John Louis

Characterising and mapping vineyard canopy using high-spatial-resolution aerial multispectral images

Airborne digital images of vineyards have potential for yielding valuable information for viticulturists and vineyard managers. This paper outlines a method of analysing high-spatial-resolution airborne images of vineyards to estimate physical variables of individual grapevines in terms of local canopy shape and size. An algorithm (“Vinecrawler”) has been developed to identify individual vine rows and extract sets of reflectance values (or combinations thereof) at quasi-regular distances (approximately one pixel length) along the rows. Key vine canopy variables, including size, foliage density and shape, were calculated from the sets of reflectance values collected by Vinecrawler. The algorithm precisely identifies individual vines, allowing conversion from image coordinates (x-pixel, y-pixel) to a (row, vine) coordinate system. The (row, vine) coordinate system is a valuable tool for directing vineyard managers to particular phenomena identified from variables returned by Vinecrawler. This paper describes the computational methods used to identify vine rows in raw airborne digital imagery and the operation of the Vinecrawler algorithm used to track along vine rows and extract vine canopy size and shape descriptors and locational information.

Relating wetland inundation to river flow using Landsat TM data

Satellite imagery has been used in many studies that seek to relate river flow to floodplain inundation. However, on rivers with moderately to highly variable daily flows it is difficult to establish a reliable relationship between river stage and area of floodplain inundation. This is because the rapid downstream movement of the flood peak results in the area of maximum inundation at any time being spatially restricted. This study presents a method that accounts for rapid variation in daily discharge using before-flood and after-flood sequences of Landsat Thematic Mapper (TM) imagery in reference to a predefined wetland vector coverage. This procedure establishes a relationship between wetland inundation and river discharge. It also reduces errors of commission arising from: the retention of water on the floodplain from previous floods; the filling of wetlands from rainfall and other non-channel sources; and pixel mis-classification.

Estimation of error in bankfull width comparisons from temporally sequenced raw and corrected aerial photographs

This study investigates the propagation of error through image-to-image comparison of 285 river bankfull width measurements of the Afon Trannon, mid-Wales. Bankfull width is quantified from both aerial photographs analysed as rectified images in ERDAS Imagine OrthoMax and raw images in Paintshop Pro. A method for the robust estimation of bankfull width measurement error through temporal sequences of scanned aerial photographs is presented and the improvement in accuracy achieved using rectified imagery is quantified. Results from this study are placed in the context of previously published rates of bankfull width change, from a wide range of river scales, and the bankfull change rates for robust medium-term analysis using approximately 1:10,000 historical aerial photography are identified.

A variational approach to the radiometric enhancement of digital imagery

In this correspondence, we present a variational approach to the problem of finding suitable radiometric image transformations that optimize desirable characteristics of the output image histogram. This variational approach can be interpreted as the minimization of the cumulative spacing between histogram bars in the least squares sense subject to some weight function. Most of the common histogram transformation procedures used in remote sensing applications can be deduced from this general variational approach with an appropriate choice of the weight function.

Vineclipper: A Proximal Search Algorithm to Tie Gps Field Locations to High Resolution Grapevine Imagery

Grapevine canopy characteristics as determined from remotely sensed imagery have been shown to be effective in forecasting grape composition parameters that can be used to estimate the quality of wine made from those grapevines. Maps of canopy characteristics are therefore valuable tools for precision viticulture practice. In a case of extracting reflectance data at the scale of individual vines from vineyard imagery with a pixel resolution of ca. 0.5 m, simple use of sample point location data provided by a GPS (the GPS points) projected onto a georectified image proved too inaccurate for the desired analysis. At the individual vine scale, the spatial error between the GPS point and the corresponding location in a georectified image was great enough to result in clearly incorrect pixels being identified as representative of the sample grapevine canopy. The sample GPS point locations were, however, sufficiently close to the correct vine canopy in the georectified image to act as a seed point for a computer search algorithm.

A simplified method for retrieval of ground level reflectance of targets from airborne video imagery

This paper describes an efficient method for retrieval of ground reflectance characteristics of targets from calibrated multispectral airborne video data for routine operational airborne missions. The method uses a simplified atmospheric scattering model in combination with a dark-object subtraction procedure to estimate the effect of the atmosphere in the path between the target and the sensor, as well as the adjacent environmental effect, on the radiation signal received by an airborne sensor. The simplicity of the atmospheric scattering model is maintained by the assumption that the air density within the targetsensor path in the lower atmosphere is sufficiently uniform for operations of the Charles Sturt Universitys (CSU) Multispectral Airborne Video System (MAVS). The MAVS acquires imagery in blue, green, red and near-infrared (NIR) narrow spectral bands. The MAVS is radiometrically calibrated and has a consistent radiometric response in-flight. An important feature of the new method is the coupling of the image based brightness data (DN) of a dark-object and the system radiometric calibration coefficients to determine the path reflectance and the environmental reflectance of the target. The sum of the path reflectance and the environment reflectance is known as haze reflectance. The haze reflectance indicates the amount of atmospheric haze in the airborne imagery. The simplified atmospheric model is then employed to determine the actual ground reflectance of the targets using the haze subtracted apparent (total) reflectance of the target at the altitude of the airborne sensor. The apparent reflectance of the target at the sensor altitude is obtained directly from the image based DN data and the system radiometric calibration coefficients. An interesting aspect of this simplified method is that an estimate of the environmental reflectance can be obtained as a by-product of the atmospheric haze calculation using a dark-object subtraction technique. The retrieved ground reflectance characteristics from calibrated MAVS imagery are now being used routinely for remote quantitative monitoring of agricultural and environmental targets.

Radiometric Calibration of Multispectral Airborne Video Systems

This paper describes the operational characteristics and radiometric calibration of the Multispectral Airborne Video System (MAVS) at Charles Sturt University. The system consists of an array of four high-resolution Charge-Coupled Device (CCD) cameras, each with a narrow band filter. The four channels of image data are digitised in real time using a data acquisition system, which also provides for continuous interactive viewing while the system is in operation. The characteristics of system performance, the results of aperture calibration and the results of system radiometric calibration are presented. The video imaging system is found to have a highly linear response. The differences of the radiance based and reflectance based system calibration curves are investigated through a newly developed radiometric calibration model. As a result of this, a method for calculation of atmospheric optical thickens is presented. Calibrated imagery from this system is now being used routinely for remote monitoring of l...

Edge waves over an exponential continental shelf in a uniformly rotating ocean

The linearized long wave equations are solved fully for edge waves over an exponential shelf. Analytic forms are found for both classes, i.e. the inertiogravitational high frequency and the quasi-geostrophic low frequency waves, without neglecting the horizontal divergence. A dispersion relation for each class is determined and that for the quasi-geostrophic edge waves in the ocean is compared with the previously known relation which was obtained by neglecting the horizontal divergence. Agreement is found to 3 sig. figs. thereby justifying the neglect of horizontal divergence in the ocean for that class of edge wave. The continental shelf off Sydney has approximately an exponential profile and dispersion curves are presented for both classes of edge waves assuming the shelf is of finite width.

A new image enhancement algorithm on MasPar and Parallel Virtual Machine (PVM) environments

In this paper we discuss the numerical solution of a set of partial differential equations arising from an image enhancement technique based on variational minimisation procedures. The solution of these differential equations in a sequential computing environment requires a considerable amount of time. In view of the need to adjust parameters and calculate repeated enhancements in near real time when searching for an optimal image enhancement, the additional computing power available in a parallel environment is required. We first implement the algorithm in the coarse grain Parallel Virtual Machine (PVM) environment by mapping the solution of each differential equation to a different machine in a network of SUN Sparc2 work stations. Secondly, we solve this set of differential equations in a MasPar environment as a representative of a fine grain computation environment. A processing time comparison is provided in two different environments.