Multispectral imagery has been used as the data source for water and land observational remote sensing from airborne and satellite systems since the early 1960s. Over the past two decades, advances in sensor technology have made it possible for the collection of several hundred spectral bands. This is commonly referred to as hyperspectral imagery. This review details the differences between multispectral and hyperspectral data; spatial and spectral resolutions and focuses on the application of hyperspectral imagery in water resource studies and, in particular the classification and mapping of land uses and vegetation.
Abstract. It is well accepted that the total evaporation in forested areas is greater than in grasslands, largely due to the differences in the amount of rainfall that is intercepted by the forest canopy and litter and due to higher transpiration rates. However, interception is the least studied of these components of the hydrological cycle. The study aims to measure and quantify the canopy and litter interception by Eucalyptus grandis, Pinus patula and Acacia mearnsii, at the Two Streams research catchment in the KwaZulu-Natal Midlands of South Africa for the three-year period April 2008 to March 2011. The results from this study showed that canopy and litter interception contributed a significant amount of the water evaporated in a forest water balance. The canopy interception by E. grandis, A. mearnsii and P. patula was 14.9 %, 27.7 % and 21.4 % of gross precipitation, respectively, while litter interception was 8.5 %, 6.6 % and 12.1 % of gross precipitation, respectively.
It is well accepted that the total evaporation in forested areas is greater than in grasslands, largely due to the differences in the amount of rainfall that is intercepted by the forest canopy and litter and higher transpiration rates. However, interception is the least studied of these components of the hydrological cycle. The study aims to measure and quantify the canopy and litter interception by <i>Eucalyptus grandis</i>, <i>Pinus patula</i> and <i>Acacia mearnsii</i>, at the Two Streams research catchment in the KwaZulu-Natal Midlands of South Africa for the three year period April 2008 to March 2011. The results from this study showed that canopy and litter interception contributed a significant amount of the water evaporated in a forest water balance. The canopy interception by <i>E. grandis</i>, <i>A. mearnsii</i> and <i>P. patula</i> was 14.9%, 27.7% and 21.4% of gross precipitation respectively, while litter interception was 8.5%, 6.6% and 12.1% respectively
Abstract. The establishment of commercial forestry plantations in natural grassland vegetation, results in increased transpiration and interception which in turn, results in a streamflow reduction. Methods to quantify this impact typically require LAI as an input into the various equations and process models that are applied. The use of remote sensing technology as a tool to estimate leaf area index (LAI) for use in estimating canopy interception is described in this paper. Remote sensing provides a potential solution to effectively monitor the spatial and temporal variability of LAI. This is illustrated using Hyperion hyperspectral imagery and three vegetation indices, namely the normalized difference vegetation index (NDVI), soil adjusted vegetation index (SAVI) and Vogelmann index 1 to estimate LAI in a catchment afforested with Eucalyptus, Pinus and Acacia genera in the KwaZulu-Natal midlands of South Africa. Of the three vegetation indices used in this study, it was found that the Vogelmann index 1 was the most robust index with an R 2 and root mean square error (RMSE) values of 0.7 and 0.3 respectively. However, both NDVI and SAVI could be used to estimate the LAI of 12 year old Pinus patula accurately. If the interception component is to be quantified independently, estimates of maximum storage capacity and canopy interception are required. Thus, the spatial distribution of LAI in the catchment is used to estimate maximum canopy storage capacity in the study area.
Abstract. There remains a gap in the knowledge of both canopy and litter interception processes in forest hydrology and limitations in the models used to represent them. In South Africa, interception is typically considered to constitute only a small portion of the total evaporation and in some models is disregarded. Interception is a threshold process, as a certain amount of water is required before successive processes can take place. Therefore an error or false assumption introduced in modelling interception will automatically introduce errors in the calibration of subsequent models/processes. Field experiments to assess these processes, viz. canopy and litter interception were established for the three main commercial forestry genera in South Africa, namely Pinus, Acacia and Eucalyptus, which are described in a companion paper. Drawing on both field and laboratory data, the "Variable Storage Gash" model for canopy interception and an idealised drying curve litter interception model were developed to represent these processes for South African conditions. The Variable Storage Gash model was compared with the original Gash model and it was found that it performed better than the original model in forests with high storage capacities yet was similar to the original model in stands with a low storage capacity. Thus, the models developed here were shown to adequately represent the interception processes and provide a way forward for more representative water resources planning modelling. It was found that canopy and litter interception can account for as much as 26.6 % and 13.4 % of gross precipitation, respectively, and are therefore important hydrological processes to consider in forested catchments in South Africa. Despite the limitation of both the Variable Storage Gash model and the idealised drying curve litter interception model being reliant on empirical relationships, their application highlights the importance of considering canopy and litter interception in water resources management and planning.
scite is a Brooklyn-based organization that helps researchers better discover and understand research articles through Smart Citations–citations that display the context of the citation and describe whether the article provides supporting or contrasting evidence. scite is used by students and researchers from around the world and is funded in part by the National Science Foundation and the National Institute on Drug Abuse of the National Institutes of Health.
customersupport@researchsolutions.com
10624 S. Eastern Ave., Ste. A-614
Henderson, NV 89052, USA
This site is protected by reCAPTCHA and the Google Privacy Policy and Terms of Service apply.
Copyright © 2024 scite LLC. All rights reserved.
Made with 💙 for researchers
Part of the Research Solutions Family.