Search

Through the ISPRS scientific initiative presented in this paper, we aim to make geospatial educational resources available and discoverable to those who teach and those who want to learn. In earlier work, we designed and implemented a prototype catalogue for geospatial educational resources, aimed at a target audience in higher education. The success of search and discovery in any catalogue relies heavily on the metadata that describes catalogue entries. Initial feedback showed that users find it difficult to use some of the metadata elements in the prototype to describe their teaching materials. In order to better understand their difficulties and further refine the metadata for describing educational resources that are used for geospatial purposes specifically, we asked a number of participants to describe geospatial educational resources according to four sets of metadata attributes. This paper presents the results of the study and recommends a set of metadata attributes that are specifically useful for geospatial educational resources. Implementation trade-offs are discussed, e.g., deciding between metadata attributes that are very specific or more generic, and catalogue entries that are immediately available to Web search engines without any quality checks vs. catalogue entries that are moderated by a community of educators before publishing them. By providing metadata about geospatial educational resources, the international geospatial community can contribute to the UN Sustainable Development Goal 4 to ensure inclusive and equitable quality education and to promote lifelong learning opportunities for all.

Animal traditions are increasingly threatened by human impact on natural habitats, posing a challenge to conservation policies. In northeastern Brazil, bearded capuchins (Sapajus libidinosus) inhabiting theCerrado-Caatingabiome of Fazenda Boa Vista use stone hammers and anvils to crack open palm nuts and other encased foods. The same species inhabiting the mangroves of Morro do Boi ambush crabs and process them using wooden hammers and anvils. These traditions are gradually acquired by young capuchins exposed to the tool using activity of skilled older group members. Changes in land cover have threatened the persistence of this species, where these rare tool-use traditions occur. To assess land cover changes over the past 30 years, we analyzed a time series of remotely sensed imagery and quantified trends in land cover and agriculture across both study sites. We also developed a predictive model to forecast future changes in land cover by 2034. Our results show that agriculture increased by more than 300% in both sites from 1987 to 2017. If current trends continue in Morro do Boi, only 42% of forest (0.15 km(2)) will remain, which is insufficient to support the resident population of capuchins. In Fazenda Boa Vista, most of the land suitable for agriculture has already been used for that purpose. If private conservation efforts at Fazenda Boa Vista are to be effective through 2034, agricultural use should not be expanded any further. Imminent erosion and loss of natural vegetation will exacerbate the current situation, even if agriculture is not expanded. Our study is an example of the need for conservation to take behavioral traditions into account, as they are not widespread across the species distribution.

Existing geospatial educational resources are not always easy to find and to integrate into an academic module, amongst others, because the required metadata is not available. As a consequence, simple search attempts do not bring us to these resources, and we miss out on some material that may be very useful in teaching and learning. Our aim is to develop a searchable catalogue of existing geospatial educational resources that can be used by communities, such as ISPRS or GeoForAll, universities and other educational institutions. The catalogue will index new and existing geospatial educational resources (e.g. electronic textbooks, tutorials, and quizzes) so that the resources can be searched and discovered. Based on the metadata, educators can select appropriate educational resources for integration into an educational event, such as an online course or a module at university level. We believe such an open catalogue of searchable geospatial educational resources is valuable for educators worldwide and will provide students with the opportunity to learn using local and international examples to widen their knowledge. In addition, this future catalogue should broaden overall access to geospatial education and empower communities for the benefit of society. In this paper, we discuss requirements of preparing such a catalogue and some preliminary efforts we have made towards implementing one, including review of 114 existing systems and resources.

Strategies of navigation have been shown to play a critical role when animals revisit resource sites across large home ranges. The habitual route system appears to be a sufficient strategy for animals to navigate while avoiding the cognitive cost of traveling using the Euclidean map. We hypothesize that wild elephants travel more frequently using habitual routes to revisit resource sites as opposed to using the Euclidean map. To identify the elephants' habitual routes, we created a python script, which accounted for frequently used route segments that constituted the habitual routes. Results showed elephant navigation flexibility traveling at Kruger National Park landscape. Elephants shift strategies of navigation depend on the familiarity of their surroundings. In the core area of their home range, elephants traveled using the Euclidean map, but intraindividual differences showed that elephants were then converted to habitual routes when navigating within the less familiar periphery of their home range. These findings are analogous to the recent experimental results found in smaller mammals that showed that rats encode locations according to their familiarity with their surroundings. In addition, as recently observed in monkeys, intersections of habitual routes are important locations used by elephants when making navigation decisions. We found a strong association between intersections and new segment usage by elephants when they revisit resource sites, suggesting that intersection choice may contribute to the spatial representations elephants use when repeatedly revisiting resource sites.

The Santa Fe River (SFR) is within the north Florida area of the regional Floridan aquifer system. The extent of recent flood damage in the SFR and tributaries in Bradford County has been attributed to rainfall and wind damage to trees associated with Hurricane Irma, September 2017. Implications of the determined cause of a disaster can include the allocation of disaster relief funds. Bradford County, Florida obtained approximately $2.5 million from the United States Department of Agriculture’s (USDA) Natural Resources Conservation Service (NRCS) for emergency flood abatement assistance and $255,875 from the Suwannee River Water Management District (SRWMD), combined with $13,750 in-kind match provided by the county, based on the attributed cause of that damage to rainfall and winds from Hurricane Irma. On January 2, 2018, Bradford County commissioners also approved grant applications to the SRWMD for $2.2 million for Alligator Creek Flood Mitigation and for $90,250 for Hampton Lake Canal to Santa Fe River Flood Mitigation, requiring in-kind matches from the county of $110,000 and $4750, respectively. Our study analyzed historical precipitation data for the SFR Basin and headwaters from 1895 through 2017 and recorded discharge and gage heights from the United States Geological Survey (USGS) to evaluate that presumed cause of flood damage in that basin and to provide a better understanding of historical relationships between precipitation, gage data and flooding in that basin. Recorded USGS peak gage height and Digital Elevation Models (DEMs) also were used to illustrate the lateral extent and relative depth of flooding associated with an extreme precipitation event in the lower SFR vicinity of O’Leno State Park. Finally, we evaluated the condition of the trees in the SFR Basin as an indicator of long-term anthropogenic groundwater alterations. Those data and analyses did not support the conclusion that Hurricane Irma was the only cause of the magnitude and extent of SFR flooding and tree damage in Bradford County and adjacent counties. Other contributors to stream flow in the SFR basin include heavy mineral mining wastewater discharges that have exceeded the maximum discharge volume of “40 million gallons a day” (MGD) under the National Pollutant Discharge Elimination System (NPDES) permit issued by the Florida Department of Environmental Protection (FDEP) to the Chemours Company TT LLC (Chemours, formerly DuPont) for Trail Ridge mining operations. The magnitude of those discharges suggests that those discharges and extensive Trail Ridge mining in Baker, Bradford, Clay, and Duval Counties contributed to the flooding and were a factor in the tree destruction in the SFR Basin.

Background Increased Attalea butyracea palm propagation, notable for its role as key habitat for the primary Chagas disease vector in Panama, has been linked to landscape disturbance in single-palm observations in this region. Close proximity of these palms to human dwellings is proposed to increase risk of Chagas disease transmission from sylvatic transmission cycles to domestic transmission involving human populations. This study examines the relationship between landscape disturbance and mature A. butyracea spatial distribution, density, and proximity to human populations and vector and reservoir species’ movement corridors at a regional scale in a 300 km2 heterogeneous tropical landscape in central Panama. Methods We remotely identified the locations of over 50,000 mature A. butyracea palms using high-resolution WorldView2 satellite imagery. A local Getis-Ord Gi* spatial analysis identified significant clusters of aggregated palms. Associations between palm and cluster abundance and a landscape disturbance gradient, derived from official Panama land cover data, were tested using Chi-square tests for Homogeneity and Z-test for proportions. Kruskall-Wallis non-parametric analysis of variance tests were run to assess whether palm cluster area varied by disturbance level, or whether disturbance was associated with proximity of palms and palm clusters to susceptible populations or vector movement corridors. Results Our findings indicate a regional relationship between landscape disturbance and A. butyracea occurrence. We observe a significant increase in both individual and clustered A. butyracea in secondary forest, but a reduction of palms in agricultural settings. We do not detect evidence of any reduction in abundance of palms in residential settings. The majority of residential and commercial buildings in our study area are within vector flight distance of potential vector habitat in palm crowns. Conclusions We observe probable anthropogenic elimination of A. butyracea palms in agricultural, but not residential, settings. Even in heavily deforested regions, significant concentrations of mature palms remain in close proximity to human establishments.

There is a need for sustainable infrastructure planning that includes environmental, social, economic, and transportation management consideration. A portion of a former railway corridor around Atlanta, Georgia was converted to a multi-use trail called the Atlanta BeltLine to provide walking and bicycling access to businesses and homes. Although the pedestrian-transit trail brings renewed development and services, it also triggers increases in home values and displaces existing communities. This study uses remote sensing and geospatial analysis to focus on changes in the structural conditions of housing along the Westside segment of the Atlanta BeltLine. The first segment of the Beltline, the Eastside Trail completed in 2007, demonstrated an alarming influx of development. Increases in property values opened the doors for private investors to purchase properties and open new businesses in communities adjacent to the BeltLine. The proposed Westside segment of the BeltLine has raised concerns by community members who fear the impacts of gentrification. An assessment of housing conditions was conducted by researchers ranking the structural conditions of homes adjacent to the Westside BeltLine. To conduct an estimate of green spaces along both segments of BeltLines, Sentinel-2 Earth Observation Satellite was used to calculate the percentage of green spaces in. A preliminary concept agent-based simulation model (ABM) is being developed to forecast human movement and housing condition around the BeltLine. Combined, the housing survey, green space inventory, and ABM model provides a baseline method to record and identify social and the environmental impacts.

Background: Chagas disease is a vector-borne zoonotic disease endemic to Latin America. In Panama, Attalea butyracea palm trees are the preferred habitat of the region’s primary Chagas disease vector (Rhodnius pallescens). Close proximity of these palms to human dwellings is linked to increased risk of Chagas disease transmission. However, these palms thrive in disturbed habitats associated with human settlement and agriculture. This study examines the relationship between landscape disturbance and mature A. butyracea spatial distribution, density, and proximity to susceptible populations and vector movement corridors in a heterogeneous tropical region in central Panama. Presence of A. butyracea does not guarantee corresponding presence of R. pallescens, but as the vectors’ preferred habitat, quantifying A. butyracea response to disturbance may provide new insight into Chagas disease transmission risks in changing landscapes. Methods: We remotely identified the locations of over 50,000 mature A. butyracea palms using high-resolution WorldView2 satellite imagery. A local Getis-Ord Gi* spatial analysis identified significant clusters of aggregated palms. Associations between palm and cluster abundance and a landscape disturbance gradient, derived from official Panama landcover data, were tested using Chi-square tests for Homogeneity and Z-test for proportions. Kruskall-Wallace non-parametric analysis of variance tests were run to assess whether palm cluster area varied by disturbance level, or whether disturbance influenced average proximity of palms and palm clusters to susceptible populations or vector movement corridors.Results: Our findings indicate a regional relationship between landscape disturbance and A. butyracea occurrence. We observe a significant increase in both individual and clustered A. butyracea in secondary forest, but a reduction in palms in agricultural settings. Notably, we do not detect evidence of any thinning in abundance of palms in residential settings. All but one household in our study area is within vector flight distance of potential vector habitat in palm crowns.Conclusions: We observe probable anthropogenic thinning of A. butyracea palms in agricultural, but not residential, settings. Even in heavily deforested regions, significant concentrations of mature palms remain in close proximity to human establishments. The potential of A. butyracea palms as a source of infectious Chagas disease vectors in this region warrants further study.

Challenges in remote sensing, including remote sensing of vegetation, include the spectral characterization of objects over space and time. One key aspect for this characterization involves the geo...

In this age of computer gaming, portable device video and high definition entertainment, students are exposed to sophisticated graphics and virtual reality every day. As a result, students arrive at universities with a high level of expectation and experience in visualization and 3D graphics. Traditional materials for education and outreach rely predominantly on two-dimensional displays of maps, photographs, data graphs/histograms and conceptual diagrams. Advances in geospatial technologies, including unmanned aerial systems and virtual/ augmented reality devices can be used to enhance and innovate instructional materials in classrooms from pre-K to graduate degree programs. This work reports on these technologies and the integration of the 3D Immersion and Geovisualization (3DIG) system at the Center for Geospatial Research at the University of Georgia, USA. We present system components, lessons learned during design and implementation of the system, and the incorporation of 3DIG into teaching, learning and research. Data flow is used as a multi-component system integrator and shows how interconnected and complementary technologies can provide hands-on and immersive experiential learning to students in the geosciences. System evaluation shows increased student interest/engagement and indicates that 3DIG facilitates the understanding of complex concepts.

There is renewed interest in inventory and monitoring projects, due in part to mandates to evaluate the effects of surrounding development and climate change on the biotic communities of public lands. We inventoried an understudied area, Wormsloe State Historic Site, near Savannah, GA. We directly observed or trapped 21 herpetofaunal (i.e., amphibian and reptile) species. Chao estimates predicted that

Our case study analyzed the proximity of previously mapped fractures in the aquifer matrix to 93 Florida panther (Puma concolor coryi) dens mapped from 2007-2016 in south Florida. Dens occurred in five counties (Collier = 77, Dade = 1, Hendry = 9, Lee = 5, and Monroe = 1) and three sub-basins of the Greater Everglades Basin (Big Cypress Swamp = 83, Caloosahatchee = 3, and Everglades = 7). Fractured aquifers occur worldwide, but are not the focus of habitat suitability studies, despite evidence that fractures influence plant species composition and density. Habitat alterations can occur many kilometers from the surface footprint of groundwater alterations in the regional Floridan aquifer system via preferential flow through fractures. Increased natural discharge from and recharge to the aquifer occur at fracture intersections. Greater induced recharge and habitat changes also may occur at fracture intersections. All dens were within 5 km of a previously mapped fracture; 36% and 74% were within 1 km and 2 km, respectively, of those fractures; and 47%, 74%, and 90% of dens were within 2 km, 3.25 km and 5 km, respectively, from the nearest fracture intersection. Results suggest fractures influence the suitability and/or availability of habitat for panther dens, selection of den sites, and availability as well as abundance of high quality prey items essential for the nutritional demands of successfully rearing panther kittens in the wild. We recommend more detailed investigations of: a) vegetation characteristics near dens, b) groundwater alterations and cumulative impacts of those alterations associated with fractures in panther habitat (e.g., altered plant species composition and density), and c) influence of aquifer fractures in all habitats underlain by fractures.

Recent developments for acquiring and distributing remotely-sensed data have greatly increased data availability to the user community. The past two decades have witnessed an explosion in data acquisition by a variety of ground, airborne and orbital sensors. The popularization of Unmanned Aerial Systems (UAS) and the development of reduced cost orbital platforms should guarantee that even higher data volumes will be available to future analysts. The past decades also saw the opening of image data archives (e.g., Landsat, CBERS, Sentinel), making access to a rich database of moderate resolution satellite images a reality across the globe. This increased volume and variety of remotely-sensed data increases the demand for methods and procedures for data handling and information extraction. This chapter describes recent efforts to expand the analyst’s data processing toolset and includes the theory and strategies used in manipulating remotely-sensed data by digital systems. The text focuses on presenting algorithms and techniques for image processing and analysis and emphasizes recent developments not covered by previous editions of the ASPRS Manual of Remote Sensing. Although the main topics covered by the chapter involve the direct processing of images, the text also covers concepts involved in processing remote sensing data that may not have been collected or stored as images, such as spectral curves acquired by spectroradiometers. Several sections of this chapter match this description, including Spectral Vegetation Indices and Spectral Mixture Analysis. Image processing includes not only the analysis of images, but also the necessary steps involved in preparing images for analysis, such as geometric correction, atmospheric correction and several techniques associated with image enhancement. Spectral indices resulting from the combination of multiple spectral bands are presented, with emphasis on the description of vegetated targets. A detailed treatment is given to the mixture problem resulting from the contribution of multiple materials within the instantaneous field of view (IFOV) of a given sensor. Because multiple applications can benefit from the increased explanation power provided by a large number of spectral bands, hyperspectral data processing is also presented and discussed. Further, the chapter addresses the benefits and challenges involved in combining datasets acquired by different systems (Data Fusion). Image classification addresses multiple strategies involved in assigning classes to images (e.g., Support Vector Machine, and Decision Trees); and includes advances in Object-Based Image Analysis (OBIA), particularly those related to image segmentation in preparation for classification. Given the increasing length of remotely-sensed data time series, particular attention is given to preparing sequences of images and data, including multiple techniques for smoothing, spike removal and the retrieval of metrics associated with temporal variations of targets. The chapter also brings multiple examples of use of products derived from processing remotely-sensed data as input to a variety of workflows, including modeling and analysis efforts. Finally, very current topics involving recent advances in image acquisition and availability, are presented for generating 3D surfaces from multiple images using Structure from Motion (SfM); processing of very large datasets (Big Data); and processing of images in the cloud are presented.

Concerns about food sovereignty in western nations have increased in recent years, as incidents of food-borne pathogens are highlighted in the popular press, and calls for locally-sourced food have increased. Wild food foraging has emerged as a response by some segments of the population under the twin rubrics of food sovereignty and food justice. However, virtually all studies looking at these activities focus outside of the U.S. South and contain little information on African American involvement. We investigate both perceptions and participation in urban foraging by African Americans in Atlanta’s Browns Mill-Lakewood community and smaller sections of adjacent communities, with attention to the role of collective efficacy as a predictor of foraging and foraging as a precursor of collective efficacy. A modified proportionate, census guided, systematic random sampling method was used to administer a door-to-door, household survey in the study area to gather these data. Twenty percent of the nearly all African American sample indicated that they had foraged in their neighborhood in the past five years, but not being aware of wild food locations was the most-cited barrier to participating. Results from ordered, logistic regression models also indicated that women were significantly less likely than men to forage, other factors equal; and those who foraged were more likely to have higher collective efficacy scores. Recommendations are made for increasing awareness of wild food locations in southeast Atlanta communities. This involves partnering with a local foraging non-profit group, Concrete Jungle.

The tornado outbreak of April 2011 in the Southeastern United States caused major damage to property and natural ecosystems. During the outbreak, the Great Smoky Mountains National Park (GRSM) was hit by an EF4 tornado, resulting in a long strip of broken branches and toppled old-growth forest trees. Little is known of the consequences of extreme windthrow events, partly due to limitations in characterizing and monitoring wind-driven vegetation disturbance and recovery over large areas and over time. This work analyzed vegetation damage in the GRSM resulting from the 2011 tornado outbreak and monitored vegetation recovery in the region over a four-year period. Anomalies of the Enhanced Vegetation Index (EVI) calculated using Landsat scenes showed that the 2011 tornado affected 21.38 km2 of forest, including submesic to mesic oak/hardwoods, Southern Appalachian cove hardwood forests and montane alluvial forests. Tornado damage severity was mapped and investigated by using anomalies of EVI over space and time and showed track discontinuity and significant variation in damage intensity along the tornado track, suggesting vortex-topography interactions. Temporal profiles and spatial representations of EVI anomalies for the period 2011-2015 indicated that EVI in 2015 was above pre-event values, indicating homogeneous canopy and lack of vertical structure during regrowth.

Mangroves are critical in the ecological, economic and social development of coastal rural and urban communities. However, they are under threat by climate change and anthropogenic activities. The Sunda Banda Seascape (SBS), Indonesia, is among the world’s richest regions of mangrove biomass and biodiversity. To inform current and future management strategies, it is critical to provide estimates of how mangroves will respond to climate change in this region. Therefore, this paper utilized spatial analysis with model-based climatic indicators (temperature and precipitation) and mangrove distribution maps to estimate a benchmark for the mangrove biomass of the SBS in six scenarios, namely the Last Inter-glacial Period, the current scenario (1950–2000) and all four projected Representative Concentration Pathways in 2070 due to climate change. Despite mangroves gaining more biomass with climate change (the increase in CO2 concentration), this paper highlighted the great proportion of below-ground biomass in mangrove forests. It also showed that the changes in spatial distribution of mangrove biomass became more variable in the context of climate change. As mangroves have been proposed as an essential component of climate change strategies, this study can serve as a baseline for future studies and resource management strategies.

The NASA DEVELOP National Program bridges the gap between NASA Earth Science and society by building capacity in both participants and partner organizations that collaborate to conduct projects. These rapid feasibility projects highlight the capabilities of satellite and aerial Earth observations. Immersion of decision and policy makers in these feasibility projects increases awareness of the capabilities of Earth observations and contributes to the tools and resources available to support enhanced decision making. This paper will present the DEVELOP model, best practices, and two case studies, the Colombia Ecological Forecasting project and the Miami-Dade County Ecological Forecasting project, that showcase the successful adoption of tools and methods for decision making. Through over 90 projects each year, DEVELOP is always striving for the innovative, practical, and beneficial use of NASA Earth science data.

Documentation of the three-dimensional (3D) cultural landscape has traditionally been conducted during site visits using conventional photographs, standard ground surveys and manual measurements. In recent years, there have been rapid developments in technologies that produce highly accurate 3D point clouds, including aerial LiDAR, terrestrial laser scanning, and photogrammetric data reduction from unmanned aerial systems (UAS) images and hand held photographs using Structure from Motion (SfM) methods. These 3D point clouds can be precisely scaled and used to conduct measurements of features even after the site visit has ended. As a consequence, it is becoming increasingly possible to collect non-destructive data for a wide variety of cultural site features, including landscapes, buildings, vegetation, artefacts and gardens. As part of a project for the U.S. National Park Service, a variety of data sets have been collected for the Wormsloe State Historic Site, near Savannah, Georgia, USA. In an effort to demonstrate the utility and versatility of these methods at a range of scales, comparisons of the features mapped with different techniques will be discussed with regards to accuracy, data set completeness, cost and ease-of-use.

With the increased availability of very high-resolution satellite imagery, terrain based imaging and participatory sensing, inexpensive platforms, and advanced information and communication technologies, the application of imagery is now ubiquitous, playing an important role in many aspects of life and work today. As a leading organisation in this field, the International Society for Photogrammetry and Remote Sensing (ISPRS) has been devoted to effectively and efficiently obtaining and utilising information from imagery since its foundation in the year 1910. This paper examines the significant challenges currently facing ISPRS and its communities, such as providing high-quality information, enabling advanced geospatial computing, and supporting collaborative problem solving. The state-of-the-art in ISPRS related research and development is reviewed and the trends and topics for future work are identified. By providing an overarching scientific vision and research agenda, we hope to call on and mobilise all ISPRS scientists, practitioners and other stakeholders to continue improving our understanding and capacity on information from imagery and to deliver advanced geospatial knowledge that enables humankind to better deal with the challenges ahead, posed for example by global change, ubiquitous sensing, and a demand for real-time information generation.

This study explores the empirical relationship between city-level urban forms and CO2 emissions in 104 Chinese prefectural-level cities. Although the analytical focus is on polycentric urba...

Feral Hogs (Sus scrofa) are an invasive species that have occupied the Great Smoky Mountains National Park since the early 1900s. Recent studies on vegetation, mast, and harvest history were important for our work. Using these data, a model with discrete time and space was formulated to represent the feral hog dynamics in the Park. Management strategies and key characteristics of the population were investigated. The model uses observed mast variation to help govern population dynamics and results indicate that Park control efforts have limited the growth of the population.

Cognitive mechanisms underlying the choice of movement patterns between resource sites for nonhuman primates are not well understood. Specifically, the influence of landscape features on decision making and spatial memory of naturally ranging animals has not been explicitly investigated. We evaluated three models of bearded capuchin monkey, Sapajus libidinosus, movement decisions that incorporated varying degrees of landscape and memory influences, and we conducted a field experiment using a novel call-back technique to test these influences. The movements and spatial decisions of the monkeys were modelled between temporal stop points and spatial change points during natural travel using straight-line path, a minimum-resistance path and landscape-perceiving path models. For these movement models, resistance was calculated as the inverse of habitat suitability, a surface based on the natural movement patterns of the study group. Of the three models, natural travel most closely resembled the straight-line path model in its landscape resistance, but not in its geometry. This result indicates that while the monkeys travel in zones of low resistance, they do not minimize distance or landscape resistance between travel nodes. When monkeys were called to an artificial resource site using the call-back experiment, their travel was more linear and higher in landscape resistance. The limited quantity and high quality of the food resource in the artificial resource sites may have influenced the nature of the monkeys' travel in these experiments. We present the advantages and challenges of the call-back method of experimental analysis of animal movement and we conclude that future analyses of spatial cognition should include consideration of landscape context.

Coal fires that are induced by natural spontaneous combustion or result from human activities occurring on the surface and in underground coal seams destroy coal resources and cause serious environmental degradation. Thermal infrared image data, which directly measure surface temperature, can be an important tool to map coal fires over large areas. As the first of two parts introducing our coal fire detection method, this paper proposes a self-adaptive threshold-based approach for coal fire detection using ASTER thermal infrared data: the self-adaptive gradient-based thresholding method (SAGBT). This method is based on an assumption that the attenuation of temperature along the coal fire’s boundaries generates considerable numbers of spots with extremely high gradient values. The SAGBT method applied mathematical morphology thinning to skeletonize the potential high gradient buffers into the extremely high gradient lines, which provides a self-adaptive mechanism to generate thresholds according to the thermal spatial patterns of the images. The final threshold was defined as an average temperature value reading from the high temperature buffers (segmented by 1.0 σ from the mean) and along a sequence of extremely high gradient lines (thinned from the potential high gradient buffers and segmented within the lower bounds, ranging from 0.5 σ to 1.5 σ and with an upper bound of 3.2 σ, where σ is the standard deviation), marking the coal fire areas. The SAGBT method used the basic outer boundary of the coal-bearing strata to simply exclude false alarms. The intermediate thresholds reduced the coupling with the temperature and converged by changing the potential high gradient buffers. This simple approach can be economical and accurate in identifying coal fire areas. In addition, it allows for the identification of thresholds using multiple ASTER TIR scenes in a consistent and uniform manner, and supports long-term coal fire change analyses using historical images in local areas. This paper focuses on the introduction of the methodology. Furthermore, an improvement to SAGBT is proposed. In a subsequent paper, subtitled “Part 2, Validation and Sensitivity Analysis,” we address satellite-field simultaneous observations and report comparisons between the retrieved thermal anomalies and field measurements in different aspects to prove that the coal fires are separable by the SAGBT method. These comparisons allowed us to estimate the accuracy and biases of the SAGBT method. As an application of the SAGBT, a relationship between coal fires’ decadal variation and coal production was also examined. Our work documented a total area increase in the beginning of 2003, which correlates with increased mining activities and the rapid increase of energy consumption in China during the decade (2001–2011). Additionally, a decrease in the total coal fire area is consistent with the nationally sponsored fire suppression efforts during 2007–2008. It demonstrated the applicability of SAGBT method for long-term change detection with multi-temporal images.

This paper describes a method for predicting the locations and heights of the ten tallest trees in the Tennessee portion of the Great Smoky Mountains National Park. Iterative computation tools were utilized to process the data along with the lidarderived bare earth digital elevation models and digital surface models to create canopy height models for the Tennessee portion of the park. A height threshold of 51.8 meters was chosen as the minimum value for a tree of extraordinary height. Ten potential sites containing tall trees were identified using this methodology, and seven of the top ten ranking trees’ heights were field measured using accepted forestry methodology. The trees detected using these methods are potentially the tallest trees ever measured on the East Coast of the United States. These methods show that unique tall trees can be successfully detected in a large, heterogeneous forest area using lidar data.

Alpine, subalpine and boreal tree species, of low genetic diversity and adapted to low optimal temperatures, are vulnerable to the warming effects of global climate change. The accurate prediction of these species’ distributions in response to climate change is critical for effective planning and management. The goal of this research is to predict climate change effects on the distribution of red spruce (Picea rubens Sarg.) in the Great Smoky Mountains National Park (GSMNP), eastern USA. Climate change is, however, conflated with other environmental factors, making its assessment a complex systems problem in which indirect effects are significant in causality. Predictions were made by linking a tree growth simulation model, red spruce growth model (ARIM.SIM), to a GIS spatial model, red spruce habitat model (ARIM.HAB). ARIM.SIM quantifies direct and indirect interactions between red spruce and its growth factors, revealing the latter to be dominant. ARIM.HAB spatially distributes the ARIM.SIM simulations under the assumption that greater growth reflects higher probabilities of presence. ARIM.HAB predicts the future habitat suitability of red spruce based on growth predictions of ARIM.SIM under climate change and three air pollution scenarios: 10% increase, no change and 10% decrease. Results show that suitable habitats shrink most when air pollution increases. Higher temperatures cause losses of most low-elevation habitats. Increased precipitation and air pollution produce acid rain, which causes loss of both low- and high-elevation habitats. The general prediction is that climate change will cause contraction of red spruce habitats at both lower and higher elevations in GSMNP, and the effects will be exacerbated by increased air pollution. These predictions provide valuable information for understanding potential impacts of global climate change on the spatiotemporal distribution of red spruce habitats in GSMNP.

The expansion of feral hog (Sus scrofa) populations in the United States has resulted in increased efforts to develop and implement control strategies designed to minimize the impacts done by this invasive species. We describe an individual-based model for feral hogs in Great Smoky Mountains National Park (GSMNP). The objectives of the model are to provide an understanding of the population dynamics of this feral hog population and to determine the efficacy of the annual harvest as a population control method. Results suggest that the dynamics of the population are driven by fall hard mast production and the GSMNP harvests currently limit growth of the population, but these control efforts have not reduced the population.

Red spruce ( Picea rubens Sargent) has exhibited widespread growth decline and high mortality for the last half century in the eastern United States. Good prediction of this species’ distribution in relation to environmental conditions is critical for effective management. This study projects red spruce distribution in response to multiple causal mechanisms in the Great Smoky Mountains National Park (GSMNP) of the Southern Appalachian Mountains by coupling a temporal simulation model of tree growth (ARIM.SIM) to a species distribution model (ARIM.HAB). ARIM.HAB computed habitat suitability, estimated from ARIM.SIM-generated red spruce growth, for every spatial 30 m grid cell in GSMNP. ARIM.SIM showed that different factors were responsible for habitat suitability and growth at higher vs. lower elevations. The air pollution variables (acid rain and cloud immersion frequency) caused low habitat suitability at higher elevations (1800–2028 m). Reduced air pollution but greater stress from climatic variables (high temperatures, reduced precipitation) caused medium suitability at lower elevations (1400–1600 m). And less stress from air pollution and climate variables combined with ample water to produce highest suitability at intermediate elevations (1600–1800 m). The projected range was verified with an existing geospatial database for red spruce and showed excellent correspondence with present-day distribution (AUC = 0.99, kappa = 0.87 and TSS = 0.88). This research shows that species distribution models coupled with a process-based temporal simulation models can improve the precision and accuracy of, respectively, habitat suitability and range projections for species at local scales.

Lung cancer is the second most commonly diagnosed cancer in both men and women in Georgia, USA. However, the spatio-temporal patterns of lung cancer risk in Georgia have not been fully studied. Hierarchical Bayesian models are used here to explore the spatio-temporal patterns of lung cancer incidence risk by race and gender in Georgia for the period of 2000–2007. With the census tract level as the spatial scale and the 2-year period aggregation as the temporal scale, we compare a total of seven Bayesian spatio-temporal models including two under a separate modeling framework and five under a joint modeling framework. One joint model outperforms others based on the deviance information criterion. Results show that the northwest region of Georgia has consistently high lung cancer incidence risk for all population groups during the study period. In addition, there are inverse relationships between the socioeconomic status and the lung cancer incidence risk among all Georgian population groups, and the relationships in males are stronger than those in females. By mapping more reliable variations in lung cancer incidence risk at a relatively fine spatio-temporal scale for different Georgian population groups, our study aims to better support healthcare performance assessment, etiological hypothesis generation, and health policy making.

Intersection relations are important topological considerations in database update processes. The differentiation and identification of non-empty intersection relations between new updates and existing objects is one of the first steps in the automatic incremental update process for a land parcel database. The basic non-empty intersection relations are meet, overlap, cover, equal and inside, but these basic relationships cannot reflect the complex and detailed non-empty relations between a new update and the existing objects. It is therefore necessary to refine the basic non-empty topological relations to support and trigger the relevant update operations. Such relations have been refined by several researchers using topological invariants e.g., dimension, type and sequence to represent the intersection components. However, the intersection components often include only points and lines, and the refined types of 2-dimensional intersection components that occur between land parcels have not been defined. This study examines the refinement of non-empty relations among 2-dimensional land parcels and proposes a computation model. In this model, an entire spatial object is directly used as the operand, and two set operations i.e., intersection ∩ and difference \ are applied to form the basic topological computation model. The Euler number is introduced to refine the relations with a single 2-dimensional intersection i.e., cover, inside and overlap and to distinguish the refined types of 2-dimensional intersection components for the relations with multiple intersections. In this study, the cover and overlap relations with single intersections between regions are refined into seven cases, and nine basic types of 2-dimensional intersection components are distinguished. A composite computation model is formed with both Euler number values and dimensional differences. In this model, the topological relations with single intersections are differentiated by the value of the dimension and the Euler number of the resulting set of the whole-object intersection and differences, whereas the relations with multiple intersections are discriminated by the value of the resulting set at a coarse level and are further differentiated by the type and sequence of the whole-object intersection component in a hierarchical manner. Based on the refined topological relations, an improved method for automatic and incremental updating of the land parcel database is presented. The effectiveness of the models and algorithms was verified by the incremental update of a land cover database. The results of this study represent a new avenue for automatic spatial data handling in incremental update processes.

Worldwide, Salmonella spp. is a significant cause of disease for both humans and wildlife, with wild birds adapted to urban environments having different opportunities for pathogen exposure, infection, and transmission compared to their natural conspecifics. Food provisioning by people may influence these factors, especially when high-density mixed species flocks aggregate. White Ibises (Eudocimus albus), an iconic Everglades species in decline in Florida, are becoming increasingly common in urbanized areas of south Florida where most are hand-fed. We examined the prevalence of Salmonella shedding by ibises to determine the role of landscape characteristics where ibis forage and their behavior, on shedding rates. We also compared Salmonella isolated from ibises to human isolates to better understand non-foodborne human salmonellosis. From 2010-2013, 13% (n = 261) adult/subadult ibises and 35% (n = 72) nestlings sampled were shedding Salmonella. The prevalence of Salmonella shedding by ibises significantly decreased as the percent of Palustrine emergent wetlands and herbaceous grasslands increased, and increased as the proportion of open-developed land types (e.g. parks, lawns, golf courses) increased, suggesting that natural ecosystem land cover types supported birds with a lower prevalence of infection. A high diversity of Salmonella serotypes (n = 24) and strain types (43 PFGE types) were shed by ibises, of which 33% of the serotypes ranked in the top 20 of high significance for people in the years of the study. Importantly, 44% of the Salmonella Pulsed-Field Gel Electrophoresis patterns for ibis isolates (n = 43) matched profiles in the CDC PulseNet USA database. Of these, 20% came from Florida in the same three years we sampled ibis. Importantly, there was a negative relationship between the amount of Palustrine emergent wetland and the number of Salmonella isolates from ibises that matched human cases in the PulseNet database (p = 0.056). Together, our results indicate that ibises are good indicators of salmonellae strains circulating in their environment and they have both the potential and opportunity to transmit salmonellae to people. Finally, they may act as salmonellae carriers to natural environments where other more highly-susceptible groups (nestlings) may be detrimentally affected.

Coastal plains with a unique geographic setting and renewable natural resources are promising for sustainable development; however, these areas may be subjected to some environmental hazards due to their geological setting. One of those hazards is the seasonal flash flood that can threaten existing and future development projects in such critical areas. Southwestern Sinai, Egypt, is a coastal plain that is characterized by complex geological setting an arid climate with seasonal rainfall which can result in a high runoff. The aim of this work is to model spatially the runoff amount and density related to flash flood development and to create a flash flood hazard map of the plain as an example of coastal plain in a desert environment with large and complex hydrologic setting. In this research, ASTER images are used to develop a digital elevation model (DEM) and land use/land cover (LULC) data sets of the study area. Geographic information system (GIS) was used to perform runoff and ash potential flood analyses of the created databases and to show distributed runoff and flooding potential in spatial maps. A module was created in a GIS environment to develop a flash flood potential index map. It was clear that the main two factors controlling runoff amounts and flash flood potential in such kinds of areas are the slope and soil types. The final dataset map procedure by this work can be very helpful in land use planning by highlighting the areas subjected to flash floods. Análisis Geoespacial para Determinar las Características Hidromorfológicas y Evaluar las Inundaciones Potenciales en Llanuras Costeras Áridas: Caso de Estudio en el Suroccidente de Sinaí, Egipto ResumenLas llanuras costeras que poseen recursos naturales renovables y una configuración geográfíca única son promisorias para el desarrollo sostenible. Estas áreas, sin embargo, son objeto de algunas amenazas ambientales debido a su escenario geológico. Una de estas amenazas es la temporada de inundaciones rápidas que pueden poner en riesgo los proyectos de desarrollo existentes y los futuros en estas zonas críticas. El suroccidente de Sinaí, Egipto, es una llanura costera que se caracteriza por su compleja configuración geológica de clima árido, con temporadas de lluvia que pueden resultar en una gran escorrentía. El objetivo de este trabajo fue modelar espacialmente la cantidad y densidad de escorrentía relacionada al desarrollo de inundaciones rápidas y elaborar un mapa de amenazas de inundación rápida en este valle, como un ejemplo de llanura costera en un ambiente desértico con un escenario hidrológico grande y complejo. En este trabajo se utilizaron imágenes ASTER para desarrollar un Modelo de Elevación Digital (DEM, en inglés) y establecer la información de uso del suelo/cobertura del suelo (LULC, en inglés) en el área de estudio. A partir del Sistema de Información Geográfica (GIS) se analizaron la escorrentía y el potencial de inundación de las bases de datos creadas, y se mostró la escorrentía y el potencial de inundación en mapas espaciales. Se creó un módulo en un ambiente del GIS para desarrollar un mapa del índice inundación rápida potencial. Se estableció que los dos factores que controlan la cantidad de escorrentía y el potencial de inundaciones rápidas en estas áreas son la inclinación y los tipos de suelo. El mapa final de procemiento con el conjunto de datos de este trabajo es de gran ayuda en la planeación del uso de suelos, ya que evidencia las áreas con posibilidad de inundaciones rápidas.