A review of hyperspectral remote sensing and its application in vegetation and water resource studies

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

Modelling canopy and litter interception in commercial forest plantations in South Africa using the Variable Storage Gash model and idealised drying curves

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 <i>Pinus, Acacia</i> and <i>Eucalyptus</i>, 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

A comparison of satellite hyperspectral and multispectral remote sensing imagery for improved classification and mapping of vegetation

In recent years the use of remote sensing imagery to classify and map vegetation over different spatial scales has gained wide acceptance in the research community. Many national and regional datasets have been derived using remote sensing data. However, much of this research was undertaken using multispectral remote sensing datasets. With advances in remote sensing technologies, the use of hyperspectral sensors which produce data at a higher spectral resolution is being investigated. The aim of this study was to compare the classification of selected vegetation types using both hyperspectral and multispectral satellite remote sensing data. Several statistical classifiers including maximum likelihood, minimum distance, mahalanobis distance, spectral angular mapper and parallelepiped methods of classification were used. Classification using mahalanobis distance and maximum likelihood methods with an optimal set of hyperspectral and multispectral bands produced overall accuracies greater than 80%.Keywords: hyperspectral, multispectral, satellite data, statistical classifiers, vegetation classificatio

Improving coastal livelihoods through sustainable aquaculture practices - a report to the collaborative APEC Grouper Research and Development Network

Wild-harvest fisheries for live reef fish are largely over-exploited or unsustainable because of over-fishing and the widespread use of destructive fishing practices such as blast and cyanide fishing. Sustainable aquaculture – such as that of groupers – is one option for meeting the strong demand for reef fish, as well as potentially maintaining or improving the livelihoods of coastal communities. This report from a short study by the STREAM Initiative draws on secondary literature, media sources and four diverse case studies from at-risk reef fisheries, to frame a strategy for encouraging sustainable aquaculture as an alternative to destructive fishing practices. It was undertaken as a component of the APEC-funded project Collaborative Grouper Research and Development Network (FWG/01/2001) to better understand how recent technical advances in grouper culture and other complementary work – including that of the Asia-Pacific Marine Finfish Aquaculture Network (APMFAN) hosted by NACA – could better support the livelihoods of poor coastal communities. (PDF contains 49 pages

Gesture and naming therapy for people with severe aphasia: a group study

In this study, the authors (a) investigated whether a group of people with severe aphasia could learn a vocabulary of pantomime gestures through therapy and (b) compared their learning of gestures with their learning of words. The authors also examined whether gesture therapy cued word production and whether naming therapy cued gestures

Spatial mapping of leaf area index using hyperspectral remote sensing for hydrological applications with a particular focus on canopy interception

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 <i>Eucalyptus</i>, <i>Pinus</i> and <i>Acacia</i> 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 <i>R</i><sup>2</sup> 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 <i>Pinus patula</i> 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

Field data collection and analysis of canopy and litter interception in commercial forest plantations in the KwaZulu-Natal Midlands, South Africa

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 <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% of gross precipitation, respectively

Improving the understanding of rainfall distribution and characterisation in the Cathedral Peak catchments using a geo-statistical technique

The characterisation of rainfall variability, spatially and temporally, is essential for hydrological and ecological analyses. Inherently, this variability is distinctly more obvious in mountainous areas compared to lowlands. The objective of this study was to ascertain if the use of the regression-Kriging technique would provide improved estimates and understanding of the rainfall distribution across the Cathedral Peak catchments in the Drakensberg escarpment region, South Africa. Findings showed longitude and altitude to be the overall best predictors of the distribution of rainfall for the annual period, wet season and dry season, with longitude explaining 72% and altitude explaining 26% of the rainfall variability for mean annual precipitation, 73% and 26% for the wet season and 50% and 22% for the dry season, respectively. The combination of both longitude and altitude showed a larger coefficient of determination, of 0.73, 0.74 and 0.51, for the annual, wet season and dry season, respectively. Long-term mean annual rainfall patterns showed an overall strong directional distribution from west to east with a distinct pattern observed during the dry season. It was concluded that regression-Kriging is a useful alternative method for characterising rainfall distribution as well as prediction errors for mountainous areas