Urban Air Pollution Patterns, Land Use, and Thermal Landscape: An Examination of the Linkage Using GIS

This article investigates the relationship of local air pollution pattern with urban land use and with urban thermal landscape using a GIS approach. Ambient air quality measurements for sulfur dioxide, nitrogen oxide, carbon monoxide, total suspended particles, and dust level were obtained for Guangzhou City in South China between 1981 and 2000. Landsat TM images and aerial photo derived maps were used to examine city's land use and land cover at different times and changes. Landsat thermal infrared data were employed to compute land surface temperatures and to assess urban thermal patterns. Relationships among the spatial patterns of air pollution, land use, and thermal landscape were sought through GIS and correlation analyses. Results show that the spatial patterns of air pollutants probed were positively correlated with urban built-up density, and with satellite derived land surface temperature values, particularly with measurements taken during the summer. It is suggested that further studies investigate the mechanisms of this linkage, and that remote sensing of air pollution delves into how the energy interacts with the atmosphere and the environment and how sensors see pollutants. Thermal infrared imagery could play a unique role in monitoring and modeling atmospheric pollution.     

Assessing the impact of multiple drivers of land sensitivity to desertification in a Mediterranean country

Experiencing climate changes and increased human pressure, Mediterranean regions are considered representative hotspots of desertification. However, relatively few studies have been devoted to quantify the individual impact of different factors shaping land sensitivity to desertification in these contexts. Our study contributes to this deserving (positive and normative) issue with a diachronic analysis of the impact of multiple drivers of desertification risk on six indicators of land sensitivity based on the Environmentally Sensitive Area (ESA) approach. Indicators (average and maximum ESA score, coefficient of variation and normalized range in the ESA scores, share of ‘fragile’ and ‘critical’ areas in total landscape) were calculated in 777 rural districts of Italy at three time points (early-1960s, early-1990s, and early-2010s). Multivariate models were used to determine the impact of 12 predictors (climate, soil, vegetation, and land management quality) on each indicator of land sensitivity. Results of the analysis identified two non-redundant dimensions respectively associated with the average level of land sensitivity and its intrinsic variability across space. Impacts of climate and vegetation qualities on the level of land sensitivity were high, decreasing over time, and more intense respectively in Northern and Southern Italy. Impacts of soil and land management qualities were moderate, increasing over time, and involving almost all the country's area. Our study emphasizes the role of context-based measures promoting sustainable land management. The ‘local’ dimension proved to be crucial in any strategy of risk mitigation undertaken at disaggregated spatial scales.     

An examination of the effect of landscape pattern, land surface temperature, and socioeconomic conditions on WNV dissemination in Chicago

This paper developed an approach by the synthesis of remote sensing, landscape metrics, and statistical methods to examine the effects of landscape pattern, land surface temperature, and socioeconomic conditions on the spread of West Nile virus (WNV) caused by mosquitoes and animal hosts in Chicago, USA. Land use/land cover and land surface temperature images were derived from Terra’s Advanced Spaceborne Thermal Emission and Reflection Radiometer imagery. An analytical procedure using landscape metrics was developed, applying configuration analysis of landscape patterns in the study area. The positive reports of mosquitoes and animal hosts for WNV in fall, 2001–2006, were collected from the Cook County Public Health Department. Forty-nine municipalities were found to have WNV-positive records in mosquitoes and animal hosts in fall 2004. Socioeconomic data were obtained from the 2000 US Census. Statistical analysis was applied to WNV data in fall 2004 to identify the relationship between potential predictors and WNV spread. As a result, landscape factors, such as landscape aggregation index and the urban areas and areas of grass and water, showed strong correlations with the WNV-positive records. Socioeconomic conditions, such as the population over 65 years old, also showed a strong correlation with WNV-positive records. Thermal conditions of water showed a less but still considerable correlation to WNV-positive records. This research offers an opportunity to explore the effects of landscape pattern, land surface temperature, and socioeconomic conditions on the spread of WNV caused by mosquitoes and animal hosts. Results can contribute to public health and environmental management in the study area.     

Landslide susceptibility mapping in an area of underground mining using the multicriteria decision analysis method

Landslides are geomorphological phenomena that affect anthropogenic and natural features on the Earth’s surface. Many previous studies have identified several factors that have contributed to landslides. Among these factors are physical characteristics, such as slope, aspect, and land cover, of Earth’s surface. Moreover, landslides can be triggered by human activities such as underground mining. This study aims to identify landslide susceptibility areas by analyzing landslide-related factors, including land subsidence triggered by underground mining. The area of interest was Kozlu, Turkey, where underground mining has been in progress for the past 100 years. Thus, to identify landslide risk zones, the multicriteria decision analysis method, together with the analytical hierarchy method, was used. The datasets included were topography, land cover, geological settings, and mining-induced land subsidence. The spatial extent of land subsidence was estimated using a previously published model. A landslide susceptibility map (LSM) was developed using a purposely developed GIS-based software. The results were compared with a terrain deformation map, which was developed in a separate study using the differential synthetic aperture radar interferometry (DInSAR) technique. The results showed a substantial correlation between the LSM and DInSAR map. Furthermore, it was found that ~?88% of the very high and high landslide risk areas coincided with location of the past landslide events. These facts suggest that the algorithm and data sources used were sufficient to produce a sufficiently accurate LSM, which may be used for various purposes such as urban planning.     

基于TM资料对上海区域热环境特征的分析

为了揭示城市热岛(UHI)形成机制,以TM卫星遥感资料为主要数据源,结合地面自动气象站(AWS)实测的气象资料,利用地表能量平衡参数化(SEBAL)的方法估算了净辐射通量和土壤热通量,分析了上海区域热环境特征.结果表明,TM地表温度与AWS实测地表温度具有较好的一致性；不同类型地表其地表温度差异明显,城市道路是城市中重要热量来源,绿地和水体面积的增加能有效地减轻城市热岛强度,同时也表明了卫星遥感资料在城市气候环境研究中的潜在价值.     

Thermal monitoring and analysis of the large-scale field earth-dam breach process

Thermal imaging is a nondestructive testing method for monitoring internal material changes that are indicated by changes in an object’s surface temperature. In this study, field observation using thermographs was applied to monitor and analyze the breach process of large-scale earth dams. The earth dam test site was Landao Creek in Nantou County, Taiwan. Four field tests were performed to monitor and analyze a single earth dam and two successive earth dams. Ponding first occurred at the lowland of the riverbed upstream, and base seepage occurred at the base of the dam downstream; overtopping failure soon followed. Earth-dam failure mode is affected by the topographic characteristics of the riverbed; specifically, lowland areas are prone to ponding upstream, which causes piping and seepage downstream as well as subsequent breaches. Ponding and piping cause water seepage and soil wetting, which are reflected in lower surface temperatures recorded on thermographs. Thermographs can monitor changes in surface temperature to evaluate the potential failure modes of dams. Dam surfaces with large temperature variations may be potential failure areas. If confirmed, this fact may prove useful for failure-mode prediction. This paper proposes a monitoring index to reflect the temperature changes in a given period, and this study verified it empirically.     

Land quality,sustainable development and environmental degradation in agricultural districts: A computational approach based on entropy indexes

Land Degradation (LD) in socio-environmental systems negatively impacts sustainable development paths. This study proposes a framework to LD evaluation based on indicators of diversification in the spatial distribution of sensitive land. We hypothesize that conditions for spatial heterogeneity in a composite index of land sensitivity are more frequently associated to areas prone to LD than spatial homogeneity. Spatial heterogeneity is supposed to be associated with degraded areas that act as hotspots for future degradation processes. A diachronic analysis (1960–2010) was performed at the Italian agricultural district scale to identify environmental factors associated with spatial heterogeneity in the degree of land sensitivity to degradation based on the Environmentally Sensitive Area Index (ESAI). In 1960, diversification in the level of land sensitivity measured using two common indexes of entropy (Shannon's diversity and Pielou's evenness) increased significantly with the ESAI, indicating a high level of land sensitivity to degradation. In 2010, surface area classified as “critical” to LD was the highest in districts with diversification in the spatial distribution of ESAI values, confirming the hypothesis formulated above. Entropy indexes, based on observed alignment with the concept of LD, constitute a valuable base to inform mitigation strategies against desertification.     

Establishing trace element concentrations for lichens and bryophytes in the ring of fire region of the Hudson Bay Lowlands,Ontario, Canada

Environmental Monitoring and Assessment - Streams and rivers cover a larger proportion of the Earth’s surface but are highly affected by human pressures. Conversely, bioassessment methods are...     

The development of stream temperature model in a mountainous river of Taiwan

Formosan landlocked salmon is an endangered species and is very sensitive to stream temperature change. This study attempts to improve a former stream temperature model (STM) which was developed for the salmon’s habitat to simulate stream temperature more realistically. Two modules, solar radiation modification (SRM) and surface/subsurface runoff mixing (RM), were incorporated to overcome the limitation of STM designed only for clear-sky conditions. It was found that daily temperature difference is related to cloud cover and can be used to adjust the effects of cloud cover on incident solar radiation to the ground level. The modified model (STM + SRM) improved the simulation during a baseflow period in both winter and summer with the Nash-Sutcliffe efficiency coefficient improved from 0.37 (by STM only) to 0.71 for the winter and from ?0.18 to 0.70 for the summer. On the days with surface/subsurface runoff, the incorporation of the two new modules together (STM + SRM + RM) improved the Nash-Sutcliffe efficiency coefficient from 0.00 to 0.65 and from 0.29 to 0.83 in the winter and the summer, respectively. Meanwhile, the contributions of major thermal sources to stream temperature changes were identified. Groundwater is a major controlling factor for regulating seasonal changes of stream temperature while solar radiation is the primary factor controlling daily stream temperature variations. This study advanced our understanding on short-term stream temperature variation, which could be useful for the authorities to restore the salmon’s habitat.     

The use of spatial autocorrelation analysis to identify PAHs pollution hotspots at an industrially contaminated site

The identification of contamination “hotspots” are an important indicator of the degree of contamination in localized areas, which can contribute towards the re-sampling and remedial strategies used in the seriously contaminated areas. Accordingly, 114 surface samples, collected from an industrially contaminated site in northern China, were assessed for 16 polycyclic aromatic hydrocarbons (PAHs) and were analyzed using multivariate statistical and spatial autocorrelation techniques. The results showed that the PCA leads to a reduction in the initial dimension of the dataset to two components, dominated by Chr, Bbf&Bkf, Inp, Daa, Bgp, and Nap were good representations of the 16 original PAHs; Global Moran’s I statistics indicated that the significant autocorrelations were detected and the autocorrelation distances of six indicator PAHs were 750, 850, 1,200, 850, 750, and 1,200 m, respectively; there were visible high–high values (hotspots) clustered in the mid-bottom part of the site through the Local Moran’s I index analysis. Hotspot identification and spatial distribution results can play a key role in contaminated site investigation and management.     

Seasonal variations in the relationship between landscape pattern and land surface temperature in Indianapolis, USA

This paper intended to examine the seasonal variations in the relationship between landscape pattern and land surface temperature based on a case study of Indianapolis, United States. The integration of remote sensing, GIS, and landscape ecology methods was used in this study. Four Terra's ASTER images were used to derive the landscape patterns and land surface temperatures (LST) in four seasons in the study area. The spatial and ecological characteristics of landscape patterns and LSTs were examined by the use of landscape metrics. The impact of each land use and land cover type on LST was analyzed based on the measurements of landscape metrics. The results show that the landscape and LST patterns in the winter were unique. The rest of three seasons apparently had more agreeable landscape and LST patterns. The spatial configuration of each LST zone conformed to that of each land use and land cover type with more than 50% of overlap in area for all seasons. This paper may provide useful information for urban planers and environmental managers for assessing and monitoring urban thermal environments as result of urbanization.     

Thermal terrain modeling of spatial objects, a tool for environmental and climatic change assessment

The aim of the current research effort is to include biophysical multi-temporal data and more specifically land surface temperature (LST) in the terrain modeling process that traditionally was based only on digital elevation data processing. The terrain partition framework (spatial objects) is defined by the borderlines of prefecture authorities of Greece. Each object is represented by a set of attributes derived from the digital elevation data, and objects are organized into clusters on the basis of their terrain dependent representation. Finally, the terrain is segmented to regions on the basis of the multi-temporal LST data, each region presenting a different thermal signature. The thermal regions are used in the spatial objects parametric representation and a new index is devised (LST climatic index) expressing the biophysical suitability of spatial objects at moderate resolution scale.     

Assessment of thermal stratification within stream pools as a mechanism to provide refugia for native trout in hot, arid rangelands

Native trout species, such as the redband trout (Oncorhynchus mykiss), occupy thermally harsh stream habitats in hot, arid rangeland basins of the western United States. Declines in the distribution and abundance of these species has generated interest in understanding how these cold water species survive in these systems, as well as in identifying opportunities to restore these species to their former ranges. The purpose of this study was to assess the potential for thermal stratification to provide thermal refuge for redband trout in stream pools characterized by warm intermittent flow conditions on arid rangelands. We studied vertical thermal stratification in two pools during three summers on Boles Creek located on the Modoc Plateau in extreme northeastern California. Water and air temperature data were collected on a 0.5 h time step from 15-Jun through 15-Sep during 1996, 1997, and 2000 using commercial temperature data-loggers. Water temperature was measured at the top (0.3 m below pool surface) and bottom (0.3 m above pool substrates) of each pool. Vertical thermal stratification occurred within these pools creating conditions as much as 7.6 ˚C cooler and consistently more constant at the bottom of pools compared to pool surface waters. Thermal stratification was dependent upon air temperature with the magnitude of stratification increasing as air temperature increased. The magnitude of thermal stratification varied significantly from year to year, likely reflecting variation in annual weather conditions. The thermal regime in the study pools was often near the upper lethal limit reported for redband trout, but temperatures at the bottom of these pools did offer refuge from lethal temperatures realized near the pool surface. Temperatures at pool bottom were consistently above optimal levels published for redbands.     

Land cover mapping based on random forest classification of multitemporal spectral and thermal images

Thematic mapping of complex landscapes, with various phenological patterns from satellite imagery, is a particularly challenging task. However, supplementary information, such as multitemporal data and/or land surface temperature (LST), has the potential to improve the land cover classification accuracy and efficiency. In this paper, in order to map land covers, we evaluated the potential of multitemporal Landsat 8’s spectral and thermal imageries using a random forest (RF) classifier. We used a grid search approach based on the out-of-bag (OOB) estimate of error to optimize the RF parameters. Four different scenarios were considered in this research: (1) RF classification of multitemporal spectral images, (2) RF classification of multitemporal LST images, (3) RF classification of all multitemporal LST and spectral images, and (4) RF classification of selected important or optimum features. The study area in this research was Naghadeh city and its surrounding region, located in West Azerbaijan Province, northwest of Iran. The overall accuracies of first, second, third, and fourth scenarios were equal to 86.48, 82.26, 90.63, and 91.82 %, respectively. The quantitative assessments of the results demonstrated that the most important or optimum features increase the class separability, while the spectral and thermal features produced a more moderate increase in the land cover mapping accuracy. In addition, the contribution of the multitemporal thermal information led to a considerable increase in the user and producer accuracies of classes with a rapid temporal change behavior, such as crops and vegetation.     

Land use and land cover (LULC) of the Republic of the Maldives: first national map and LULC change analysis using remote-sensing data

The Maldives islands in recent decades have experienced dramatic land-use change. Uninhabited islands were turned into new resort islands; evergreen tropical forests were cut, to be replaced by fields and new built-up areas. All these changes happened without a proper monitoring and urban planning strategy from the Maldivian government due to the lack of national land-use and land-cover (LULC) data. This study aimed to realize the first land-use map of the entire Maldives archipelago and to detect land-use and land-cover change (LULCC) using high-resolution satellite images and socioeconomic data. Due to the peculiar geographic and environmental features of the archipelago, the land-use map was obtained by visual interpretation and manual digitization of land-use patches. The images used, dated 2011, were obtained from Digital Globe’s WorldView 1 and WorldView 2 satellites. Nine land-use classes and 18 subclasses were identified and mapped. During a field survey, ground control points were collected to test the geographic and thematic accuracy of the land-use map. The final product’s overall accuracy was 85%. Once the accuracy of the map had been checked, LULCC maps were created using images from the early 2000s derived from Google Earth historical imagery. Post-classification comparison of the classified maps showed that growth of built-up and agricultural areas resulted in decreases in forest land and shrubland. The LULCC maps also revealed an increase in land reclamation inside lagoons near inhabited islands, resulting in environmental impacts on fragile reef habitat. The LULC map of the Republic of the Maldives produced in this study can be used by government authorities to make sustainable land-use planning decisions and to provide better management of land use and land cover.     

Magnetic mapping of fly-ash pollution and heavy metals from soil samples around a point source in a dry tropical environment

The Singrauli region in the southeastern part of Uttar Pradesh, India is one of the most polluted industrial sites of Asia. It encompasses 11 open cast coalmines and six thermal power stations that generate about 7,500 MW (about 10% of India’s installed generation capacity) electricity. Thermal power plants represent the main source of pollution in this region, emitting six million tonnes of fly-ash per annum. Fly-ash is deposited on soils over a large area surrounding thermal power plants. Fly-ashes have high surface concentrations of several toxic elements (heavy metals) and high atmospheric mobility. Fly ash is produced through high-temperature combustion of fossil fuel rich in ferromagnetic minerals. These contaminants can be identified using rock-magnetic methods. Magnetic susceptibility is directly linked to the concentration of ferromagnetic minerals, primarily high values of magnetite. In this study, magnetic susceptibility of top soil samples collected from surrounding areas of a bituminous-coal-fired power plant were measured to identify areas of high emission levels and to chart the spatial distribution of airborne solid particles. Sites close to the power plant have shown higher values of susceptibility that decreases with increasing distance from the source. A significant correlation between magnetic susceptibility and heavy metal content in soils is found. A comparison of the spatial distribution of magnetic susceptibility with heavy-metal concentrations in soil samples suggests that magnetic measurements can be used as a rapid and inexpensive method for proxy mapping of air borne pollution due to industrial activity.     

Accuracy assessment of land surface temperature retrievals from Landsat 7 ETM + in the Dry Valleys of Antarctica using iButton temperature loggers and weather station data

The McMurdo Dry Valleys of Antarctica are the largest snow/ice-free regions on this vast continent, comprising 1 % of the land mass. Due to harsh environmental conditions, the valleys are bereft of any vegetation. Land surface temperature is a key determinate of microclimate and a driver for sensible and latent heat fluxes of the surface. The Dry Valleys have been the focus of ecological studies as they arguably provide the simplest trophic structure suitable for modelling. In this paper, we employ a validation method for land surface temperatures obtained from Landsat 7 ETM + imagery and compared with in situ land surface temperature data collected from four transects totalling 45 iButtons. A single meteorological station was used to obtain a better understanding of daily and seasonal cycles in land surface temperatures. Results show a good agreement between the iButton and the Landsat 7 ETM + product for clear sky cases. We conclude that Landsat 7 ETM + derived land surface temperatures can be used at broad spatial scales for ecological and meteorological research.     

泉州市移动通信基站电磁辐射环境影响分析

对泉州市移动通信GSM基站和TD—SCDMA基站电磁辐射状况进行监测与分析。通过理论计算预测基站电磁辐射安全距离，对典型敏感目标、典型基站进行电磁辐射的监测，结果与理论预测情况相符。选取302个GSM基站和306个TD—SCDMA基站进行电磁辐射的监测，结果表明，各基站电磁辐射满足单个项目管理低于目标限值0．08W／m2的标准。分析表明，基站在正常运行时，对周围的电磁辐射环境影响能满足国家相应标准的要求。     

Inter-comparison of remote sensing sensing-based shoreline mapping techniques at different coastal stretches of India

Many techniques are available for detection of shorelines from multispectral satellite imagery, but the choice of a certain technique for a particular study area can be tough. Hence, for the first time in literature, an inter-comparison of the most widely used shoreline mapping techniques such as Normalized Difference Water Index (NDWI), Modified NDWI (MNDWI), Improved Band Ratio (IBR) Method, and Automatic Water Extraction Index (AWEI) has been done along four different coastal stretches of India using multitemporal Landsat data. The obtained results have been validated with the high-resolution images of Cartosat-2 (panchromatic) and multispectral images from Google Earth. Performance of the above indices has been analyzed based on the statistics, such as overall accuracy, kappa coefficient, user’s accuracy, producer’s accuracy, and the average deviation from the reference line. It is observed that the performance of NDWI and IBR techniques are dependent on the physical characteristics of the sites, and therefore, it varies from one site to another. Results indicate that unlike these two indices, the AWEI algorithm performs consistently well followed by MNDWI irrespective of the land cover types.     

The monitoring results of electromagnetic radiation of 110-kV high-voltage lines in one urban location in Chongqing P.R. China

To understand electromagnetic radiation field strength and its influencing factors of certain 110-kV high-voltage lines in one urban area of Chongqing by measuring 110-kV high-voltage line’s electromagnetic radiation level. According to the methodology as determined by the National Hygienic Standards, we selected certain adjacent residential buildings, high-voltage lines along a specific street and selected different distances around its vertical projection point as monitoring points. The levels of electromagnetic radiations were measured respectively. In this investigation within the frequency of 5–1,000 Hz both the electric field strength and magnetic field strength of each monitoring sites were lower than the public exposure standards as determined by the International Commission on Non-Ionizing Radiation Protection. However, the electrical field strength on the roof adjacent to the high-voltage lines was significantly higher than that as measured on the other floors in the same buildings (p < 0.05). The electromagnetic radiation measurements of different monitoring points, under the same high-voltage lines, showed the location which is nearer the high-voltage line maintain a consistently higher level of radiation than the more distant locations (p < 0.05). Electromagnetic radiation generated by high-voltage lines decreases proportionally to the distance from the lines. The buildings can to some extent shield (or absorb) the electric fields generated by high-voltage lines nearby. The electromagnetic radiation intensity near high-voltage lines may be mitigated or intensified by the manner in which the high-voltage lines are set up, and it merits attention for the potential impact on human health.