Abstract
Reflectance indices are a method for reducing the dimensionality of spectral measurements used to quantify material properties. Choosing the optimal wavelengths for developing an index based on a given material and property of interest is made difficult by the large number of wavelengths typically available to choose from and the lack of homogeneity when remotely sensing agricultural materials. This study aimed to determine the feasibility of using a low-cost method for sensing the moisture content of background materials in traditional crop remote sensing. Moisture-controlled soil and wheat stalk residue samples were measured at varying heights using a reflectance probe connected to visible and near-infrared spectrometers. A program was written that used reflectance data to determine the optimal pair of narrowband wavelengths to calculate a normalized difference water index (NDWI). Wavelengths were selected to maximize the slope of the linear index function (i.e., sensitivity to moisture) and either maximize the coefficient of determination (R2) or minimize the root mean squared error (RMSE) of the index. Results showed that wavelengths centered near 1300 nm and 1500 nm, within the range of 400 to 1700 nm, produced the best index for individual samples. Probe height above samples and moisture content were examined for statistical significance using the selected wavelengths. The effect of moisture was significant for both bare soil and wheat stalks, but probe height was only significant for wheat stalk samples. The index, when applied to all samples, performed well for soil samples but poorly for wheat stalk samples. Index calculations from soil reflectance measurements were highly linear (R2 > 0.95) and exhibited small variability between samples at a given moisture content, regardless of probe height. Index calculations from wheat stalk reflectance measurements were highly variable, which limited the usefulness of the index for this material. Based on these results, it is expected that crop residues, such as wheat stalks, will reduce the accuracy of remotely sensed soil surface moisture measurements.
Original language | English |
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Pages (from-to) | 1479-1487 |
Number of pages | 9 |
Journal | Transactions of the ASABE |
Volume | 60 |
Issue number | 5 |
DOIs | |
State | Published - 2017 |
Bibliographical note
Funding Information:This is Publication No. 17-05-083 of the Kentucky Agricultural Experiment Station and is published with the approval of the director. This work is supported in part by the USDA National Institute of Food and Agriculture, Multi-state Project S1069. This work is supported in part by the National Science Foundation under Grant No. 1539070, Collaboration Leading Operational UAS Development for Meteorology and Atmospheric Physics (CLOUD-MAP), to Oklahoma State University in partnership with the University of Oklahoma, the University of Nebraska-Lincoln, and the University of Kentucky. Special thanks to Jason Walton of the Department of Plant and Soil Sciences at the University of Kentucky for his help with preparing soil samples and collecting the wheat stalk residue used in this study.
Funding Information:
This is Publication No. 17-05-083 of the Kentucky Agricultural Experiment Station and is published with the approval of the director. This work is supported in part by the USDA National Institute of Food and Agriculture, Multistate Project S1069. This work is supported in part by the National Science Foundation under Grant No. 1539070, Collaboration Leading Operational UAS Development for Meteorology and Atmospheric Physics (CLOUD-MAP), to Oklahoma State University in partnership with the University of Oklahoma, the University of Nebraska-Lincoln, and the University of Kentucky. Special thanks to Jason Walton of the Department of Plant and Soil Sciences at the University of Kentucky for his help with preparing soil samples and collecting the wheat stalk residue used in this study.
Publisher Copyright:
© 2017 American Society of Agricultural and Biological Engineers.
Keywords
- Near-infrared reflectance
- Normalized difference water index
- Remote sensing
- Soil moisture
- Spectroscopy
ASJC Scopus subject areas
- Forestry
- Food Science
- Biomedical Engineering
- Agronomy and Crop Science
- Soil Science