Detecting land-use/land-cover change in rural–urban fringe areas using extended change-vector analysis

Detecting land-use/land-cover (LULC) changes in rural–urban fringe areas (RUFAs) timely and accurately using satellite imagery is essential for land-use planning and management in China. Although traditional spectral-based change-vector analysis (CVA) can effectively detect LULC change in many cases, it encounters difficulties in RUFAs because of deficiencies in the spectral information of satellite images. To detect LULC changes in RUFAs effectively, this paper proposes an extended CVA approach that incorporates textural change information into the traditional spectral-based CVA. The extended CVA was applied to three different pilot RUFAs in China with different remotely sensed data, including Landsat Thematic Mapper (TM), China–Brazil Earth Resources Satellite (CBERS) and Advanced Land Observing Satellite (ALOS) images. The results demonstrated the improvement of the extended CVA compared to the traditional spectral-based CVA with the overall accuracy increased between 4.66% and 8.00% and the kappa coefficient increased between 0.10 and 0.15, respectively. The advantage of the extended CVA lies in its integration of both spectral and textural change information to detect LULC changes, allowing for effective discrimination of LULC changes that are spectrally similar but texturally different in RUFAs. The extended CVA has great potential to be widely used for LULC-change detection in RUFAs, which are often heterogeneous and fragmental in nature, with rich textural information.     

Delineation and classification of rural–urban fringe using geospatial technique and onboard DMSP–Operational Linescan System

This study aims to analyse the processes and patterns of peri-urbanization using diurnal earth observation data-sets from onboard DMSP–Operational Linescan System. In this study, multiple correlation, simple and conditional linear regression are used to find out the degree of relationship and spatial behavioural pattern of the factors responsible for the urbanization. All the factors are standardized using the Analytical Hierarchy Process (AHP) coupled fuzzy membership functions. AHP is used to derive the weighting of the factors to produce the urbanity index. In total three functional zones – urban, rural and urban shadow are generated based on factor standardization and spatial contiguity index. Urban fringe is sharing ≥ 60% of Urbanity Index followed by rural fringe (39.50–60% of urbanity index) and urban shadow <39.50% of urbanity index. Shape index indicates that the city is going through unplanned development following cross to star shape growth.     

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.     

Spatial pattern of urban functional landscapes along an urban–rural gradient: A case study in Xiamen City,China

Since there is an increasing demand for integrating landscape ecology and urban planning theories to study complex urban ecosystems and establish rational and ecological urban planning, we introduced a new concept-urban functional landscapes which can be reclassified based on detailed land use data to fulfill the various urban functions, such as residential, commercial, industrial, and infrastructure purposes. In this paper, urban functional landscapes were defined based on urban land use data produced from Pleiades images, and then landscape metrics and population density were combined to identify the urban functional zones along an urban–rural gradient. The features of urban functional landscape patterns and population density were also analyzed, and their relationship has been explored. The results showed that the pattern of urban functional landscapes and population density in the urban functional zones (Urban center, Urban peripheral area, Landscape barrier, Satellite city and Far-suburb) along the urban–rural gradient in Xiamen doesn't totally conform to the classical theories in spatial and social aspects. Urban functional landscapes is potential of acting as bridges between the landscape ecology and urban planning theories, providing scientific support for rational urban landscape planning and urban land use policy making.     

Extracting urban water bodies from high-resolution radar images: Measuring the urban surface morphology to control for radar’s double-bounce effect

Satellite remote sensing is an effective method for extracting water bodies on a large scale. Radar imagery, such as synthetic aperture radar (SAR) imagery, can penetrate clouds and provide opportunities for water body identification when in situ observations are difficult to obtain because of severe weather conditions. However, when using SAR images in urban areas to extract water bodies, the radar’s double-bounce effect results in complicated backscatter patterns of water near urban features such as buildings due to the side-looking properties of SAR sensors and the vertical urban structures. Therefore, the objective of this study is to propose a reliable urban water extraction framework for SAR images that integrates urban surface morphological features for controlling radar’s multiple bounces. Statistical (logistic regression) and machine-learning (random forest) models were used to explore how radar’s double-bounce effect influences the prediction performance of urban water extraction. Our findings indicate that when extracting urban water bodies, urban water’s backscatter values could be significantly interfered by the neighboring building density above a threshold height that contributes to radar’s multiple bounces. Without model calibration, our framework incorporating urban surface morphology demonstrates high prediction ability with an Area Under the Curve (AUC) of 0.914 and with 97.0% of urban water cells correctly identified by testing in another city sharing similar urban forms. In summary, our study provides a better understanding of the role of the urban surface morphology in the double-bounce effect in SAR images, specifically for differentiating urban water and land, thereby improving the accuracy of urban water extraction and enhancing the feasibility of further applications of SAR imagery under complex urban landscapes.     

Simulating urban land-use change based on the multi-hierarchal planning–environment interaction process

Urban land-use change is the result of coupling interaction between planning and environment systems. The aim of our study was to construct an effective model to show how the urban land-use changes under the planning–environment interaction system with multi-hierarchy and major function oriented zoning. Combining the Cellular automata (CA) model with logistic regression model, the proposed multi-hierarchal vector CA model (MH-VCA3) was constructed by mining multi-hierarchal land-use transition rules under the planning–environment interaction system. Taking Jiangyin City (China) as an example, we compared the simulated result of the proposed model to those of the well-accepted Logistic CA and traditional multi-level CA models to demonstrate the effectiveness of the consideration of top-down decomposition constraint and bottom-up updating. Furthermore, by simulating the land-use changes under different population regionalization scenarios, we found that in order to form the spatial pattern of “agglomeration in the north and ecology in the south,” the planned population growth at the global hierarchal level should be allocated to the district units according to the law of Central district > Chengxi district > Chengdong district > Chengnan district > Chengdongnan district. The proposed model is expected to provide scientific support for the formulation of urban planning schemes in the future.     

Using DORIS measurements for modeling the vertical total electron content of the Earth’s ionosphere

The Doppler orbitography and radiopositioning integrated by satellite (DORIS) system was originally developed for precise orbit determination of low Earth orbiting (LEO) satellites. Beyond that, it is highly qualified for modeling the distribution of electrons within the Earth’s ionosphere. It measures with two frequencies in L-band with a relative frequency ratio close to 5. Since the terrestrial ground beacons are distributed quite homogeneously and several LEOs are equipped with modern receivers, a good applicability for global vertical total electron content (VTEC) modeling can be expected. This paper investigates the capability of DORIS dual-frequency phase observations for deriving VTEC and the contribution of these data to global VTEC modeling. The DORIS preprocessing is performed similar to commonly used global navigation satellite systems (GNSS) preprocessing. However, the absolute DORIS VTEC level is taken from global ionospheric maps (GIM) provided by the International GNSS Service (IGS) as the DORIS data contain no absolute information. DORIS-derived VTEC values show good consistency with IGS GIMs with a RMS between 2 and 3 total electron content units (TECU) depending on solar activity which can be reduced to less than 2 TECU when using only observations with elevation angles higher than \(50^\circ \) . The combination of DORIS VTEC with data from other space-geodetic measurement techniques improves the accuracy of global VTEC models significantly. If DORIS VTEC data is used to update IGS GIMs, an improvement of up to 12  % can be achieved. The accuracy directly beneath the DORIS satellites’ ground-tracks ranges between 1.5 and 3.5 TECU assuming a precision of 2.5 TECU for altimeter-derived VTEC values which have been used for validation purposes.     

Do households prefer to move up or down the urban hierarchy during an economic crisis?

Journal of Geographical Systems - In this paper, we investigate the relationship between adverse economic circumstances and the desire of Dutch households to move up or down the urban hierarchy. We...     

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.     

Ground deformation associated with post-mining activity at the French–German border revealed by novel InSAR time series method

We present a novel methodology for integration of multiple InSAR data sets for computation of two dimensional time series of ground deformation. The proposed approach allows combination of SAR data acquired with different acquisition parameters, temporal and spatial sampling and resolution, wavelength and polarization. Produced time series have combined coverage, improved temporal resolution and lower noise level. We apply this methodology for mapping coal mining related ground subsidence and uplift in the Greater Region of Luxembourg along the French–German border. For this we processed 167 Synthetic Aperture Radar ERS-1/2 and ENVISAT images acquired between 1995 and 2009 from one ascending (track 29) and one descending (track 337) tracks and created over five hundred interferograms that were used for time series analysis. Derived vertical and east–west linear deformation rates show with remarkable precision a region of localized ground deformation located above and caused by mining and post-mining activities. Time series of ground deformation display temporal variability: reversal from subsidence to uplift and acceleration of subsidence in the vertical component, and horizontal motion toward the center of the subsidence on the east–west component. InSAR results are validated by leveling measurements collected by the French Geological Survey (BRGM) during 2006–2008. We determined that deformation rate changes are mainly caused by water level variations in the mines. Due to higher temporal and spatial resolution the proposed space-borne method detected a larger number of subsidence and uplift areas in comparison to leveling measurements restricted to annual monitoring of benchmark points along roads. We also identified one deformation region that is not precisely located above the mining sites. Comparison of InSAR measurements with the water levels measured in the mining pits suggest that part of the water that filled the galleries after termination of the dewatering systems may come from this region. Providing that enough SAR data is available, this method opens new opportunities for detecting and locating man-made and natural ground deformation signals with high temporal resolution and precision.     

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.     

Improvement of edge effect of the wavelet time–frequency spectrum: application to the length-of-day series

 The edge effect in the wavelet time–frequency spectrum of a time series is treated. The time series is first extended on both ends by applying a non-linear model, namely the leap-step time series analysis (LSTSA) model, prior to the wavelet transform. The results of a series of simulation experiments and an application to the observed length-of-day (LOD) series demonstrate that the edge effect is effectively reduced this way. Thus, the application of the LSTSA model improves the wavelet time–frequency spectrum, especially enhancing the ability to detect the low-frequency signals. Received: 15 September 1998 / Accepted: 4 October 1999     

Spatio-temporal divergence in the responses of Finland’s boreal forests to climate variables

Spring greening in boreal forest ecosystems has been widely linked to increasing temperature, but few studies have attempted to unravel the relative effects of climate variables such as maximum temperature (TMX), minimum temperature (TMN), mean temperature (TMP), precipitation (PRE) and radiation (RAD) on vegetation growth at different stages of growing season. However, clarifying these effects is fundamental to better understand the relationship between vegetation and climate change. This study investigated spatio-temporal divergence in the responses of Finland’s boreal forests to climate variables using the plant phenology index (PPI) calculated based on the latest Collection V006 MODIS BRDF-corrected surface reflectance products (MCD43C4) from 2002 to 2018, and identified the dominant climate variables controlling vegetation change during the growing season (May–September) on a monthly basis. Partial least squares (PLS) regression was used to quantify the response of PPI to climate variables and distinguish the separate impacts of different variables. The study results show the dominant effects of temperature on the PPI in May and June, with TMX, TMN and TMP being the most important explanatory variables for the variation of PPI depending on the location, respectively. Meanwhile, drought had an unexpectedly positive impact on vegetation in few areas. More than 50 % of the variation of PPI could be explained by climate variables for 68.5 % of the entire forest area in May and 87.7 % in June, respectively. During July to September, the PPI variance explained by climate and corresponding spatial extent rapidly decreased. Nevertheless, the RAD was found be the most important explanatory variable to July PPI in some areas. In contrast, the PPI in August and September was insensitive to climate in almost all of the regions studied. Our study gives useful insights on quantifying and identifying the relative importance of climate variables to boreal forest, which can be used to predict the possible response of forest under future warming.     

Temperature dependence of variations in the end of the growing season from 1982 to 2012 on the Qinghai–Tibetan Plateau

A growing number of studies have focused on variations in vegetation phenology and their correlations with climatic factors. However, there has been little research on changes in spatial heterogeneity with respect to the end of the growing season (EGS) and on responses to climate change for alpine vegetation on the Qinghai–Tibetan Plateau (QTP). In this study, the satellite-derived normalized difference vegetation index (NDVI) and the meteorological record from 1982 to 2012 were used to characterize the spatial pattern of variations in the EGS and their relationship to temperature and precipitation on the QTP. Over the entire study period, the EGS displayed no statistically significant trend; however, there was a strong spatial heterogeneity throughout the plateau. Those areas showing a delaying trend in the EGS were mainly distributed in the eastern part of the plateau, whereas those showing an advancing trend were mostly scattered throughout the western part. Our results also showed that change in the vegetation EGS was more closely correlated with air temperature than with precipitation. Nonetheless, the temperature sensitivity of the vegetation EGS became lower as aridity increased, suggesting that precipitation is an important regulator of the response of the vegetation EGS to climate warming. These results indicate spatial differences in key environmental influences on the vegetation EGS that must be taken into account in current phenological models, which are largely driven by temperature.     

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 cosmo-skymed images to detect wet snow cover on the Kraków Ice Field,King George Island,Antarctica

This work analysed the spatio-temporal variation of snow cover on the Kraków Ice Field, located in the King George Island, Antarctica. High spatial resolution images of COSMO-SkyMed were used in this study. These X-band images are vertically and horizontally co-polarized and their intensity data were converted to amplitude (dB). The COSMO-SkyMed images were classified by a minimum distance algorithm and post-classified based on knowledge of adjacency relationships of snow zones. Hypsometric, slope, aspect and solar radiation maps to support the interpretation of backscatter patterns in the COSMO-SkyMed images. Three radar zones were classified in these images: percolation, slush and wet snow radar zone. Positive surface air temperatures and rainfall events, registered from a meteorological station, lead to increase in wet snow and slush zones. The COSMO-SkyMed images and minimum distance algorithm were adequate to discriminate the snow cover and to assess the supraglacial melting pattern during the ablation season in the study area.     

GPS–TEC response to the substorm onset during April 5, 2010, magnetic storm

We consider disturbances of total electron content (TEC) of the high-latitude ionosphere provided by the GPS global navigation satellite system before and during the magnetic storm on April 5, 2010. Simultaneously, we examine magnetic data from all available magnetometer arrays in the northern hemisphere, augmented with data from scanning photometers and riometers. The substorm onset, during both non-storm and storm periods, is found to cause significant enhancement of TEC scintillations characterized by the TEC time derivative dTEC. Comparison of 2D maps of the spectral power of magnetic fluctuations in the Pc5 band (1–10 mHz) and dTEC during substorms shows a good spatial and temporal correspondence between them. Both magnetic and ionospheric fluctuations tend to concentrate inside the auroral oval, the boundaries of which are determined from the OVATION model. The time–space evolution of TEC scintillations is rather similar to that of ultra-low-frequency magnetic fluctuations, but not to that of the ionospheric electrojet. GPS signal phase slips, resulting in non-physical TEC jumps (>1 TECu/min), occur predominantly inside the auroral oval and in the vicinity of its equatorward boundary.     

Aggregate accessibility to population at the county level: U.S. 1940–2000

 A classic study by Harris (1954) shows a map of U.S. national accessibility. Harris argued that access to population and income represents a critical factor for location analysis. Such maps and analyses are now readily produced by geographical information systems, allowing experimentation with various parameters, and explorations of changes. By comparing changes in these measurements we can develop a synthetic picture of the impacts of population redistribution. This paper offers a comprehensive review of these calculations and illustrates their use with maps from county population in the continental U.S. from 1940 through to 2000. Received: September 2002 / Accepted: January 2003 RID="*" ID="*" Previous versions of this paper were presented to the Initiative in Population Research (IPR) workshop at the Ohio State University (Horner) and to the Center for Spatially Integrated Social Sciences (CSISS) Summer Workshop in Accessibility (O'Kelly). Thanks to the referees for helpful comments.