Presentation on theme: "Miguel A. González-Botello Stephen H. Bullock and J. Mario Salazar Ceseña Comparison of Satellite and Ground Vegetation Indexes to Estimate Erosion in."— Presentation transcript:
Miguel A. González-Botello Stephen H. Bullock and J. Mario Salazar Ceseña Comparison of Satellite and Ground Vegetation Indexes to Estimate Erosion in a Mediterranean-climate Watershed Terrestrial Ecology Lab Conservation Biology Department Centro de Investigaciones Científicas y de Estudios Superiores de Ensenada
No 2 Introduction w Soil erosion is a natural process that reworks the distribution of organic matter, nutrients, and sediments. Accelerated erosion is part of the desertification process: loss of productivity, stored carbon and biodiversity
No 3 Soil erosion across a 5,000 km 2 watershed in NW Baja California has been estimated* using the Revised Universal Soil Loss Equation (RUSLE), in GIS. Introduction *Smith, S. V. et al. in press. Soil Erosion and its Potential Significance for Carbon Fluxes in a Mountainous Mediterranean-Climate Watershed. Ecological Applications
No 4 In a small area of southern France, DeJong* found a weak, linear relation of C to the Normalized Difference Vegetation Index (NDVI). Introduction *De Jong, S.M Derivation of vegetative variables from a Landsat TM image for modelling soil erosion. Earth Surface Processes and Landforms, Vol. 19, C = (NDVI) ( NIR – R) ( NIR + R) NDVI=
No 5 Our project will evaluate the relation of C (measured in the field with precise methods and large samples distributed over ~3000 km 2 ) to NDVI and to terrain variables (exposure, slope and elevation) and vegetation variables. Our objective
No 6 Mediterranean-climate part of Mexico. Rainfall of 265 mm Between November and April. Three Terrestrial Prioritized Regions. Chaparral and coastal scrub. Study area
No 7 GIS has been an important tool in designing the field work and will be essential to integration of ground and satellite data. The location of the field sites (c. 67) involved the following seven steps: Use of GIS in Site Selection
No 8 1.Update land use maps
No 9 2.Exclude non-shrub areas Settled, agricultural and woodland or grassland/meadow areas
No 10 3.Digitize paved and dirt roads
No 11 4.Create Map of Accessible Areas 40 and 250 m From the roads
No 12 5.Compare frequency distributions WatershedAccessible area ASPECT NDVI* * May 2005
No 13 WatershedAccessible area ELEVATION SLOPE
No 14 6.Select potential field sites Ca. 120 sites. substantially uniform over more than 1 hectare regarding slope, exposure and vegetation (visual or NDVI).
No 15 Site selection involved High resolution images of Digital Globe (Google Earth), INEGIs Ortophotos, NDVI, and Slope, Aspect & Height. Google Earth Images Digital Globe INEGIs Digital Orthophoto Web Service (WMS) On ArcGIS 9 NDVI (May 2005) On ArcGIS 9 Aspect derived from Inegis DEM On ArcGIS 9 Slope derived from Inegis DEM On ArcGIS 9
No 16 7.Select among potential sites We selected the sites to best represent the frequencies from the previous slides.
No 17 Aspect (North) Slope SouthNorth
No 18 Height NDVI
No 19 With KMLer 1.2, extensive interaction between Google Earth 3 and ArcGIS 9 was possible. Versatility
No 20 Field measurements were based on 30 m line transects. Drip height, soil surface cover, and types of cover were recorded at 20 random points along the line. Field Sampling Method
No 21 To assess aerial cover, we recorded the interception of each plant >20 cm diameter along the entire transect. We also recorded plant species, height, and perpendicular diameter. Field Sampling Method
No 22 Also, to better calibrate the erosion model, we collected samples of soil and litter. Terrain variables were recorded to compare with estimates from the digital elevation model. Field Sampling Method
No 23 Landsat data from late April-early May 2007 will be processed for NDVI (and EVI) and variance among years of contrasting rainfall will also be analyzed (2001, 2003, 2005). Satellite Image Processing
No 24 Preliminary Results The major part of sites shows a high soil cover (G Subfactor, 0 – 0.1). This reduces substantially the field calculated C Factor.
No 25 Preliminary Results De Jong Model tend to overestimate the C factor.
No 26 Our preliminary results suggests that the deJong Model is not suitable to assess erosion in Baja California Chaparral and Coastal Scrub.
No 27 Next steps Most analyses are pending as field work is recently finished. The acquisition of 2007 Landsat images are in process, the NDVI is not yet available.
No 28 Thanks to: Conservation Program 2007 Global Scholarship Program Centro de Investigaciones Científicas y de Estudios Superiores de Ensenada