Determination of carrying capacity for Sheep‐breeding in Southern Greenland by means of Satellite mapping

Arctic and sub‐arctic areas can be regarded as very less favored in consideration to agricultural production. In the southern Greenland sheep‐breeding is crucial for the self‐reliance economy. The article deals with a mapping project that was carried out in order to assess the carrying capacity. The natural conditions are briefly described as background for the mapping which by means of NDVI and Principal Component Analysis of Landsat MSS data has proven very powerful. The aspects of growing season, climate and landscape variation are discussed.

The investigation was carried out at Institute for Geography, Socio‐Economic Analysis and Computer Science, Roskilde University Centre, Denmark.     

Development of the second-order derivatives of the Earth’s potential in the local north-oriented reference frame in orthogonal series of modified spherical harmonics

The second-order derivatives of the Earth’s potential in the local north-oriented reference frame are expanded in series of modified spherical harmonics. Linear relations are derived between the spectral coefficients of these series and the spectrum of the geopotential. On the basis of these relations, recurrence procedures are developed for evaluating the geopotential coefficients from the spectrum of each derivative and, inversely, for simulating the latter from a known geopotential model. Very simple structure of the derived expressions for the derivatives is convenient for estimating the geopotential coefficients by the least-squares procedure, at a certain step of processing satellite gradiometry data. Due to the orthogonality of the new series, the quadrature formula approach can be also applied, which allows avoidance of aliasing errors caused by the series truncation. The spectral coefficients of the derivatives are evaluated on the basis of the derived relations from the geopotential models EGM96 and EIGEN-CG01C at a mean orbital sphere of the GOCE satellite. Various characteristics of the spectra are studied corresponding to the EGM96 model. Electronic supplementary material  The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

The welfare benefit of a home’s location: an empirical comparison of spatial and non-spatial model estimates

This article compares results from non-spatial and new spatial methods to examine the reliability of welfare estimates (direct and multiplier effects) for locational housing attributes in Seattle, WA. In particular, we assess if OLS with spatial fixed effects is able to account for the spatial structure in a way that represents a viable alternative to spatial econometric methods. We find that while OLS with spatial fixed effects accounts for more of the spatial structure than simple OLS, it does not account for all of the spatial structure. It thus does not present a viable alternative to the spatial methods. Similar to existing comparisons between results from non-spatial and established spatial methods, we also find that OLS generates higher coefficient and direct effect estimates for both structural and locational housing characteristics than spatial methods do. OLS with spatial fixed effects is closer to the spatial estimates than OLS without fixed effects but remains higher. Finally, a comparison of the direct effects with locally weighted regression results highlights spatial threshold effects that are missed in the global models. Differences between spatial estimators are almost negligible in this study.     

Spatial Preference Modelling for equitable infrastructure provision: an application of Sen’s Capability Approach

To determine whether the inclusion of spatial neighbourhood comparison factors in Preference Modelling allows spatial decision support systems (SDSSs) to better address spatial equity, we introduce Spatial Preference Modelling (SPM). To evaluate the effectiveness of this model in addressing equity, various standardisation functions in both Non-Spatial Preference Modelling and SPM are compared. The evaluation involves applying the model to a resource location-allocation problem for transport infrastructure in the Special Province of Yogyakarta in Indonesia. We apply Amartya Sen’s Capability Approach to define opportunity to mobility as a non-income indicator. Using the extended Moran’s I interpretation for spatial equity, we evaluate the distribution output regarding, first, ‘the spatial distribution patterns of priority targeting for allocation’ (SPT) and, second, ‘the effect of new distribution patterns after location-allocation’ (ELA). The Moran’s I index of the initial map and its comparison with six patterns for SPT as well as ELA consistently indicates that the SPM is more effective for addressing spatial equity. We conclude that the inclusion of spatial neighbourhood comparison factors in Preference Modelling improves the capability of SDSS to address spatial equity. This study thus proposes a new formal method for SDSS with specific attention on resource location-allocation to address spatial equity.     

Observation of the Earth’s nutation by the VLBI: how accurate is the geophysical signal

We compare nutation time series determined by several International VLBI Service for geodesy and astrometry (IVS) analysis centers. These series were made available through the International Earth Rotation and Reference Systems Service (IERS). We adjust the amplitudes of the main nutations, including the free motion associated with the free core nutation (FCN). Then, we discuss the results in terms of physics of the Earth’s interior. We find consistent FCN signals in all of the time series, and we provide corrections to IAU 2000A series for a number of nutation terms with realistic errors. It appears that the analysis configuration or the software packages used by each analysis center introduce an error comparable to the amplitude of the prominent corrections. We show that the inconsistencies between series have significant consequences on our understanding of the Earth’s deep interior, especially for the free inner core resonance: they induce an uncertainty on the FCN period of about 0.5 day, and on the free inner core nutation (FICN) period of more than 1000 days, comparable to the estimated period itself. Though the FCN parameters are not so much affected, a 100 % error shows up for the FICN parameters and prevents from geophysical conclusions.     

Cultural and economic residential sorting of Auckland’s population, 1991–2013: an entropy approach

Journal of Geographical Systems - Auckland, the largest city of New Zealand, is one of the most diverse cities in the world, with more than 40% of its population born abroad, more than 200...     

Modeling commuting patterns in a multi-regional input–output framework: impacts of an ‘urban re-centralization’ scenario

The paper suggests a modeling approach for assessing economic and social impacts of changes in urban forms and commuting patterns that extends a multi-regional input–output framework by incorporating a set of commuting-related consequences. The Lisbon Metropolitan Area case with an urban re-centralization scenario is used as an example to illustrate the relevance of this modeling approach for analyzing commuting-related changes in regional income distribution on the one side and in household consumption structures on the other.     

Monitoring and analysing the Emirate of Dubai’s land use/land cover changes: an integrated,low-cost remote sensing approach

This study presents a modified low-cost approach, which integrates the spectral angle mapper and image difference algorithms in order to enhance classification maps for the purpose of monitoring and analysing land use/land cover change between 2000 and 2015 for the Emirate of Dubai. The approach was modified by collecting 320 training samples from QuickBird images with a spatial resolution of 0.6 m, as well as carrying out field observations, followed by the application of a 3?×?3 Soble filter, sieving classes, majority/minority analysis, and clump classes of the obtained classification maps. The accuracy assessment showed that the targeted 2000, 2005, 2010 and 2015 classification maps have 88.1252%, 89.0699%, 90.1225% and 96.0965% accuracy, respectively. The results showed that the built-up area increased by 233.721?km² (5.81%) between 2000 and 2005 and continues to increase even up and till the present time. The assessment of changes in the periods 2000–2005 and 2010–2015 confirmed that net vegetation area losses were more pronounced from 2000 to 2005 than from 2010 to 2015, dropping from 47,618 to 40,820?km², respectively. This study is aimed to assist urban planners and decision-makers, as well as research institutes.     

Corn Area Extraction by the Integration of MODIS-EVI Time Series Data and China’s Environment Satellite (HJ-1) Data

In this paper, we intent to use the remotely sensed MODerate resolution Imaging Spectroradiometer (MODIS) data and China’s Environment Satellite (HJ-1) data for extracting the corn cultivated area over a regional scale. The high resolution HJ-1 data was to extract corn distribution at a small scale class with Support Vector Machine (SVM). The mean Enhanced Vegetation Index (EVI) time series curve of corn from MODIS was derived for the reference area and validated in a larger area. The MODIS-EVI time series curve derived from the reference area instead of the MODIS-EVI time series curve derived from the study area after validation, which was taken as the standard MODIS-EVI time series curve in for generating a standard MODIS-EVI image of corn. The mean absolute distance (MAD) between the standard MODIS-EVI image of corn and the MODIS-EVI time series image was used to detect the maximum possible extent of corn distribution in the study area. The results showed that the overall accuracy of the method was 82.17 %, with commission and omission errors of 16.85 and 15.40 %, respectively; at the county level, the satellite-estimated corn area and statistical data were well correlated (R ²?=?0.85, N?=?50) for the whole Jilin Province. It indicated that the MODIS data integrated with higher spatial resolution of HJ-1 satellite data could be utilized to enhance the extraction accuracy of corn cultivated area at a larger scale.     

Feasibility of Estimating Heavy Metal Contaminations in Floodplain Soils Using Laboratory-Based Hyperspectral Data—A Case Study Along Le’an River, China

It is necessary to estimate heavy metal concentrations within soils for understanding heavy metal contaminations and for keeping the sustainable developments of ecosystems.This study,with the floodplain along Le’an River and its two branches in Jiangxi Province of China as a case study,aimed to explore the feasibility of estimating concentrations of heavy metal lead(Pb),copper(Cu) and zinc(Zn) within soils using laboratory-based hyperspectral data.Thirty soil samples were collected,and their hyperspectral data,soil organic matters and Pb,Cu and Zn concentrations were measured in the laboratory.The potential relations among hyperspectral data,soil organic matter and Pb,Cu and Zn concentrations were explored and further used to estimate Pb,Cu and Zn concentrations from hyperspectral data with soil organic matter as a bridge.The results showed that the ratio of the first-order derivatives of spectral absorbance at wavelengths 624 and 564 nm could explain 52% of the variation of soil organic matter;the soil organic matter could ex-plain 59%,51% and 50% of the variation of Pb,Cu and Zn concentrations with estimated standard errors of 1.41,48.27 and 45.15 mg·kg-1;and the absolute estimation errors were 8%-56%,12%-118% and 2%-22%,and 50%,67% and 100% of them were less than 25% for Pb,Cu and Zn concentration estimations.We concluded that the laboratory-based hyperspectral data hold potentials in esti-mating concentrations of heavy metal Pb,Cu and Zn in soils.More sampling points or other potential linear and non-linear regression methods should be used for improving the stabilities and accuracies of the estimation models.     

Feasibility of estimating heavy metal contaminations in floodplain soils using laboratory-based hyperspectral data—A case study along Le’an River,China

It is necessary to estimate heavy metal concentrations within soils for understanding heavy metal contaminations and for keeping the sustainable developments of ecosystems. This study, with the floodplain along Le’an River and its two branches in Jiangxi Province of China as a case study, aimed to explore the feasibility of estimating concentrations of heavy metal lead (Pb), copper (Cu) and zinc (Zn) within soils using laboratory-based hyperspectral data. Thirty soil samples were collected, and their hyperspectral data, soil organic matters and Pb, Cu and Zn concentrations were measured in the laboratory. The potential relations among hyperspectral data, soil organic matter and Pb, Cu and Zn concentrations were explored and further used to estimate Pb, Cu and Zn concentrations from hyperspectral data with soil organic matter as a bridge. The results showed that the ratio of the first-order derivatives of spectral absorbance at wavelengths 624 and 564 nm could explain 52% of the variation of soil organic matter; the soil organic matter could explain 59%, 51% and 50% of the variation of Pb, Cu and Zn concentrations with estimated standard errors of 1.41, 48.27 and 45.15 mg·kg?; and the absolute estimation errors were 8%–56%, 12%–118% and 2%–22%, and 50%, 67% and 100% of them were less than 25% for Pb, Cu and Zn concentration estimations. We concluded that the laboratory-based hyperspectral data hold potentials in estimating concentrations of heavy metal Pb, Cu and Zn in soils. More sampling points or other potential linear and non-linear regression methods should be used for improving the stabilities and accuracies of the estimation models.     

The static gravity field model DGM-1S from GRACE and GOCE data: computation, validation and an analysis of GOCE mission’s added value

We present a global static model of the Earth’s gravity field entitled DGM-1S based on GRACE and GOCE data. The collection of used data sets includes nearly 7 years of GRACE KBR data and 10 months of GOCE gravity gradient data. The KBR data are transformed with a 3-point differentiation into quantities that are approximately inter-satellite accelerations. Gravity gradients are processed in the instrumental frame. Noise is handled with a frequency-dependent data weighting. DGM-1S is complete to spherical harmonic degree 250 with a Kaula regularization being applied above degree 179. Its performance is compared with a number of other satellite-only GRACE/GOCE models by confronting them with (i) an independent model of the oceanic mean dynamic topography, and (ii) independent KBR and gravity gradient data. The tests reveal a competitive quality for DGM-1S. Importantly, we study added value of GOCE data by comparing the performance of satellite-only GRACE/GOCE models with models produced without GOCE data: either ITG-Grace2010s or EGM2008 depending on which of the two performs better in a given region. The test executed based on independent gravity gradients quantifies this added value as 25–38 % in the continental areas poorly covered with terrestrial gravimetry data (Equatorial Africa, Himalayas, and South America), 7–17 % in those with a good coverage with these data (Australia, North America, and North Eurasia), and 14 % in the oceans. This added value is shown to be almost entirely related to coefficients below degree 200. It is shown that this gain must be entirely attributed to gravity gradients acquired by the mission. The test executed based on an independent model of the mean dynamic topography suggests that problems still seem to exist in satellite-only GRACE/GOCE models over the Pacific ocean, where noticeable deviations between these models and EGM2008 are detected, too.     

Flying-fox species and Hendra virus spillover risk: comment on ‘Factors explaining the dispersal of Hendra virus disease in South-East Queensland’ by Burnham and Chong (2016)

The approach taken by Burnham and Chong to explain the occurrence of Hendra virus incidents in Australia, while analytically valid, is compromised by erroneous and incomplete biological data underpinning the analyses. Firstly, they erroneously state the peak mating, pregnancy and birthing periods in black, grey-headed and little red flying-foxes, thus their related interpretations and conclusions are flawed. Secondly, the reported association between grey-headed flying-fox density and HeV incidents is at odds with recent findings suggesting grey-headed flying-foxes are an insubstantial host. While this broader epidemiological perspective was not within their stated aims, it is appropriate that it be canvassed in discussion of their geo-spatial analyses given the level of horse-industry, public and media interest in Hendra virus and the potential for confusion and mixed messages regarding HeV exposure risk management. We suggest that a broader collaborative cross-disciplinary approach offers synergies that produce robust, real-world ‘one health’ outputs.     

Horizontal and vertical accuracy of Google Earth®: comment on ‘Positional accuracy of the Google Earth terrain model derived from stratigraphic unconformities in the Big Bend region,Texas, USA’ by S.C. Benker,R.P. Langford and T.L. Pavlis

Comment on ‘Positional accuracy of the Google Earth terrain model derived from stratigraphic unconformities in the Big Bend region, Texas, USA’ by S.C. Benker, R.P. Langford and T.L. Pavlis (Geocarto Int. 26:291–303, doi: 10.1080/10106049.2011.568125).