E.J. Milton

The use of the empirical line method to calibrate remotely sensed data to reflectance

To have lasting quantitative value, remotely sensed data must be calibrated to physical units of reflectance. The empirical line method offers a logistically simple means of generating acceptable estimates of surface reflectance. A review and case-study identify the ease with which this method can be applied, but also some of the pitfalls that can be encountered if it is not planned and implemented properly. A number of theoretical assumptions and practical considerations should be taken into account before applying this approach. It is suggested that the empirical line method allows the calibration of remotely sensed data to reflectance with errors of only a few percent.

Review Article Principles of field spectroscopy

Abstract Field spectroscopy involves the study of the interrelationships between the spectral characteristics of objects and their biophysical attributes in the field environment. It is a technique of fundamental importance in remote sensing, yet its full potential is rarely exploited. In this article the principles of the subject are explained and its historical development reviewed with reference to the instruments and methods adopted. Field spectroscopy has a role to play in at least three areas of remote sensing. Firstly, it acts as a ridge between laboratory measurements of spectral reflectance and the field situation and is thus useful in the calibration of airborne and satellite sensors. Secondly, it is useful in predicting the optimum spectral bands, viewing configuration and time to perform a particular remote sensing task. Thirdly, it provides a tool for the development, refinement and testing of models relating biophysical attributes to remotely-sensed data.

Linking remote sensing, land cover and disease

Land cover is a critical variable in epidemiology and can be characterized remotely. A framework is used to describe both the links between land cover and radiation recorded in a remotely sensed image, and the links between land cover and the disease carried by vectors. The framework is then used to explore the issues involved when moving from remotely sensed imagery to land cover and then to vector density/disease risk. This exploration highlights the role of land cover; the need to develop a sound knowledge of each link in the predictive sequence; the problematic mismatch between the spatial units of the remotely sensed and epidemiological data and the challenges and opportunities posed by adding a temporal mismatch between the remotely sensed and epidemiological data. The paper concludes with a call for both greater understanding of the physical components of the proposed framework and the utilization of optimized statistical tools as prerequisites to progress in this field.

Seasonal variations in the spectral reflectance of deciduous tree canopies

Abstract The directional spectral reflectance of deciduous forests changes markedly throughout the year as a consequence of the phenology of the canopy and understorey and changes in the spatial arrangement and density of scene components. This paper presents the results of a 1-year experiment using a tower-mounted spectroradiometer to measure the seasonal changes in the nadir reflectance properties of ash and beech canopies. Seasonal variations in reflectance in red wavelengths were found to be inversely related to percentage cover, whilst variations in near-infrared reflectance were directly related to percentage cover although for both wavelength regions changes in reflectance were not always exactly synchronous with changes in percentage cover. A strong rectilinear relation was observed between NDVI and percentage cover when data from both species were combined. The shape of the seasonal NDVI profile revealed differences between the two species that was ascribed to phenological differences between ash...

An ecological survey of deciduous woodlands using airborne remote sensing and geographical information systems (GIS)

Gaps within woodland canopies have important ecological roles and their spatial characteristics influence regeneration processes and the diversity and distribution species. This paper investigates the potential of airborne imaging spectrometer data for characterizing the spatial properties of gaps within deciduous woodlands. Imagery obtained in summer with an Compact Airborne Spectrographic Imager (CASI) was classified to produce an accurate map of canopy gaps within several deciduous woodlands. Imagery obtained in winter proved much less informative. Principal components analysis (PCA) of separate and combined summer and winter images revealed PCs that provided information on woodland canopy structure and could be classified to give an improved delineation of canopy gaps. The spatial characteristics within the woodlands were quantified using a raster-based GIS and pattern-process relationships were used to infer the relative ecological status of the different woodlands. The ability of the aircraft to fly at short notice and the high sensitivity and high spatial and spectral resolution of the airborne spectrometer offered many advantages over broad-band satellite sensors for this application.

Calibration of dual‐beam spectroradiometric data

An experiment to determine the most accurate and repeatable method for generating instrument inter‐calibration functions (ICFs) is described, based upon data collected with a dual‐beam GER1500 spectroradiometer system. The quality of reflectance data collected using a dual‐beam spectroradiometer system is reliant upon accurate inter‐calibration of the sensor pairs to take into account differences in their radiant sensitivity and spectral characteristics. A cos‐conical field‐based method for inter‐calibrating dual‐beam spectroradiometers was tested alongside laboratory inter‐calibration procedures. The field‐based method produced the most accurate results when a field‐derived ICF collected close in time was used to correct the spectral scan. A regression model to predict the ICF at a range of wavelengths was tested, using inputs of solar zenith angle, cosine of solar zenith angle and broadband diffuse‐to‐global irradiance ratios. The linear multiple regression model described up to 78% of the variability in ICF; the remainder of the variability was most likely due to complexities of instrumental behaviour in response to warm‐up time, ambient temperature and environmental conditions at the time of measurement. Collection of ICFs using a stable laboratory source was shown to provide unsatisfactory results due to differences between lamp outputs and the field‐measured solar spectrum. Consequently, the most practical and accurate method of deriving inter‐calibration functions is to use field‐derived ICFs, collected close in time and space to the data requiring correction.

Filling the gaps: remote sensing meets woodland ecology

Natural disturbance has considerable ecological significance, and within woodlands tree-falls significantly change environmental conditions. The spatial characteristics of canopy gaps influence regeneration dynamics, and species diversity and distribution. In this study imagery from a Compact Airborne Spectrographic Imager (CASI) was analysed to produce a vegetation cover map for a range of types of deciduous woodlands. This map was used to delineate canopy gaps in these areas. A raster-based GIS was used to derive a range of measures to describe he spatial characteristics of canopy gaps, in order to infer the relative ecological status of different types of deciduous woodland. For the study sites, spatial characteristics have been used to derive information on: (1) gap creation mechanisms: large gaps are created by progressive enlargement rather than instantaneously by a catastrophic event; (2) regeneration dynamics:

Ground radiometry and airborne multispectral survey of bare soils

Abstract Results are presented from studies of bare soils conducted during the NERC MSS-82, -83 and -84 campaigns. Test areas throughout southern and eastern England were selected to represent a wide range of British soils, and data from these sites are discussed in relation to the problems of intercalibrating ground and airborne data, as well as the effects of solar-sensor geometry on such intercalibration.

Remote sensing of salt marsh vegetation in the first four proposed Thematic Mapper bands

Abstract The potential for using data collected in the first four bands of the proposed thematic mapper for monitoring intertidal salt marsh vegetation is assessed, using ground spectral data collected with a portable multiband radiometer. Results from a field study in Chichester Harbour, Southern England, show that certain species can be separated using transformations of these data. The estimation of above ground biomass from ground spectral data was not possible for Spartina × townsendii agg., due to the combined effects of mixtures of different substrate types and mixtures of live and dead vegetation within the field of view of the radiometer. However, biomass estimation was possible for both Zostera marina L. and Fucus vesiculosus L. The relationships between biomass and bidirectional reflectance for these species followed a similar pattern, despite Fucus vesiculosus having carotenoids rather than chlorophylls as the dominant leaf pigments.

Supervised band selection for optimal use of data from airborne hyperspectral sensors

This paper presents a practical supervised band selection procedure for airborne imaging spectrometers and Maximum Likelihood classification (MLC) as data application. The output band set is optimal in band location, width and number regarding the MLC accuracy of the classification task. The supervised algorithm is based on feature selection and requires a user-defined class set. For two given semi-natural vegetation data and class sets, the selected band sets performed superior to established vegetation band sets used in current satellite and airborne sensors, most noticeably for the first few bands. The algorithm was implemented in IDLTM/ENVITM. It may also be used for feature selection, the generation of classdiscriminate colour composites, the prioritization of already existing band sets, and the determination of the intrinsic discriminant dimensionality of the data set.