Geographic Information System-based Analysis Research Articles

Land use-land cover dynamics, and local perceptions of change drivers among Nyangatom agro-pastoralists, Southwest Ethiopia

Understanding the spatio-temporal dynamics of land use and land cover (LULC) and their drivers is instrumental in synthesizing knowledge for informed natural resource management, planning, and associated decisions. The objective of this study was to analyze LULC dynamics and their drivers in the Nyangatom district of southwest Ethiopia. This study adopted a mixed-method approach, comprising remote sensing and geographic information system-based analysis, focus-group discussions, key informant interviews, and structured interviews covering 384 agro-pastoral households. Land use and land cover maps were compiled with Landsat image data from 1992, 1999, 2010, and 2020 using supervised pixel-based classification with a maximum likelihood algorithm. The study revealed that grassland (33%) and shrub land (27%) are the dominant LULC classes in the study periods. The results show a significant increase in settlement, cropland, and bare land, between 1992 and 2020 following demand for fertile lands, overgrazing, and climate changes. Reductions in the water body, open woodland, riverine forest, and dense woodland of − 23%, − 18%, − 18%, and − 7%, respectively, were observed for the same period with an overall accuracy of 80%. Agro-pastoralists identified agricultural expansion, overgrazing, and drought as the main drivers of LULC changes, followed by conflicts, invasion of alien plant species, and change in policy institutions. The impacts of unplanned LULC change can be reduced through appropriate land-use planning with genuine stakeholder engagement. Updated information on present and future LULC dynamics can support these social dynamics and align a shared understanding among stakeholders that replaces polarization and erosion of mutual trust.

Geographic Information System-Based Analysis of Fish Diversity Trends of River Meenachil, Southern Western Ghats, Kerala.

In this study, the fish fauna of different geographical zones of Meenachil River was investigated using the spatial interpolation techniques of the Geographical Information System. The variations in fish diversity trends during the pre-monsoon, monsoon, and post-monsoon seasons from 2016 to 2020 along the longitudinal gradient of the Meenachil River were determined using the Kriging interpolation method and semivariograms. Sixty-seven fish species belonging to 15 orders, 29 families, and 46 genera were recorded from the river during the study period. Twenty-five were endemic to the Western Ghats, three were exclusive to Kerala, five were nearly threatened, and three were vulnerable. The midstream of the river recorded maximum diversity indices ranging from (H’) 2.608 to 3.171, reflecting the outcome of local river conservation efforts, and the downstream station with the lowest range (H’) 2.305 -2.643. Cluster analysis showed the spatial similarities in fish diversities between sampling stations. Deterioration in water quality downstream was reflected in the fluctuating levels of TDS (ppm) (21.300±116.828 to 365.000±116.828), Conductivity(µSmcm-1) (42.500±252.372 to 815.000±252.372), Salinity(ppt) (0.100±0.083 to 0.400±0.083) and dissolved oxygen levels(mgL-1) (2.900±0.876 to 5.600±0.876). The study highlights the necessity to broaden local conservation efforts and implement legal measures to protect the habitats and the native fish fauna of the tourism-dominated lower stretches of the Meenachil River. By integrating data in spatial maps, the geographic component added by GIS gives a clearer insight into the various data and efficiently supports global conservation measures, enhancing biodiversity protection.

Analisis Penyebaran dan Radius Jangkauan Fasilitas Kesehatan di Kabupaten Way Kanan Berbasis Sistem Informasi Geografis

Geospatial Information System (GIS) is a system that can be used to assist in making decisions based on the spatial analysis performed. GIS can be used in various disciplines according to its purpose. One of the functions of GIS is to determine the distribution and radius of coverage of public facilities in an area. An increase in the population in an area will affect the use and need for available public facilities. One type of public facility that is urgently needed is a health facility. Way Kanan Regency is one of the areas experiencing an increase in population. Increasing the population in an area must be supported by the construction of adequate and equitable health facilities in each region. Based on this description, a geographic information system-based analysis is needed to determine the distribution of health facilities and their radius of coverage to the pattern of population settlements in Way Kanan Regency. The method used in this research is spatial analysis with the buffer method. Based on the results of the analysis, it was found that the distribution of health facilities in Way Kanan Regency was not evenly distributed and there were several sub-districts that had not been reached by health facilities. This is evidenced by several sub-districts in Way Kanan Regency which are outside the radius of the service coverage of health facilities. The suggestion in this study is to increase the number of health facilities, taking into account the existing settlement patterns.

Spatiotemporal Analysis of Highway Traffic Patterns in Hurricane Irma Evacuation

The State of Florida is significantly vulnerable to catastrophic hurricanes that cause widespread infrastructural damage and claim lives annually. In 2017, Hurricane Irma, a Category 4 hurricane, took on the entirety of Florida, causing the state’s largest evacuation ever as 7 million residents fled the hurricane. Floridians fleeing the hurricane faced the unique challenge of where to go, since Irma made an unusual landfall from the south, enveloping the entire state, forcing evacuees to drive farther north, and creating traffic jams along Florida’s evacuation routes that were worse than during any other hurricane in Florida's history. This study aimed to assess the spatiotemporal traffic impacts of Irma on Florida’s major highways based on real-time traffic data before, during, and after the hurricane made landfall. First, we conducted a time-series-based analysis to evaluate the temporal evacuation patterns of this large-scale evacuation. Second, we developed a metric, namely the congestion index (CI), to assess the spatiotemporal evacuation patterns on I-95, I-75, I-10, I-4, and turnpike (SR-91) highways with a focus on both evacuation and returning traffic. Third, we employed a geographic information system-based analysis to visually illustrate the CI values of corresponding highway sections with respect to different dates and times. Findings clearly showed that imperfect forecasts and the uncertainty surrounding Irma’s predicted path resulted in high levels of congestion and severe delays on Florida’s major evacuation routes.

Geographic information system-based analysis of COVID-19 cases in India during pre-lockdown, lockdown, and unlock phases

ObjectiveThe World Health Organization formally announced the global COVID-19 pandemic on March 11, 2020 due to widespread infections. In this study, COVID-19 cases in India were critically analyzed during the pre-lockdown (PLD), lockdown (LD), and unlock (UL) phases. MethodAnalyses were conducted using geospatial technology at district, state, and country levels, and comparisons were also made with other countries throughout the world that had the highest infection rates. India had the third highest infection rate in the world after the USA and Brazil during UL2.0–UL3.0 phases, the second highest after the USA during UL4.0–UL5.0 phases, and the highest among South Asian Association for Regional Cooperation (SAARC) countries in PLD–UL5.0 period. ResultsThe trend in the number of COVID-19 cases was associated with the population density where higher numbers tended to be record in the eastern, southern, and west–central parts of India. The death rate in India throughout the pandemic period under study was lower than the global average. Kerala reported the maximum number of infections during PLD whereas Maharashtra had the highest numbers during all LD and UL phases. Eighty percent of the cases in India were concentrated mainly in highly populous districts. ConclusionThe top 25 districts accounted for 70.99%, 69.38%, 54.87%, 44.23%, 40.48%, and 38.96% of the infections from the start of UL1.0 until the end of UL phases, respectively, and the top 26–50 districts accounted for 6.38%, 6.76%, 11.23%, 12.98%, 13.40%, and 13.61% of cases in these phase, thereby indicating that COVID-19 cases spread during the UL period. By October 31, 2020, Delhi had the highest number of infections, followed by Bengaluru Urban, Pune, Mumbai, Thane, and Chennai. No decline in the infection rate occurred, even in UL5.0, thereby indicating a highly alarming situation in India.

Mapping Potential Habitat and Range-Wide Surveying for the Texas Kangaroo Rat

Abstract The Texas kangaroo rat Dipodomys elator is considered a species of conservation concern by state and federal agencies. There have been a limited number of sightings in only seven counties in northern Texas during the past 30 y. The apparent decline of the species has been attributed to habitat loss due to increasing conversion of natural areas into cropland. The magnitude and exact cause of the decline are difficult to determine because of insufficient data on the distribution of the species and its habitat within its relatively small geographic range. Habitat studies have focused on the microhabitat of burrows rather than a coarser-scale identification of habitat and its distribution within the species' historic range. Multiple species of Dipodomys have demonstrated strong associations with certain soil and land-cover types. Therefore our goal was to develop a range-wide map of potential habitat on the basis of the association of D. elator with specific soil and land-cover types. We used the map to guide roadside surveys and also updated the map with information on D. elator distribution obtained during the surveys. Over the course of two summers (2016 and 2017) we documented D. elator at 138 separate point locations in five counties. A geographic information system-based analysis of soil and land-cover data revealed that the species is associated with clay-loam and loam soils and mixed-grass/shortgrass prairie. We also found an unexpected association with cropland, although we do not know the exact extent to which D. elator actually uses cropland. The surveys provide an updated assessment of the species distribution and the maps of potential habitat indicate areas where the species may still exist.

Anticipating Environmental and Environmental-Health Implications of Extreme Storms: ARkStorm Scenario

AbstractThe ARkStorm Scenario predicts that a prolonged winter storm event across California would cause extreme precipitation, flooding, winds, physical damages, and economic impacts. This study uses a literature review and geographic information system-based analysis of national and state databases to infer how and where ARkStorm could cause environmental damages, release contamination from diverse natural and anthropogenic sources, affect ecosystem and human health, and cause economic impacts from environmental-remediation, liability, and health-care costs. Examples of plausible ARkStorm environmental and health concerns include complex mixtures of contaminants such as petroleum, mercury, asbestos, persistent organic pollutants, molds, and pathogens; adverse physical and contamination impacts on riverine and coastal marine ecosystems; and increased incidences of mold-related health concerns, some vector-borne diseases, and valley fever. Coastal cities, the San Francisco Bay area, the Sacramento-San Joa...

GEOGRAPHIC AND ECOLOGICAL AMPLITUDE IN THE NECTARIVOROUS BAT ANOURA FISTULATA (PYHLLOSTOMIDAE: GLOSSOPHAGINAE)

The wide range of feeding habits among phyllostomid bats has resulted in the selection of unique and contrasting morphological attributes. It has been suggested that nectarivorous bat species co-evolve with the plants they use as primary source of food, and changes in morphology and behavior in the bat, are in some way directed by changes in morphology and phenological cycles of the plants. The nectarivorous bat Anoura fistulata (Pyhllostomidae: Glossophaginae) has the longest tongue in proportion to body size among mammals; feature that apparently allows the species to take nectar from flowers with long corollas, some of them typical of highland ecosystems. In spite of this unique morphological adaptation, little is known on the ecological requirements of the species. Herein, Geographic Information System-based analyses and niche modeling techniques were applied to investigate the geographic and ecological niche breath of A. fistulata. We also introduce the first Bolivian record of the species collected at Hernando Siles, Department of Chuquisaca (20°10’0.0’’ S, 64°15’0.00’’ W, at 1,524 m), which represents a remarkable extension in the distribution of the species of more than 7°. Our analyses revealed that A. fistulata occurs in contrasting ecosystems, from Andean montane and pre-montane moist forest in Western Ecuador and Central Colombia, up to arid and semiarid environments in southern Colombia and Bolivia. Anoura fistulata occurs across a wide elevational range between 1,175 and 2,510 m, which is well represented along the geologic unit of the Batholith of Ecuador. A constriction of this elevational belt along the Peruvian Punas and Yungas was suggested as a natural barrier for the establishment of A. fistulata. The Peruvian Punas and Yungas isolate A. fistulata of Bolivia from records in the northern range of the distribution of the species.

The Levelized Cost of Energy (LCOE) of wave energy using GIS based analysis: The case study of Portugal

Abstract The main objective of this paper is to establish an economic modelling of wave energy through a Geographical Information System (GIS). Furthermore, this method has been tested for the particular case of the Portuguese coast. It determines the best sea areas to install wave energy converters in this region, using spatial analysis of the Levelized Cost of Energy (LCOE). Several economic parameters, as capital or O&M costs, have been considered. In addition, a sensitivity analysis has been performed by varying the discount rate in three different scenarios. Several types of physical restrictions have been taken into account: bathymetry, submarine electrical cables, seabed geology, environmental conditions, protected areas in terms of heritage, navigation areas, seismic fault lines, etc. Spatial operations have been carried out to complete the procedure, using Model Builder of GIS software. Results indicate the most suitable areas in economic terms in Portugal to install wave energy devices.

A comparative study of landslide susceptibility mapping using landslide susceptibility index and artificial neural networks in the Krios River and Krathis River catchments (northern Peloponnesus, Greece)

The main scope of this study is to compare the performance of a conventional statistical method like the landslide susceptibility index (LSI) and a soft computing method like artificial neural networks (ANNs). These models were applied in order to realistically map landslide susceptibility (LS) in the Krathis and Krios drainage basins in northern Peloponnesus. The relationship between landslides and various conditioning factors contributing to their occurrence was investigated through geographic information system-based analysis. A landslide inventory was realised using aerial-photos, satellite images and field surveys. Eight conditioning factors, including land cover, geology, elevation, slope, aspect, distance to road network, distance to drainage network, distance to structural elements, were considered. Subsequently, LS maps were produced using LSI and ANNs, and they were then compared and validated accordingly. Model performance was checked by an independent validation set of landslide events. For the validation process, the receiver operating curve was drawn and the area-under-the-curve (AUC) values were calculated. The calculated AUC values were 0.852 for the LSI model, and 0.842 for the ANNs; thus, both methods seem to lead to quite similar results. Based on these results, with an average percentage of correctly predicting landslides of about 84 %, model validation confirms that extrapolation results are very good, and that both models can be used to mitigate hazards related to landslides, and to aid in generalised land-use planning assessment purposes.

A geographic information system-based analysis of ambulance station coverage area in Samsun, Turkey

The location of ambulance stations are of great importance, as location is a determining factor of whether ambulances are able to respond to emergency calls within the critical period. The aim of the present study was to determine whether the ambulance stations in the provincial centre of Samsun, Turkey, were able to cover their entire operational area within 10 mins of receiving an emergency call. This study was based on emergency calls received by the emergency medical services of the study area. Detailed address data from the calls was used to produce thematic maps using the geographic information system (GIS). Buffer analysis was used to determine the adequacy of the stations' locations in relation to the time taken to respond to the emergency calls. In the study area, there were a total of 11,506 emergency ambulance calls made in 2009, which revealed a call density of 0.7 calls per ha and 23.8 calls per 1,000 population. A total of 75.8% of the calls were made due to medical reasons, while 11.6% were related to traffic accidents. The GIS-based investigation revealed that the 10-min coverage areas for the four ambulance stations in the provincial centre of Samsun served 76.9% of the area and 97.9% of its population. Of the 10,380 calls for which detailed address data were available, 99.2% were within the stations' 10-min coverage areas. According to the buffer analysis, the ambulance stations in the provincial centre of Samsun are able to reach 97.9% of the population within the critical 10-min response time. This study demonstrates that GIS is an indispensable tool for processing and analysing spatial data, which can in turn aid decision-making in the field of geographical epidemiology and public health.

Distinct Niche Divergence Characterizes the Homoploid Hybrid Speciation ofPinus densataon the Tibetan Plateau

Ecological divergence and selection for novel adaptations to new habitats have been theoretically proposed to play important roles in promoting homoploid hybrid speciation (HHS). The successful establishment of Pinus densata on the Tibetan Plateau is one of the few known examples of HHS. In this study, we carried out extensive field expeditions to obtain representative coverage of occurrence sites of P. densata and its two putative parents. We then applied a series of geographic information system-based analyses to define the patterns of environmental variation within and among the three pine species, to remove potentially confounding effects of spatial autocorrelation in the environmental data due to allopatric ranges, and to build species distribution models. All results consistently indicated that the ecological preferences of P. densata and its parental species have diverged, and they identified candidate ecological factors associated with habitat-specific adaptation. Projections from niche modeling indicated that P. densata could extend across a vast range along the parallel valley systems of the southeastern Tibetan Plateau. Our findings provide evidence of a distinct niche shift in P. densata and support the hypothesis that local adaptation and geographic isolation help maintain and reinforce between-species differences and reproductive isolation in the species complex.

A geographical information system-based analysis of cancer mortality and population exposure to coal mining activities in West Virginia, United States of America

Cancer incidence and mortality rates are high in West Virginia compared to the rest of the United States of America. Previous research has suggested that exposure to activities of the coal mining industry may contribute to elevated cancer mortality, although exposure measures have been limited. This study tests alternative specifications of exposure to mining activity to determine whether a measure based on location of mines, processing plants, coal slurry impoundments and underground slurry injection sites relative to population levels is superior to a previously-reported measure of exposure based on tons mined at the county level, in the prediction of age-adjusted cancer mortality rates. To this end, we utilize two geographical information system (GIS) techniques--exploratory spatial data analysis and inverse distance mapping--to construct new statistical analyses. Total, respiratory and "other" age-adjusted cancer mortality rates in West Virginia were found to be more highly associated with the GIS-exposure measure than the tonnage measure, before and after statistical control for smoking rates. The superior performance of the GIS measure, based on where people in the state live relative to mining activity, suggests that activities of the industry contribute to cancer mortality. Further confirmation of observed phenomena is necessary with person-level studies, but the results add to the body of evidence that coal mining poses environmental risks to population health in West Virginia.

A typology of stand structure and dynamics of Quaking aspen in northwestern Colorado

The regeneration of Quaking aspen ( Populus tremuloides) in the western U.S. in some habitats occurs after severe fire which removes competing conifers and also triggers root suckering of aspen. Consequently, fire exclusion during the 20th century, sometimes in combination with elk browsing, has often been argued to have resulted in a decline in the extent of aspen relative to its pre-20th century extent. However, aspen regeneration is not always dependent on fire and many stands have structures indicative of aspen persistence even in the absence of fire. Thus, to investigate regeneration dynamics of both persistent and seral aspen stands, we reconstructed patterns of stand development in 26 aspen stands in northwestern Colorado. Seral and persistent aspen stands were initially selected based on geographic information system-based analysis of historic vegetation and fire occurrence. Stand-level age structures were determined from 1919 increment cores and size structures from counts and diameters of all juvenile, subcanopy and canopy trees in 40 m × 40 m plots. Stand structures were interpreted to determine modes of tree regeneration and patterns of stand development. As expected, in the eight seral stands aspen regeneration generally depended on coarse-scale, severe disturbance by fire. However, most aspen stands in this study showed signs of aspen self-replacement despite presence of conifers. In the 16 persistent aspen stands showing no conifer invasion, aspen are able to regenerate through a variety of regeneration modes that did not appear to require severe disturbance. Over 70% of the persistent aspen stands sampled did not require coarse-scale disturbance to regenerate. Two (11%) of the persistent stands regenerated continuously through time, and 11 (61%) had aspen cohorts that appeared to develop episodically without being triggered by severe fire or other severe disturbance. In the persistent stands sampled in our study, episodic regeneration not dependent on severe fire is the main mode of stand re-initiation. At many sites in northwestern Colorado aspen regeneration occurs episodically and fits a general stand development model of cohort senescence. According to this model, many of the currently “decadent” or deteriorating aspen stands in western Colorado may be replaced by regenerating stands as the senescent stages experience high levels of canopy tree mortality, thus assuring aspen persistence in the future.

The area of potential shallow-water tropical and subtropical coral ecosystems in the United States

Geographic information system-based analysis was used to derive comprehensive, consistent estimates of the potential area of broadly defined, shallow-water, tropical and subtropical coral ecosystems within the territorial sea and exclusive economic zone of the United States. A coral ecosystem is composed of habitats including unconsolidated sediment, mangrove, hermatypic coral, colonized hardbottom, and submerged vegetation, and major structural zones like reef crest, lagoon, and fore reef. This broad definition reflects the importance of both reef and non-reef habitats and structural zones in the function of these ecosystems. Nautical charts, published by the National Oceanic and Atmospheric Administration’s Office of the Coast Survey, provide a consistent source of 10-fathom (∼18 m) and 100-fathom (∼183 m) depth curve information. The 10-fathom or 100-fathom depth curves are used as surrogates for the potential distribution and extent of shallow-water coral ecosystems in tropical and subtropical U.S. waters. An estimated 36,813 sq·km area has been identified where coral ecosystems can potentially be found in waters less than 10 fathoms (18 m) deep. In addition, an estimated 143,059 sq·km area has been identified where coral ecosystems potentially can be found in U.S. waters at depths down to 100 fathoms (183 m). Results also indicate that previous studies underestimated the extent of potential coral ecosystems for some locations in U.S. tropical and subtropical waters by as much as 100% and that the regional distribution of coral ecosystems has been incorrectly reported.

Commute Rates on Urban Trails: Indicators from the 2000 Census

During the past 10 years the U.S. Department of Transportation has spent $3.9 billion on bicycle and pedestrian facilities through the Transportation Enhancements Program. These funds have been distributed to 11,456 projects. Of these funds $2.53 billion has been spent on off-road trails, for 6,537 projects. Many of these projects have been built, and the question of the degree to which these trails are being used for transportation can be asked. The term "transportation trip" means that a person riding a bicycle on a trail is headed for a destination, such as work, shopping, or school. To explore the question, a geographic information system-based analysis using the block-group level of journey-to-work data from the 2000 census was performed on 13 trails in urban areas. The research explores the overall bike-to-work rate for households in the county in which the trail is located and compares that rate with that of the subset of households that are within 0.5 mi of the trail. The hypothesis that households closer to the trail would have a greater bike-to-work rate is supported by the data in 9 of the 13 analyzed trails. For those 9 trails, households within 0.5 mi of the trail show an average bike-to-work rate of 1.55% as compared with the average of the whole county of 0.52% and a national average of 0.4%. Additionally, fully 25% of bike commuters in those counties live within 0.5 mi of the trail. Factors that influence bicycle commute rates on trails are also reviewed.