globalchange  > 气候变化事实与影响
DOI: 10.1016/j.jag.2015.03.002
Scopus记录号: 2-s2.0-84943519442
论文题名:
Evaluating the relationship between biomass, percent groundcover and remote sensing indices across six winter cover crop fields in Maryland, United States
作者: Prabhakara K; , Dean Hively W; , McCarty G; W
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2015
卷: 39
起始页码: 88
结束页码: 102
语种: 英语
英文关键词: Biomass ; Percent groundcover ; Remote sensing ; Vegetation indices ; Winter cover crops
Scopus关键词: biomass ; cover crop ; ground cover ; remote sensing ; spectral reflectance ; vegetation index ; Maryland ; United States ; Hordeum ; Lolium ; Secale cereale ; Triticosecale ; Triticum aestivum
英文摘要: Winter cover crops are an essential part of managing nutrient and sediment losses from agricultural lands. Cover crops lessen sedimentation by reducing erosion, and the accumulation of nitrogen in aboveground biomass results in reduced nutrient runoff. Winter cover crops are planted in the fall and are usually terminated in early spring, making them susceptible to senescence, frost burn, and leaf yellowing due to wintertime conditions. This study sought to determine to what extent remote sensing indices are capable of accurately estimating the percent groundcover and biomass of winter cover crops, and to analyze under what critical ranges these relationships are strong and under which conditions they break down. Cover crop growth on six fields planted to barley, rye, ryegrass, triticale or wheat was measured over the 2012-2013 winter growing season. Data collection included spectral reflectance measurements, aboveground biomass, and percent groundcover. Ten vegetation indices were evaluated using surface reflectance data from a 16-band CROPSCAN sensor. Restricting analysis to sampling dates before the onset of prolonged freezing temperatures and leaf yellowing resulted in increased estimation accuracy. There was a strong relationship between the normalized difference vegetation index (NDVI) and percent groundcover (r2 = 0.93) suggesting that date restrictions effectively eliminate yellowing vegetation from analysis. The triangular vegetation index (TVI) was most accurate in estimating high ranges of biomass (r2 = 0.86), while NDVI did not experience a clustering of values in the low and medium biomass ranges but saturated in the higher range (>1500 kg/ha). The results of this study show that accounting for index saturation, senescence, and frost burn on leaves can greatly increase the accuracy of estimates of percent groundcover and biomass for winter cover crops.
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资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79510
Appears in Collections:气候变化事实与影响

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作者单位: Department of Geographical Sciences, University of Maryland, 2181 Samuel J. LeFrak Hall, College Park, MD, United States; U.S Geological Survey Eastern Geographic Science Center, 12201 Sunrise Valley Drive, Reston, VA, United States; U.S Department of Agriculture, Agricultural Research Service, Hydrology and Remote Sensing Laboratory, Bldg 007, BARC-W, 10300 Baltimore Avenue, Beltsville, MD, United States

Recommended Citation:
Prabhakara K,, Dean Hively W,, McCarty G,et al. Evaluating the relationship between biomass, percent groundcover and remote sensing indices across six winter cover crop fields in Maryland, United States[J]. International Journal of Applied Earth Observation and Geoinformation,2015-01-01,39
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