Using long time series of Landsat data to monitor fire events and post-fire dynamics and identify driving factors.: A case study in the Ayora region (eastern Spain)

被引:150
作者
Roeder, Achim [1 ]
Hill, Joachim [1 ]
Duguy, Beatriz [2 ]
Alloza, Jose Antonio [2 ]
Vallejo, Ramon [2 ]
机构
[1] Univ Trier, Remote Sensing Dept, D-54286 Trier, Germany
[2] Fdn Ctr Estudios Ambientales Mediterraneo, Valencia 46980, Spain
关键词
Landsat; radiometric processing; spectral mixture analysis; trend analysis; fire mapping; post-fire dynamics;
D O I
10.1016/j.rse.2007.05.001
中图分类号
X [环境科学、安全科学];
学科分类号
08 ; 0830 ;
摘要
The Ayora region, situated about 60 km southwest of the city of Valencia/Spain, was chosen to demonstrate pathways of characterizing fire events and post-fire succession in Mediterranean ecosystems using multi-temporal satellite imagery. A corresponding time series of 6 Landsat MSS, 13 Landsat-5 TM and 1 Landsat-7 ETM+images, covering the period 1975-2000, was processed to account for geometric and radiometric distortions as well as sensor calibration. Spectral Mixture Analysis was applied to derive estimates of photosynthetic active green vegetation cover as a primary indicator. A combination of pixel-based linear trend analysis and diachronic thresholding was employed to procure a fire perimeter data base and characterize post-fire dynamics based on a temporally stratified trend analysis. The results were integrated with auxiliary information to evaluate driving factors and further interpreted in relation to field-based information on plant communities and post-fire succession patterns. Reflecting typical recovery phases with an initial establishment of grasses and herbaceous species, followed by a gradual development of a shrub layer and the subsequent colonization of tree individuals, temporal trajectories could be described by exponential functions and were related to plot-based botanical information. (C) 2007 Published by Elsevier Inc.
引用
收藏
页码:259 / 273
页数:15
相关论文
共 91 条
[51]   Hyperspectral mixture modeling for quantifying sparse vegetation cover in arid environments [J].
McGwire, K ;
Minor, T ;
Fenstermaker, L .
REMOTE SENSING OF ENVIRONMENT, 2000, 72 (03) :360-374
[52]  
Millan MM, 1998, LARGE FOREST FIRES, P1
[53]  
Moreno JM, 1998, LARGE FOREST FIRES, P159
[54]  
MORENO JM, 1999, MEDITERRANEAN DESERT, P115
[55]  
Naveh Z., 1994, ROLE FIRE MEDITERRAN, P163, DOI [10.1007/978-1-4613-8395-6_9, DOI 10.1007/978-1-4613-8395-6_9]
[56]   THE USE OF VITAL ATTRIBUTES TO PREDICT SUCCESSIONAL CHANGES IN PLANT-COMMUNITIES SUBJECT TO RECURRENT DISTURBANCES [J].
NOBLE, IR ;
SLATYER, RO .
VEGETATIO, 1980, 43 (1-2) :5-21
[57]   Practical limits on hyperspectral vegetation discrimination in arid and semiarid environments [J].
Okin, GS ;
Roberts, DA ;
Murray, B ;
Okin, WJ .
REMOTE SENSING OF ENVIRONMENT, 2001, 77 (02) :212-225
[58]  
PATTERSON MW, 1998, REMOTE SENS ENVIRON, V65, P122
[59]   A comparative evaluation of NOAA/AVHRR vegetation indexes for burned surface detection and mapping [J].
Pereira, JMC .
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, 1999, 37 (01) :217-226
[60]  
Quinn RD, 1994, ROLE FIRE MEDITERRAN, P46, DOI DOI 10.1007/978-1-4613-8395-6_4