DETECTING BEETLE INFESTATIONS IN PINE FORESTS USING MODIS NDVI TIME-SERIES DATA

被引:8
作者
Anees, Asim [1 ]
Olivier, J. C. [1 ]
O'Rielly, Malgorzata [2 ]
Aryal, Jagannath [3 ]
机构
[1] Univ Tasmania, Sch Engn, Hobart, Tas 7005, Australia
[2] Univ Tasmania, Math & Phys, Hobart, Tas 7001, Australia
[3] Univ Tasmania, Geography & Environm Sci, Hobart, Tas 7001, Australia
来源
2013 IEEE INTERNATIONAL GEOSCIENCE AND REMOTE SENSING SYMPOSIUM (IGARSS) | 2013年
关键词
MODIS; NDVI; Extended Kalman Filter; Nonlinear Least Squares; Time-series; Change Detection; DEFOLIATION; DAMAGE; MORTALITY;
D O I
10.1109/IGARSS.2013.6723540
中图分类号
TM [电工技术]; TN [电子技术、通信技术];
学科分类号
0808 ; 0809 ;
摘要
The paper considers the detection of beetle infestations in North American pine forests using high temporal resolution, coarse spatial resolution MODIS remotely sensed satellite images. Two methods are proposed to detect beetle infestation, both applying a triply modulated cosine model. The first method uses an Extended Kalman Filter (EKF) for estimating model parameters, and the second a Least Squares estimator. When beetles infest a forest, the changes in the affect large geographical area. Therefore, the change detection metrics are based on the time series of each pixel, and do not utilize information from neighboring pixels. Using data from the Rocky Mountain region of the United States and of British Columbia in Canada, we show that our methods are highly effective at detecting beetle infestations.
引用
收藏
页码:3329 / 3332
页数:4
相关论文
共 28 条
[1]   An autonomous Earth-observing sensorweb [J].
Chien, S ;
Cichy, B ;
Davies, A ;
Tran, D ;
Rabideau, G ;
Castaño, R ;
Sherwood, R ;
Mandl, D ;
Frye, S ;
Shulman, S ;
Jones, J ;
Grosvenor, S .
IEEE INTELLIGENT SYSTEMS, 2005, 20 (03) :16-24
[2]   Integrating remotely sensed and ancillary data sources to characterize a mountain pine beetle infestation [J].
Coops, Nicholas C. ;
Wulder, Michael A. ;
White, Joanne C. .
REMOTE SENSING OF ENVIRONMENT, 2006, 105 (02) :83-97
[3]   Prediction and assessment of bark beetle-induced mortality of lodgepole pine using estimates of stand vigor derived from remotely sensed data [J].
Coops, Nicholas C. ;
Waring, Richard H. ;
Wulder, Michael A. ;
White, Joanne C. .
REMOTE SENSING OF ENVIRONMENT, 2009, 113 (05) :1058-1066
[4]   Estimating the effect of gypsy moth defoliation using MODIS [J].
de Beurs, K. M. ;
Townsend, P. A. .
REMOTE SENSING OF ENVIRONMENT, 2008, 112 (10) :3983-3990
[5]   Mapping insect defoliation in Scots pine with MODIS time-series data [J].
Eklundh, Lars ;
Johansson, Thomas ;
Solberg, Svein .
REMOTE SENSING OF ENVIRONMENT, 2009, 113 (07) :1566-1573
[6]   Mountain pine beetle red-attack forest damage classification using stratified Landsat TM data in British Columbia, Canada [J].
Franklin, SE ;
Wulder, MA ;
Skakun, RS ;
Carroll, AL .
PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING, 2003, 69 (03) :283-288
[7]   Mapping insect-induced tree defoliation and mortality using coarse spatial resolution satellite imagery [J].
Fraser, RH ;
Latifovic, R .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2005, 26 (01) :193-200
[8]   Curve fitting of time-series Landsat imagery for characterizing a mountain pine beetle infestation [J].
Goodwin, Nicholas R. ;
Magnussen, Steen ;
Coops, Nicholas C. ;
Wulder, Michael A. .
INTERNATIONAL JOURNAL OF REMOTE SENSING, 2010, 31 (12) :3263-3271
[9]  
Jakubauskas ME, 2001, PHOTOGRAMM ENG REM S, V67, P461
[10]   FFT analysis on NDVI annual cycle and climatic regionality in northeast Brazil [J].
Juárez, RIN ;
Liu, WT .
INTERNATIONAL JOURNAL OF CLIMATOLOGY, 2001, 21 (14) :1803-1820