Contribution of Land Surface Temperature (TCI) to Vegetation Health Index: A Comparative Study Using Clear Sky and All-Weather Climate Data Records

被引:41
作者
Bento, Virgilio A. [1 ]
Trigo, Isabel F. [1 ,2 ]
Gouveia, Celia M. [1 ,2 ]
DaCamara, Carlos C. [1 ]
机构
[1] Univ Lisbon, Fac Ciencias, Inst Dom Luiz, P-1749016 Lisbon, Portugal
[2] Inst Portugues Mar Atmosfera IP, Rua C Aeroporto, P-1749077 Lisbon, Portugal
关键词
drought monitoring; land surface temperature; vegetation health index; Meteosat; climate data records; standardized precipitation-evapotranspiration index; DROUGHT VARIABILITY; LONG-TERM; THERMAL INERTIA; IMPACT; SPACE; FREQUENCY; EVENTS; ALBEDO;
D O I
10.3390/rs10091324
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The Vegetation Health Index (VHI) is widely used for monitoring drought using satellite data. VHI depends on vegetation state and thermal stress, respectively assessed via (i) the Vegetation Condition Index (VCI) that usually relies on information from the visible and near infra-red parts of the spectrum (in the form of Normalized Difference Vegetation Index, NDVI); and (ii) the Thermal Condition Index (TCI), based on top of atmosphere thermal infrared (TIR) brightness temperature or on TIR-derived Land Surface Temperature (LST). VHI is then estimated as a weighted average of VCI and TCI. However, the optimum weights of the two components are usually not known and VHI is usually estimated attributing a weight of 0.5 to both. Using a previously developed methodology for the Euro-Mediterranean region, we show that the multi-scalar drought index (SPEI) may be used to obtain optimal weights for VCI and TCI over the area covered by Meteosat satellites that includes Africa, Europe, and part of South America. The procedure is applied using clear-sky Meteosat Climate Data Records (CDRs) and all-sky LST derived by combining satellite and reanalysis data. Results obtained present a coherent spatial distribution of VCI and TCI weights when estimated using clear- and all-sky LST. This study paves the way for the development of a future VHI near-real time operational product for drought monitoring based on information from Meteosat satellites.
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页数:20
相关论文
共 73 条
[1]  
Aminou D.M, 2009, SPIE, V7474
[2]   GlobCover ESA service for Global land cover from MERIS [J].
Arino, Olivier ;
Gross, Dorit ;
Ranera, Franck ;
Leroy, Marc ;
Bicheron, Patrice ;
Brockman, Carsten ;
Defourny, Pierre ;
Vancutsem, Christelle ;
Achard, Frederic ;
Durieux, Laurent ;
Bourg, Ludovic ;
Latham, John ;
Di Gregorio, Antonio ;
Witt, Ron ;
Herold, Martin ;
Sambale, Jacqueline ;
Plummer, Stephen ;
Weber, Jean-Louis .
IGARSS: 2007 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM, VOLS 1-12: SENSING AND UNDERSTANDING OUR PLANET, 2007, :2412-+
[3]   Standardized precipitation evapotranspiration index (SPEI) revisited: parameter fitting, evapotranspiration models, tools, datasets and drought monitoring [J].
Begueria, Santiago ;
Vicente-Serrano, Sergio M. ;
Reig, Fergus ;
Latorre, Borja .
INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2014, 34 (10) :3001-3023
[4]   A MULTISCALAR GLOBAL DROUGHT DATASET: THE SPEIBASE A New Gridded Product for the Analysis of Drought Variability and Impacts [J].
Begueria, Santiago ;
Vicente-Serrano, Sergio M. ;
Angulo-Martinez, Marta .
BULLETIN OF THE AMERICAN METEOROLOGICAL SOCIETY, 2010, 91 (10) :1351-1354
[5]   A climatological assessment of drought impact on vegetation health index [J].
Bento, Virgilio A. ;
Gouveia, Celia M. ;
DaCamara, Carlos C. ;
Trigo, Isabel F. .
AGRICULTURAL AND FOREST METEOROLOGY, 2018, 259 :286-295
[6]   Developing a Remotely Sensed Drought Monitoring Indicator for Morocco [J].
Bijaber, Noureddine ;
El Hadani, Driss ;
Saidi, Mariam ;
Svoboda, Mark D. ;
Wardlow, Brian D. ;
Hain, Christopher R. ;
Poulsen, Calvin Christian ;
Yessef, Mohammed ;
Rochdi, Atmane .
GEOSCIENCES, 2018, 8 (02)
[7]   Frequency, duration and severity of drought in the Semiarid Northeast Brazil region [J].
Brito, S. S. B. ;
Cunha, A. P. M. A. ;
Cunningham, C. C. ;
Alvala, R. C. ;
Marengo, J. A. ;
Carvalho, M. A. .
INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2018, 38 (02) :517-529
[8]   Creating consistent datasets by combining remotely-sensed data and land surface model estimates through Bayesian uncertainty post-processing: The case of Land Surface Temperature from HIRS [J].
Coccia, Gabriele ;
Siemann, Amanda L. ;
Pan, Ming ;
Wood, Eric F. .
REMOTE SENSING OF ENVIRONMENT, 2015, 170 :290-305
[9]   Spatiotemporal drought variability in the Mediterranean over the last 900years [J].
Cook, Benjamin I. ;
Anchukaitis, Kevin J. ;
Touchan, Ramzi ;
Meko, David M. ;
Cook, Edward R. .
JOURNAL OF GEOPHYSICAL RESEARCH-ATMOSPHERES, 2016, 121 (05) :2060-2074
[10]  
Dai AG, 2013, NAT CLIM CHANGE, V3, P52, DOI [10.1038/nclimate1633, 10.1038/NCLIMATE1633]