Raster is a program for the analysis of data from a low cost remote sensing platform known as airborne videography. The application of the technique in Eucalypt forests is described by Coops et al 1998. Raster was developed to apply these technique in a mixed Callitris/Eucalyptus woodland located at Burrendong in New South Wales.
Raster is used to import the raw data files produced by the Specterra Systems Digital Multispectral Video System (DMSV). These binary files have a 512 byte header, followed by data structures representing light intensity in four bands (red, green, blue and near-infrared). Raster imports these files and converts the red, green and blue bands into a single bitmap (32 bit). The near-infrared (NIR) band is also saved as a bitmap. Facilities are available for converting files between four formats: Grid ASCII (Arc Info), BIL (binary inter-leaved), SUB (the raw format) and Windows bitmaps.
The interface allows you to filter out particular RGB values from an image, or transform the image using arbitrarily complex manipulations of the RGB values. The program also computes the habitat complexity score described by Coops et al 1998, and there are facilities for comparing the complexity scores with the original files. You can see a screenshot here, and download either a zipped file, or a self-installing exe (each is about 2.2Mb - including a test file). The program was developed for in-house use, and so I haven't had time to write a help file. If you have problems, please contact email@example.com.
I thank Nicholas Coops and Darius Culvenor for help in constructing the program. For further details, please consult the article by: Coops, N. C. & Catling, P. C. (1997) Utilising airborne multispectral videography to predict habitat complexity in eucalypt forests for wildlife management. Wildlife Research, 24, 691-702; or see the web page of Coops et al 1998.
GLORIA is a computer modelling system that simulates the births and deaths (demography) of livestock populations. It is a tool for exploring the way management interventions affect smallhold farmers. Because the model deals with small numbers of stock, it is necessarily a stochastic model — meaning that there is some element of chance in the final outcome. This makes the model appropriate for examining not only the gross returns from interventions, but also the risks that are inherent in any farming system. The current version of the program has been released to demonstrate the utility of such a model for both formal analysis of interventions, and as a unifying framework for production of extension materials. To support this dual role, the model provides two modes of operation. In "advanced" mode, the software package provides great flexibility in the specification of the demographic system, and provides access to a suite of tools for analytical studies. These tools allow the user to estimate the probability distributions of financial outcomes or other system metrics as a function of arbitrary interventions. In "ordinary" mode, the analytical tools are hidden, and the emphasis of the program is on (1) demonstrating or exploring the consequences of interventions in terms of gross financial outcomes and risk, and (2) the provision of a flexible, html-based information support package. The predefined scenarios provided in the current package are derived from studies of the goat raising in the Philippines, and parts of the interface reflect that historical background. However, the software package is capable of modelling a variety of livestock systems — not just goats. There has been no formal assessment of the validity of the parameters used in the predefined scenarios, and so the scenarios should not yet be used for predicting the outcome of interventions.