Simon D. Jones

The Performance of Random Forests in an Operational Setting for Large Area Sclerophyll Forest Classification

Mapping and monitoring forest extent is a common requirement of regional forest inventories and public land natural resource management, including in Australia. The state of Victoria, Australia, has approximately 7.2 million hectares of mostly forested public land, comprising ecosystems that present a diverse range of forest structures, composition and condition. In this paper, we evaluate the performance of the Random Forest (RF) classifier, an ensemble learning algorithm that has recently shown promise using multi-spectral satellite sensor imagery for large area feature classification. The RF algorithm was applied using selected Landsat Thematic Mapper (TM) imagery metrics and auxiliary terrain and climatic variables, while the reference data was manually extracted from systematically distributed plots of sample aerial photography and used for training (75%) and accuracy (25%) assessment. The RF algorithm yielded an overall accuracy of 96% and a Kappa statistic of 0.91 (confidence interval (CI) 0.909–0.919) for the forest/non-forest classification model, given a Kappa maximised binary threshold value of 0.5. The area under the receiver operating characteristic plot produced a score of 0.91, also indicating high model performance. The framework described in this study contributes to the operational deployment of a robust, but affordable, program, able to collate and process large volumes of multi-sourced data using open-source software for the production of consistent and accurate forest cover maps across the full spectrum of Victorian sclerophyll forest types.

Development of a Multi-Spatial Resolution Approach to the Surveillance of Active Fire Lines Using Himawari-8

Satellite remote sensing is regularly used for wildfire detection, fire severity mapping and burnt area mapping. Applications in the surveillance of wildfire using geostationary-based sensors have been limited by low spatial resolutions. With the launch in 2015 of the AHI (Advanced Himawari Imaginer) sensor on board Himawari-8, ten-minute interval imagery is available covering an entire earth hemisphere across East Asia and Australasia. Existing active fire detection algorithms depend on middle infrared (MIR) and thermal infrared (TIR) channels to detect fire. Even though sub-pixel fire detection algorithms can detect much smaller fires, the location of the fire within the AHI 2 × 2 km (400 ha) MIR/TIR pixel is unknown. This limits the application of AHI as a wildfire surveillance and tracking sensor. A new multi-spatial resolution approach is presented in this paper that utilizes the available medium resolution channels in AHI. The proposed algorithm is able to map firelines at a 500 m resolution. This is achieved using near infrared (NIR) (1 km) and RED (500 m) data to detect burnt area and smoke within the flagged MIR (2 km) pixel. Initial results based on three case studies carried out in Western Australia shows that the algorithm was able to continuously track fires during the day at 500 m resolution. The results also demonstrate the utility for wildfire management activities.

Critical Metadata for Spectroscopy Field Campaigns

A field spectroscopy metadata standard is defined as those data elements that explicitly document the spectroscopy dataset and field protocols, sampling strategies, instrument properties and environmental and logistical variables. Standards for field spectroscopy metadata affect the quality, completeness, reliability, and usability of datasets created in situ. Currently there is no standardized methodology for documentation of in situ spectroscopy data or metadata. This paper presents results of an international experiment comprising a web-based survey and expert panel evaluation that investigated critical metadata in field spectroscopy. The survey participants were a diverse group of scientists experienced in gathering spectroscopy data across a wide range of disciplines. Overall, respondents were in agreement about a core metadataset for generic campaign metadata, allowing for a prioritization of critical metadata elements to be proposed including those relating to viewing geometry, location, general target and sampling properties, illumination, instrument properties, reference standards, calibration, hyperspectral signal properties, atmospheric conditions, and general project details. Consensus was greatest among individual expert groups in specific application domains. The results allow the identification of a core set of metadata fields that enforce long term data storage and serve as a foundation for a metadata standard. This paper is part one in a series about the core elements of a robust and flexible field spectroscopy metadata standard.

Continuous wavelet transformations for hyperspectral feature detection

A novel method for the analysis of spectra and detection of absorption features in hyperspectral signatures is proposed, based on the ability of wavelet transformations to enhance absorption features. Field spectra of wheat grown on different levels of available nitrogen were collected, and compared to the foliar nitrogen content. The spectra were assessed both as absolute reflectances and recalculated into derivative spectra, and their respective wavelet transformed signals. Wavelet transformed signals, transformed using the Daubechies 5 motherwavelet at scaling level 32, performed consistently better than reflectance or derivative spectra when tested in a bootstrapped phased regression against nitrogen.

Using discrete-return airborne laser scanning to quantify number of canopy strata across diverse forest types

The vertical arrangement of forest canopies is a key descriptor of canopy structure, a driver of ecosystem function and indicative of forest successional stage. Yet techniques to attribute for canopy vertical structure across large and potentially heterogeneously forested areas remain elusive. This study introduces a new technique to estimate the Number of Strata (NoS) that comprise a canopy profile, using discrete-return Airborne Laser Scanning (ALS) data. Vertically resolved gap probability (P-gap) aggregated over a plot is generalized with a nonparametric cubic spline regression (P-s). Subsequently a count of the positive zero-crossings of second derivative of 1 - P-s is used to estimate NoS. Comparison with inventory derived estimates at 24 plots across three diverse study areas shows a good agreement between the two techniques (RMSE=041 strata). Furthermore, this is achieved without altering model parameters, indicating the transferability of the technique across diverse forest types. NoS values ranged from 0 to 4 at a further 239 plots, emphasizing the need for a method to quantify canopy vertical structure across forested landscapes. Comparison of NoS with other commonly derived ALS descriptors of canopy structure (canopy height, canopy cover and return height coefficient of determination) returned only a moderate correlation (r(2)<04). It is proposed the presented method provides a primary descriptor of canopy structure to complement canopy height and cover, as well as a candidate Ecological Biodiversity Variable for characterizing habitat structure.

Assessing metrics for estimating fire induced change in the forest understorey structure using terrestrial laser scanning

Quantifying post-fire effects in a forested landscape is important to ascertain burn severity, ecosystem recovery and post-fire hazard assessments and mitigation planning. Reporting of such post-fire effects assumes significance in fire-prone countries such as USA, Australia, Spain, Greece and Portugal where prescribed burns are routinely carried out. This paper describes the use of Terrestrial Laser Scanning (TLS) to estimate and map change in the forest understorey following a prescribed burn. Eighteen descriptive metrics are derived from bi-temporal TLS which are used to analyse and visualise change in a control and fire-altered plot. Metrics derived are Above Ground Height-based (AGH) percentiles and heights, point count and mean intensity. Metrics such as AGH50change, mean AGHchange and point countchange are sensitive enough to detect subtle fire-induced change (28%–52%) whilst observing little or no change in the control plot (0–4%). A qualitative examination with field measurements of the spatial distribution of burnt areas and percentage area burnt also show similar patterns. This study is novel in that it examines the behaviour of TLS metrics for estimating and mapping fire induced change in understorey structure in a single-scan mode with a minimal fixed reference system. Further, the TLS-derived metrics can be used to produce high resolution maps of change in the understorey landscape.

A Comparison of High and Low Gain DMSP/OLS Satellite Images for the Study of Socio-Economic Metrics

The Operational Linescan System (OLS) onboard the Defense Meteorological Satellite Program (DMSP) group of satellites, unlike other passive remote sensing sensors, is capable of recording the emissions from artificial lights on the earth surface. Along with detecting light from forest fires, shipping fleets and gas flares, the OLS sensor also records the light emitted from cities at night. This paper reports on a study that uses the DMSP Operational Linescan (DMSP-OLS) images with fixed gain settings of 20 dB and 50 dB to model selected metrics used in the Indian census for the state of Maharashtra. The study firstly looks into the utility of non-composited single fixed gain radiance calibrated DMSP-OLS products for proposing a method which might help to build a surrogate method for Indian census. Several parameters are considered in this analysis, with detailed focus on population density, total population and proportion of households with electricity access for 35 districts within the state of Maharashtra. Results show that spatial scale plays an important role in selection of the images and gains. Secondly, this study provides a relative assessment of gain setting for the DMSP-OLS images in an urban Indian context. Images with a gain of 50 dB prove suitable for larger areas while those with a gain of 20 dB give better results at a smaller spatial scale. Statistical analysis and residual maps of spatial distribution of total population and population density validate the result.

An assessment of pre- and post fire near surface fuel hazard in an Australian dry sclerophyll forest using point cloud data captured using a terrestrial laser scanner

Assessment of ecological and structrual changes induced by fire events is important for understanding the effects of fire, and planning future ecological and risk mitigation strategies. This study employs Terrestrial Laser Scanning (TLS) data captured at multiple points in time to monitor the changes in a dry sclerophyll forest induced by a prescribed burn. Point cloud data was collected for two plots; one plot undergoing a fire treatment, and the second plot remaining untreated, thereby acting as the control. Data was collected at three epochs (pre-fire, two weeks post fire and two years post fire). Coregistration of these multitemporal point clouds to within an acceptable tolerance was achieved through a two step process utilising permanent infield markers and manually extracted stem objects as reference targets. Metrics describing fuel height and fuel fragmentation were extracted from the point clouds for direct comparison with industry standard visual assessments. Measurements describing the change (or lack thereof) in the control plot indicate that the method of data capture and coregistration were achieved with the required accuracy to monitor fire induced change. Results from the fire affected plot show that immediately post fire 67% of area had been burnt with the average fuel height decreasing from 0.33 to 0.13 m. At two years post-fire the fuel remained signicantly lower (0.11 m) and more fragmented in comparison to pre-fire levels. Results in both the control and fire altered plot were comparable to synchronus onground visual assessment. The advantage of TLS over the visual assessment method is, however, demonstrated through the use of two physical and spatially quantifiable metrics to describe fuel change. These results highlight the capabilities of multitemporal TLS data for measuring and mapping changes in the three dimensional structure of vegetation. Metrics from point clouds can be derived to provide quantified estimates of surface and near-surface fuel loss and accumulation, and inform prescribed burn efficacy and burn severity reporting.

A current perspective on Australian woody vegetation maps and implications for small remnant patches

Digital map products are routinely used by land managers and policy makers for environmental decision-making. This paper assesses the ability of such products to detect woody vegetation, particularly remnant patches which serve as critical landscape structures. Comparisons are made between two map products (NCAS and a SPOT-based classification) and a high spatial resolution reference dataset, across contrasting landscapes. Spatial analysis and statistical association tests are used to determine the ability of these map products to produce accurate measurements of woody vegetation. It is demonstrated that landscape structure is fundamental in determining the fitness-for-use and function of the digital map products.

Using the Geoscience Australia-CSIRO ASTER maps and airborne geophysics to explore Australian geoscience

This study evaluated the geological mapping potential of the recently released Australian CSIRO-GA ASTER satellite geoscience products in providing mineral abundance and compositional information. A range of environments was examined by using test sites including the temperate cultivated New South Wales area of Wagga Wagga, and the semi-arid rangeland Mt Fitton of South Australia. Data integration of the ASTER derived products was undertaken with geophysical data, digital elevation models and fractional vegetation cover information. The study demonstrated that these products can successfully assist geological mapping within semi-arid areas and, to a lesser extent, within temperate open woodland environments.