Assessment of different methods for shadow detection in high-resolution optical imagery and evaluation of shadow impact on calculation of NDVI, and evapotranspiration
Ver/Abrir
Autor/a
Aboutalebi, Mahyar
Torres-Rua, Alfonso F.
Kustas, William P.
Coopmans, Calvin
McKee, Mac
Fecha de publicación
2018-12-03ISSN
0342-7188
Resumen
Significant efforts have been made recently in the application of high-resolution remote sensing imagery (i.e., sub-meter) captured by unmanned aerial vehicles (UAVs) for precision agricultural applications for high-value crops such as wine grapes. However, at such high resolution, shadows will appear in the optical imagery effectively reducing the reflectance and emission signal received by imaging sensors. To date, research that evaluates procedures to identify the occurrence of shadows in imagery produced by UAVs is limited. In this study, the performance of four different shadow detection methods used in satellite imagery was evaluated for high-resolution UAV imagery collected over a California vineyard during the Grape Remote sensing Atmospheric Profile and Evapotranspiration eXperiment (GRAPEX) field campaigns. The performance of the shadow detection methods was compared and impacts of shadowed areas on the normalized difference vegetation index (NDVI) and estimated evapotranspiration (ET) using the Two-Source Energy Balance (TSEB) model are presented. The results indicated that two of the shadow detection methods, the supervised classification and index-based methods, had better performance than two other methods. Furthermore, assessment of shadowed pixels in the vine canopy led to significant differences in the calculated NDVI and ET in areas affected by shadows in the high-resolution imagery. Shadows are shown to have the greatest impact on modeled soil heat flux, while net radiation and sensible heat flux are less affected. Shadows also have an impact on the modeled Bowen ratio (ratio of sensible to latent heat) which can be used as an indicator of vine stress level.
Tipo de documento
Artículo
Versión del documento
Versión aceptada
Lengua
English
Materias (CDU)
631 - Agricultura. Agronomía. Maquinaria agrícola. Suelos. Edafología agrícola
Páginas
40
Publicado por
Springer Verlag
Publicado en
Irrigation Science
Citación
Aboutalebi, Mahyar, Alfonso F. Torres-Rua, William P. Kustas, Héctor Nieto, Calvin Coopmans, and Mac McKee. 2018. "Assessment Of Different Methods For Shadow Detection In High-Resolution Optical Imagery And Evaluation Of Shadow Impact On Calculation Of NDVI, And Evapotranspiration". Irrigation Science 37 (3): 407-429. doi:10.1007/s00271-018-0613-9.
Program
Ús Eficient de l'Aigua en Agricultura
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