Land Cover Mapping using Digital Earth Australia

This study establishes the use of the Earth Observation Data for Ecosystem Monitoring (EODESM) to generate land cover and change classifications based on the United Nations Food and Agriculture Organisation (FAO) Land Cover Classification System (LCCS) and environmental variables (EVs) available within, or accessible from, Geoscience Australia’s (GA) Digital Earth Australia (DEA). Classifications representing the LCCS Level 3 taxonomy (8 categories representing semi-(natural) and/or cultivated/managed vegetation or natural or artificial bare or water bodies) were generated for two time periods and across four test sites located in the Australian states of QueenslandandNewSouthWales. Thiswasachievedbyprogressivelyandhierarchicallycombining existing time-static layers relating to (a) the extent of artificial surfaces (urban, water) and agriculture and (b) annual summaries of EVs relating to the extent of vegetation (fractional cover) and water (hydroperiod, intertidal area, mangroves) generated through DEA. More detailed classifications that integrated information on, for example, forest structure (based on vegetation cover (%) and height (m); time-static for 2009) and hydroperiod (months), were subsequently produced for each time-step. The overall accuracies of the land cover classifications were dependent upon those reported for the individual input layers, with these ranging from 80% (for cultivated, urban and artificial water) to over95%(forhydroperiodandfractionalcover).Thechangesidentifiedincludemangrovediebackin the southeastern Gulf of Carpentaria and reduced dam water levels and an associated expansion of vegetation in Lake Ross, Burdekin. The extent of detected changes corresponded with those observed using time-series of RapidEye data (2014 to 2016; for the Gulf of Carpentaria) and Google Earth imagery (2009–2016 for Lake Ross). This use case demonstrates the capacity and a conceptual framework to implement EODESM within DEA and provides countries using the Open Data Cube (ODC) environment with the opportunity to routinely generate land cover maps from Landsat or Sentinel-1/2 data, at least annually, using a consistent and internationally recognised taxonomy

Operational continental-scale land cover mapping of Australia using the Open Data Cube

To comprehensively support national and international initiatives for sustainable development, land cover products need to be reliably and routinely generated within operational frameworks. Coupled with consistent semantics and taxonomies, ensuring confidence in mapping land cover for multiple time periods, facilitates informed decision-making at scales appropriate to multiple policy domains. The United Nations Food and Agriculture Organisation (FAO) Land Cover Classification System (LCCS) provides a taxonomy that comparable at different scales, level of detail and geographic location. The Open Data Cube (ODC) initiative offers a framework for operational continental scale land cover mapping using analysis-ready Earth Observation data. This study utilised the FAO LCCS framework and the Landsat sensor data through Digital Earth Australia (DEA; Australia’s ODC instance) to generate consistent and continent-wide land cover mapping (DEA Land Cover) of the Australian continent. DEA Land Cover provides annual maps from 1988 to 2020 at 25 m resolution. Output maps were validated with ∼12,000 independent validation points, giving an overall map accuracy of 80%. DEA Land Cover provides Australia with a nationally consistent picture of land cover, with an open-source software package using readily available global coverage data and demonstrates a pathway of adoption for national implementations across the worl

Evaluation of ASTER GDEM ver2 using GPS measurements and SRTM ver4.1 in China

The freely available ASTER GDEM ver2 was released by NASA and METI on October 17, 2011. As one of the most complete high resolution digital topographic data sets of the world to date, the ASTER GDEM covers land surfaces between 83°N and 83°S at a spatial resolution of 1 arc-second and will be a useful product for many applications, such as relief analysis, hydrological studies and radar interferometry. The stated improvements in the second version of ASTER GDEM benefit from finer horizontal resolution, offset adjustment and water body detection in addition to new observed ASTER scenes. This study investigates the absolute vertical accuracy of the ASTER GDEM ver2 at five study sites in China using ground control points (GCPs) from high accuracy GPS benchmarks, and also using a DEM-to-DEM comparison with the Consultative Group for International Agriculture Research Consortium for Spatial Information (CGIAR-CSI) SRTM DEM (Version 4.1). And then, the results are separated into GlobCover land cover classes to derive the spatial pattern of error. It is demonstrated that the RMSE (19m) and mean (-13m) values of ASTER GDEM ver2 against GPS-GCPs in the five study areas is lower than its first version ASTER GDEM ver1 (26m and -21m) as a result of the adjustment of the elevation offsets in the new version. It should be noted that the five study areas in this study are representative in terms of terrain types and land covers in China, and even for most of mid-latitude zones. It is believed that the ASTER GDEM offers a major alternative in accessibility to high quality elevation data

Tracing sources of cadmium in agricultural soils: a stable isotope approach

Cadmium (Cd) is a biotoxic heavy metal, which is accumulated by plants and animals and thereby enters the human food chain (Gray et al. 2003). The application of phosphate fertilisers has also resulted in the long-term accumulation of Cd in agricultural soils around the world, including New Zealand (NZ). In 1997, the main source of NZ phosphate fertilisers was changed from Nauru island phosphate rocks (450 mg Cd kg-1 P) to a variety of phosphate rocks with lower Cd concentrations, in order to meet more stringent Cd limits in P fertiliser. Following this change, the accumulation of Cd in topsoil samples from the Winchmore research farm (South Island, NZ) was evaluated and was found to have plateaued post-2000 (McDowell, 2012). In this study, stable isotope analysis was used to trace the fate of Cd in Winchmore farm soils in order to determine the cause of the plateau. The isotope ratio of Cd (δ114/110Cd) was measured in pre-2000 and post-2000 phosphate fertilisers, phosphate rocks, topsoil (0-7.5 cm) and control (unfertilised) subsoil (25-30 cm) samples from the Winchmore site. The analysed topsoil samples were archived samples collected over the period 1959-2015. The isotopic compositions of fertilised topsoils ranged from δ114/110Cd = 0.08 ± 0.03 to δ114/110Cd = 0.27 ± 0.04, which were comparable to pre-2000 fertilisers (δ114/110Cd = 0.10 ± 0.05 to 0.25 ± 0.04) but distinct from the post-2000 fertilisers (δ114/110Cd range of -0.17 ± 0.03 to 0.01 ± 0.05) and control subsoil (δ114/110Cd = -0.33 ± 0.04) (Salmanzadeh et al., 2017). We combined this stable isotope data with Bayesian modelling to estimate the contribution of different sources of Cd. An open source Bayesian isotope mixing model implemented in Matlab (Arendt et al., 2015) was used here with some modifications to estimate the fractional contribution of different sources of Cd through time including pre- and post-2000 fertilisers, and the control soil. The Matlab code of Arendt et al., 2015 was modified to consider only one isotope system (rather than two), and fewer sources. This modelling confirmed the dominant contribution (about 80%) of Nauru-derived (i.e. pre-2000) fertilisers in increasing the Cd concentration in Winchmore soils. To help constrain the soil Cd mass balance we used an existing model (CadBal) (Roberts and Longhurst, 2005), to estimate residual soil Cd and output fluxes based on known P fertiliser application rates, the initial Cd concentration, farm and soil type, and soil dry bulk density. We incorporated the isotope data into the mass balance expression in order to evaluate the performance of CadBal in estimating the past topsoil Cd accumulation and predicting the future concentrations and isotope ratios of Cd (up to 2030 AD). The results of mass balance modelling confirm that recent applications of phosphate fertilisers have not resulted in an accumulation of Cd during the most recent period, thus Cd removal by either leaching or crop uptake has increased, which is consistent with the modelled isotope data (Figure 1). We can conclude that it becomes possible to distinguish the sources of Cd within the soil using stable Cd isotopes (Imseng et al., 2018) and that the residual Cd in topsoil at Winchmore still mainly originates from historical phosphate fertilisers (Salmanzadeh et al., 2017). One implication of this finding is that the contemporary applications of phosphate fertiliser are not resulting in further Cd accumulation. We aim to continue our research into Cd fate, mobility, and transformations in the NZ environment by applying Cd isotopes in soils and aquatic environments across the country. Figure 1. Results of Cd mass balance modelling in CadBal for the period of topsoil fertilisation including a prediction up to the year 2030 AD. (a) Mean concentration of Cd in the dryland treatment of Winchmore long-term irrigation trial (symbols) and the CadBal model (lines) outputs (red symbols = this study- plot 15 of Winchmore site; grey symbols = McDowell study-average of all plots; solid black line = dryland optimized CadBal from McDowell (2012) for all irrigation plots; black dashed line = Plot 15 dryland optimized CadBal-this study, first scenario; blue line = Plot 15 dryland optimized CadBal-this study, second scenario; red line = Plot 15 dryland optimized CadBal-this study, third scenario; red dashed line = Plot 15 dryland optimized CadBal-this study, fourth scenario); (b) Measured and modelled Cd isotope ratios based on CadBal outputs, isotope ratios measured in fertilisers and the fractionation factors of Wiggenhauser, et al. (2016); lines designate modelling scenarios as in (a), red dots are the third scenario with no fractionation (α factor not applied); (c) modeled scenario 3 (solid) and scenario 4 (dashed) isotope ratios in topsoil (red lines), leachate (blue lines) and pasture (green lines)

Literature review of the remote sensing of natural resources

Abstracts of 596 documents related to remote sensors or the remote sensing of natural resources by satellite, aircraft, or ground-based stations are presented. Topics covered include general theory, geology and hydrology, agriculture and forestry, marine sciences, urban land use, and instrumentation. Recent documents not yet cited in any of the seven information sources used for the compilation are summarized. An author/key word index is provided

Projected technological requirements for remote sensing of terrain variables

Contributions of remote sensing to hydrogeomorphology and terrain analysis are reviewed in order to identify characteristics that should receive support in system and sensor configuration planning. Fluvial morphological studies, peak discharge modeling, and hydrogeomorphic floodplain mapping using large scale (1:12,000) to small scale (1:750,000) orbital photography are discussed as well as quantitative assessment of terrain variables for specific applications

Mesoscale mapping of sediment source hotspots for dam sediment management in data-sparse semi-arid catchments

Land degradation and water availability in semi-arid regions are interdependent challenges for management that are influenced by climatic and anthropogenic changes. Erosion and high sediment loads in rivers cause reservoir siltation and decrease storage capacity, which pose risk on water security for citizens, agriculture, and industry. In regions where resources for management are limited, identifying spatial-temporal variability of sediment sources is crucial to decrease siltation. Despite widespread availability of rigorous methods, approaches simplifying spatial and temporal variability of erosion are often inappropriately applied to very data sparse semi-arid regions. In this work, we review existing approaches for mapping erosional hotspots, and provide an example of spatial-temporal mapping approach in two case study regions. The barriers limiting data availability and their effects on erosion mapping methods, their validation, and resulting prioritization of leverage management areas are discussed.BMBF, 02WGR1421A-I, GROW - Verbundprojekt SaWaM: Saisonales Wasserressourcen-Management in Trockenregionen: Praxistransfer regionalisierter globaler Informationen, Teilprojekt 1DFG, 414044773, Open Access Publizieren 2019 - 2020 / Technische Universität Berli