In:
Photogrammetric Engineering & Remote Sensing, American Society for Photogrammetry and Remote Sensing, Vol. 88, No. 5 ( 2022-05-01), p. 303-310
Abstract:
Accurate ground measurements of fractional vegetation cover (FVC) are key for characterizing ecosystem functions and evaluating remote sensing products. The increasing performance of cameras equipped in smartphones opens new opportunities for extensive FVC measurement through citizen
science initiatives. However, the wide field of view (FOV) of smartphone cameras constitutes a key source of uncertainty in the estimation of vegetation parameters, which has been largely ignored. We designed a practical method to characterize the FOV of smartphones and improve the FVC estimation. The method was assessed in a mountainous forest based on the comparison with in situ fisheye photographs. After the FOV correction, the agreement of smart-phone and fisheye FVC estimates highly improved: root-mean-square error (RMSE) of 0.103 compared to 0.242 of the original smartphone FVC
estimates without considering the FOV effect, mean difference of 0.074 versus 0.213, and coefficient of determination R 2 of 0.719 versus 0.353. Smartphone cameras outperform traditional fisheye cameras: the overexposure and low vertical resolution of fisheye photographs introduced
uncertainties in FVCestimation while the insensitivity to exposure and high spatial resolution of smartphone cameras make photograph acquisition and analysis more automatic and accurate. The smartphone FVCestimates highly agree with the GF-1 satellite product: RMSE = 0.066, bias = 0.007, and R 2 = 0.745. This study opens new perspectives for the validation of satellite products.
Type of Medium:
Online Resource
ISSN:
0099-1112
DOI:
10.14358/PERS.21-00038R2
Language:
English
Publisher:
American Society for Photogrammetry and Remote Sensing
Publication Date:
2022
detail.hit.zdb_id:
2317128-5
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