Neil Sims

A Classification of Floodplains and Wetlands of the Murray-Darling Basin Based on Changes in Flows Following Water Resource Development

We present a regional classification of 40 floodplains and wetlands of the Murray-Darling Basin, Australia, based on changes in flows since river regulation and water resource development. The classification is based on a similarity percentage analysis of nine metrics relating to frequency, duration and volume of floods, and seasonality of flows. The major changes in flows were a delay in mean Julian day of occurrence of low flow and reduced variation in occurrence, lower frequency of flood events and reduced variation of flood duration. The spatial distribution of floodplain classes highlights the differential effects of river regulation across the Basin, with greatest change in rivers in the southern Basin, particularly the Murray, Murrumbidgee, and Lachlan, and the least change in unregulated or less-regulated rivers, predominantly in the north. There is generally good spatial concordance between distribution of floodplain classes and the Murray-Darling Basin Sustainable Rivers Audit index of riverine ecosystem health, and the distribution of major communities of waterbirds. Our results suggest, when compared with published reports of ecological condition, that very low-gradient, terminal floodplain wetlands characterized by low discharge volume and anastomosing distributary channels may be particularly susceptible to adverse ecological impacts arising from relatively slight alterations to flows.

Automated In-Situ Laser Scanner for Monitoring Forest Leaf Area Index

An automated laser rangefinding instrument was developed to characterize overstorey and understorey vegetation dynamics over time. Design criteria were based on information needs within the statewide forest monitoring program in Victoria, Australia. The ground-based monitoring instrument captures the key vegetation structural information needed to overcome ambiguity in the estimation of forest Leaf Area Index (LAI) from satellite sensors. The scanning lidar instrument was developed primarily from low cost, commercially accessible components. While the 635 nm wavelength lidar is not ideally suited to vegetation studies, there was an acceptable trade-off between cost and performance. Tests demonstrated reliable range estimates to live foliage up to a distance of 60 m during night-time operation. Given the instruments scan angle of 57.5 degrees zenith, the instrument is an effective tool for monitoring LAI in forest canopies up to a height of 30 m. An 18 month field trial of three co-located instruments showed consistent seasonal trends and mean LAI of between 1.32 to 1.56 and a temporal LAI variation of 8 to 17% relative to the mean.

Application of narrow-band digital camera imagery to plantation canopy condition assessment

Ensuring forest plantations remain in optimum health and condition is critical to minimizing adverse losses in productivity. A health monitoring program capable of accurately assessing the extent and severity of symptoms of canopy strain could permit forest managers to take a proactive course of action to minimize losses in productivity and tree mortality. Across a range of factors associated with tree stress and defoliation (a fungal pathogen Sphaeropsis sapinea, low soil nitrogen (N) availability, and an aphid Essigella californica), we compared field-based observations of canopy condition with coincident imagery obtained in September 2002 and 2003 from digital camera technology fitted with selected narrow-band (10 nm) spectral interference filters. From these wavelengths a number of chlorophyll and red-edge spectral indices were derived at 50 cm spatial resolution. In the case of S. sapinea where infection is significant and results in necrotic breakdown of needle tissue, the slope of the upper red-edge was the variable most highly correlated with crown attributes (r2 = 0.76 and 0.88 for the 2 years), with an independent classification accuracy of over 90%. Feeding by E. californica is commonly associated with needle chlorosis and defoliation and was predicted at a lower level of accuracy with a simple chlorophyll index (67% overall accuracy). The results indicate that narrow-band digital camera imagery can be used to derive indices of chlorophyll sensitivity and red-edge wavelengths. Comparison of predictions over a 2 year period indicate that the red-edge-based indicators can detect differences in canopy condition and that these relationships appear robust. The results indicate the chlorophyll-based indices were less robust through time, possibly due to interactions with needle defoliation.

Delineation of riparian vegetation from Landsat multi‐temporal imagery using PCA

A deficiency in crucial digital data, such as vegetation cover, in remote regions is a challenging issue for water management and planning, especially for areas undergoing rapid development, such as mining in the Pilbara, Western Australia. This is particularly relevant to riparian vegetation, which provides important ecological services and, as such, requires regional protection. The objective of this research was to develop an approach to riparian vegetation mapping at a regional scale using remotely sensed data. The proposed method was based on Principal Component Analysis (PCA) applied to multi-temporal Normalised Difference Vegetation Index (NDVI) datasets derived from Landsat TM 5 imagery. To delimit the spatial extent of riparian vegetation, a thresholding method was required and various thresholding algorithms were tested. The accuracy of results was estimated for various NDVI multi-temporal datasets using available ground-truth data. The combination of a 14-dry-date dataset and Kittlers thresholding method provided the most accurate delineation of riparian vegetation. This article is protected by copyright. All rights reserved.

Multiband SAR data for rangeland pasture monitoring

Rangelands in Australia cover approximately 80 percent of the continent and include a diverse group of relatively undisturbed ecosystems such as tropical savannas, woodlands, shrublands and grasslands. It is important to monitor and understand change in the rangelands so that effective actions can be taken to maintain ecological, economic and social values in Australia. Efficient use of feed resources in the livestock industries of Australia is a major factor in determining farm profitability and sustainability. With limited information, many producers forego potential production because of ineffective management of their feed resources. Further, poor management can also lead to environmental degradation. Therefore, CSIRO have invested to investigate, develop and validate new methodologies for integration of remote sensing data with in-situ field measurements, in order to map the dynamics in aboveground plant biomass in forests, crops, grassland and rangelands of Australia. Pasture biomass mapping is a main component of this project given rangelands the majority of Australia. Due to good sensitive to diverse rangelands in tropical and subtropical regions, multi-band SAR data for pasture mapping are investigated in this paper.

Spectral separability and mapping potential of cassava leaf damage symptoms caused by whiteflies (Bemisia tabaci)

Abstract BACKGROUND This study examines whether leaf spectra can be used to measure damage to cassava plants from whitefly (Bemisia tabaci), and the potential to translate measurements from leaf to landscape scale in eastern Africa. Symptoms of the cassava brown streak disease (CBSD) and cassava mosaic disease (CMD) viruses, and sooty mould (SM) blackening of lower leaves from whiteflies feeding on the upper leaves, were measured at the leaf scale with a high‐resolution spectroradiometer and a single photon avalanche diode (SPAD) meter, which retrieves relative chlorophyll concentration. Spectral measurements were compared to the five‐level visual scores used to assess the severity of each of the three damaging agents in the field, and also to leaf chemistry data. RESULTS Leaves exhibiting severe CBSD and CMD were spectrally indistinguishable from leaves without any symptoms. Severe SM was spectrally distinctive but is likely to be difficult to map because of its occurrence in the lower crown. SPAD measurements were highly correlated with most foliar chemistry measurements and field scores of disease severity. Regression models between simulated Sentinel 2 bands, field scores and SPAD measurements were strongest using wavelengths with high importance weightings in random forest models. CONCLUSION SPAD measurements are highly correlated to many foliar chemistry parameters, and should be considered for use in mapping disease severity over larger areas. Remaining challenges for mapping relate to the subtle expression of symptoms, the spatial distribution of disease severity within fields, and the small size and complex structure of the cassava fields themselves.

The use of historical environmental monitoring data to test predictions on cross-scale ecological responses to alterations in river flows

Abstract Determination of ecological responses to river flows is fundamental to understanding how flow-dependent ecosystems have been altered by regulation, water diversions and climate change, and how to effect river restoration. Knowledge of ecohydrological relationships can support water management and policy, but this is not always the case. Management rules have tended to be developed ahead of scientific knowledge. The lag between practice and knowledge could be addressed by using historical monitoring data on ecological responses to changes in flows to determine significant empirical ecohydrological relationships, as an adjunct to investigating responses prospectively. This possibility was explored in the Murray–Darling Basin, Australia. We assessed 359 data sets collected during monitoring programs across the basin. Of these, only 32 (9%) were considered useful, based on a match between the scale at which sampling was done and ecological responses are likely to occur, and used to test flow–ecology predictions for phytoplankton, macroinvertebrates, fishes, waterbirds, floodplain trees, basin-scale vegetation and estuarine biota. We found relationships between flow and ecological responses were likely to be more strongly supported for large, long-lived, widespread biota (waterbirds, basin-scale vegetation, native fishes), than for more narrowly distributed (e.g. estuarine fishes) or smaller, short-lived organisms (e.g. phytoplankton, macroinvertebrates). This pattern is attributed to a mismatch between the design of monitoring programs and the response time frames of individual biota and processes, and to the use of local river discharge as a primary predictor variable when, for many biotic groups, other predictors need to be considered.

An automated method for normalising large Landsat time series datasets to like values for change detection

The increased availability of Landsat imagery provides the opportunity to monitor changes in the land surface over long time frames. This paper presents an automated method for normalizing satellite images to a calibrated reference image using pseudo invariant features (PIFs). The method is repeatable, objective and fast, and has been used to prepare a large collection of Landsat images for flood inundation detection.