Study of the NDVI with multi-scale and time-series analysis using SPOT imagery during the period 1998-2012 in Uruguay

M. Ceroni, M. Achkar, I. Gazzano, J. Burgueño


Vegetation indices are a relevant source of information for spatial monitoring of vegetation at multiple scales. Among them, the Normalized Difference Vegetation Index (NDVI) is one of the most commonly used. This study aims to describe and analyze the spatial patterns of the NDVI in terrestrial systems in Uruguay at the onset of the 21st Century. A multiscalar approach (country, basin and sites) was applied using time series analysis of NDVI values obtained from SPOT 4 and 5 images through the program Instrument Vegetation (VGT). The analyzed time series showed a significant fit of the Autocorrelated Integrated Moving Averages (ARIMA) model, with an autocorrelation of order 2 and a level of integration of order 1, ARIMA (211). A significant decline of the NDVI over all spatial units was found, with agricultural units (site scale) showing the most negative slope. This study provides baseline data on changes in vegetation productivity for Uruguay, and develops an accurate and robust methodology for spatio-temporal analysis of NDVI series. Remote sensing techniques are shown to be relevant to improve the management of environmental systems.


NDVI; time series; SPOT; multi-scalar approach; remote sensing

Full Text:



Barbosa, H., Tote, C., Kumar, L., Bamutaze, Y. 2013. Harnessing Earth Observation and Satellite Information for Monitoring Desertification, Drought and Agricultural Activities in Developing Countries. En S. S. Young y S. E. Silvern (Eds.), Environmental Change and Sustainability (Vol. 1, pp. 91-121).

Campbell, J. B. 1996. Introduction to remote sensing. London: Taylor & Francis.

Carlson, T. N., Ripley, D. A. 1997. On the relation between NDVI, fractional vegetation cover, and leaf area index. Remote Sensing of Environment, 62(3), 241-252.

Carreras, J., Shimabukuro, J., Pereira., Y. 2002. Fraction images derived from SPOT-4 VEGETATION data to assess land-cover change over the State of Mato Grosso, Brazil. International Journal Remote Sensing, 23(23), 4983-4987.

Cihlar, J., Latifovic, R., Beaubien, J., Guindon, B., Palmer, M. 2003. Tematic Mapper (TM) based accuracy assessment of a land cover product for Canada derived from SPOT4/VGT data. Canadian Journal of Remote Sensing, 29(2), 154-170.

Chapin, F., Zavaleta, E., Eviner, V., Naylor, R., Vitousek, P., Reynolds, H., Hooper, D., Lavorel, S., Sala, O. E., Hobbie, S. E., Mack, M. C., Díaz, S. 2000.Consequences of changing biodiversity. Nature, 405, 234-242.

Chiesi, M., Maselli, F., Bindi, M., Fibbi, L., Cherubini, P., Arlotta, E., Tirone, G., Matteucci, G., Seufert, G. 2005. Modelling carbon budget of Mediterranean forests using ground and remote sensing measurements. . Agricultural and Forest Meteorology, 135(1), 22-34.

Chirici, G., Barbati, A., Maselli, F. 2007. Modelling of Italian forest net primary productivity by the integration of remotely sensed and GIS data. Forest Ecology and Management, 246(2), 285-295.

Chuvieco, E. 2000. Fundamentos de teledetección espacial. Madrid: Rialp.

D’Ozouville, N., Deffontaines, B., Benveniste, J., Wegmüller, U., Violette, S., Marsily, G. 2008. DEM generation using ASAR (ENVISAT) for addressing the lack of freshwater ecosystems management, Santa Cruz Island, Galapagos. Remote Sensing of Environment, 112(11), 4131-4147.

Deng, X., Huang, J., Rozelle, S., Uchida, E. 2006. Cultivated land conversion and potential agricultural productivity in China. Land Use Policy, 23(4), 372-384.

DIEA. 2013. Anuario 2012. Obtenido de,diea,diea-anuario-2012,O,es,0, Acceso: abril de 2015.

Fang, J., Piao, S., Tang, Z. 2001. Interannual Variability in Net Primary Production and Precipitation. Science, 293(5536), 1723.

Font, N. 2000. Local y Sostenible. En: N. Font y J. Subirats (Eds.), Local y Sostenible: La agenda 21 local de España (pp. 9-29). Barcelona: Icaria

Funtowicz, S., Ravetz, J. 1991. A New Scientific Methodology for Global Environmental Issues. En: R. Constanza (Ed.), Ecological Economics: The Science and Management of Sustainability (pp. 137-152). New York: Columbia University Press.

García Préchac, F., Ernst, O., Arbeletche, P., Bidegain, M. P., Pritsch, C., Ferenczi, A.,Rivas M. (eds.). 2010. Intensificación agrícola: oportunidades y amenazas para un país productivo y natural. Montevideo: Universidad de la República. CSIC.

Gasto, J., Panario, D., Morato, E., Gallardo, S. 1987. Sitio en el sistema de clasificación de pastizales. Santiago: Central de Apuntes de Ingenieria.

GMES. 1998. Global Monitoring for Environment and Security. Obtenido de: Último acceso: 3 de marzo, 2014.

Gonzáles, M., Román, M. 2009. Expansión agrícola en áreas extrapampeanas de la Argentina. Una mirada desde los actores sociales. Cuadernos de Desarrollo Rural, 62(6), 99-120. Obtenido de Acceso:abril de 2015.

Guerschman, J., Paruelo, J., Di Bella, M., Giallorenzi,M., Pacin, F. 2003. Land cover classification in the Argentine Pampas using multi-temporal Landsat TM data. International Journal Remote Sensing, 24(17), 3381-3402.

Guissard, V., Defourny, P., Ledent, J. 2004. Crop specific information extraction based on coarse resolution pixel sampling. Proceedings VEGETATION 2004,1(1), 391-398. Obtenido de Acceso: abril de 2015.

Holben, B. N. 1986. Characteristics of maximumvalue composite images from temporal AVHRR data. International Journal of Remote Sensing, 7(11), 1417-1434.

Hooper, D., Chapin, F., Ewel, J., Hector, A., Inchausti, P., Lavorel, S., Hawton, J., Naeem, D., Schmid, B., Setälä, H., Symstasd, A., VAndermeer, J., Wardle, D. 2005. Effects of biodiversity on ecosystem functioning: a consensus of current knowledge. Ecological Monographs, 75(1), 3-35.

IAI. 2011. Newsletter. San Pablo: Inter-American Institute for Global Change Research (IAI).

INIA-GRAS. 1999. NDVI. Último acceso: 14 de diciembre, 2014, obtenido de:

Jiménez, J. F., Sánchez, R., Gázquez, J. C. 2006. La capacidad predictiva en los métodos Box- Jenkis y Holt-Winters: una aplicación al sector turístico. Revista Europea de Dirección y Economía de la Empresa, 15(3), 185-197. Acceso: abril de 2015.

Kinyanjui, M. J. 2011. NDVI-based vegetation monitoring in Mau forest complex, Kenya. African Journal of Ecology, 49(2), 165-174.

Levin, S. 1992. The problem of pattern and scale in ecology. Ecology, 73(6), 1943-1967.

Mohamed, M., Babiker, I., Chen, Z., Ikeda, K., Ohta, K., Kato, K. 2004. The role of climate variability in the inter-annual variation of terrestrial net primary production (NPP). Science of the Total Environment., 332(1-3), 123-137.

Moulin, S., Zurita, R., Guérif, M., Baret, F. 2003. Characterizing the spatial and temporal variability of biophysical variables of a whwat crop using hyper-spectral measurements. Geoscience and Remote Sensing Symposium, 2003. IGARSS ‘03. Proceedings. 2003 IEEE International, vol. 4.

Norris, R., CaswelL-Chen , E., Kogan, M. 2003. Ecosystems biodiversity and IPM. En: R. Norris (Ed.), Concepts in integrated pest management. USA: Prentice Hall.

O’neill, R. V., King, A. W. 1998. Homage to St. Michael; or why are there so many books on scale ? En: D. L. Peterson y V. T. Parker (Eds.), Ecological Scale: Theory and Applications (pp. 3-15). New York: Columbia University Press.

Paruelo, J., Epstein, H., Lauenroth, W., Burke, I. 1997. ANPP estimates from NDVI for the central grassland region of the United States. Ecology, 78(3), 953-958.[0953:AEFNFT]2.0.CO;2

Paruelo, J., Garbulsky, M., Guerschman, J., Jobbágy, E. G. 2004. Two decades of Normalized Difference Vegetation Index changes in South America: identifying the imprint of global change. International Journal Remote Sensing, 25(14), 2793-2806.

Preciozzi, F., Spoturno, J., Heinzen, W., Rossi, R. 1985. Memoria explicativa de la Carta Geológica del Uruguay del Uruguay a la escala 1:500.000.

Prince, S. D. 1991. A model of regional primary production for use with coarse resolution satellite data. nternational Journal Remote Sensing, 12(6), 1313-1330.

Riaño, D., Chuvieco, E., Salas, J., Aguado, I. 2003. Assessment of different topographic corrections in Landsat-TM data for mapping vegetation types. Geoscience and Remote Sensing, 41(5), 1056-1061.

Rödelsperger, S., Becker, M., Gerstenecker, C., Läufer, G., Schilling, K., Steineck, D. 2010. Digital elevation model with the ground-based SAR IBIS-L as basis for volcanic deformation monitoring. Journal of Geodynamics, 49(3), 241-246.

Samanta, A., Costa, M., Nunes, E., Vieira, S., Xu, L., Myneni, R. 2011. Comment on “Drought-Induced Reduction in Global Terrestrial Net Primary Production from 200 Through 2009”. Science, 333(6049), 1093-1094.

Santos, G., Camargo, F. 1999. Fundamentos da matéria Orgânica do Solo: Ecosistemas Tropicais e subtropicais. Porto Alegre: Gênesis.

Seyler, F., Chaplot, V., Muller, F., Cerri, C. E. P., Bermoux, M., Ballestar, V., Feller, C., Cerri, C. C. C. 2002. Pasture mapping by classification of Landsat TM images. Analysis of the spectral behaviour of he pasture class in a real medium-scale environment : the case of the Piracicaba Catchment (12400 km², Brazil). International Journal

Remote Sensing, 23(23), 4985-5004.

Simic, A., Chen, J. M., Liu, J., Csillag, F. 2004. Spatial scaling of net primary productivity using subpixel information. Remote Sensing of Environment, 93(1-2), 246-258.

Tarnavsky, E., Garrigues, S., Brown, M. 2008. Multiscale geostatistical analysis of AVHRR, SPOTVGT, and MODIS global NDVI products. Remote Sensing of Environment, 112(2), 535-549.

Telesca, L., Lasaponara, R. 2006. Quantifying intraannual persistent behaviour in SPOT-VEGETATION NDVI data for Mediterranean ecosystems of southern Italy. Remote Sensing of Environment, 101(1), 95-103.

Tucker, C., Sellers, P. 1986. Satellite remote sensing of primary production. International Journal Remote Sensing, 7(11), 1395-1416.

Vitousek, P., Mooney, H., Lubchenco, J., Melillo, J. 1997. Human Domination of Earth’s Ecosystems. Science, 277(5325), 494-499.

Wiens, J. A. 1989. Spatial scaling in ecology. Functional Ecology, 3(4), 385-397. Obtenido de Acceso: abril de 2015.

Xiao, X., Boles, S., Liu, J., Zhuang, D., Liu, M. 2002. Characterization of forest types in Northeastern China, using multi-temporal SPOT-4 Vegetation sensor data. Remote Sensing of Environment, 82(2-3), 335-348.

Xiaoliang, L., Ronggao, L., Jiyuan, L., Shunlin, L. 2007. Removal of Noise by Wavelet Method to Generate High Quality Temporal Data of Terrestrial MODIS Products. Photogrammetric Engineering and Remote Sensing, 73(10), 1129-1139.

Yan, H., Liu, J., Huang, H. Q., Tao, B., Cao, M. 2009. Assessing the consequence of land use change on agricultural productivity in China. Global and Planetary Change, 67(1-2), 13-19.

Zapata, C., Toro, M., Marín, I. 2012. Definición de un método basado en patrones de análisis para la interoperabilidad entre sistemas de información geográfica Número. Revista EIA, 9(18), 179-194.

Zhang, C., Jordan, C., Higgins, A. 2007. Using neighbourhood statistics and GIS to quantify and visualize spatial variation in geochemical variables: An example using Ni concentrations in the topsoils of Northern Ireland. Geoderma, 13(3), 466-476.

Zhang, G., Kang, Y., Han, G., Sakurai, K. 2011. Effect of climate change over the past half Century on the distribution, extent and NPP of ecosystems of Inner Mongolia. Global Change Biology 17(1), 377-389.

Zhao, M., Running, S. 2010. Drought-Induced Reduction in Global Terrestrial Net Primary Production from 200 Through 2009. Science, 329(5994), 940-942.

Abstract Views

Metrics Loading ...

Metrics powered by PLOS ALM


Cited-By (articles included in Crossref)

This journal is a Crossref Cited-by Linking member. This list shows the references that citing the article automatically, if there are. For more information about the system please visit Crossref site

1. From a Vegetation Index to a Sustainable Development Goal Indicator: Forest Trend Monitoring Using Three Decades of Earth Observations across Switzerland
Erica Honeck, Roberto Castello, Bruno Chatenoux, Jean-Philippe Richard, Anthony Lehmann, Gregory Giuliani
ISPRS International Journal of Geo-Information  vol: 7  issue: 12  first page: 455  year: 2018  
doi: 10.3390/ijgi7120455


This journal is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International

Universitat Politècnica de València

Official Journal of the Spanish Association of Remote Sensing

e-ISSN: 1988-8740    ISSN: 1133-0953