Modeling seasonal changes in live fuel moisture and equivalent water thickness using a cumulative water balance index

被引:72
作者
Dennison, PE [1 ]
Roberts, DA
Thorgusen, SR
Regelbrugge, JC
Weise, D
Lee, C
机构
[1] Univ Calif Santa Barbara, Dept Geog, Santa Barbara, CA 93106 USA
[2] Univ Arizona, Dept Geog, Tucson, AZ 85721 USA
[3] USDA, Forest Serv, San Bernardino Natl Forest, San Bernardino, CA 92408 USA
[4] USDA, Forest Serv, Riverside Forest Fire Lab, Riverside, CA 92507 USA
[5] Calif State Univ Long Beach, Dept Geog, Long Beach, CA 90840 USA
基金
美国国家航空航天局;
关键词
live fuel moisture; equivalent water thickness; cumulative water balance index;
D O I
10.1016/j.rse.2003.08.015
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
Live fuel moisture, an important determinant of fire danger in Mediterranean ecosystems, exhibits seasonal changes in response to soil water availability. Both drought stress indices based on meteorological data and remote sensing indices based on vegetation water absorption can be used to monitor live fuel moisture. In this study, a cumulative water balance index (CWBI) for a time series spanning 1994-1997 and 1999-2001 was compared to field measured live fuel moisture and to equivalent water thickness (EWT) calculated from remote sensing data. A sigmoidal function was used to model the relationships between CWBI, live fuel moisture, and EWT. Both live fuel moisture and EWT reach minima at large CWBI deficits. Minimum and maximum live fuel moisture, minimum and maximum EWT, and the modeled inflection points of both live fuel moisture and EWT were found to vary with vegetation type. Modeled minimum and maximum EWT were also found to vary with vegetation biomass. Spatial variation in modeled EWT inflection points may be due to vegetation type and to local variation in soil moisture. Based on their temporal and spatial attributes, CWBI and EWT offer complimentary methods for monitoring live fuel moisture for fire danger assessment. (C) 2003 Elsevier Inc. All rights reserved.
引用
收藏
页码:442 / 452
页数:11
相关论文
共 27 条
[1]  
[Anonymous], IRR DRAIN SESS P WAT
[2]   AUTOMATIC CORN SOYBEAN CLASSIFICATION USING LANDSAT MSS DATA .2. EARLY SEASON CROP PROPORTION ESTIMATION [J].
BADHWAR, GB .
REMOTE SENSING OF ENVIRONMENT, 1984, 14 (1-3) :31-37
[3]  
BURGAN RE, 1988, SE273 USDA SE FOR EX
[4]  
CLARK RN, 1993, 4 ANN JPL AIRB GEOSC, P35
[5]  
Countryman C. M., 1979, MEASURING MOISTURE C
[6]   The effects of vegetation phenology on endmember selection and species mapping in southern California chaparral [J].
Dennison, PE ;
Roberts, DA .
REMOTE SENSING OF ENVIRONMENT, 2003, 87 (2-3) :295-309
[7]  
Devore J.L., 2000, PROBABILITY STAT ENG
[8]   Predicting live herbaceous moisturecontent from a seasonal drought index [J].
Dimitrskopoulos, AP ;
Bemmerzouk, AM .
INTERNATIONAL JOURNAL OF BIOMETEOROLOGY, 2003, 47 (02) :73-79
[9]   NDWI - A normalized difference water index for remote sensing of vegetation liquid water from space [J].
Gao, BC .
REMOTE SENSING OF ENVIRONMENT, 1996, 58 (03) :257-266
[10]   RETRIEVAL OF EQUIVALENT WATER THICKNESS AND INFORMATION RELATED TO BIOCHEMICAL-COMPONENTS OF VEGETATION CANOPIES FROM AVIRIS DATA [J].
GAO, BC ;
GOETZ, AFH .
REMOTE SENSING OF ENVIRONMENT, 1995, 52 (03) :155-162