such as soil coring or proximal sensors to estimate the chemistry of vegetation. Hyperspectral sensors for commentarial and scientific activities are increasingly available and cost effective, providing a great opportunity to measure and detect changes in the environment and ecosystem. This can be used to extract critical information to develop more advanced management practices.

In this research, we provide an overview of the data acquisition, processing and analysis of airborne, full-spectrum hyperspectral imagery from a small-scale aerial mapping project in hill-country farms in New Zealand, using an AISA Fenix sensor (Specim, Finland). The imagery has been radiometrically and atmospherically corrected, georectified and mosaicked. The hyperspectral data cube was then spectrally and spatially smoothed using Savitzky-Golay and median filter, respectively. The mosaicked imagery used to calculate bio-chemical properties of surface vegetation, such as pasture. Ground samples (n = 200) were collected a few days after the over-flight are used to develop a calibration model using partial least squares regression method. In-leaf nitrogen, potassium and phosphorous concentration were calculated using the reflectance values from the airborne hyperspectral imagery. In total, three surveys of an example property have been acquired that show changes in the pattern of availability of a major element in vegetation canopy, in this case nitrogen.

Paper Details

Date Published: 25 October 2016
PDF: 7 pages
Proc. SPIE 9998, Remote Sensing for Agriculture, Ecosystems, and Hydrology XVIII, 999813 (25 October 2016); doi: 10.1117/12.2240418
Show Author Affiliations
Ian J. Yule, Massey Univ. (New Zealand)
Reddy R. Pullanagari, Massey Univ. (New Zealand)
G. Kereszturi, Massey Univ. (New Zealand)

Published in SPIE Proceedings Vol. 9998:
Remote Sensing for Agriculture, Ecosystems, and Hydrology XVIII
Christopher M. U. Neale; Antonino Maltese, Editor(s)

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