Land-Cover Change

In this chapter, land-cover change based on the Normalized Difference Vegetation Index (NDVI) derived from the NOAA AVHRR Global Vegetation Index (GVI) for the Lhasa area at the central Tibetan Plateau from 1985 to 1999 is presented, and its sensitivity to climate conditions is discussed, followed by analysis on vegetation phenologies and dynamics using the discrete Fourier transform (DFT). The time series of NDVI demonstrate a positive trend from 1985 to 1999, which means that general vegetation biomass on land surface presents increasing, and this trend is strongly associated with increased rainfall and temperature from the mid-1980s to 1990s. The correlation analysis shows that the NDVI is more sensitive to precipitation (r = 0.75, P < 0.01) than temperature (r = 0.63, P < 0.01) in this semiarid climate zone. The study also indicated that DFT is a very useful tool to understand vegetation phenologies and dynamic change through decomposition of temporal data to frequency domain.

[1]  Dirk Pflugmacher,et al.  Land use and land cover change in Inner Mongolia - understanding the effects of China's re-vegetation programs , 2018 .

[2]  M. Menenti,et al.  Assessment of climate impact on vegetation dynamics by using remote sensing , 2003 .

[3]  M. Disney,et al.  Terrestrial ecosystems from space: a review of earth observation products for macroecology applications , 2012 .

[4]  Christopher O. Justice,et al.  Monitoring the grasslands of the Sahel using NOAA AVHRR data: Niger 1983 , 1986 .

[5]  William Salas,et al.  Fourier analysis of multi-temporal AVHRR data applied to a land cover classification , 1994 .

[6]  A. Belward,et al.  The IGBP-DIS global 1km land cover data set, DISCover: First results , 1997 .

[7]  Damien Sulla-Menashe,et al.  A global land-cover validation data set, part I: fundamental design principles , 2012 .

[8]  Dan Tarpley,et al.  The Enhanced NOAA Global Land Dataset from the Advanced Very High Resolution Radiometer , 1995 .

[9]  Lenard Milich,et al.  GAC NDVI images: Relationship to rainfall and potential evaporation in the grazing lands of The Gourma (northern Sahel) and in the croplands of the Niger-Nigeria border (southern Sahel) , 2000 .

[10]  S. Hay,et al.  Predicting the distribution of tsetse flies in West Africa using temporal Fourier processed meteorological satellite data. , 1996, Annals of tropical medicine and parasitology.

[11]  Limin Yang,et al.  Development of a global land cover characteristics database and IGBP DISCover from 1 km AVHRR data , 2000 .

[12]  Stephen Polasky,et al.  Projected land-use change impacts on ecosystem services in the United States , 2014, Proceedings of the National Academy of Sciences.

[13]  R. DeFries,et al.  Detecting Long-term Global Forest Change Using Continuous Fields of Tree-Cover Maps from 8-km Advanced Very High Resolution Radiometer (AVHRR) Data for the Years 1982–99 , 2004, Ecosystems.

[14]  Wout Verhoef,et al.  Mapping agroecological zones and time lag in vegetation growth by means of Fourier analysis of time series of NDVI images , 1993 .

[15]  Edwin W. Pak,et al.  An extended AVHRR 8‐km NDVI dataset compatible with MODIS and SPOT vegetation NDVI data , 2005 .

[16]  J. Townshend,et al.  Global land cover classifications at 8 km spatial resolution: The use of training data derived from Landsat imagery in decision tree classifiers , 1998 .

[17]  B. Holben,et al.  Red and near-infrared sensor response to off-nadiir viewing , 1984 .

[18]  Aaron Moody,et al.  Land-Surface Phenologies from AVHRR Using the Discrete Fourier Transform , 2001 .

[19]  F. Chapin,et al.  Consequences of changing biodiversity , 2000, Nature.

[20]  Alexander Ignatov,et al.  Global land monitoring from AVHRR: potential and limitations , 1995 .

[21]  Y. Richard,et al.  A statistical study of NDVI sensitivity to seasonal and interannual rainfall variations in Southern Africa , 1998 .

[22]  I. Douglas,et al.  Hydrological investigations of forest disturbance and land cover impacts in South-East Asia: a review. , 1999, Philosophical transactions of the Royal Society of London. Series B, Biological sciences.

[23]  E. Chuvieco Fundamentals of Satellite Remote Sensing , 2009 .

[24]  E. Lambin,et al.  Land use transitions: Socio-ecological feedback versus socio-economic change , 2010 .

[25]  Manfred Ehlers,et al.  Application of SPOT data for regional growth analysis and local planning , 1990 .

[26]  Feyera Senbeta,et al.  The impact of land use/land cover change on ecosystem services in the central highlands of Ethiopia , 2017 .

[27]  C. Potter,et al.  Global analysis of empirical relations between annual climate and seasonality of NDVI , 1998 .

[28]  Qihao Weng Land use change analysis in the Zhujiang Delta of China using satellite remote sensing, GIS and stochastic modelling. , 2002, Journal of environmental management.

[29]  Massimo Menenti,et al.  Mapping vegetation-soil-climate complexes in southern Africa using temporal Fourier analysis of NOAA-AVHRR NDVI data , 2000 .

[30]  R. Quiroz,et al.  Understanding precipitation patterns and land use interaction in Tibet using harmonic analysis of SPOT VGT‐S10 NDVI time series , 2005 .

[31]  M. Herold,et al.  Revisiting land cover observation to address the needs of the climate modeling community , 2011 .

[32]  Shilong Piao,et al.  NDVI‐indicated decline in desertification in China in the past two decades , 2005 .

[33]  Hankui K. Zhang,et al.  Using the 500 m MODIS Land Cover Product to Derive a Consistent Continental Scale 30 m Landsat Land Cover Classification , 2017 .

[34]  Robert J. Charlson,et al.  Atmospheric chemistry and air quality , 1975 .

[35]  C. Fürst,et al.  Assessing driving forces of land use and land cover change by a mixed-method approach in north-eastern Ghana, West Africa. , 2017, Journal of environmental management.

[36]  R. Stöckli,et al.  European plant phenology and climate as seen in a 20-year AVHRR land-surface parameter dataset , 2004 .

[37]  P. Dirmeyer,et al.  University of Nebraska-Lincoln DigitalCommons @ University of Nebraska-Lincoln Papers in Natural Resources Natural Resources , School of 2014 Land cover changes and their biogeophysical effects on climate , 2016 .

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

[39]  A. Belward,et al.  The international geosphere biosphere programme data and information system global land cover data set (DIScover) , 1997 .

[40]  C. Justice,et al.  The generation of global fields of terrestrial biophysical parameters from the NDVI , 1994 .

[41]  J. Townshend,et al.  Global discrimination of land cover types from metrics derived from AVHRR pathfinder data , 1995 .

[42]  J. Townshend,et al.  African Land-Cover Classification Using Satellite Data , 1985, Science.

[43]  William L. Briggs,et al.  The DFT : An Owner's Manual for the Discrete Fourier Transform , 1987 .

[44]  James E. Vogelmann,et al.  Comparison between two vegetation indices for measuring different types of forest damage in the north-eastern United States , 1990 .

[45]  L. Eklundh,et al.  Fourier series for analysis of temporal sequences of satellite sensor imagery , 1994 .

[46]  Philip Lewis,et al.  Topographic effects in AVHRR NDVI data , 1995 .