The geospatial relationship of geologic strata, geological fractures, and land use attained by a time-series aridity index in a semiarid region.

In a vast semiarid region of the Baja California Peninsula, remote sensing and GIS techniques were applied to moderate resolution images of Landsat 5 TM to explore the geospatial correlation among the grid aridity index (AI), shapefiles of geologic strata, land use, and geological fractures. A dataset of randomized sample points in a time-series of one hydrologic year along with vector file GIS delineated geologic fractures-including the area between their left/right parallel buffer lines-was used as mask analysis. MANOVA results were significant (p < 0.05) for geologic strata, land use, and basin. Overall results reveal the effects of soil texture on water retention on deeper soil horizons and the rate of vertical motion of rainwater. Despite the fact that geologic fractures underlie a large number of biotic communities, in both latitude and longitude gradients of the peninsula, no statistical significance was observed among the fractures themselves or the areas between their parallel buffer lines. One pulse rainfall event was documented by the AI grid maps enabling a robust vegetative response in early summer to an abnormal amount of rain provided by tropical storm Julio. AI grids appear to be useful for characterizing an ecosystem's dynamism. New options are suggested for this research strategy by expanding the number of datasets and incorporating geographic exclusion areas.

Vegetation response to hydrologic and geomorphic factors in an arid region of the Baja California Peninsula.

Remotely sensed imageries were used to analyze the response of desert vegetation to physiographic factors and accumulated precipitation in drier and wetter years within a region of >16,500 km(2) sampled with 5,000 random pixels of 30 m. Vegetation development was indexed by the annual maximum values for greenness (SAVI) and canopy water content (NDII). Precipitation was interpolated from the 0.25° grid of the Tropical Rainfall Measurement Mission satellite-based estimates, showing a regional average of ∼55 mm in the wetter year. The vegetation indices were only weakly related to total precipitation, often in a negative sense. Terrain factors that most often affected the vegetation indices, in multiple regression models, were Topographic Wetness Index, elevation, and slope gradient; these often had different signs for SAVI and for NDII. Models for NDII on intrusive igneous rocks gave better results than on extrusive igneous rocks. The strongest patterns in vegetation development were the contrast among Pacific coast, Cordillera, and Gulf coast subregions and the generally stronger results for NDII than SAVI.