Spectral characteristics of alpine grassland and their changes responding to grassland degradation on the Tibetan Plateau

Remote sensing is used as the indispensable technology in alpine grassland degradation assessment especially at regional scale on the Tibetan Plateau. However, the lack of field spectral data, as the foundation of remote sensing, due to the formidable natural and climate conditions hinders the understanding of spectral characteristics of alpine grassland and their degradation assessment. In this study, spectral characteristics of alpine grasslands and their changes responding to degradation were explored. The results showed that the main spectral characteristics for discriminating the dominant species of alpine meadow (Kobresia littledalei and Kobresia pygmaea), alpine steppe (Stipa purpurea) and desert (Potentilla fruticosa) are spectral features of chlorophyll, cellulose and water which are related to their growth form, plant inclination and residue of withered leaf sheaths. The spectral curves of alpine meadow have a much smaller variety over the whole spectral region compared to those of alpine steppe and desert which generally have weaker chlorophyll and water absorption features and more noticeable non-vegetation features. Different grassland degradation processes exhibit different patterns of spectral characteristics change due to the species composition, vegetation succession, vegetation coverage and soil background. Grassland degradation can happen without obvious vegetation coverage reduction or even with an increment of NDVI (normalized difference vegetation index). Therefore, the assessment of grassland degradation cannot be fulfilled well using single vegetation index or spectral feature. The combination of several vegetation indices or hyperspectral remote sensing along with the priori knowledge is needed in order to perform the assessment more accurately in further studies.

[1]  Xiong Wei,et al.  Grassland degradation in Northern Tibet based on remote sensing data , 2006 .

[2]  Josep Peñuelas,et al.  Visible and near-infrared reflectance techniques for diagnosing plant physiological status , 1998 .

[3]  A. Huete,et al.  Overview of the radiometric and biophysical performance of the MODIS vegetation indices , 2002 .

[4]  M. Eismann Hyperspectral Remote Sensing , 2012 .

[5]  Li Yingnian,et al.  Estimation of Biomass and Annual Turnover Quantities of Potentilla Froticosa Shrub , 2006 .

[6]  Pastures in South and Central Tibet ( China ) 11 . Probable Causes ofPasture Degradation , 2007 .

[7]  D. Roberts,et al.  Green vegetation, nonphotosynthetic vegetation, and soils in AVIRIS data , 1993 .

[8]  Jin Zhang,et al.  Analog–digital conversion signal-to-noise ratio analysis for synthetic aperture interferometric radiometer , 2014 .

[9]  Qingzhu Gao,et al.  Alpine grassland degradation index and its response to recent climate variability in Northern Tibet, China , 2010 .

[10]  Liu Shu-zhen Research on Grassland Degradation Assessment Model based on ETM+Image——A Case Study in Naqu County of Tibet , 2007 .

[11]  Xinquan Zhao,et al.  Status and Dynamics of the Kobresia pygmaea Ecosystem on the Tibetan Plateau , 2008, Ambio.

[12]  Liu Shu-zhen,et al.  A Model of Grassland Degradation Assessment Based on NDVI---Taking the Grassland in Tibet as an Example , 2003 .

[13]  Yongchao Zhao,et al.  Hyperspectral remote sensing in China , 2001, International Symposium on Multispectral Image Processing and Pattern Recognition.

[14]  Benjamin Komac,et al.  Self-organized spatial patterns of vegetation in alpine grasslands , 2007 .

[15]  Weishou Shen,et al.  Deriving vegetation fraction information for the alpine grassland on the Tibetan plateau using in situ spectral data , 2014 .

[16]  G. Pickup,et al.  Remote‐Sensing‐Based Condition Assessment for Nonequilibrium Rangelands Under Large‐Scale Commercial Grazing , 1994 .

[17]  J. Peñuelas,et al.  Estimation of plant water concentration by the reflectance Water Index WI (R900/R970) , 1997 .

[18]  Wang Yibo,et al.  Degradation of the Eco-Environmental System in Alpine Meadow on the Tibetan Plateau , 2005 .

[19]  J. Qiu China: The third pole , 2008, Nature.

[20]  Jinzhong Min,et al.  Observed surface wind speed in the Tibetan Plateau since 1980 and its physical causes , 2014 .

[21]  R. Harris Rangeland degradation on the Qinghai-Tibetan plateau: A review of the evidence of its magnitude and causes , 2010 .

[22]  G. Wu,et al.  Role of the Tibetan Plateau thermal forcing in the summer climate patterns over subtropical Asia , 2005 .

[23]  Xuefeng Cui,et al.  Recent land cover changes on the Tibetan Plateau: a review , 2009 .

[24]  A. Huete A soil-adjusted vegetation index (SAVI) , 1988 .

[25]  Shuangcheng Li,et al.  Spatial pattern of non-stationarity and scale-dependent relationships between NDVI and climatic factors—A case study in Qinghai-Tibet Plateau, China , 2012 .

[26]  Jan Hanspach,et al.  Plant communities of central Tibetan pastures in the Alpine Steppe / Kobresia pygmaea ecotone , 2011 .

[27]  J. Marc Foggin,et al.  Depopulating the Tibetan Grasslands , 2008 .

[28]  Wenfeng Qi,et al.  Distribution of 0 and 1 in the highest level of primitive sequences overZ/(2e) (II) , 1998 .

[29]  Chengfeng Li,et al.  Seasonal Heating of the Tibetan Plateau and Its Effects on the Evolution of the Asian Summer Monsoon , 1992 .

[30]  Hongxing Zheng,et al.  Glacier and lake variations in the Yamzhog Yumco basin, southern Tibetan Plateau, from 1980 to 2000 using remote-sensing and GIS technologies , 2007, Journal of Glaciology.

[31]  T. Yao,et al.  Review of climate and cryospheric change in the Tibetan Plateau , 2010 .

[32]  B. Gao NDWI—A normalized difference water index for remote sensing of vegetation liquid water from space , 1996 .

[33]  Wu Ning,et al.  A REVIEW OF RANGELAND PRIVATISATION AND ITS IMPLICATIONS IN THE TIBETAN PLATEAU, CHINA , 2005 .

[34]  Lei Zhou,et al.  [Hyperspectral remote sensing monitoring of grassland degradation]. , 2010, Guang pu xue yu guang pu fen xi = Guang pu.

[35]  Albrecht E. Melchinger,et al.  Prediction of grain yield using reflectance spectra of canopy and leaves in maize plants grown under different water regimes , 2012 .

[36]  Song Feng,et al.  New evidence for the Qinghai-Xizang (Tibet) Plateau as a pilot region of climatic fluctuation in China , 1998 .

[37]  Wang Yibo,et al.  Effects of permafrost thawing on vegetation and soil carbon pool losses on the Qinghai–Tibet Plateau, China , 2008 .

[38]  Lukas W. Lehnert,et al.  A hyperspectral indicator system for rangeland degradation on the Tibetan Plateau: A case study towards spaceborne monitoring , 2014 .

[39]  C. Elvidge Visible and near infrared reflectance characteristics of dry plant materials , 1990 .

[40]  Jiahua Zhang,et al.  Evaluation of Grassland Dynamics in the Northern-Tibet Plateau of China Using Remote Sensing and Climate Data , 2007, Sensors.

[41]  Tsuyoshi Akiyama,et al.  Grassland degradation in China: Methods of monitoring, management and restoration , 2007 .

[42]  Feng Zhang,et al.  Eco-environmental degradation in the northeastern margin of the Qinghai–Tibetan Plateau and comprehensive ecological protection planning , 2008 .

[43]  C. Daughtry,et al.  Cellulose absorption index (CAI) to quantify mixed soil-plant litter scenes , 2003 .