Two important indicators with potential to identify Caragana microphylla in xilin gol grassland from temporal MODIS data

Abstract Shrub expansion in arid and semi-arid environment leads to serious issues to earth system regarding net primary production, nutrient cycling, and global carbon balance. Caragana microphylla is a shrub species distributed in Xilin Gol grassland, China, which is expanding into and degrading grassland areas. The current paper proposed two important indicators from Moderate Resolution Imaging Spectroradiometer (MODIS) data that will help potentially distinguish C. microphylla from grass species around it: Difference of Maximum ( DM ) NDVI/EVI and Difference of Accumulated ( DA ) NDVI/EVI between wet and dry years. The two indicators were developed based on relative drought resistance of woody vs. grass species. Accuracy assessment was performed using the field survey data collected in Xilin Gol grassland. The results demonstrated that the proposed indicators were effective for identifying C. microphylla , with the overall accuracy of 81.67% and Kappa coefficient of 0.6300. Due to the mixed pixel effect, the performance of the indicators was less desirable when the coverage of C. microphylla was on low levels. In addition, the proposed indicators would be more effective if two years with significant variation in precipitation could be selected. Furthermore, the indicators developed are anticipated to be sensitive to other similar drought resistant shrubs around the world.

[1]  Masayuki Tamura,et al.  Hyperspectral identification of grassland vegetation in Xilinhot, Inner Mongolia, China , 2003 .

[2]  C. Tucker.  Red and photographic infrared linear combinations for monitoring vegetation , 1979 .

[3]  G. Asner,et al.  Woody plants in grasslands: post-encroachment stand dynamics. , 2008, Ecological applications : a publication of the Ecological Society of America.

[4]  Myron P. Gutmann,et al.  The Structure and Function of Ecosystems in the Central North American Grassland Region , 1999 .

[5]  Debra P. C. Peters,et al.  High-resolution images reveal rate and pattern of shrub encroachment over six decades in New Mexico, U.S.A. , 2003 .

[6]  J. Mustard,et al.  Green leaf phenology at Landsat resolution: Scaling from the field to the satellite , 2006 .

[7]  Corinna Cortes,et al.  Support-Vector Networks , 1995, Machine Learning.

[8]  A. Strahler,et al.  Monitoring vegetation phenology using MODIS , 2003 .

[9]  N. Reid,et al.  Soil hydrological and erosional responses in patches and inter-patches in vegetation states in semi-arid Australia , 2011 .

[10]  B. Nolen,et al.  Vegetation changes in the Jornada Basin from 1858 to 1998 , 2005 .

[11]  M. Cheng.  Interspecific Transition Among Caragana microphylla, C. davazamcii and C. korshinskii Along Geographic Gradient. II. Characteristics of Photosynthesis and Water Metabolism , 2003 .

[12]  D. Cairns,et al.  Patterns and processes of global shrub expansion , 2011 .

[13]  Geoffrey M. Henebry,et al.  Spatio-Temporal Statistical Methods for Modelling Land Surface Phenology , 2010 .

[14]  Renduo Zhang,et al.  Determination of evapotranspiration in the desert area using lysimeters , 1998 .

[15]  A. Huete,et al.  A comparison of vegetation indices over a global set of TM images for EOS-MODIS , 1997 .

[16]  Graciela Metternicht,et al.  Spatial and Temporal Rates and Patterns of Mesquite (Prosopis species) Invasion in Western Australia , 2008 .

[17]  Xiong Xiao,et al.  Increased distribution of Caragana microphylla in rangelands and its causes and consequences in Xilin River Basin , 2003 .

[18]  J. Blair,et al.  An Ecosystem in Transition: Causes and Consequences of the Conversion of Mesic Grassland to Shrubland , 2005 .

[19]  E. Bork,et al.  Shrub Encroachment Impacts the Potential for Multiple Use Conflicts on Public Land , 2009, Environmental management.

[20]  Jesslyn F. Brown,et al.  Measuring phenological variability from satellite imagery , 1994 .

[21]  B. Holben.  Characteristics of maximum-value composite images from temporal AVHRR data , 1986 .

[22]  Florian Jeltsch,et al.  Analysing Shrub Encroachment in the Southern Kalahari: A Grid-Based Modelling Approach , 1997 .

[23]  K. Price,et al.  Response of seasonal vegetation development to climatic variations in eastern central Asia , 2003 .

[24]  Shaun R. Levick,et al.  Context-dependent vegetation dynamics in an African savanna , 2011, Landscape Ecology.

[25]  R. Clark,et al.  Mapping vegetation in Yellowstone National Park using spectral feature analysis of AVIRIS data , 2003 .

[26]  Jin Chen,et al.  A simple method for reconstructing a high-quality NDVI time-series data set based on the Savitzky-Golay filter , 2004 .

[27]  D. Schimel,et al.  Mechanisms of shrubland expansion: land use, climate or CO2? , 1995 .