Anthea L. Mitchell

Use of stereo aerial photography for quantifying changes in the extent and height of mangroves in tropical Australia

The study investigated the use of aerial photographs, acquired in 1950 and1991, for assessing the temporal dynamics of mangroves along the WestAlligator River in Australias Northern Territory. For both years,mangrove extent was mapped using an unsupervised classification of thedigital orthomosaic and Digital Elevation Models (DEMs), or height maps,of the mangrove canopy were derived from stereo pairs. Helicopter andfield observations in 1998 and 1999 respectively provided ground truthfor interpreting the derived datasets. The comparison of mangrove extentrevealed a substantial movement over the 41-year period, perhaps inresponse to hydrological changes that have resulted in a landward extensionof saline conditions. Changes in the height of mangroves were observedbut were difficult to quantify due to the reduced quality of the 1950 DEM. The study demonstrated the viability of using time-series of aerialphotography for monitoring and understanding the long-term response ofmangroves to environmental change, including hydrological variations andsea level rise.

Joint Processing of Landsat and ALOS-PALSAR Data for Forest Mapping and Monitoring

Recent technological advances in the field of radar remote sensing have allowed the deployment of an increasing number of new satellite sensors. These provide an important source of Earth observation data, which add to the currently existing optical data sets. In parallel, the development of robust methods for global forest monitoring and mapping is becoming increasingly important. As a consequence, there is significant interest in the development of global monitoring systems that are able to take advantage of the potential synergies and complementary nature of optical and radar data. This paper proposes an approach for the combined processing of Landsat and ALOS-PALSAR data for the purpose of forest mapping and monitoring. This is achieved by incorporating the PALSAR data into an existing operational Landsat-based processing system. Using a directed discriminant technique, a probability map of forest presence/absence is first generated from the PALSAR imagery. This SAR classification data is then combined with a time series of similar Landsat-based maps within a Bayesian multitemporal processing framework, leading to the production of a time series of joint radar-optical maps of forest extents. This approach is applied and evaluated over a pilot study area in northeastern Tasmania, Australia. Experimental outcomes of the proposed joint processing framework are provided, demonstrating its potential for the integration of different types of remote sensing data for forest monitoring purposes.

Current remote sensing approaches to monitoring forest degradation in support of countries measurement, reporting and verification (MRV) systems for REDD+

Forest degradation is a global phenomenon and while being an important indicator and precursor to further forest loss, carbon emissions due to degradation should also be accounted for in national reporting within the frame of UN REDD+. At regional to country scales, methods have been progressively developed to detect and map forest degradation, with these based on multi-resolution optical, synthetic aperture radar (SAR) and/or LiDAR data. However, there is no one single method that can be applied to monitor forest degradation, largely due to the specific nature of the degradation type or process and the timeframe over which it is observed. The review assesses two main approaches to monitoring forest degradation: first, where detection is indicated by a change in canopy cover or proxies, and second, the quantification of loss (or gain) in above ground biomass (AGB). The discussion only considers degradation that has a visible impact on the forest canopy and is thus detectable by remote sensing. The first approach encompasses methods that characterise the type of degradation and track disturbance, detect gaps in, and fragmentation of, the forest canopy, and proxies that provide evidence of forestry activity. Progress in these topics has seen the extension of methods to higher resolution (both spatial and temporal) data to better capture the disturbance signal, distinguish degraded and intact forest, and monitor regrowth. Improvements in the reliability of mapping methods are anticipated by SAR-optical data fusion and use of very high resolution data. The second approach exploits EO sensors with known sensitivity to forest structure and biomass and discusses monitoring efforts using repeat LiDAR and SAR data. There has been progress in the capacity to discriminate forest age and growth stage using data fusion methods and LiDAR height metrics. Interferometric SAR and LiDAR have found new application in linking forest structure change to degradation in tropical forests. Estimates of AGB change have been demonstrated at national level using SAR and LiDAR-assisted approaches. Future improvements are anticipated with the availability of next generation LiDAR sensors. Improved access to relevant satellite data and best available methods are key to operational forest degradation monitoring. Countries will need to prioritise their monitoring efforts depending on the significance of the degradation, balanced against available resources. A better understanding of the drivers and impacts of degradation will help guide monitoring and restoration efforts. Ultimately we want to restore ecosystem service and function in degraded forests before the change is irreversible.

Historical perspectives on the mangroves of Kakadu National Park

Mangroves are a major ecosystem within Kakadu National Park in Australia’s Northern Territory, providing coastal protection, high biodiversity and an important resource for Aboriginal people. In the late Holocene (from c. 6000 before present), mangroves occupied much of the estuarine and coastal plains, but their range has subsequently contracted to the main river systems (the West Alligator, South Alligator and East Alligator Rivers, and the Wildman River), tributary creeks and offshore islands (Field and Barrow Islands). On the basis of maps of mangrove extent generated from aerial photography (1950, 1975, 1984 and 1991), compact airborne spectrographic imagery (CASI; 2002), light detection and ranging (LIDAR; 2011) and RapidEye data (2014 onward), changes in net area have been minor but significant redistribution has occurred, with this being attributed to both inland intrusion and seaward colonisation of mangroves. The greatest area changes have been associated with lower-stature mangroves dominated by Avicennia marina and Sonneratia alba, as determined from these datasets. Aerial surveys, conducted using a remote piloted aircraft (RPA) and fixed wing aircraft in September 2016, showed dieback of mangroves, with spaceborne RapidEye observations suggesting this occurred between late 2015 and 2016 and at the same time as the extensive mangrove losses reported in the Gulf of Carpentaria. Given the recent dieback and the associated need to better monitor and protect mangroves and proximal ecosystems in the World Heritage- and Ramsar-listed Kakadu National Park, the study recommends the development and implementation of a robust and long-term monitoring system that better utilises existing and ongoing earth observation and ground data, and is supported by a national approach.

Towards an operational SAR monitoring system for monitoring environmental flows in the Macquarie Marshes

Multi-frequency synthetic aperture radar (SAR) data was acquired over the Macquarie Marshes Nature Reserve in north central New South Wales (NSW), Australia, to demonstrate the potential of imaging radar for mapping and monitoring wetland extent and inundation patterns in an inland, semi-arid wetland environment. A sequence of ALOS PALSAR and TerraSAR-X images acquired between January 2007 and April 2008 captured the wetlands in three successive phases: dry, wet and transitional. Visual observation of multi-temporal and multi-frequency SAR backscatter data confirmed the capacity of SAR to respond to changes in surface water, soil moisture and biomass. Longer wavelength L-band SAR provides a tool for discriminating wetlands, mapping surface water and detecting below-canopy inundation. Shorter wavelength X-band SAR provides a tool for detecting flushes in growth of vegetation in response to higher soil moisture from flooding. PALSAR data demonstrated a high capacity for discrimination of different wetland classes, while TerraSAR-X data was less suited to discriminating between cover types. The integration of X- and L-band data revealed the extent of floodplain inundation and presence of aquatic vegetation in ponded areas. Given a stable, well-calibrated time-series of SAR data, change analysis provides a mechanism for understanding the hydrological and/or ecological change in an area. In the longer term, it is envisioned that radar will provide a valuable tool within an operational system for monitoring the impact of environmental flows in NSW inland wetlands.

Wall-to-wall mapping of forest extent and change in Tasmania using ALOS PALSAR data

Consistent estimation of carbon stocks at national level requires the integration of wall-to-wall, time-series satellite and in situ data of forest area, type and change. In this paper we demonstrate a consistent approach to the generation of wall-to-wall time-series mosaics using ALOS PALSAR data acquired over 2007 to 2009 for Tasmania, Australia. The project is part of a series of National Demonstrators initiated by the Group on Earth Observations (GEO) Forest Carbon Tracking (FCT) task that emphasize the contribution and operational use of satellite measurements for forest monitoring and national carbon accounting. Interoperability between optical and Synthetic Aperture Radar (SAR) derived forest measurements will also be demonstrated. The project will deliver a series of forest monitoring products and technical documentation, which will be made available as a guide to GEO member countries with a desire to develop their own national carbon accounting systems.

Dual polarised Entropy/alpha decomposition and coherence optimisation for improved forest height mapping

In this paper we propose an approach implementing the dual polarised Entropy/alpha decomposition [1] and coherence optimisation [8] for improved forest mapping. We explore the dual polarised Entropy/alpha decomposition for better forest/non-forest discrimination and the multiple partial polarimetric coherence optimisation for subsequent forest canopy/height estimation. The integrated forest discrimination and coherence-forest height estimation for the task of producing forest extent, change and trend information are examined with in situ LiDAR data.

Hyperspectral discrimination of halophytic vegetation as an indicator of stressed arable land

The spectral properties of eleven Australian halophytic grass species were analysed for key spectral characteristics to assist in hyperspectral image interpretation and mapping. Six halophyte species were successfully mapped using hyperspectral imagery over an area suffering from dry‐land salinity in central west NSW. The resultant class map of halophytes was statistically compared to interpolated electrical conductivity data via a confusion matrix. Variations in the spatial abundance of different halophyte species are shown to significantly reflect the level of landscape stress in terms of salt scalding and electrical conductivity. This illustrates the ability of such technology to map environmental stress as indicated by halophyte populations.

Integrated Land Cover and Change Classifications

For nature conservation, regular provision of consistent, timely and useable classifications of land covers and change is highly beneficial but is rarely achieved. This chapter outlines the concepts behind the Earth Observation Data for Ecosystem Monitoring (EODESM) system, which facilitates the description and classification of any site worldwide according to the Food and Agriculture Organisations (FAO) Land Cover Classification System (LCCS; Version 2) and with reference to environmental variables retrieved from earth observation. Changes in land cover, as well as causes and consequences, are described through the accumulation of evidence and the system recognises these to be numerous, highly variable and specific to different elements of the landscapes. Hence, they can be captured by considering information provided by a range of sensors operating in different modes and over different temporal frequencies and scales. The EODESM system is available at no cost and its ease of use makes it well suited to supporting nature conservation.

Forest mapping and monitoring in Tasmania using multi-temporal Landsat and ALOS-PALSAR data

Developing a large-scale forest monitoring system able to take advantage of the complementary nature of optical and radar remote sensing data presents a number of technical and conceptual challenges. This paper investigates the issue of sensor interoperability in a time series of Landsat and ALOS-PALSAR data for purposes related to forest mapping and monitoring. The proposed approach relies on the processing methods developed in the frame of an existing and operational Landsat-based forest monitoring system. These methods are here applied to a PALSAR dataset within a bioregion of north-eastern Tasmania, Australia. Particular attention is given to the selection of training data in an attempt to generate results comparable to those obtained with the original Landsat-only time series, thereby allowing for a relevant assessment of interoperability. Results are presented in the form of forest maps and areal forest estimates. Despite similar gross amounts of forest extents, these results highlight differences in the forest (and change) classifications produced using different sensors. Combinations of sensors should therefore be carefully considered in light of what is required of the monitoring system.