Vegetation cover quality assessment through MODIS time series satellite data in an urban region

To preserve urban vegetation land cover quality and mitigate its degradation is an important task for urban planning and environmental management of Bucharest metropolitan area in Romania. Since vegetation land cover dynamics directly affect the urban landscape characteristics and air quality, remote sensing represents an effective tool for vegetation land cover quality assessment at regional scale. In particular, the use of satellite-based vegetation indices, like the NDVI (Normalized Difference Vegetation Index), can provide important information when evaluating Urban Vegetation Cover Quality (UVCQ) patterns in urban areas, which represents one of the most sensitive landscape components to urban environmental degradation. This paper proposes an approach for the regional-scale assessment of UVCQ by means of an NDVI-based (functional) indicator using freely available time series MODIS Terra/Aqua (Moderate Resolution Imaging Spectroradiometer) satellite data. As a case study, Bucharest metropolitan area landscape experiencing climate and anthropogenic changes, increasing human pressure and high vulnerability to degradation was chosen. As UVCQ indicator, the NDVI-based vegetation cover classification was produced by means of unsupervised multivariate statistical techniques and compared with spatio-temporal changes during 2002-2012 period, statistical indicators, and field data related to land cover management observed in the study area. Results demonstrate that the obtained remotely sensed vegetation land cover characterization can be effectively considered as a proxy of the UVCQ status of the examined area. Due to the large availability over time and low cost of satellite images, the proposed approach can be applied to wider urban/periurban regions, to monitor vegetation quality and indirectly control vegetation land degradation.

[1]  Asbjørn Aaheim,et al.  Integrated modelling approaches to analysis of climate change impacts on forests and forest management , 2011 .

[2]  B. Duchemin NOAA/AVHRR Bidirectional Reflectance , 1999 .

[3]  R. Lunetta,et al.  Land-cover characterization and change detection using multitemporal MODIS NDVI data , 2005, International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, 2005..

[4]  Edward J. Milton,et al.  Estimating the irradiance spectrum from measurements in a limited number of spectral bands , 2006 .

[5]  Charalabos Ioannidis,et al.  Towards a strategy for control of suburban informal buildings through automatic change detection , 2009, Comput. Environ. Urban Syst..

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

[7]  A F Goetz,et al.  Imaging Spectrometry for Earth Remote Sensing , 1985, Science.

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

[9]  Rob J Hyndman,et al.  Detecting trend and seasonal changes in satellite image time series , 2010 .

[10]  J. A. Simmons,et al.  Forest to reclaimed mine land use change leads to altered ecosystem structure and function. , 2008, Ecological applications : a publication of the Ecological Society of America.

[11]  L. Ji,et al.  Performance evaluation of spectral vegetation indices using a statistical sensitivity function , 2007 .

[12]  O. Sen,et al.  Impacts of Re-greening the Desertified Lands in Northwestern China: Implications from a Regional Climate Model Experiment , 2004 .

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

[14]  C. Lo,et al.  Using a time series of satellite imagery to detect land use and land cover changes in the Atlanta, Georgia metropolitan area , 2002 .

[15]  Bradley C. Reed,et al.  Integration of MODIS-derived metrics to assess interannual variability in snowpack, lake ice, and NDVI in southwest Alaska. , 2009 .

[16]  G. Carter Ratios of leaf reflectances in narrow wavebands as indicators of plant stress , 1994 .

[17]  D. Horler,et al.  The red edge of plant leaf reflectance , 1983 .

[18]  M. Alberti,et al.  Using NDVI to Assess Vegetative Land Cover Change in Central Puget Sound , 2006, Environmental monitoring and assessment.