The factor of scale in remote sensing

In this paper we consider how we may determine the relative proportions of ground cover components in a mixed pixel. We assume the usual linear model for signal mixing and examine a number of methods, closely related, for estimating the proportions. We also show how the precision of our estimates can be defined. We introduce a new estimator which is based on regularisation principles and which produces a smoother set of images than other methods, and gives more accurate estimates. The methods are compared on a simulated data set.

http://www2.geog.ucl.ac.uk/~mdisney/teaching/3051/hdf_prac/settle_drake_1993.pdf

Linear mixing and the estimation of ground cover proportions

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.

Review Article Principles of field spectroscopy

The climate system is driven, primarily, by energy absorbed at the surface. Surface albedo sensitivity is incorporated into all types of climate models, and changes can lead to large feedback effects. For example, alterations in the extent and/or state of the cryosphere and large-scale modification of vegetation cause significant perturbations in climate model results. The specification of surface albedo in general circulation climate models (GCM's) differs. An improved and agreed surface albedo data set is urgently required for climate modeling. It is likely that the most appropriate means of achieving consistent and credible surface albedos is by using well-designed satellite surveillance to augment global inventories of soils and vegetation. However, retrieval of surface albedo values for all sky and surface conditions from satellite observations is difficult. Atmospheric distortion is especially hard to remove. Some of the sensitivity of GCM's to surface albedo values may be the result of inadequate parameterization of other climatic components. The accuracy of information demanded by climate modelers could be reduced and made more consistent. Recommendations are made for the implementation of a new global scale observational program with the aim of providing surface albedo data at an accuracy of ±0.05 within 5–10 years. Immediate initiation is urged.

Surface albedo data for climatic modeling

An improved model of scenes for image analysis purposes, a nested-hierarchical approach which explicitly acknowledges multiple scales of objects or categories of objects, is presented. A multiple-pass, region-based segmentation algorithm improves the segmentation of images from scenes better modeled as a nested hierarchy. A multiple-pass approach allows slow and careful growth of regions while interregion distances are below a global threshold. Past the global threshold, a minimum region size parameter forces development of regions in areas of high local variance. Maximum and viable region size parameters limit the development of undesirably large regions. Application of the segmentation algorithm for forest stand delineation in TM imagery yields regions corresponding to identifiable features in the landscape. The use of a local variance, adaptive-window texture channel in conjunction with spectral bands improves the ability to define regions corresponding to sparsely stocked forest stands which have high internal variance.

Nested-hierarchical scene models and image segmentation

An approximate maximum likelihood technique employing a widely available discriminant analysis program is discussed that has been developed for resolving the percentage of component terrains within single resolution elements. The method uses all four channels of Landsat data simultaneously and does not require prior knowledge of the percentage of components in mixed pixels. It was tested in five cases that were chosen to represent mixtures of outcrop, soil and vegetation which would typically be encountered in geologic studies with Landsat data. For all five cases, the method proved to be superior to single band weighted average and linear regression techniques and permitted an estimate of the total area occupied by component terrains to within plus or minus 6% of the true area covered. Its major drawback is a consistent overestimation of the pixel component percent of the darker materials (vegetation) and an underestimation of the pixel component percent of the brighter materials (sand).

Resolving the percentage of component terrains within single resolution elements

A statistical method is presented for smoothing discriminant analysis classification maps by including pixel-specific prior probability estimates that have been determined from the frequency of tentative class assignments in a window moving across an initial per-point classification map. The class at the center of the window is reevaluated using the data for that location and the prior probability estimates obtained from the window area. An example using Landsat spectral data demonstrates the effectiveness of the method and shows an increase in classification accuracy after smoothing.

A prior probability method for smoothing discriminant analysis classification maps

A relation between landsat digital numbers, surface reflectance, and the cosine of the solar zenith angle

The VIIRS day/night band (DNB) high gain stage (HGS) pixel effective dwell time is in the range of 2–3 milliseconds (ms), which is about one third of the flicker cycle present in lighting powered by alternating current. Thus, if flicker is present, it induces random fluctuations in nightly DNB radiances. This results in increased variance in DNB temporal profiles. A survey of flicker characteristics conducted with high-speed camera data collected on a wide range of individual luminaires found that the flicker is most pronounced in high-intensity discharge (HID) lamps, such as high- and low-pressure sodium and metal halides. Flicker is muted, but detectable, in incandescent luminaires. Modern light-emitting diodes (LEDs) and fluorescent lights are often nearly flicker-free, thanks to high-quality voltage smoothing. DNB pixel footprints are about half a square kilometer and can contain vast numbers of individual luminaires, some of which flicker, while others do not. If many of the flickering lights are drawing from a common AC supplier, the flicker can be synchronized and leave an imprint on the DNB temporal profile. In contrast, multiple power supplies will throw the flickering out of synchronization, resulting in a cacophony with less radiance fluctuation. The examination of DNB temporal profiles for locations before and after the conversion of high-intensity discharge (HID) to LED streetlight conversions shows a reduction in the index of dispersion, calculated by dividing the annual variance by the mean. There are a number of variables that contribute to radiance variations in the VIIRS DNB, including the view angle, cloud optical thickness, atmospheric variability, snow cover, lunar illuminance, and the compilation of temporal profiles using pixels whose footprints are not perfectly aligned. It makes sense to adjust the DNB radiance for as many of these extraneous effects as possible. However, none of these adjustments will reduce the radiance instability introduced by flicker. Because flicker is known to affect organisms, including humans, the development of methods to detect and rate the strength of flickering from space will open up new areas of research on the biologic impacts of artificial lighting. Over time, there is a trend towards the reduction of flicker in outdoor lighting through the replacement of HID with low-flicker LED sources. This study indicates that the effects of LED conversions on the brightness and steadiness of outdoor lighting can be analyzed with VIIRS DNB temporal profiles.

/pdf/the-viirs-day-night-band-a-flicker-meter-in-space-13g91adb.pdf

William S. Kowalik

Papers

Resolving the percentage of component terrains within single resolution elements

A prior probability method for smoothing discriminant analysis classification maps

A relation between landsat digital numbers, surface reflectance, and the cosine of the solar zenith angle

The VIIRS Day/Night Band: A Flicker Meter in Space?