Mapping Agricultural Change in Eastern Africa: A Geographic Information Systems (GIS) Approach to Early Imperial Sources, 1857–76

Recent studies have shown that mercury (Hg) levels in many fish from remote lakes exceed the recommended guidelines for human consumption. Most of these studies conclude that the source of contamination lies in the atmosphere. Kejimkujik National Park (KNP), Nova Scotia, Canada, is considered to be a pristine ecosystem in which fish and loon Hg levels are anomalously high. Studies in the park have shown that atmospheric Hg concentrations may not be high enough to account for the Hg levels in the biota, indicating that the park may be an unusual system in terms of Hg distribution and migration. In an attempt to summarise and synthesise the numerous Hg data sets which have been produced in the park over the last 5–10 years, a geographic information systems (GIS) approach was used to create a common database using the watersheds in the park as the common parameter. By using a GIS database, new relationships and correlations are established and the spatial distribution of Hg levels is more readily evaluated and quantified. The results indicate that geological sources of Hg, arising from biotite-rich granite rocks, may play a larger role in the contamination of the park than previously thought.

The productive waters of Newfoundland, Canada, render this region host to nationally and globally important breeding seabird populations.This study updates estimates and trends of three major populations using a Geographic Information System (GIS) approach to estimate occupied areas of high-density breeding seabirds, correcting for slope.Our results show that the Common Murre Uria aalge breeding population on Funk Island remains the largest in the western North Atlantic at 472 259 SE 32 740 (CI 398 669-545 849) pairs and increased at a rate of +0.3% per year between 1972 and 2009.The Atlantic Puffin Fratercula arctica colony on Great Island, Witless Bay, increased between 1979 and 1994 and continues to host the largest population of this species in North America at 174 491 (CI 147 559-201 423) breeding pairs estimated in 2011; the population has stabilized and may be showing signs of decline.Finally, Leach's Storm-Petrel Oceanodroma leucorhoa breeding on Great Island, previously the second largest population in the western North Atlantic, has declined by 55% since 1979; it was estimated at 134 139 (CI 76,459) pairs in 2011, and is the lowest to date.Our GIS approach incorporated a 3D model to correct for slope of nesting areas; compared with traditional non-GIS techniques, this approach increased the estimated occupied area by 5%-10% for flat surfaces occupied by murres, by 16%-36% for moderate slopes occupied by storm-petrels, and by 40%-46% for steep slopes occupied by puffins.The application of newer tools such as high resolution satellite imagery and digital elevation models, coupled with GIS, are becoming more common and continue to improve the efficiency and accuracy of assessing occupied areas of highdensity breeding seabirds.

A geographical information system (GIS) approach was used successfully on a federal wilderness area in southwestern Missouri to examine vegetative succession relative to fire management in a glades ecosystem. Maps of vegetation were obtained by interpreting aerial photographs taken in 1938, 1958, 1966, 1975 and 1986. Maps of topography, streams, soils and the location of fires which burned during the period 1938 to 1986 were also procured from a variety of public agencies. All maps were digitized and incorporated into a raster-based GIS with 25 m pixels. It was concluded that (1) both glades and oak-hickory forest have an affinity for distinct physiographic areas and (2) fire can help decrease the rate of processes of natural succession which cause glades to convert to forest. The probable effects of controlled fire on three areas proposed by the Forest Service were evaluated and summarized.

This study aims to identify the areas which have a highest air pollution especially CO and PM1O in province of Yogyakarta Special Region by the Geographical information Systems (GiS) approach. By using Geographical information Systems (GiS) approach, the mapping result shows that highest CO pollution concentrated in Yogyakarta City and Sleman Regency. The areas which have highest CO pollution according to the results of this method are the area located in country of Yogyakarta City, they are Jetis, Gondomanan, Wirobrajan, Kraton, Mantrijeron, sebagian wilayah Ngampilan, Gedongtengen, dan Mergangsan Districts. Some counties of Sleman Regency such as Depok, Ngagiik and Kaiasan Districts have highest CO pollution too. The areas which have PM10 pollutant in province of Yogyakarta Speciai Region are some parts of Yogyakarta City (Mantrijeron, Kraton, Gondomanan, Ngampiian, Gedongtengen, Danurejan, Wirobrajan, Mergangsan, Pakualaman, Jetis, and Gondokusuman Districts) and Gunung Kidul Regency (Karangmojo District) The result of this study can be recommendation for next research to evaluate the areas so that policy maker minimize the negative impacts of air poilution especially for society health. Keywords: Geographical Information Systems (GIS), PM10, CO. Â

Abstract. Although the global importance of high mountains is increasingly being recognised, their geomorphic process System has not been completely understood as yet. While Systems theory and geographical information Systems (GIS) approaches have been long-serving in alpine geomorphology, the implementation of remote sensing (RS) tools is still rare. However, objeet-oriented image analysis lends itself to alpine applications, as it unites the benefits of RS and GIS. The Systems approach and the object-oriented classification of an ASTER satellite scene with digital elevation information are parallelized in the Reintal (Bavarian Alps). In a hierarchical, multiscale data segmentation and Classification, alpine landforms can be detected with high accuracy. Hence, RS techniques represent a valuable tool for high mountain geomorphology.

Coastal zones are considered to be highly vulnerable to the effects of climate change, such as erosion, flooding, and storms, including sea level rise (SLR). The effects of rising sea levels endanger several nations, including Indonesia, and it potentially affects the coastal population and natural environment. Quantification is needed to determine the degree of vulnerability experienced by a coast since measuring vulnerability is a fundamental phase towards effective risk reduction. Therefore, the main objective of this research is to identify how vulnerable the coastal zone of Bali Province by develop a Coastal Vulnerability Index (CVI) of areas exposed to the sea-level rise on regional scales using remote sensing and Geographic Information System (GIS) approaches. This study was conducted in Bali Province, Indonesia, which has a beach length of ~640 km, and six parameters were considered in the creation to measure the degree of coastal vulnerability by CVI: geomorphology, shoreline change rate, coastal elevation, sea-level change rate, tidal range, and significant wave height. The different vulnerability parameters were assigned ranks ranging from 1 to 5, with 1 indicating the lowest and 5 indicating the highest vulnerabilities. The study revealed that about 138 km (22%) of the mapped shoreline is classified as being at very high vulnerability and 164 km (26%) of shoreline is at high vulnerability. Of remaining shoreline, 168 km (26%) and 169 km (26%) are at moderate and low risk of coastal vulnerability, respectively. This study outcomes can provide an updated vulnerability map and valuable information for the Bali Province coast, aimed at increasing awareness among decision-makers and related stakeholders for development in mitigation and adaptation strategies. Additionally, the result may be utilized as basic data to build and implement appropriate coastal zone management.

This study addresses the critical challenge of unsustainable groundwater exploitation in Mubi South Local Government Area (LGA), Adamawa State, Nigeria, by employing a Remote Sensing (RS) and Geographic Information Systems (GIS) approach to assess and zone groundwater potential for sustainable urban management. Rapid urbanization and increasing water demand in the region have heightened the need for a comprehensive understanding of groundwater resources. Integrating multi-source geospatial data—including Landsat imagery, Digital Elevation Model (DEM), soil data, and settlement information—the study analyzes six key factors (Drainage Density, Slope, Soil, Elevation, Land Use/Land Cover (LULC), and Aspect) to generate a composite groundwater potential index. Five distinct groundwater potential zones were identified: Marginally High (12,093.42 hectares), Average (7,189.67 hectares), High (8,361.73 hectares), Low (11,927.18 hectares), and Very Low (7,676.06 hectares). These zones exhibit varying degrees of groundwater availability, with the High and Marginally High zones supporting 38 and 72 settlements, respectively, while the Low and Very Low zones encompass 49 and 43 settlements. The findings reveal that depth, recharge rates, water quality, and sustainability are critical factors influencing groundwater potential. By enumerating settlements within each zone, the study provides actionable insights for local water resource management. This research contributes a nuanced understanding of groundwater dynamics in Mubi South LGA, offering a robust foundation for sustainable urban development and water resource planning. The results underscore the importance of zone-specific management strategies to optimize groundwater utilization and enhance resilience to climate change.

Drought is a critical global challenge that severely impacts farmers and communities, and its effects are exacerbated by climate change. The Dharmapuri District in Tamil Nadu, India, is chosen as the study area because it is highly prone to drought. In this region, approximately 70% of the population depends on agriculture. Various parameters are used, including the normalized difference vegetation index, normalized difference water index, land use and land cover, geology, soil, rainfall, slope, lineament density, temperature, geomorphology, elevation, and normalized multiband drought index. These parameters were selected from the literature review on drought vulnerability. The aim of the study area is to determine Drought Vulnerability Zones (DVZ) by integrating Trapezoidal Fuzzy Numbers Analytical Hierarchy Process (TRFNAHP) method and Geographic Information System (GIS) approaches. The results of the DVZ classification are as follows: very low (12.63%), low (27.33%), moderate (24.87%), high (22.95%), and very high (12.22%). The drought vulnerability index is validated using the receiver operating characteristic curve. In the receiver operating characteristic curve, an area under the curve value of 0.89% indicated the best prediction accuracy in the study area.

A geographic information system (GIS) is a tool that collects, organizes, interprets, and maps different kinds of data. The geospatial method consists of the gathering, displaying, and manipulating of imagery, GPS, satellite photos, and historical data that are used with geographic models and either explicitly specified in terms of geographic coordinates. Political science studies regional, state, and national governments, political actors, political discourse in the media, and the connections between political figures and groups. In this study, Geographic Information System and Geospatial approaches for Political Science studies are used to develop Urban Development Analysis. Political scientists have been incorporating GIS technology into their statistical analyses in recent years. This study's understanding of GIS as a mix of technology, methodology, and situated social practices is the foundation of the GIS. With the development of a permanent and easily editable database in a particular area, where various types of data may be kept, merged, and graphically displayed, GIS technologies make it all this simpler. GIS allow researchers to deal with complex, multivariate, and multidimensional historical processes more successfully as well as uncover historical, political, or social issues that may not always be readily apparent when using more conventional research and analytical techniques.

In 2022, the number of diarrhea cases increased to 958 sufferers, with the highest incidence occurring in Bulurejo village. Physically, the sources of clean water still exhibit discoloration and unpleasant odor. The latrine construction lacks a roof, and the walls are made of cloth. The construction of waste bins lacks covers, and the wastewater disposal facilities (SPAL) are open. This research aims to determine the correlation between basic sanitation and the prevalence of diarrhea using the Geographic Information System (GIS) method. The study is descriptive-analytical through observations and a GIS approach in the form of a map. From the observations, bivariate and univariate analyses were conducted using the chi-square test. The results show that basic household sanitation is related to the prevalence of diarrhea in Bulurejo. Clean water facilities, with a p-value of 0.014, indicate a significant relationship. Toilet facilities, with a p-value of 0.347, show no significant relationship. SPAL facilities, with a p-value of 0.009, indicate a significant relationship. Waste disposal facilities, with a p-value of 0.029, indicate a significant relationship. After analysis, the results were represented in the form of a map. The Geographic Information System (GIS) approach was utilized to develop more effective mapping strategies for the improvement of sanitation and diarrhea control in the area. These findings indicate the necessity for enhancing basic sanitation facilities and implementing programs at community health centers to reduce diarrhea cases in Bulurejo.

Landslide hazard zoning using the GIS approach—A case study from the Ramganga catchment, Himalayas

The traditional method of identifying road accident hot zones is through the examination of accident frequency and nature, which sometimes, can be subjective and inaccurate. To overcome the limitation of the traditional method, researchers have applied Geographic Information System (GIS) approaches to identify and visualise road traffic accidences in real-time. However, these approaches still treat accidences as occasional and discrete events and can not support accurate analysis and prediction of accidences at some point. This paper takes the spatial autocorrelation nature of accidents (i.e. the interdependence of accident data and the relationship between the accident and space) into account and proposes an innovative spatial-autocorrelation-based method to identify freeway accident hot zones. Based on the spatial autocorrelation and mathematical statistics, this method constructs a point-line connectivity network to realise the space localisation and validation of accidents. Combined with GIS approaches, our approach can also automatically identify and visualise accident-prone areas. At the moment, the approach has been tentatively applied in a highway in China. The result demonstrates an algorithm behind the approach, which can effectively convert accident data into spatial data, cluster accident hot zones of any length and predict the whereabouts of likely accidents in the future. In conclusion, the robustness and accuracy of the approach innovates this study.

Accessibility patterns and community integration among previously homeless adults: A Geographic Information Systems (GIS) approach

Aerial photo interpretation of high resolution airborne imagery (ADS40) was used in a three-dimensional (3-D) digital Geographic Information System (GIS) environment to map native plant communities defined in the NSW Vegetation Classification and Assessment (NSW VCA) in central-southern New South Wales. NSW VCA plant community types form part of the NSW BioMetric vegetation type dataset underpinning NSW natural resource management (NRM) planning frameworks. This region was previously devoid of detailed vegetation mapping. In addition to developing a novel method for mapping plant communities, the use of ADS40 imagery allowed for capture of multiple attributes in each map polygon including attributes pertaining to dominant species and vegetation condition. Such data informs multi-attribute models used in conservation planning, providing utility beyond that of a singular plant community map. A total of 546,150 hectares of native vegetation in 100 native plant communities was mapped across the study area (Coolamon, Cootamundra, Junee, Lockhart, Narrandera, Tarcutta, Urana, Wagga Wagga and Yanco 1:100,000 mapsheets and Ariah Park, Wallaroobie Range and Yoogali 1:50,000 mapsheets). Exotic pine plantations and native species plantings were also mapped. Remnants of greater than one hectare were captured through on-screen GIS digitising at scales of approximately 1:4,000. The plant community type mapping was independently assessed using random blind validation points as having a user accuracy of 87%. This level of accuracy demonstrates the applicability of the methodology for mapping open forests, woodlands and open woodlands of south-eastern Australia and probably other vegetation elsewhere. Such accurate mapping provides end users with confidence when using vegetation maps in environmental assessment and land use planning.

Analysis and Integration of Reconnaissance Data in a Mineral-Resource Assessment of Austria