Application of Landsat satellite imagery to monitor land‐cover changes at the Athabasca Oil Sands,Alberta, Canada

A major advantage of satellite remote sensing is that the imagery acquired provides a synoptic view of the landscape. Thus, repeat coverage by the satellite on a regular basis permits the detection of changes in land‐cover over time. This study demonstrates the application of remote sensing technology to the monitoring of mining activities at the Athabasca Oil Sands region of Alberta, Canada. First, we describe the techniques used to match a time sequence of Landsat imagery, both spatially and spectrally, to ensure that the spectral changes through time are due to land‐cover variations. A series of spectral trajectories were then extracted to assess changes in land‐cover through time. Secondly, a land‐cover classification was produced from the baseline 1984 imagery and, using historic and future mine extents, the classification was analyzed to determine the proportion of each land‐cover type affected through development. Results of the analysis indicate that since 1984 there has been a larger reduction in mixedwood dense and broadleaf vegetation classes than mixedwood sparse or dense conifer stands in the area. Based on the delineations of mine‐site activity, the area of woodland and wetland habitat subject to development has increased from approximately 2,520 hectare (ha) in 1984 to 32,930 ha in 2005.     

NDVI variation and its relation to climate in Canadian ecozones

Parks Canada began the Northern Satellite Monitoring Program in 1997, with the objective of tracking large‐scale vegetation variation in Canadian ecosystems and helping land managers to develop appropriate management practices in response to climate change. Under this program, a sequence of 10‐day composite Advanced Very High Resolution Radiometer (AVHRR)‐derived Normalized Difference Vegetation Index (NDVI) data from 1985 to 2007 was examined to study seasonal and inter‐annual relationships between vegetation and climate data over Canadian ecosystems using statistical and wavelet analysis. Statistical analysis showed that temperature was the principal driver for seasonal variability in greenness, explaining more than 70 percent of seasonal variation in vegetation for most Canadian ecozones. In comparison with temperature, the relationships between NDVI and precipitation were weaker but still significant. Maximum annual NDVI showed increasing trends in Canadian ecozones during the study period, although increasing rates were spatially heterogeneous. Wavelet analysis confirmed that inter‐annual variation in NDVI was different at two ecozones in Canada. NDVI variation in the Northern Arctic was significant at scales of 3–4 years from 1997 to 2001, which was associated with temperature and precipitation variation. Comparatively, NDVI variation in the Boreal Shield was significant at scales of 5–8 years from 1991 to 1999, but did not correspond with climate variation.     

Assessment of Relationships Between Precipitation and Satellite Derived Vegetation Condition Within South Australia

The normalised difference vegetation index (NDVI) has evolved as a primary tool for monitoring continental‐scale vegetation changes and interpreting the impact of short to long‐term climatic events on the biosphere. The objective of this research was to assess the nature of relationships between precipitation and vegetation condition, as measured by the satellite‐derived NDVI within South Australia. The correlation, timing and magnitude of the NDVI response to precipitation were examined for different vegetation formations within the State (forest, scrubland, shrubland, woodland and grassland). Results from this study indicate that there are strong relationships between precipitation and NDVI both spatially and temporally within South Australia. Differences in the timing of the NDVI response to precipitation were evident among the five vegetation formations. The most significant relationship between rainfall and NDVI was within the forest formation. Negative correlations between NDVI and precipitation events indicated that vegetation green‐up is a result of seasonal patterns in precipitation. Spatial patterns in the average NDVI over the study period closely resembled the boundaries of the five classified vegetation formations within South Australia. Spatial variability within the NDVI data set over the study period differed greatly between and within the vegetation formations examined depending on the location within the state. ACRONYMS AVHRR Advanced Very High Resolution Radiometer ENVSAEnvironments of South Australia EOS Terra‐Earth Observing System EVIEnhanced Vegetation Index MODIS Moderate Resolution Imaging Spectro‐radiometer MVC Maximum Value Composite NDVINormalised Difference Vegetation Index NIRNear Infra‐Red NOAANational Oceanic and Atmospheric Administration SPOT Systeme Pour l’Observation de la Terre     

The new Siberia

This paper assesses relationships between Scottish ice climbing and daily weather conditions between 1961 and 1990. Synoptic air flow and instrumental climate data from Braemar and Fort Augustus were analysed in relation to first ascents of ice climbs in the Cairngorms, and on Ben Nevis and Creag Meagaidh. Lagged weather variables were calculated and stepwise logistic regression was used to estimate optimum models for both areas. Significant variables are anticyclonicity, low minimum air temperature and northerly or easterly airflow (Cairngorms, P = 0.0006); and northerly or easterly airflow, low minimum air temperature and low precipitation (Ben Nevis and Creag Meagaidh, P < 0.0001). A five‐day cold spell is optimum for Ben Nevis and Creag Meagaidh. A week with relatively little precipitation is beneficial in both areas. Air flow direction is more influential than vorticity, the optimum predictors of ice conditions using synoptic data alone are a persistent easterly component (beneficial), and a persistent southerly and westerly component (detrimental), P < 0.0001.     

Energy input and spectral variations of precipitated particles during three nights of the Energy Budget Campaign

Observations were carried out during the Energy Budget Campaign with the aim of measuring keV particle precipitation in the ionosphere over a region covering the rocket range. These measurements are important as particle precipitation constitutes one of the major energy inputs into the ionosphere during an auroral substorm. Estimates of electron precipitation have been made in three different regions of the energy spectrum. Two optical emissions were measured that are proportional to electron precipitation of a few hundred eV and a few keV, respectively, and cosmic noise absorption related to electrons of a few tens of keV. The relative variation between the signals may be interpreted as changes of the energy spectrum of the particles. Measurements from the ground have been compared with satellite measurements to obtain the relation between the two methods. The ground-based observations, which are continuous in time and cover a large area, may be used to separate the spatial and temporal variations and to give the large scale substorm frame of reference for the rocket data. The results may also be used in the interpretation of other measurements on board rockets where a knowledge of the precipitated particles is required.     

Synoptic weather patterns and wave conditions,Surfers Paradise Beach,south-eastern Queensland, 1988

Wave conditions experienced along the beaches of south-eastern Australia are controlled by winds generated by synoptic scale weather systems over the Tasman and Coral Seas. A synoptic climatological approach provides a framework to establish relationships between these synoptic weather map patterns and daily wave conditions recorded at Surfers Paradise beach. This establishes frequently recurring synoptic weather map patterns (synoptic types) and wave conditions at Surfers Paradise associated with each type. Eight synoptic types, differentiated by isobar orientation and pressure gradient, are identified for a 12 month period. Moderate wave power conditions occurred most frequently and were produced by two anticyclonic types. Less frequent, low wave power conditions were produced by synoptic types with offshore, south-west to westerly surface airflow over the southern Coral and northern Tasman Seas. Synoptic situations dominated by a tropical cyclone or extra-tropical cyclone produced the highest, but least frequent wave power conditions. The results indicated that the synoptic climatological approach provides a viable framework to establish and examine links between weather systems and wave conditions.     

Monitoring Islamic Archaeological Landscapes in Ethiopia Using Open Source Satellite Imagery

The African landscape is set to change dramatically in the coming years, and will have a detrimental impact on the inherent archaeological and cultural heritage elements if not monitored adequately. This paper explores how satellite imagery, in particular open source imagery (Google Earth, multispectral satellite imagery from Landsat and Sentinel-2), can be utilized to monitor and protect sites that are already known with particular reference to Islamic archaeological sites in Ethiopia. The four sites used are in different geographic and geomorphological areas: three on the Somali Plateau (Harlaa, Harar, and Sheikh Hussein), and one on the edge of the Afar Depression (Nora), and have varied histories. The results indicate that open source satellite imagery offers a mechanism for evaluating site status and conservation over time at a large scale, and can be used on data from other areas of Africa by heritage professionals in the African continent at no cost.     

Extreme weather events in northeastern New Brunswick (Canada) for the period 1950–2012: Comparison of newspaper archive and weather station data

In the context of global warming, changes in extreme weather and climate events are expected, particularly those associated with changes in temperature and precipitation regimes and those that will affect coastal areas. The main objectives of this study were to establish the number of extreme events that have occurred in northeastern New Brunswick, Canada in recent history, and to determine whether their occurrence has increased. By using archived regional newspapers and data from three meteorological stations in a national network, the frequency of extreme events in the study area was established for the time period 1950–2012. Of the 282 extreme weather events recorded in the newspaper archives, 70% were also identified in the meteorological time series analysis. The discrepancy might be explained by the synergistic effect of co‐occurring non‐extreme events, and increased vulnerability over time, resulting from more people and infrastructure being located in coastal hazard zones. The Mann Kendall and Pettitt statistical tests were used to identify trends and the presence of break points in the weather data time series. Results indicate a statistically significant increase in average temperatures and in the number of extreme events, such as extreme hot days, as well as an increase in total annual and extreme precipitation. A significant decrease in the number of frost‐free days and extreme cold days was also found, in addition to a decline in the number of dry days.     

An exploration of regional climate change scenarios for Scotland

Based on a high resolution regional climate model (RCM) experiment, a climate change scenario for Scotland for the end of this century is constructed with the aim of exploring the added value of utilising a regional rather than a global model (GCM) for climate change scenario construction. Spatial variations in regional seasonal average temperature and precipitation change are analysed and the local response of ‘extreme’ weather events to climate warming is assessed using daily model output. The analyses suggest that in comparison with the GCM, the RCM does not provide fundamentally different patterns of seasonal climate change and daily weather response over Scotland, although it does capture more subtle spatial variations in these changes. The RCM also simulates more realistic daily weather events than the GCM, although the relative changes in the frequencies of daily extremes are not greatly different. However, with the limited length of the single model simulation analysed here, it is not easy to establish how robust and significant are the sub‐national patterns of climate response across Scotland. To improve the quality and comprehensiveness of regional climate change scenario information, a number of research issues remain to be addressed.     

Tropical mesoscale rainfall patterns: the opening of the monsoon in the Townsville area,December 1988

Rainfall during six days of monsoonal activity in the 1988/89 wet season is examined in terms of the influence of synoptic scale winds on mesoscale rainfall activity over the Townsville coastal plain (3450 km²). The resulting rainfall patterns. which were based on observations from a dense mesoscale network of 133 gauge points. are presented as isohyetal maps of twenty-four hour totals for each day in the study period. The study has shown that the distribution of rainfall is related to the influence of synoptic scale wind vectors, which provide upper level steering of convective activity. In addition. the interaction between local winds and synoptic circulation is deemed important for inducing convergence and precipitation. Rainfall generated is then directed by the prevailing upper synoptic flow. Orographic effects also appear to be significant, in that rainfall distribution tends to favour slopes on the windward side of the synoptic scale winds. The rainfall patterns described are probably typical of many of those that occurred throughout the 1988/89 wet season, due to the likely persistence of these mesoscale precipitation mechanisms. Similar mechanisms are also likely to occur over the study area in other wet seasons and elsewhere in the seasonally wet and dry tropics.     

The Integration of VHR Satellite Imagery,GPR Survey and Boring for Archaeological Prospection at the Longcheng Site in Anhui Province,China

This paper is focused on the joint use of non‐invasive and minimal intervention techniques for supporting archaeological prospection. Very high resolution (VHR) satellite imagery analysis and ground‐penetrating radar (GPR) and boring surveys were integrated for the study of the Longcheng site, located near Hefei city in Anhui Province, China, to test their effectiveness and efficiency in prospecting archaeological remains and evaluating their degree of preservation. First, target locations of potential archaeological structures were identified on a WorldView‐2 (WV‐2) satellite image through spatial and radiometric enhancement, interpretation and object‐oriented classification. Second, archaeological features extracted from the WV‐2 imagery were further investigated by a GPR survey that provided detailed cross‐checking information about buried remains. Finally, a subsequent boring survey was conducted across those prospective archaeological structures in order to map the stratigraphic sequences on the basis of colour, compactness and the inclusions contained in the soil, and then to test their correspondence with the GPR data. The boring led to detailed confirmation of the results produced by the remote sensing analyses and GPR surveys, as well as the discovery of datable artefacts. On the basis of all the integrated data, the preliminary layout and structure of the Longcheng site was reconstructed in GIS. Furthermore, the widths, lengths, heights and burial depths of these buried archaeological structures were estimated in detail.     

Three‐Dimensional Neurointerpolation of Annual Mean Precipitation and Temperature Surfaces for China

Climatic variables such as annual mean precipitation and temperature display complex and nonlinear variation with latitude, longitude, and elevation. Neural networks are universal approximators and very good at detecting and representing nonlinear relationships between dependent and independent variables. In this paper we use resilient backpropagation (Rprop) neural networks to interpolate annual mean precipitation and temperature surfaces for China. Climate surfaces are interpolated from a total of 288 long‐term climate station data points using latitude, longitude, and elevation derived from a 5‐kilometer resolution digital elevation model. Initial trials of Rprop suggested very fast learning, insensitivity to selection of learning parameters, and a tendency not to overtrain. Cross‐validation was used to determine the best network structure and assess the error inherent in climate interpolation. With the error explicit, the final neurointerpolations of annual mean precipitation and temperature were constructed using all 288 climate station data points. Maps of residuals are also presented. The neurointerpolation of temperature was very successful and captures most of the regional trends found in established climate maps of China as well as significant topographically defined detail. For annual mean temperature the Rprop neural network was found to be an accurate and robust global spatial interpolator. However, the precipitation surface captures only the major latitudinally and continentally defined trends and misses many subregional rainfall features probably because of the influence of other nonparameterized atmospheric and topographic factors.     

Pressurised pastoralism in South Gobi, Mongolia: what is the role of drought?

The desert-steppe region of southern Mongolia is susceptible to drought and extreme winter weather ( dzud ) that in combination form Mongolia's worst natural hazard. Low precipitation and high climatic variability in this dryland environment impact the landscape and affect pastoralism, the dominant rural lifestyle. Using the Standardised Precipitation Index (SPI), this paper identifies drought occurrence in South Gobi Province, Mongolia. It then examines the relationship of drought with climate factors, interaction with vegetation (derived from Normalised Difference Vegetation Index - NDVI - data), and local human and livestock populations, and the dzuds of 1999–2001. Results show that drought is recurrent in the region, reaching extreme intensity most recently in 2005–2006. In contrast with the prevailing concept of drought impacting dzuds , the study did not find a connection between drought and dzud in South Gobi Province. Though repeated events, these natural hazards occur independently in the region. Climatic variables show increasing temperatures (>1°C), fluctuating precipitation patterns and a decline in vegetation cover. The principal long-term correlation of drought is with human population rather than natural factors, dzud or livestock numbers.     

Google earth and the archaeology of Saudi Arabia. A case study from the Jeddah area

Archaeologically, Saudi Arabia is one of the least explored parts of the Middle East. Now, thanks to Google Earth satellite imagery, a number of high-resolution ‘windows’ have been opened onto the landscape. Initial investigations already suggest large parts of the country are immensely rich in archaeological remains and most of those identified are certainly pre-Islamic and probably several thousand years old. Detailed interpretation of one ‘window’ east of Jeddah forms the basis for illustrating the richness of the heritage and how the satellite imagery can be exploited to shed important light on the character and development of the human landscape. Through this ‘window’ we set out a proposed methodology for future work and where it may lead.     

Satellite Remote Sensing of Archaeological Vegetation Signatures in Coastal West Africa

This article discusses how archaeological sites in Sierra Leone, and by extension much of West Africa, can be identified through vegetation patterns (vegetation signatures) detectable in very high-resolution (VHR) multispectral satellite imagery. Settlement sites typically have a differing pattern of vegetation from the surrounding landscape, including concentrations of very large trees with sociocultural and historical significance: cotton (Ceiba pentandra) and baobab (Adansonia digitata). These features are conspicuous elements of the landscape both from the ground and in aerial imagery. Two complementary methods of using VHR multispectral satellite imagery are discussed in this paper: visual interpretation and semi-automated subpixel classification. These techniques are aiding ongoing archaeological survey of the Sierra Leone River Estuary. The impact of recently renewed industrial activity at a site of probable archaeological significance is also assessed through visually interpreted VHR satellite imagery.     

Optimum temporal and spectral window for monitoring crop marks over archaeological remains in the Mediterranean region

This paper aims to explore the formation of crops marks over archaeological features using remote sensing data. Crop marks are very important to archaeological research since they can reveal in an indirect way buried archaeological remains. Several researches have been able to locate subsurface relics via interpretation of multispectral and hyperspectral satellite images. However the best phenophase (time-window) where these crop marks are enhanced and which spectral bands are the most capable for this enhancement are still an open question for the scientific community. This study aims to address these fundamental aspects of Remote Sensing Archaeology. For this reason an extensive dataset was used: two control archaeological sites were constructed in two different areas of Cyprus (Alampra and Acheleia). In these areas both barley and wheat, were cultivated. In situ spectroradiometric measurements were taken over a whole phenological cycle (2001–2012) for both areas. More than 30 in situ campaigns were performed and more than 2600 ground measurements were collected. The phenological analysis of these measurements have shown that a period of only 15 days is best suitable for monitoring crop marks which is connected with one phenological stage; during the beginning of the boot stage of the crops. This period can be used in areas having similar climatic condition as Cyprus (Mediterranean region). Also as it was found, this phenological stage of crops might be also influenced by the climatic conditions of the area. The evaluation of a proposed Archaeological Index was performed at the Thessalian plain (central Greece), where several Neolithic settlements are established. The evaluation was made using both Hyperion and Landsat images. The results have shown that the proposed Archaeological Index is suitable for the enhancement of crop marks in satellite imagery.     

MODIS‐derived NDVI Characterisation of Drought‐Induced Evergreen Dieoff in Western North America

Vegetation stress or mortality can be the result of many factors including drought‐induced water deficit, insect infestations and failures of, or fluctuations in, precipitation sources typical to an area. Reduction of cover and reduced health are identifiable in remotely‐sensed multispectral satellite images. A suite of images from NASA's MODIS sensor was used to calculate the Normalised Difference Vegetation Index (NDVI) during the 2000–2006 North American growing seasons. Fluctuations in NDVI over this period show a significant decline in vegetative health in the region with specific areas showing changes linked to moisture sources, prevailing wind patterns, slope aspect and solar radiation receipt. Ground‐truthing of these areas has confirmed the extent and magnitude of the dieoff signal. Historically, dieoff has been reversed through regeneration as climate conditions return to a normal regime. However, quantification of recent vegetative change in western North America suggests that the degree of change may be too severe for regrowth to occur and may have far‐reaching impacts on a scale unseen in modern times. The loss of vegetative habitat and native species in semi‐arid regions and lack of regeneration in these marginal ecosystems due to prolonged drought are growing global problems. Similar drought stress impacts on marginal ecotypes have also been observed in semi‐arid regions of Australia, South America, Asia and Africa. Observations of the spatial pattern of temperate forest vegetation globally can be used to develop a precise picture of vegetative health in these regions and how they are reacting to global climate change.     

Spatial‐temporal patterns of snow cover in western Canada

Snow cover is often measured as snow‐water equivalent (SWE), which refers to the amount of water stored in a snow pack that would be available upon melting. Snow cover and SWE represent a source of local snow‐melt release, and are sensitive to regional and global atmospheric circulation, and changes in climate. Monitoring SWE using satellite‐based passive microwave radiometry has provided nearly three decades of continuous data for North America. The availability of spatially and temporally extensive SWE data enables a better understanding of the nature of space‐time trends in snow cover, changes in these trends and linking these trends to underlying landscape and terrain characteristics. To address these interests, we quantify the spatial pattern of SWE by applying a local measure of spatial autocorrelation to 25 years of mean February SWE derived from passive microwave retrievals. Using a method for characterizing the temporal trends in the spatial pattern of SWE, temporal trends and variability in spatial autocorrelation are quantified. Results indicate that within the Canadian Prairies, extreme values of SWE are becoming more spatially coherent, with potential impacts on water availability, and hazards such as flooding. These results also highlight the need for Canadian ecological management units that consider winter conditions.     

‘Gates’: a new archaeological site type in Saudi Arabia

The availability of high‐resolution satellite imagery of Saudi Arabia on publicly available platforms such as Google Earth and Bing Maps has been transformational for archaeology. Within just a few years tens of thousands of sites previously unrecorded and scarcely known to the academic world have been mapped. Especially rich in sites are the successive lava fields (harret) stretching from southern Syria through Jordan and down the west coast of the Arabian Peninsula to Yemen, and characterised by the stone‐built structures known to the Bedouin as the ‘works of the old men’. Sites now being revealed include many types familiar from previous research in the wider region but also others of a form previously unknown. ‘Gates’ are one such type, found in large numbers in and around the Harret Khaybar in west‐central Saudi Arabia. They are stone‐built, the walls roughly made and low as with other ‘works’, but quite unlike them in form. Identification, mapping, and preliminary interpretation imply an early date in the sequence of the works—perhaps the very earliest—but no obvious explanation of their purpose can be discerned. Fieldwork is a desideratum.     

Seasonal weather sensitivity,temperature thresholds,and climate change impacts for park visitation

Historical park visitation and weather data, taken at the daily time scale from 2000 to 2009 for Pinery Provincial Park in southern Ontario (Canada), were analysed as an objective measure of the weather sensitivity, temperature thresholds, and potential impacts of projected climate change for park visitation. Three seasonal weather-visitation models were constructed using multivariable linear regression (peak, shoulder, off-season). To account for both natural and institutional seasonality, the weather-visitation models included both climatic (temperature, precipitation) and social (weekends, holidays) variables, which demonstrated equably comparable effects on visitation across the three models. Critical temperature thresholds were identified for each season using one-way analysis of variance to determine the range of temperatures within which the threshold was evident; the specific degree of temperature associated with the threshold was identified within the seasonal regression models. Temperatures over 33 °C during the peak season and over 29 °C during the shoulder season indicated critical thresholds at which point conditions that were ‘too hot’ for some caused a decline in visitation. Furthermore, temperatures below 11 °C indicated another critical threshold, where conditions were ‘too cold’ for most and therefore park visitation was less sensitive to temperature variability below this threshold. A partial sensitivity analysis for the impact of a warmer, wetter climate on park visitation was conducted, illustrating the effect of a 1 °C to 5 °C warming in maximum temperatures, coupled with a 5% to 15% increase in total precipitation. In response to projected climate change, the weather-visitation models suggested that for each additional degree of warming experienced, despite the negative effects of increasing precipitation and more frequent heat extremes, annual park visitation could increase by 3.1%, annually. The projected increase in park visitation as a result of rising temperatures was mainly associated with shoulder season visitation, with only minor increases in peak season visitation.