Spatial–temporal variations of water vapor content over Ethiopia: a study using GPS observations and the ECMWF model

GPS Solutions - We characterize the spatial–temporal variability of integrated water vapor (IWV) in Ethiopia from a network of global positioning system (GPS) stations and the European Center...     

A sun–crown–sensor model and adapted C-correction logic for topographic correction of high resolution forest imagery

Canopy shadowing mediated by topography is an important source of radiometric distortion on remote sensing images of rugged terrain. Topographic correction based on the sun–canopy–sensor (SCS) model significantly improved over those based on the sun–terrain–sensor (STS) model for surfaces with high forest canopy cover, because the SCS model considers and preserves the geotropic nature of trees. The SCS model accounts for sub-pixel canopy shadowing effects and normalizes the sunlit canopy area within a pixel. However, it does not account for mutual shadowing between neighboring pixels. Pixel-to-pixel shadowing is especially apparent for fine resolution satellite images in which individual tree crowns are resolved. This paper proposes a new topographic correction model: the sun–crown–sensor (SCnS) model based on high-resolution satellite imagery (IKONOS) and high-precision LiDAR digital elevation model. An improvement on the C-correction logic with a radiance partitioning method to address the effects of diffuse irradiance is also introduced (SCnS + C). In addition, we incorporate a weighting variable, based on pixel shadow fraction, on the direct and diffuse radiance portions to enhance the retrieval of at-sensor radiance and reflectance of highly shadowed tree pixels and form another variety of SCnS model (SCnS + W). Model evaluation with IKONOS test data showed that the new SCnS model outperformed the STS and SCS models in quantifying the correlation between terrain-regulated illumination factor and at-sensor radiance. Our adapted C-correction logic based on the sun–crown–sensor geometry and radiance partitioning better represented the general additive effects of diffuse radiation than C parameters derived from the STS or SCS models. The weighting factor W_t also significantly enhanced correction results by reducing within-class standard deviation and balancing the mean pixel radiance between sunlit and shaded slopes. We analyzed these improvements with model comparison on the red and near infrared bands. The advantages of SCnS + C and SCnS + W on both bands are expected to facilitate forest classification and change detection applications.     

Minimum mean squared error (MSE) adjustment and the optimal Tykhonov–Phillips regularization parameter via reproducing best invariant quadratic uniformly unbiased estimates (repro-BIQUUE)

In a linear Gauss–Markov model, the parameter estimates from BLUUE (Best Linear Uniformly Unbiased Estimate) are not robust against possible outliers in the observations. Moreover, by giving up the unbiasedness constraint, the mean squared error (MSE) risk may be further reduced, in particular when the problem is ill-posed. In this paper, the α-weighted S-homBLE (Best homogeneously Linear Estimate) is derived via formulas originally used for variance component estimation on the basis of the repro-BIQUUE (reproducing Best Invariant Quadratic Uniformly Unbiased Estimate) principle in a model with stochastic prior information. In the present model, however, such prior information is not included, which allows the comparison of the stochastic approach (α-weighted S-homBLE) with the well-established algebraic approach of Tykhonov–Phillips regularization, also known as R-HAPS (Hybrid APproximation Solution), whenever the inverse of the “substitute matrix” S exists and is chosen as the R matrix that defines the relative impact of the regularizing term on the final result. The delay in publishing this paper is due to a number of unfortunate complications. It was first submitted as a multi-author paper in two parts. Due to some miscommunication among the original authors, it was reassigned to one of the J Geod special issues, but later reassigned at this author’s request to a standard issue of J Geod. This compounded with a difficulty to find willing reviewers to slow the process. We apologize to the author.     

The GeoForschungsZentrum Potsdam/Groupe de Recherche de Gèodésie Spatiale satellite-only and combined gravity field models: EIGEN-GL04S1 and EIGEN-GL04C

The recent improvements in the Gravity Recovery And Climate Experiment (GRACE) tracking data processing at GeoForschungsZentrum Potsdam (GFZ) and Groupe de Recherche de Géodésie Spatiale (GRGS) Toulouse, the availability of newer surface gravity data sets in the Arctic, Antarctica and North-America, and the availability of a new mean sea surface height model from altimetry processing at GFZ gave rise to the generation of two new global gravity field models. The first, EIGEN-GL04S1, a satellite-only model complete to degree and order 150 in terms of spherical harmonics, was derived by combination of the latest GFZ Potsdam GRACE-only (EIGEN-GRACE04S) and GRGS Toulouse GRACE/LAGEOS (EIGEN-GL04S) mean field solutions. The second, EIGEN-GL04S1 was combined with surface gravity data from altimetry over the oceans and gravimetry over the continents to derive a new high-resolution global gravity field model called EIGEN-GL04C. This model is complete to degree and order 360 and thus resolves geoid and gravity anomalies at half- wavelengths of 55 km at the equator. A degree-dependent combination method has been applied in order to preserve the high accuracy from the GRACE satellite data in the lower frequency band of the geopotential and to form a smooth transition to the high-frequency information coming from the surface data. Compared to pre-CHAMP global high-resolution models, the accuracy was improved at a spatial resolution of 200 km (half-wavelength) by one order of magnitude to 3 cm in terms of geoid heights. The accuracy of this model (i.e. the commission error) at its full spatial resolution is estimated to be 15 cm. The model shows a reduced artificial meridional striping and an increased correlation of EIGEN-GL04C-derived geostrophic meridional currents with World Ocean Atlas 2001 (WOA01) data. These improvements have led to select EIGEN-GL04C for JASON-1 satellite altimeter data reprocessing. Electronic Supplementary Material The online version of this article (doi:) contains supplementary material, which is available to authorized users.     

Estimating rate uncertainty with maximum likelihood: differences between power-law and flicker–random-walk models

Recent studies have documented that global positioning system (GPS) time series of position estimates have temporal correlations which have been modeled as a combination of power-law and white noise processes. When estimating quantities such as a constant rate from GPS time series data, the estimated uncertainties on these quantities are more realistic when using a noise model that includes temporal correlations than simply assuming temporally uncorrelated noise. However, the choice of the specific representation of correlated noise can affect the estimate of uncertainty. For many GPS time series, the background noise can be represented by either: (1) a sum of flicker and random-walk noise or, (2) as a power-law noise model that represents an average of the flicker and random-walk noise. For instance, if the underlying noise model is a combination of flicker and random-walk noise, then incorrectly choosing the power-law model could underestimate the rate uncertainty by a factor of two. Distinguishing between the two alternate noise models is difficult since the flicker component can dominate the assessment of the noise properties because it is spread over a significant portion of the measurable frequency band. But, although not necessarily detectable, the random-walk component can be a major constituent of the estimated rate uncertainty. None the less, it is possible to determine the upper bound on the random-walk noise.     

Contemporary deformation in the Kashmir–Himachal,Garhwal and Kumaon Himalaya: significant insights from 1995–2008 GPS time series

We present new insights on the time-averaged surface velocities, convergence and extension rates along arc-normal transects in Kumaon, Garhwal and Kashmir–Himachal regions in the Indian Himalaya from 13 years of high-precision Global Positioning System (GPS) time series (1995–2008) derived from GPS data at 14 GPS permanent and 42 campaign stations between $29.5{-}35^{\circ }\hbox {N}$ and $76{-}81^{\circ }\hbox {E}$ . The GPS surface horizontal velocities vary significantly from the Higher to Lesser Himalaya and are of the order of 30 to 48 mm/year NE in ITRF 2005 reference frame, and 17 to 2 mm/year SW in an India fixed reference frame indicating that this region is accommodating less than 2 cm/year of the India–Eurasia plate motion ( ${\sim }4~\hbox {cm/year}$ ). The total arc-normal shortening varies between ${\sim }10{-}14~\hbox {mm/year}$ along the different transects of the northwest Himalayan wedge, between the Indo-Tsangpo suture to the north and the Indo-Gangetic foreland to the south indicating high strain accumulation in the Himalayan wedge. This convergence is being accommodated differentially along the arc-normal transects; ${\sim } 5{-}10~\hbox {mm/year}$ in Lesser Himalaya and 3–4 mm/year in Higher Himalaya south of South Tibetan Detachment. Most of the convergence in the Lesser Himalaya of Garhwal and Kumaon is being accommodated just south of the Main Central Thrust fault trace, indicating high strain accumulation in this region which is also consistent with the high seismic activity in this region. In addition, for the first time an arc-normal extension of ${\sim }6~\hbox {mm/year}$ has also been observed in the Tethyan Himalaya of Kumaon. Inverse modeling of GPS-derived surface deformation rates in Garhwal and Kumaon Himalaya using a single dislocation indicate that the Main Himalayan Thrust is locked from the surface to a depth of ${\sim }15{-}20~\hbox {km}$ over a width of 110 km with associated slip rate of ${\sim }16{-}18~\hbox {mm/year}$ . These results indicate that the arc-normal rates in the Northwest Himalaya have a complex deformation pattern involving both convergence and extension, and rigorous seismo-tectonic models in the Himalaya are necessary to account for this pattern. In addition, the results also gave an estimate of co-seismic and post-seismic motion associated with the 1999 Chamoli earthquake, which is modeled to derive the slip and geometry of the rupture plane.     

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.     

Surveying general prospects and challenges of GIS implementation in developing countries: a SWOT–AHP approach

We propose a combined method based on the strengths, weaknesses, opportunities and threats (SWOT) and analytic hierarchy process (AHP) to investigate the challenges and prospects of adopting geographic information systems (GIS) in developing countries. In this context, we identify, group, and analyse SWOT indicators in relation to the main GIS components: data, people, and technology. The relative significance of each SWOT indicator and its related SWOT groups in each GIS component is quantified. The method is then applied in a situation assessment of GIS adoption in the governmental organisations and strategic planning. The SWOT–AHP approach proves to be very useful in identifying and quantifying the relative significance of the major factors affecting GIS implementation, and effectively facilitates GIS strategic planning.      

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...     

Coloured Roads on Ordnance Survey First Edition 1 : 2500 Plans and One-Inch Maps 1897–1935, and the Rights Of Way Disclaimer

Abstract

In 1892 a government committee of inquiry into the Ordnance Survey suggested that the Survey should make a distinction between public and private second class roads at the one-inch scale. This study is confined to England and Wales and looks at the nineteenth-century practice of colouring roads on the large-scale plans, and compares the representation of coloured rural roads on early Ordnance Survey one-inch maps with near contemporary highway records of the county of Huntingdonshire, sixteen rural district councils in six counties and an estate in Suffolk. The results show that all but four of the coloured roads on the one-inch maps in these areas are recorded as publicly maintainable highways.     

Spatial and temporal variations of spatial population accessibility to public hospitals: a case study of rural–urban comparison

Quantification and assessment of nationwide population access to health-care services is a critical undertaking for improving population health and optimizing the performance of national health systems. Rural–urban unbalance of population access to health-care services is widely involved in most of the nations. This unbalance is also potentially affected by varied weather and road conditions. This study investigates the rural and urban performances of public health system by quantifying the spatiotemporal variations of accessibility and assessing the impacts of potential factors. Australian health-care system is used as a case study for the rural–urban comparison of population accessibility. A nationwide travel time-based modified kernel density two-step floating catchment area (MKD2SFCA) model is utilized to compute accessibility of travel time within 30, 60, 120, and 240 min to all public hospitals, hospitals that provide emergency care, and hospitals that provide surgery service, respectively. Results show that accessibility is varied both temporally and spatially, and the rural–urban unbalance is distinct for different types of hospitals. In Australia, from the perspective of spatial distributions of health-care resources, spatial accessibility to all public hospitals in remote and very remote areas is not lower (and may even higher) than that in major cities, but the accessibility to hospitals that provide emergency and surgery services is much higher in major cities than other areas. From the angle of temporal variation of accessibility to public hospitals, reduction of traffic speed is 1.00–3.57% due to precipitation and heavy rain, but it leads to 18–23% and 31–50% of reduction of accessibility in hot-spot and cold-spot regions, respectively, and the impact is severe in New South Wales, Queensland, and Northern Territory during wet seasons. Spatiotemporal analysis for the variations of accessibility can provide quantitative and accurate evidence for geographically local and dynamic strategies of allocation decision-making of medical resources and optimizing health-care systems both locally and nationally.     

Tree Crown Detection,Delineation and Counting in UAV Remote Sensed Images: A Neural Network Based Spectral–Spatial Method

UAVs are fast emerging as a remote sensing platform to complement satellite based remote sensing. Agriculture and ecology is one of the important applications of UAV remote sensing, also known as low altitude remote sensing (LARS). This work demonstrates the use and potential of LARS in agriculture, particularly small holder open field agriculture. Two UAVs are used for remote sensing. The first UAV is a fixed wing aircraft with a high spatial resolution visible spectrum also known as RGB camera as a payload. The second UAV is a quadrotor UAV with an RGB camera interfaced to an on-board single board computer as the payload. LARS was carried out to acquire aerial high spatial resolution RGB images of different farms. Spectral–spatial classification of high spatial resolution RGB images for detection, delineation and counting of tree crowns in the image is presented. Supervised classification is carried out using extreme learning machine (ELM), a single hidden layer feed forward network neural network classifier. ELM was modelled for RGB values as input feature vectors and binary (tree and non-tree pixels) output class. Due to similarities in spectral intensities, some of the non-tree pixels were classified as tree pixels and in order to remove them, spatial classification was performed on the image. Spatial classification was carried out using thresholded geometrical property filtering techniques. Threshold values chosen for carrying out spatial classification were analysed to obtain optimal values. Finally in the delineation and counting, the connected tree crowns were segmented using Watershed algorithm performed on the image after marking individual tree crowns using Distance Transform method. Five representative UAV images captured at different altitudes with different crowns of banana plant, mango trees and coconut trees were used to demonstrate the performance of the proposed method. The performance was compared with the traditional KMeans spectral–spatial method of clustering. Results and comparison of performance parameters of KMeans spectral–spatial and ELM spectral–spatial classification methods are presented. Results indicate that ELM performed better than KMeans.     

Land use and land cover changes over a century (1914–2007) in the Neyyar River Basin,Kerala: a remote sensing and GIS approach

Abstract

Land use and land cover change, perhaps the most significant anthropogenic disturbance to the environment, mainly due to rapid urbanization/industrialization and large scale agricultural activities. In this paper, an attempt has been made to appraise land use/land cover changes over a century (1914–2007) in the Neyyar River Basin (L=56 km; Area = 483.4 km²) in southern Kerala – a biodiversity hot spot in Peninsular India. In this study, digital remote sensing data of the Indian Remote Sensing satellite series I-D (LISS III, 2006–2007) on 1:50,000 scale, Survey of India (SOI) toposheet of 1914 (1:63,360) and 1967 (1:50,000) have been utilized to map various land use/land cover changes. Maps of different periods have been registered and resampled to similar geographic coordinates using ERDAS Imagine 9.0. The most notable changes include decreases in areas of paddy cultivation, mixed crops, scrub lands and evergreen forests, and increases in built-up areas, rubber plantations, dense mixed forests, and water bodies. Further, large scale exploitation of flood plain mud and river sand have reached menacing proportions leading to bank caving and cut offs at channel bends. Conservation of land and water resources forms an important aspect of ecosystem management in the basin.     

Fine-scale simulation of spatial population distribution by coupling GA–ABM and big data: A case study of Dongguan,China

Capturing spatial population distribution can offer useful information for urban planning to promote reasonable population distribution and allocate urban resource. Agent-based model (ABM) based on the modeling idea of “bottom-up” can offer the ability to simulate the complex individual behaviors that generate spatial population distribution. Previous ABMs were unable to be extended for simulation of spatial population distribution at a fine scale due to the shortage of fine characterization of the urban environment and the calibration of agents' behavior. This study filled these gaps by proposing a genetic algorithm-ABM (GA–ABM) for fine-scale simulation of spatial population distribution in a manufacturing metropolis. In this model, the employment and residential choice behaviors of agents were defined by the labor economic theory and discrete selection model. Multisource geospatial big data such as enterprise points-of-interest big data and building footprints data were used to finely characterize the labor market and urban environment to reflect the impact of agents' employment choices on their residential decision. Furthermore, the grid-scale population investigation big data were combined with the GA to calibrate the agents' residential decision behaviors. The proposed model was used in Dongguan, the typical manufacturing metropolis in China. As a comparison, the expert-experience-based method-ABM (EEBM–ABM) was also conducted by using the same data set. Through the comparison of the results produced by these two models, it was demonstrated that the model coefficient calibrated by GA could effectively reflect the agents' residential decisions. The calibrated GA–ABM is more capable than EEBM–ABM in simulating spatial population distribution in a manufacturing metropolis. Hence, the proposed model can be used to simulate spatial population distribution in a manufacturing metropolis which helps the urban planner to conduct scientific urban planning.     

Hedonic price models with omitted variables and measurement errors: a constrained autoregression–structural equation modeling approach with application to urban Indonesia

Omitted variables and measurement errors in explanatory variables frequently occur in hedonic price models. Ignoring these problems leads to biased estimators. In this paper, we develop a constrained autoregression–structural equation model (ASEM) to handle both types of problems. Standard panel data models to handle omitted variables bias are based on the assumption that the omitted variables are time-invariant. ASEM allows handling of both time-varying and time-invariant omitted variables by constrained autoregression. In the case of measurement error, standard approaches require additional external information which is usually difficult to obtain. ASEM exploits the fact that panel data are repeatedly measured which allows decomposing the variance of a variable into the true variance and the variance due to measurement error. We apply ASEM to estimate a hedonic housing model for urban Indonesia. To get insight into the consequences of measurement error and omitted variables, we compare the ASEM estimates with the outcomes of (1) a standard SEM, which does not account for omitted variables, (2) a constrained autoregression model, which does not account for measurement error, and (3) a fixed effects hedonic model, which ignores measurement error and time-varying omitted variables. The differences between the ASEM estimates and the outcomes of the three alternative approaches are substantial.     

Using Landsat Thematic Mapper records to map land cover change and the impacts of reforestation programmes in the borderlands of southeast Yunnan,China: 1990–2010

At the beginning of the new millennium, after a severe drought and destructive floods along the Yangtze River, the Chinese government implemented two large ecological rehabilitation and reforestation projects: the Natural Forest Protection Programme and the Sloping Land Conversion Programme. Using Landsat data from a decade before, during and after the inception of these programmes, we analyze their impacts along with other policies on land use, land cover change (LULCC) in southwest China. Our goal is to quantify the predominant land cover changes in four borderland counties, home to tens of thousands of ethnic minority individuals. We do this in three time stages (1990, 2000 and 2010). We use support vector machines as well as a transition matrix to monitor the land cover changes. The land cover classifications resulted in an overall accuracy and Kappa coefficient for forested area and cropland of respectively 91% (2% confidence interval) and 0.87. Our results suggest that the total forested area observed increased 3% over this 20-year period, while cropland decreased slightly (0.1%). However, these changes varied over specific time periods: forested area decreased between 1990 and 2000 and then increased between 2000 and 2010. In contrast, cropland increased and then decreased. These results suggest the important impacts of reforestation programmes that have accelerated a land cover transition in this region. We also found large changes in LULC occurring around fast growing urban areas, with changes in these peri-urban zones occurring faster to the east than west. This suggests that differences in socioeconomic conditions and specific local and regional policies have influenced the rates of forest, cropland and urban net changes, disturbances and net transitions. While it appears that a combination of economic growth and forest protection in this region over the past 20 years has been fairly successful, threats like drought, other extreme weather events and land degradation remain.