Biophysical Properties of Cultivated Pastures in the Brazilian Savanna Biome: An Analysis in the Spatial-Temporal Domains Based on Ground and Satellite Data

Abstract: Brazil has the largest commercial beef cattle herd in the world, with cattle ranching being particularly prominent in the 200-million ha, Brazilian neotropical moist savanna biome, known as Cerrado, one of the world’s hotspots for biodiversity conservation. As decreasing productivity is a major concern affecting the Cerrado pasturelands, evaluation of pasture conditions through the determination of biophysical parameters is instrumental for more effective management practices and herd occupation strategies. Within this context, the primary goal of this study was the regional assessment of pasture biophysical properties, through the scaling of wet- and dry-season ground truth data (total biomass, green biomass, and % green cover) via the combined use of high (Landsat-TM) and moderate (MODIS) spatial resolution vegetation index images. Based on the high correlation found between NDVI (normalized difference vegetation index) and % green cover (r = 0.95), monthly MODIS-based % green cover images were derived for the 2009–2010 hydrological cycle, which were able to capture major regional patterns and differences in pasture biophysical responses, including the increasing greenness values towards the southern portions of the biome, due to both local conditions (e.g., more fertile

[1]  R. Schowengerdt,et al.  Early results on the characterization of the Terra MODIS spatial response , 2002 .

[2]  Michel Brossard,et al.  CONVERSÃO DO CERRADO EM PASTAGENS CULTIVADAS E FUNCIONAMENTO DE LATOSSOLOS , 2005 .

[3]  Gregory P. Asner,et al.  Objective indicators of pasture degradation from spectral mixture analysis of Landsat imagery , 2008 .

[4]  Laerte Guimarães Ferreira,et al.  The Cerrado into-pieces: habitat fragmentation as a function of landscape use in the savannas of central Brazil. , 2009 .

[5]  Michael J. Hill,et al.  Quantitative mapping of pasture biomass using satellite imagery , 2011 .

[6]  T. Seastedt,et al.  Consequences of Nonequilibrium Resource Availability Across Multiple Time Scales: The Transient Maxima Hypothesis , 1993, The American Naturalist.

[7]  Felipe García-Oliva,et al.  Soil Carbon and Nitrogen Dynamics Followed by a Forest-to-pasture Conversion in Western Mexico , 2006, Agroforestry Systems.

[8]  Marcos Heil Costa,et al.  Effects of Amazon and Central Brazil deforestation scenarios on the duration of the dry season in the arc of deforestation , 2010 .

[9]  A. Huete,et al.  Development of a two-band enhanced vegetation index without a blue band , 2008 .

[10]  D. Sawyer Climate change, biofuels and eco-social impacts in the Brazilian Amazon and Cerrado , 2008, Philosophical Transactions of the Royal Society B: Biological Sciences.

[11]  C. Kummerow,et al.  The Tropical Rainfall Measuring Mission (TRMM) Sensor Package , 1998 .

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

[13]  L. Ferreiraa,et al.  Seasonal landscape and spectral vegetation index dynamics in the Brazilian Cerrado : An analysis within the Large-Scale Biosphere – Atmosphere Experiment in Amazônia ( LBA ) , 2003 .

[14]  R. Mittermeier,et al.  Biodiversity hotspots for conservation priorities , 2000, Nature.

[15]  J. V. Soares,et al.  Characterization of pasture biophysical properties and the impact of grazing intensity using remotely sensed data , 2007 .

[16]  M. H. Costa,et al.  Effects of large-scale changes in land cover on the discharge of the Tocantins River, Southeastern Amazonia , 2003 .

[17]  Robert M. Boddey,et al.  Chemical and biological indicators of decline/degradation of Brachiaria pastures in the Brazilian Cerrado , 2004 .

[18]  Josep Peñuelas,et al.  The photochemical reflectance index (PRI) and the remote sensing of leaf, canopy and ecosystem radiation use efficiencies: A review and meta-analysis , 2011 .

[19]  Manuel Eduardo Ferreira,et al.  DETECÇÃO DE DESMATAMENTOS NO BIOMA CERRADO ENTRE 2002 E 2009: PADRÕES, TENDÊNCIAS E IMPACTOS , 2012, Revista Brasileira de Cartografia.

[20]  P. Verburg,et al.  From land cover change to land function dynamics: a major challenge to improve land characterization. , 2009, Journal of environmental management.

[21]  S. Filoso,et al.  Expansion of sugarcane ethanol production in Brazil: environmental and social challenges. , 2008, Ecological applications : a publication of the Ecological Society of America.

[22]  K. Shadan,et al.  Available online: , 2012 .

[23]  K. Itten,et al.  Hyperspectral remote sensing for estimating aboveground biomass and for exploring species richness patterns of grassland habitats , 2011 .

[24]  R. Hobbs,et al.  Disturbance, Diversity, and Invasion: Implications for Conservation , 1992 .

[25]  Maosheng Zhao,et al.  Improvements to a MODIS global terrestrial evapotranspiration algorithm , 2011 .

[26]  E. E. Sano,et al.  Assessing the spatial distribution of cultivated pastures in the Brazilian savanna. , 2000 .

[27]  Yoram J. Kaufman,et al.  Atmospheric correction against algorithm for NOAA-AVHRR products: theory and application , 1992, IEEE Trans. Geosci. Remote. Sens..

[28]  V. Caselles,et al.  An alternative simple approach to estimate atmospheric correction in multitemporal studies , 1989 .

[29]  Robert A. Schowengerdt,et al.  Remote sensing, models, and methods for image processing , 1997 .

[30]  L. G. Barioni,et al.  Estimating greenhouse gas emissions from cattle raising in Brazil , 2012, Climatic Change.

[31]  Wendy Jepson,et al.  A disappearing biome? Reconsidering land‐cover change in the Brazilian savanna , 2005 .

[32]  S. Kanae,et al.  Global Hydrological Cycles and World Water Resources , 2006, Science.

[33]  A. Huete,et al.  MODIS Vegetation Indices , 2010 .

[34]  Marcos Heil Costa,et al.  Cerrado Conservation is Essential to Protect the Amazon Rainforest , 2010, AMBIO.

[35]  E. Davidson,et al.  Equivalent water thickness in savanna ecosystems: MODIS estimates based on ground and EO-1 Hyperion data , 2011 .

[36]  Edson E. Sano,et al.  Land cover mapping of the tropical savanna region in Brazil , 2010, Environmental monitoring and assessment.

[37]  José M. Paruelo,et al.  REGIONAL PATTERNS OF NORMALIZED DIFFERENCE VEGETATION INDEX IN NORTH AMERICAN SHRUBLANDS AND GRASSLANDS , 1995 .

[38]  Takahiro Wada,et al.  Scaling Effect of Area-Averaged NDVI: Monotonicity along the Spatial Resolution , 2012, Remote. Sens..

[39]  Laerte Guimarães Ferreira,et al.  Land Use Change and the Carbon Budget in the Brazilian Cerrado , 2010 .

[40]  G. B. Martha Junior,et al.  Pastagens no cerrado: baixa produtividade pelo uso limitado de fertilizantes. , 2003 .

[41]  Michael T. Coe,et al.  The effects of deforestation and climate variability on the streamflow of the Araguaia River, Brazil , 2011 .

[43]  Edson Eyji Sano,et al.  Mapeamento da cobertura vegetal do bioma cerrado. , 2009 .

[44]  Carlos A. Klink,et al.  A conservação do Cerrado brasileiro , 2005 .