Three-dimensional mapping of salt stores in the Murray-Darling Basin,Australia: 2. Calculating landscape salt loads from airborne electromagnetic and laboratory data

Salt is widespread in the Australian landscape – in soil, regolith and groundwater – leading to concerns that land management practices may be putting much agricultural land and important water resources at risk of salinisation. Defining the location and nature of salt stores is an important first step in understanding the processes leading to salinity of soils, streams and groundwater resources, and predicting areas that may be at risk. Airborne geophysics can define subsurface salt stores and mobilisation pathways. Airborne electromagnetics (AEM) can map the three-dimensional conductivity structure of the landscape but does not, intrinsically, quantify the amount of salt. Salinity, moisture content, porosity and mineralogy all contribute to the electromagnetic signal, and each can vary significantly throughout the landscape.In the Lower Balonne catchment, Queensland, the relationship between AEM and the amount of salt in the landscape was quantified using laboratory analyses of pore fluids from core samples. A general statistical relationship was established between AEM conductivity and salt load (defined as the product of pore fluid salinity, porosity and moisture content)—with a significant positive correlation although data were generally widely dispersed. Comparison of calculated salt load with borehole electromagnetic logs gives insight into the factors contributing to dispersion in the AEM data.The relationship transforms bulk conductivity to salt load in 5 m layers, allowing the generation of a three-dimensional map of the salt load. This is a powerful tool for identifying areas that may require monitoring and management interventions to reduce salinity risk. An example is given of salt loads beneath an established irrigation area in the Lower Balonne catchment, Queensland.     

Geoinformatic Modeling of Groundwater Resource Mapping of Shear Zone Regions- A Case Study on Attur Valley,Tamil Nadu,India

The general tendency of mapping groundwater resource using remote sensing and Geographic Information System (GIS) techniques involve assigning higher weightage to geomorphology. But this cannot be used as a thumb rule everywhere, especially an area where many ductile and brittle zones are prevalent. The influence of texture and structure of sheared rocks might play a control over retaining and permitting groundwater to flow. Attur valley is characterized by the presence of many shear zones and faults and hence the rocks are highly fissile within the shear zones. The present study tries to establish a new ranking and weightage scheme and hence a new spatial model for groundwater resource mapping in shear zone area like Attur Valley. This spatial model can be verified with field data such as water level data, pump test and resistivity data.     

Predicting salinity impacts of land-use change: Groundwater modelling with airborne electromagnetics and field data,SE Queensland,Australia

Throughout Australia, there is concern that land use change is mobilizing salt stored in the landscape, causing salinity in soil and water resources. Salt in the landscape becomes a salinity risk only if it is mobilized by groundwater movement. A combination of modelled groundwater behaviour under various land uses with three-dimensional salt-load maps developed from airborne electromagnetic survey (AEM) provides a practical tool to assess potential salt movement.AEM survey of the country around St. George, SE Queensland, revealed a potential salinity threat: significant salt stores in the uplands adjacent to flood plains which support important irrigation developments and which drain to the Darling River system. A conceptual model of the regional hydrogeology was built upon three-dimensional AEM data, an investigation-drilling program, and direct field measurement of hydraulic conductivities. This information was incorporated in a Flowtube groundwater model and groundwater responses to five different land management options were tested over a 100-year period. Surface water storage on relatively permeable soils and continuous irrigated cotton both resulted in water tables reaching the soil surface; rain-fed wheat and pasture both resulted in a raised watertable, but both established a new equilibrium without the water table reaching the ground surface.     

Environmental geophysics mapping salinity and water resources

Salinity and fresh water are two sides of the same coin, most conveniently measured by electrical conductivity; they can now be mapped rapidly in three dimensions using airborne electromagnetics (AEM). Recent developments in the calibration of airborne data against in-field measurements and additional information from radiometrics, magnetics and digital elevation models lend new insights into salinity, groundwater flow systems and water resources. Freshwater resources can be mapped, and salinity risk and the outcome of management interventions may be forecast, on the basis of the specific architecture of complete groundwater flow systems-enabling practical, cost-effective protection and development of water resources.     

Airborne electromagnetics supporting salinity and natural resource management decisions at the field scale in Australia

Airborne geophysics has been used at the catchment scale to map salt stores, conduits and soil variability, but few studies have evaluated its usefulness as a land management tool at the field scale. We respond to questions posed by land managers with: (1) comparison of airborne and ground-based electromagnetic surveys in the Lower Balonne catchment, Queensland, and (2) comparison with historical and anecdotal knowledge of landscape response in the country around Jamestown in mid-South Australia.In the Lower Balonne, direct comparison between ground electromagnetic survey (EM) and airborne electromagnetics (AEM) showed a strong relationship for both the absolute values and spatial patterns of conductivity. The penetration of AEM to greater than 100 m is valuable in defining hydrological barriers. In the Jamestown area, AEM conductivity corresponded well with specific outbreaks of salinity and observed variability in crop response; local inconsistencies at the ground surface could be resolved when sub-surface data were considered. AEM can provide valuable information at the field scale that is relevant to salinity management. Farmers can have confidence in any of these techniques (historical information, EM and AEM) and they may directly compare or integrate the results.     

Automatic Building Extraction from Image and LiDAR Data with Active Contour Segmentation

Automatic building extraction is an important topic for many applications such as urban planning, disaster management, 3D building modeling and updating GIS databases. Its approaches mainly depend on two data sources: light detection and ranging (LiDAR) point cloud and aerial imagery both of which have advantages and disadvantages of their own. In this study, in order to benefit from the advantages of each data sources, LiDAR and image data combined together. And then, the building boundaries were extracted with the automated active contour algorithm implemented in MATLAB. Active contour algorithm uses initial contour positions to segment an object in the image. Initial contour positions were detected without user interaction by a series of image enhancements, band ratio and morphological operations. Four test areas with varying building and background levels of detail were selected from ISPRS’s benchmark Vaihingen and Istanbul datasets. Vegetation and shadows were removed from all the datasets by band ratio to improve segmentation quality. Subsequently, LiDAR point cloud data was converted to raster format and added to the aerial imagery as an extra band. Resulting merged image and initial contour positions were given to the active contour algorithm to extract building boundaries. In order to compare the contribution of LiDAR to the proposed method, the boundaries of the buildings were extracted from the input image before and after adding LiDAR data to the image as a layer. Finally extracted building boundaries were smoothed by the Awrangjeb (Int J Remote Sen 37(3): 551–579.  https://doi.org/10.1080/01431161.2015.1131868, 2016) boundary regularization algorithm. Correctness (Corr), completeness (Comp) and accuracy (Q) metrics were used to assess accuracy of segmented building boundaries by comparing extracted building boundaries with manually digitized building boundaries. Proposed approach shows the promising results with over 93% correctness, 92% completeness and 89% quality.     

Application of Remotely-Sensed Data to Estimate a Water Budget for Data-Scarce Endorheic Basins: A Case Study of Lake Urmia basin,Iran

Estimating the water budgets of large basins is a challenge because of the lack of data and information. It becomes more complicated in endorheic basins that consist of separate land and water phases. The application of remotely-sensed data is one solution in this regard. The present study addresses this issue and develops a modeling framework to evaluate a water budget based on remotely-sensed data for endorheic basins. To explore the methodology, Lake Urmia basin was selected as a case study. The lake water level has declined steeply since 1995 and stakeholders have agreed to allocate 3100 MCM of water per year to the lake. This makes it necessary to monitor river inflow into the lake to fulfill the agreement. Gauging stations have been employed around the lake, but they could not account for shortages such as water uptake below the stations. To do this, separate water budgets for the water body and the land were required. More specifically, it was necessary to estimate actual evapotranspiration (ET _a ) from freshwater (E _f ) and saltwater (E _s ) estimated using the SEBAL model. Different methods were applied to estimate soil moisture, groundwater exploitation, and surface-groundwater inflow into the lake. A comparison of the observed and estimated amounts showed good agreement. For instance, the coefficient of determination for the observed/reported and estimated ET _a and E _f were 0.83 and 0.84, respectively. The average annual inflow was estimated to be 2.2 BCM/year for 2002–2008 using the RS model, which is about 84 % of the total inflow from the last recording stations before the lake and shows influence of water exploitation after these stations. Future study should focus on increasing temporal and spatial resolution of the method     

A model comparison in least squares collocation

The well known least squares collocation model (I) $$\ell = Ax + \left[ {\begin{array}{*{20}c} O \\ I \\ \end{array} } \right]^T \left[ {\begin{array}{*{20}c} s \\ {s' + n} \\ \end{array} } \right]$$ is compared with the model (II) $$\ell = Ax + \left[ {\begin{array}{*{20}c} R \\ I \\ \end{array} } \right]^T \left[ {\begin{array}{*{20}c} s \\ n \\ \end{array} } \right]$$ The basic differences of these two models in the framework of physical geodesy are pointed out by analyzing the validity of the equation $$s' = Rs$$ that transforms one model into the other, for different cases. For clarification purposes least squares filtering, prediction and collocation are discussed separately. In filtering problems the coefficient matrix R becomes the unit matrix and by this the two models become identical. For prediction and collocation problems the relation s′=Rs is only fulfilled in the global limit where s becomes either a continuous function on the earth or an intinite set of spherical harmonic coefficients. Applying Model (II), we see that for any finite dimension of s the operator equations of physical geodesy are approximated by a finite matrix relation whereas in Model (I) the operator equations are applied in their correct form on a continuous, approximate function \(\tilde s\) .     

Crop acreage estimation using ERS-1 SAR data

Synthetic Aperture Radar (SAR) data from the European Remote Sensing Satellite (ERS-1) acquired in July, October and November, 1992 covering the kharif season of the region were used separately and in combination to identify the major crops and for estimation of their acreage before harvest Separability indices were calculated for major cover types and it was found that single-date SAR data cannot be used for accurate identification of various crops. Multi-temporal colour composite facilitated better identification of crop types. Comparison of area estimates made with ERS-1 SAR and IRS-1B LISS II data showed that the commonly used digital data analysis techniques (per pixel classifiers) are not adequate for accurate estimation of crop acreage using SAR data.     

Assessing<Emphasis Type="Italic">jhum</Emphasis>-induced forest loss in Dibang valley,Arunachal Himalayas — A remote sensing perspective

There has been a significant advancement in the application of remote sensing from various space altitudes for inventorying and monitoring ofjhum (shifting) cultivation associated forest loss. The dynamic nature ofjhum system, complex physiography, small size of individualjhum plots and their discontinuous nature of distribution, highly heterogeneous vegetation and ever-changing atmospheric condition in the Arunachal Himalaya posses a great challenge to local flora and fauna. Indian Remote Sensing (IRS)-1C/1D LISS-III data were used to classify the current and abandonedjhum areas in Dibang valley district. The amount of area occupied by current and abandonedjhum corresponds to 199.34 km²(1.53%) and 225.40 km²(1.73%) respectively. Field data were collected following stratified random sampling method to gather information on plant community occurring in abandonedjhum cultivated areas. It was observed that only nine species out of 45 contribute to 50% of the important value index (IVI). Of the 45 species, 7 species (15.56%) have been found to be endemic to Eastern Himalayas. Population inducedjhum cultivation has led to deforestation, biodiversity loss, increased surface soil erosion, and sedimentation of water bodies in this area. The potential use of satellite-derived maps can best be used for better management and land use planning.     

Seasonal low-degree changes in terrestrial water mass load from global GNSS measurements

Large-scale mass redistribution in the terrestrial water storage (TWS) leads to changes in the low-degree spherical harmonic coefficients of the Earth’s surface mass density field. Studying these low-degree fluctuations is an important task that contributes to our understanding of continental hydrology. In this study, we use global GNSS measurements of vertical and horizontal crustal displacements that we correct for atmospheric and oceanic effects, and use a set of modified basis functions similar to Clarke et al. (Geophys J Int 171:1–10, 2007) to perform an inversion of the corrected measurements in order to recover changes in the coefficients of degree-0 (hydrological mass change), degree-1 (centre of mass shift) and degree-2 (flattening of the Earth) caused by variations in the TWS over the period January 2003–January 2015. We infer from the GNSS-derived degree-0 estimate an annual variation in total continental water mass with an amplitude of \((3.49 \pm 0.19) \times 10^{3}\) Gt and a phase of \(70^{\circ } \pm 3^{\circ }\) (implying a peak in early March), in excellent agreement with corresponding values derived from the Global Land Data Assimilation System (GLDAS) water storage model that amount to \((3.39 \pm 0.10) \times 10^{3}\) Gt and \(71^{\circ } \pm 2^{\circ }\), respectively. The degree-1 coefficients we recover from GNSS predict annual geocentre motion (i.e. the offset change between the centre of common mass and the centre of figure) caused by changes in TWS with amplitudes of \(0.69 \pm 0.07\) mm for GX, \(1.31 \pm 0.08\) mm for GY and \(2.60 \pm 0.13\) mm for GZ. These values agree with GLDAS and estimates obtained from the combination of GRACE and the output of an ocean model using the approach of Swenson et al. (J Geophys Res 113(B8), 2008) at the level of about 0.5, 0.3 and 0.9 mm for GX, GY and GZ, respectively. Corresponding degree-1 coefficients from SLR, however, generally show higher variability and predict larger amplitudes for GX and GZ. The results we obtain for the degree-2 coefficients from GNSS are slightly mixed, and the level of agreement with the other sources heavily depends on the individual coefficient being investigated. The best agreement is observed for \(T_{20}^C\) and \(T_{22}^S\), which contain the most prominent annual signals among the degree-2 coefficients, with amplitudes amounting to \((5.47 \pm 0.44) \times 10^{-3}\) and \((4.52 \pm 0.31) \times 10^{-3}\) m of equivalent water height (EWH), respectively, as inferred from GNSS. Corresponding agreement with values from SLR and GRACE is at the level of or better than \(0.4 \times 10^{-3}\) and \(0.9 \times 10^{-3}\) m of EWH for \(T_{20}^C\) and \(T_{22}^S\), respectively, while for both coefficients, GLDAS predicts smaller amplitudes. Somewhat lower agreement is obtained for the order-1 coefficients, \(T_{21}^C\) and \(T_{21}^S\), while our GNSS inversion seems unable to reliably recover \(T_{22}^C\). For all the coefficients we consider, the GNSS-derived estimates from the modified inversion approach are more consistent with the solutions from the other sources than corresponding estimates obtained from an unconstrained standard inversion.     

Ranchi mega lineament and its correlation with geological and geophysical data

Remotely-sensed satellite data of Landsat 5 (TM) and IRS-1A (LISS II) covering parts of central portion of Chotanagapur plateau have been analysed visually to delineate some prominent lineaments in Ranchi district and its adjoining area. One of the most prominent lineament “Ranchi mega lineament? has been analysed in this paper. This lineament is a potential site for base metal mineralisation at some places, and it acts as good groundwater conduit in the region. No earlier attempt to map this entire structural unit as a separate entity is known. Geophysical bouguer gravity anomaly map, lithological and structural maps have some remarkable correlation with this lineament. In the present paper authors have tried to analyse the lineament with respect to its tectonic, mineralisation and groundwater prospects. Resistivity survey carried in close proximity of this lineament at selected sites, indicate that rocks are well fractured at depth. Available lithological and structural map support this lineament as a shear near Purulia (W.B.) and also having base-metal mineralisation potential in this area. Authors opine that existing gravity anomaly map may be further augmented in the light of present study.     

Evaluation of Cartographic accuracy of IRS-1A LISS II data for upgrading linear details on the existing maps (A case study of Chandigarh area)

Considering the fest pace of development, up-to-date maps have become imperative in developmental planning. Conventional map updating techniques are expensive and time consuming. The present paper makes an attempt to tackle the problem using GIS techniques. Maps generated from IRS-1A LISS II data and Survey of India (SOI) toposheets were used as input maps in GIS. These maps were overlaid to obtain the positional errors at road junction points. The area statistics of each sector were calculated taking the SOI map as reference data. The results show that the areas calculated from LISS II data and SOI map are well comparable and the deviations are within 10%, whereas the positional accuracy (MSE) of points is within 30 m. The study demonstrates that the IRS-1A LISS II data can be used for updating of maps on scale 1:100,000 and smaller in areas where linear features are identifiable in the IRS LISS II image.     

A high-precision digital astrogeodetic traverse in an area of steep geoid gradients close to the coast of Perth,Western Australia

We present results from a new vertical deflection (VD) traverse observed in Perth, Western Australia, which is the first of its kind in the Southern Hemisphere. A digital astrogeodetic QDaedalus instrument was deployed to measure VDs with \({\sim }\)0.2\(''\) precision at 39 benchmarks with a \({{\sim }}1~\hbox {km}\) spacing. For the conversion of VDs to quasigeoid height differences, the method of astronomical–topographical levelling was applied, based on topographical information from the Shuttle Radar Topography Mission. The astronomical quasigeoid heights are in 20–30 mm (RMS) agreement with three independent gravimetric quasigeoid models, and the astrogeodetic VDs agree to 0.2–0.3\(''\) (north–south) and 0.6–0.9\(''\) (east–west) RMS. Tilt-like biases of \({\sim }1\,\,\hbox {mm}\) over \({\sim }1\,\,\hbox {km}\) are present for all quasigeoid models within \({\sim }20\,\,\hbox {km}\) of the coastline, suggesting inconsistencies in the coastal zone gravity data. The VD campaign in Perth was designed as a low-cost effort, possibly allowing replication in other Southern Hemisphere countries (e.g., Asia, Africa, South America and Antarctica), where VD data are particularly scarce.     

On the equivalence of spherical splines with least-squares collocation and Stokes’s formula for regional geoid computation

This work is an investigation of three methods for regional geoid computation: Stokes’s formula, least-squares collocation (LSC), and spherical radial base functions (RBFs) using the spline kernel (SK). It is a first attempt to compare the three methods theoretically and numerically in a unified framework. While Stokes integration and LSC may be regarded as classic methods for regional geoid computation, RBFs may still be regarded as a modern approach. All methods are theoretically equal when applied globally, and we therefore expect them to give comparable results in regional applications. However, it has been shown by de Min (Bull Géod 69:223–232, 1995. doi: 10.1007/BF00806734) that the equivalence of Stokes’s formula and LSC does not hold in regional applications without modifying the cross-covariance function. In order to make all methods comparable in regional applications, the corresponding modification has been introduced also in the SK. Ultimately, we present numerical examples comparing Stokes’s formula, LSC, and SKs in a closed-loop environment using synthetic noise-free data, to verify their equivalence. All agree on the millimeter level.     

Selection criteria for linear regression models to estimate individual tree biomasses in the Atlantic Rain Forest,Brazil

Background

Biomass models are useful for several purposes, especially for quantifying carbon stocks and dynamics in forests. Selecting appropriate equations from a fitted model is a process which can involves several criteria, some widely used and others used to a lesser extent. This study analyzes six selection criteria for models fitted to six sets of individual biomass collected from woody indigenous species of the Tropical Atlantic Rain Forest in Brazil. Six models were examined and the respective fitted equations evaluated by the residual sum of squares, adjusted coefficient of determination, absolute and relative estimates of the standard error of estimate, and Akaike and Schwartz (Bayesian) information criteria. The aim of this study was to analyze the numeric behavior of these model selection criteria and discuss the ease of interpretation of them. The importance of residual analysis in model selection is stressed.

Results

The adjusted coefficient of determination (\( R^{2}_{adj.} \)) and the standard error of estimate in percentage (Syx%) are relative model selection criteria and are not affected by sample size and scale of the response variable. The sum of squared residuals (SSR), the absolute standard error of estimate (Syx), the Akaike information criterion and the Schwartz information criterion, in turn, depend on these quantities. The best fit model was always the same within a given data set regardless the model selection criteria considered (except for SSR in two cases), indicating they tend to converge to a common result. However, such criteria are not always closely related across different data sets. General model selection criteria are indicative of the average goodness of fit, but do not capture bias and outlier effects. Graphical residual analysis is a useful tool to this detection and must always be used in model selection.

Conclusions

It is concluded that the criteria for model selection tend to lead to a common result, regardless their mathematical formulation and statistical significance. Relative measures of goodness of fitting are easier to interpret than the absolute ones. Careful graphical residual analysis must always be used to confirm the performance of the models.

     

The first Australian gravimetric quasigeoid model with location-specific uncertainty estimates

We describe the computation of the first Australian quasigeoid model to include error estimates as a function of location that have been propagated from uncertainties in the EGM2008 global model, land and altimeter-derived gravity anomalies and terrain corrections. The model has been extended to include Australia’s offshore territories and maritime boundaries using newer datasets comprising an additional \({\sim }\)280,000 land gravity observations, a newer altimeter-derived marine gravity anomaly grid, and terrain corrections at \(1^{\prime \prime }\times 1^{\prime \prime }\) resolution. The error propagation uses a remove–restore approach, where the EGM2008 quasigeoid and gravity anomaly error grids are augmented by errors propagated through a modified Stokes integral from the errors in the altimeter gravity anomalies, land gravity observations and terrain corrections. The gravimetric quasigeoid errors (one sigma) are 50–60 mm across most of the Australian landmass, increasing to \({\sim }100\) mm in regions of steep horizontal gravity gradients or the mountains, and are commensurate with external estimates.     

Harmonic maps

Harmonic maps are generated as a certain class of optimal map projections. For instance, if the distortion energy over a meridian strip of the International Reference Ellipsoid is minimized, we are led to the Laplace–Beltrami vector-valued partial differential equation. Harmonic functions x(L,B), y(L,B) given as functions of ellipsoidal surface parameters of Gauss ellipsoidal longitude L and Gauss ellipsoidal latitude B, as well as x(,q), y(,q) given as functions of relative isometric longitude =L–L₀ and relative isometric latitude q=Q–Q₀ gauged to a vector-valued boundary condition of special symmetry are constructed. The easting and northing {x(b,),y(b,)} of the new harmonic map is then given. Distortion energy analysis of the new harmonic map is presented, as well as case studies for (1) B[–40°,+40°], L[–31°,+49°], B₀= ±30°, L₀=9° and (2) B[46°,56°], L{[4.5°, 7.5°]; [7.5°, 10.5°]; [10.5°,13.5°]; [13.5°,16.5°]}, B₀= 51°, L₀ {6°,9°,12°,15°}.     

Impact Assessment of GIS Based Land Resource Inventory Towards Optimizing Agricultural Land Use Plan in Dandakaranya and Easternghats Physiographic Confluence of India

GIS based land resource inventory (LRI) with fine resolution imagery is considered as most authentic tool for soil resource mapping. Soil resource mapping using the concept of soil series in a smaller scale limits its wide application and also its impact assessment for crop suitability is controversial. In this study, we attempted to develop LRI at large scale (1:10,000 scale) at block level land use planning (LUP) in Dandakaranya and Easternghats physiographic confluence of India. The concept of land management unit was introduced in this endeavour. The impact assessment of LRI based LUP was exercised to develop efficient crop planning with best possible management practices. The study area comprised six landforms with slope gradient ranging from very gentle (1–3%) to steep slopes (15–25%). The very gently sloping young alluvial plains occupied maximum areas (19.95% of TGA). The single cropped (paddy) land appears to dominate the land use systems (40.0% of TGA). Thirty three landscape ecological units were resulted by GIS-overlay. Eighteen soils mapping units were generated. The area was broadly under two soil orders (Inceptisols and Alfisols); three great group (Haplaquepts, Rhodustalfs and Endoaquepts) and ten soil series. Crop suitability based impact assessment of LRI based LUP revealed that average yield of different crops increased by 39.2 and 14.5% in Kharif (rainy season) and Rabi (winter) seasons respectively and annual net returns by 83.4% for the cropping system, compared to traditional practices. Productivity and net returns can be increased several folds if customized recommended practices are adopted by the farmers. Informations generated from the study emphasized the potentiality of LRI towards optimizing LUP and exhibited an ample scope to use the methodology as a tool to assess in other physiographic regions in India and abroad.