Monitoring vegetation change and dynamics on U.S. Army training lands using satellite image time series analysis

Journal of Environmental Management - Tập 150 - Trang 355-366 - 2015
J.M.S. Hutchinson1, A. Jacquin2, S.L. Hutchinson3, J. Verbesselt4
1Department of Geography, Kansas State University, 118 Seaton Hall, Manhattan, KS 66506-2904, USA
2Université de Toulouse, INPT, Ecole d'Ingénieurs de Purpan, UMR 1201 DYNAFOR, 75, voie du TOEC, BP 57611, F-31076 Toulouse Cedex 03, France
3Department of Biological and Agricultural Engineering, Kansas State University, 129 Seaton Hall, Manhattan, KS 66506-2904, USA
4Laboratory of Geo-Information Science and Remote Sensing, Wageningen University, Droevendaalsesteeg 3, 6708 PB Wageningen, The Netherlands

Tài liệu tham khảo

Ahl, 2006, Monitoring spring canopy phenology of a deciduous broadleaf forest using MODIS, Remote Sens. Environ., 104, 88, 10.1016/j.rse.2006.05.003 Althoff, 2006, Plant community and bare ground trends on Fort Riley, Kansas: Implications for monitoring of a highly disturbed landscape, Trans. Kans. Acad. Sci., 109, 101, 10.1660/0022-8443(2006)109[101:PCABGT]2.0.CO;2 Bai, 2003, Computation and analysis of multiple structural change models, J. Appl. Econ., 18, 1, 10.1002/jae.659 1994 Beck, 2006, Improved monitoring of vegetation dynamics at very high latitudes: a new method using MODIS NDVI, Remote Sens. Environ., 100, 321, 10.1016/j.rse.2005.10.021 Borak, 2000, The use of temporal metrics for land-cover change detection at coarse spatial scales, Int. J. Remote Sens., 21, 1415, 10.1080/014311600210245 Brockwell, 1996 Chancellor, 1977 Cleveland, 1979, Robust locally weighted regression and smoothing scatterplots, J. Am. Stat. Assoc., 74, 829, 10.1080/01621459.1979.10481038 Cleveland, 1988, Locally-Weighted regression: an approach to regression analysis by local fitting, J. Am. Stat. Assoc., 83, 596, 10.1080/01621459.1988.10478639 Cleveland, 1990, STL: a seasonal-trend decomposition procedure based on loess, J. Off. Stat., 6, 3 Cohn, 1996, New defenders of wildlife, Bioscience, 46, 11, 10.2307/1312649 Congressional Research Service, 2012 Dash, 2010, The use of MERIS terrestrial chlorophyll index to study spatio-temporal variation in vegetation phenology over India, Remote Sens. Environ., 114, 1388, 10.1016/j.rse.2010.01.021 de Beurs, 2005, A statistical framework for the analysis of long image time series, Int. J. Remote Sens., 26, 1551, 10.1080/01431160512331326657 de Jong, 2011, Analysis of monotonic greening and browning trends from global NDVI time-series, Remote Sens. Environ., 115, 692, 10.1016/j.rse.2010.10.011 de Jong, 2013, Shifts in global vegetation activity trends, Remote Sens., 5, 1117, 10.3390/rs5031117 Department of Defense, 2010 Department of Defense, 2011 Department of the Army, 1988 Department of the Army, 2005 Egbert, 2001 Fensholt, 2009, Evaluation of earth observation based long term vegetation trends intercomparing NDVI time series trend analysis consistency of Sahel from AVHRR GIMMS, Terra MODIS and SPOT VGT data, Remote Sens. Environ., 113, 1886, 10.1016/j.rse.2009.04.004 Forkel, 2013, Trend change detection in NDVI time series: effects of inter-annual variability and methodology, Remote Sens., 5, 2113, 10.3390/rs5052113 Houston, 2001, Environmental risk of Army ranges and impact areas: an ecological framework for assessment, Fed. Facil. Environ. J., 11, 93, 10.1002/ffej.3330120110 Huete, 2002, Overview of the radiometric and biophysical performance of the MODIS vegetation indices, Remote Sens. Environ., 83, 195, 10.1016/S0034-4257(02)00096-2 Jacquin, 2010 Jacquin, 2010, Vegetation cover degradation assessment in Madagascar savanna based on trend analysis of MODIS NDVI time series, Int. J. Appl. Earth Observ. Geoinform., 12S, S3, 10.1016/j.jag.2009.11.004 Jacquin, 2013, Using spatial statistics tools on remote-sensing data to identify fire regime linked with savanna vegetation degradation, Int. J. Agric. Environ. Inform. Syst., 4, 69 Johnson, 2008 Jönsson, 2002, Seasonality extraction by function fitting to time-series of satellite sensor data, IEEE Trans. Geosci. Remote Sens., 40, 1824, 10.1109/TGRS.2002.802519 Julien, 2009, Global land surface phenology trends from GIMMS database, Int. J. Remote Sens., 30, 3495, 10.1080/01431160802562255 Knapp, 1998 Lambert, 2011, Comparison of two remote sensing time series analysis methods for monitoring forest decline, 93 Lambert, 2013, Monitoring forest decline through remote sensing time series analysis, GISci. Remote Sens., 1 Liu, 2009, Influence of turning radius on wheeled military vehicle induced rut formation, J. Terramech., 46, 49, 10.1016/j.jterra.2009.02.004 Lu, 2001 Meigs, 2011, A Landsat time series approach to characterize bark beetle and defoliator impacts on tree mortality and surface fuels in conifer forests, Remote Sens. Environ., 115, 3707, 10.1016/j.rse.2011.09.009 Milchunas, 1999, Plant community response to disturbance by mechanized military maneuvers, J. Environ. Qual., 28, 1533, 10.2134/jeq1999.00472425002800050019x Millward, 2006, Time series analysis of medium-resolution, multisensor satellite data for identifying landscape change, Photogram. Eng. Remote Sens., 72, 653, 10.14358/PERS.72.6.653 Multi-Resolution Land Characteristics Consortium (MLRC), 2013 PRISM Climate Group, 2012 Quist, 2003, Military training effects on terrestrial and aquatic communities on a grassland military installation, Ecol. Appl., 13, 432, 10.1890/1051-0761(2003)013[0432:MTEOTA]2.0.CO;2 Serneels, 2001, Land-cover changes around a major East African wildlife reserve: the Mara ecosystem, Int. J. Remote Sens., 22, 3397, 10.1080/01431160152609236 Slayback, 2003, Northern hemisphere photosynthetic trends 1982–99, Glob. Change Biol., 9, 1, 10.1046/j.1365-2486.2003.00507.x Sonnenschein, 2011, Differences in Landsat-based trend analyses in drylands due to the choice of vegetation estimate, Remote Sens. Environ., 115, 1408, 10.1016/j.rse.2011.01.021 Thurow, 1991, Hydrology and erosion (p. 141–159) Thurow, 1993, Tracked vehicle traffic effects on the hydrologic characteristics of central texas rangeland, Trans. ASAE, 36, 1645, 10.13031/2013.28507 U.S Department of Agriculture, Soil Conservation Service, 1975 U.S. Department of Agriculture, 2012 Verbesselt, 2010, Detecting trend and seasonal changes in satellite image time series, Remote Sens. Environ., 114, 106, 10.1016/j.rse.2009.08.014 Verbesselt, 2010, Phenological change detection while accounting for abrupt and gradual trends in satellite image time series, Remote Sens. Environ., 114, 2970, 10.1016/j.rse.2010.08.003 Zeileis, 2005, Validating multiple structural change models-a case study, J. Appl. Econ., 20, 685, 10.1002/jae.856 Zhang, 2003, Monitoring vegetation phenology using MODIS, Remote Sens. Environ., 84, 471, 10.1016/S0034-4257(02)00135-9