DOI: 10.1016/j.jag.2017.06.008
Scopus记录号: 2-s2.0-85032205826
论文题名: Modeling seasonal surface temperature variations in secondary tropical dry forests
作者: Cao S ; , Sanchez-Azofeifa A
刊名: International Journal of Applied Earth Observation and Geoinformation
ISSN: 15698432
出版年: 2017
卷: 62 起始页码: 122
结束页码: 134
语种: 英语
英文关键词: Land surface temperature
; Landsat-8
; Radiative transfer equation
; Secondary tropical dry forests
; Wireless sensor network
Scopus关键词: dry forest
; land surface
; Landsat
; numerical model
; radiative transfer
; secondary forest
; sensor
; surface temperature
; tropical forest
; Costa Rica
; Guanacaste
; Santa Rosa National Park
英文摘要: Secondary tropical dry forests (TDFs) provide important ecosystem services such as carbon sequestration, biodiversity conservation, and nutrient cycle regulation. However, their biogeophysical processes at the canopy-atmosphere interface remain unknown, limiting our understanding of how this endangered ecosystem influences, and responds to the ongoing global warming. To facilitate future development of conservation policies, this study characterized the seasonal land surface temperature (LST) behavior of three successional stages (early, intermediate, and late) of a TDF, at the Santa Rosa National Park (SRNP), Costa Rica. A total of 38 Landsat-8 Thermal Infrared Sensor (TIRS) data and the Surface Reflectance (SR) product were utilized to model LST time series from July 2013 to July 2016 using a radiative transfer equation (RTE) algorithm. We further related the LST time series to seven vegetation indices which reflect different properties of TDFs, and soil moisture data obtained from a Wireless Sensor Network (WSN). Results showed that the LST in the dry season was 15–20 K higher than in the wet season at SRNP. We found that the early successional stages were about 6–8 K warmer than the intermediate successional stages and were 9–10 K warmer than the late successional stages in the middle of the dry season; meanwhile, a minimum LST difference (0–1 K) was observed at the end of the wet season. Leaf phenology and canopy architecture explained most LST variations in both dry and wet seasons. However, our analysis revealed that it is precipitation that ultimately determines the LST variations through both biogeochemical (leaf phenology) and biogeophysical processes (evapotranspiration) of the plants. Results of this study could help physiological modeling studies in secondary TDFs. © 2017 Elsevier B.V. Citation statistics:
资源类型: 期刊论文
标识符: http://119.78.100.158/handle/2HF3EXSE/79967
Appears in Collections: 气候变化事实与影响
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作者单位: Department of Earth and Atmospheric Sciences, University of Alberta, Edmonton, Canada
Recommended Citation:
Cao S,, Sanchez-Azofeifa A. Modeling seasonal surface temperature variations in secondary tropical dry forests[J]. International Journal of Applied Earth Observation and Geoinformation,2017-01-01,62