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Ecological applications of remote-sensing techniques are generally limited to images after atmospheric correction, though other radiometric correction data are potentially valuable. In this article, six spectral vegetation indices (VIs) were derived from a SPOT 5 image at four radiometric correction levels: digital number (DN), at-sensor radiance (SR), top of atmosphere reflectance (TOA) and post-atmospheric correction reflectance (PAC). These VIs include the normalized difference vegetation index (NDVI), ratio vegetation index (RVI), slope ratio of radiation curve (K), general radiance level (L), visible-infrared radiation balance (B) and band radiance variation (V). They were then related to the leaf area index (LAI), acquired from in situ measurement in Hetian town, Fujian Province, China. The VI–LAI correlation coefficients varied greatly across vegetation types, VIs as well as image radiometric correction levels, and were not surely increased by image radiometric corrections. Among all 330 VI–LAI models established, the R 2 of multi-variable models were generally higher than those of the single-variable ones. The independent variables of the best VI–LAI models contained all VIs from all radiometric correction levels, showing the potentials of multi-radiometric correction images in LAI estimating. The results indicated that the use of VIs from multiple radiometric correction images can better exploit the capabilities of remote-sensing information, thus improving the accuracy of LAI estimating. [ABSTRACT FROM AUTHOR]

Soil erosion by water under forest cover is a serious problem in southern China. A comparative study was carried out on the use of leaf area index (LAI) and vegetation fractional coverage (VFC) in quantifying soil loss under vegetation cover. Five types of vegetation with varied LAI and VFC under field conditions were exposed to two rainfall rates (40 mm h and 54 mm h) using a portable rainfall simulator. Runoff rate, sediment concentration and soil loss rate were measured at relatively runoff stable state. Significant negative exponential relationship (p < 0.05, R = 0.83) and linear relationship (p < 0.05, R = 0.84) were obtained between LAI and sediment concentration, while no significant relationship existed between VFC and sediment concentration. The mechanism by which vegetation canopy prevents soil loss was by reducing rainfall kinetic energy and sediment concentration. LAI could better quantify such a role than VFC. However, neither LAI nor VFC could explain runoff rate or soil loss rate. Caution must be taken when using LAI to quantify the role of certain vegetation in soil and water conservation. [ABSTRACT FROM AUTHOR]

Soil erosion is the most severe environmental problem in the red soil region of southern China. Erosion has been significantly reduced over the last 30 years through the deployment of a massive government re-forestation program. Nevertheless, soil erosion is still severe in some areas, and an efficient method for assessing soil erosion under secondary forest canopy is needed. Traditionally the vegetation indices derived from remotely sensed imagery have been used for identifying eroded areas. However, under high density forest canopy (HDFC) their applicability suffers due to biomass light absorption, which varies by canopy structure. A mapping method was developed by integrating remote sensing parameters to identify eroded areas. The remotely sensed vegetation indices, vegetation fractional canopy (VFC) and leaf area index (LAI) were calibrated based on soil erosion measurements from previous runoff plot experiments and extrapolated from USLE modeling to a regional scale. Using vegetation restoration degree (VRD), based on VFC ( VRD VFC = VFC / VIT VFC ) and LAI ( VRD LAI = LAI / VIT LAI ), soil erosion under HDFC was identified. Results indicate that the threshold value of VFC (VIT VFC ) and LAI (VIT LAI ) ranged from 0.45 to 0.60, and from 1.3 to 2.7, respectively. Secondary forest associated with VRD VFC > 100% or VRD LAI > 100% occupied 75.8% and 37.8% of the total study area, respectively. About 50% of the area distinguished as being eroded by LAI, was mapped as having no obvious erosion by VFC. LAI based mapping had a precision of 96.7% according to field validation. The eroded areas were primarily distributed in locations with elevation between 300 to 500 m and slope angles below 25°. The present method for distinguishing soil erosion under HDFC by combining VRD VFC and VRD LAI is effective and can be used for operational erosion monitoring in the red soil region of southern China. [ABSTRACT FROM AUTHOR]