Evaluating the relationship between biomass, percent groundcover and remote sensing indices across six winter cover crop fields in Maryland, United States

被引:190
作者
Prabhakara, Kusuma [1 ]
Hively, W. Dean [2 ]
McCarty, Gregory W. [3 ]
机构
[1] Univ Maryland, Dept Geog Sci, College Pk, MD 20742 USA
[2] US Geol Survey, Eastern Geog Sci Ctr, Reston, VA 22092 USA
[3] USDA ARS, Hydrol & Remote Sensing Lab, Beltsville, MD 20705 USA
关键词
Winter cover crops; Biomass; Percent groundcover; Remote sensing; Vegetation indices; HYPERSPECTRAL VEGETATION INDEXES; AREA INDEX; GREEN; ALGORITHMS; WHEAT; BAND; SOIL; RED;
D O I
10.1016/j.jag.2015.03.002
中图分类号
TP7 [遥感技术];
学科分类号
081102 ; 0816 ; 081602 ; 083002 ; 1404 ;
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 (r(2) = 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 (r(2) = 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. Published by Elsevier B.V.
引用
收藏
页码:88 / 102
页数:15
相关论文
共 37 条
[1]   LOW-TEMPERATURE STRESS IN FIELD AND FORAGE CROP PRODUCTION - AN OVERVIEW [J].
ANDREWS, CJ .
CANADIAN JOURNAL OF PLANT SCIENCE, 1987, 67 (04) :1121-1133
[2]  
ASAE, 2005, TERM DEF SOIL TILL S
[3]   Point sampling digital imagery with "SamplePoint' [J].
Booth, D. Terrance ;
Cox, Samuel E. ;
Berryman, Robert D. .
ENVIRONMENTAL MONITORING AND ASSESSMENT, 2006, 123 (1-3) :97-108
[4]   Deriving green crop area index and canopy chlorophyll density of winter wheat from spectral reflectance data [J].
Broge, NH ;
Mortensen, JV .
REMOTE SENSING OF ENVIRONMENT, 2002, 81 (01) :45-57
[5]   Comparing prediction power and stability of broadband and hyperspectral vegetation indices for estimation of green leaf area index and canopy chlorophyll density [J].
Broge, NH ;
Leblanc, E .
REMOTE SENSING OF ENVIRONMENT, 2001, 76 (02) :156-172
[6]   Estimating aboveground biomass of grassland having a high canopy cover: an exploratory analysis of in situ hyperspectral data [J].
Chen, Jin ;
Gu, Song ;
Shen, Miaogen ;
Tang, Yanhong ;
Matsushita, Bunkei .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2009, 30 (24) :6497-6517
[7]  
Chesapeake Bay Program, 2013, CONT HIGH RES MIN SO
[8]  
Dabney SM, 1998, J SOIL WATER CONSERV, V53, P207
[9]   Using winter cover crops to improve soil and water quality [J].
Dabney, SM ;
Delgado, JA ;
Reeves, DW .
COMMUNICATIONS IN SOIL SCIENCE AND PLANT ANALYSIS, 2001, 32 (7-8) :1221-1250
[10]  
Daniel J. B., 1999, Journal of Cotton Science, V3, P74