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A Hybrid Visual Estimation Method for the Collection of Ground Truth Fractional Coverage Data in a Humid Tropical Environment

Citation

Delamater, Paul L.; Messina, Joseph P.; Qi, Jiaguo; & Cochrane, Mark A. (2012). A Hybrid Visual Estimation Method for the Collection of Ground Truth Fractional Coverage Data in a Humid Tropical Environment. International Journal of Applied Earth Observation and Geoinformation, 18, 504-514.

Abstract

A substantial body of research exists exploring the spectral unmixing of remotely sensed image data. Specifically, we refer to the attempts and successes to model the percent vegetation cover (2-dimensional horizontal density) within a pixel, known as fractional coverage (fc). With this paper, we present a hybrid visual estimation method for fc field data collection in the complex landscapes found in humid tropical environments. The method includes a scalable theoretical model of fc, integrates the visual estimation technique with hemispherical photography collection, and is conducted over a systematic ground collection area. We present results from a case study conducted in the humid tropical region of Ecuador. Specifically, we report on the relationship between fc data modeled using a linear NDVI transformation and observed fc data collected using our hybrid visual estimation method. Our study found a significant, positive linear relationship (β=0.795, r2>0.84, and p<0.001) between modeled and observed fc values. Because the accuracy of both modeled and observed values are unknown, a full validation of the proposed method of collection is not possible. Therefore, we conduct an error assessment, identifying limitations in the modeling method (e.g., non-linear relationship between modeled and true values and potential for saturation) and hybrid ground-truth collection method (e.g., subjectivity of visual estimation and positional errors in the ground collection area) that explain the deviation from a 1:1 relationship. We believe the proposed method of ground truth data collection is a significant contribution towards efforts to validate biophysical information gained from remotely sensed data.

URL

https://doi.org/10.1016/j.jag.2011.10.005

Reference Type

Journal Article

Year Published

2012

Journal Title

International Journal of Applied Earth Observation and Geoinformation

Author(s)

Delamater, Paul L.
Messina, Joseph P.
Qi, Jiaguo
Cochrane, Mark A.