Simple Geographic Information System Research Articles

GIS-Based Analysis for UAV-Supported Field Experiments Reveals Soybean Traits Associated With Rotational Benefit.

Recent advances in unmanned aerial vehicle (UAV) remote sensing and image analysis provide large amounts of plant canopy data, but there is no method to integrate the large imagery datasets with the much smaller manually collected datasets. A simple geographic information system (GIS)-based analysis for a UAV-supported field study (GAUSS) analytical framework was developed to integrate these datasets. It has three steps: developing a model for predicting sample values from UAV imagery, field gridding and trait value prediction, and statistical testing of predicted values. A field cultivation experiment was conducted to examine the effectiveness of the GAUSS framework, using a soybean–wheat crop rotation as the model system Fourteen soybean cultivars and subsequently a single wheat cultivar were grown in the same field. The crop rotation benefits of the soybeans for wheat yield were examined using GAUSS. Combining manually sampled data (n = 143) and pixel-based UAV imagery indices produced a large amount of high-spatial-resolution predicted wheat yields (n = 8,756). Significant differences were detected among soybean cultivars in their effects on wheat yield, and soybean plant traits were associated with the increases. This is the first reported study that links traits of legume plants with rotational benefits to the subsequent crop. Although some limitations and challenges remain, the GAUSS approach can be applied to many types of field-based plant experimentation, and has potential for extensive use in future studies.

GEOGRAPHICAL INFORMATION SYSTEM (GISy) IMPLEMENTATION WITHOUT GEOGRAPHICAL INFORMATION SCIENCE (GISc) FUNDAMENTAL

This article reviews the use of Geographical Information System (GIS) has been primarily applied in spatial decision making from simple to complex geospatial problems. GIS is usually referred to as a computer system used explicitly to store, manage, analyze, manipulate, and visualize geospatial data. GIS can produce meaningful information for a better understanding of solving related geographic/spatial problems. With the technology, hardware, and software assistance, GIS is at its progressive pace even though GIS starts with a simple and straightforward question of geographic features/event location. This rapid development has made GIS and spatial data becoming a critical commodity today. However, without the basic knowledge and GIS understanding, the actual GIS capabilities, such as understanding geographical concepts, managing geographic phenomena, and solving geographical problems, become limited. To become worse, GIS is was seen as a tool to facilitate map display and simple spatial analysis. Furthermore, the market's professional training emphasizes simple GIS components such as hardware, software, geospatial data mapping, extracting geographical data from tables (tabular data), simple queries or display, and spatial data editing mastered using GIS manuals in training. Thus, this article highlights the impact of implementing GIS without sufficient GIS fundamental knowledge, resulting in complicated spatial decision planning issues.

More accurate less meaningful? A critical physical geographer’s reflection on interpreting remote sensing land-use analyses

Land-use and land-cover analyses based on satellite image classification are used in most, if not all, sub-disciplines of physical geography. Data availability and increasingly simple image classification techniques – nowadays, even implemented in simple geographic information systems – increase the use of such analyses. To assess the quality of such land-use analyses, accuracy metrics are applied. The results are considered to have sufficient quality, exceeding thresholds published in the literature. A typical practice in many studies is to confuse accuracy in remote sensing with quality, as required by physical geography. However, notions such as quality are subject to normative considerations and performative practices, which differ between scientific domains. Recent calls for critical physical geography have stressed that scientific results cannot be understood separately from the values and practices underlying them. This article critically discusses the specific understanding of quality in remote sensing, outlining norms and practices shaping it and their relation to physical geography. It points out that, as a seeming paradox, results considered more accurate in remote sensing terms can be less informative – or meaningful – in geographical terms. Finally, a roadmap of how to apply remote sensing land-use analyses more constructively in physical geography is proposed.

Abstract IA08: Improving researcher accessibility to publicly available data through creative integration, geospatial visualization, and open data portals

Abstract The increased accessibility of population-level data made available by the government and public health and consumer agencies provides a unique opportunity for integrative data analysis, spatial visualization with much higher resolution to identify clusters of disease, and their correlation with geospatial, socioeconomic, and demographic predictors. However, interactive mapping and spatial analysis tools are underutilized by health researchers and decision-makers as a result of scarce training materials, few examples demonstrating their successful use, and poor mechanisms for sharing results generated by geovisualization. Further, in the wake of massive amounts of new data and analytical tool availability, consumers of cancer population health data, such as academic researchers and public health practitioners, are facing an ongoing transformation of practice resulting in the need for effective collaboration and sharing of resources within and across disciplinary and geographic boundaries. In this talk we will summarize three of our ongoing projects that leverage web-based technologies with the aim to reduce barriers to data sharing, promote simultaneous analysis of multiple datasets, and enable geovisualization of cancer outcomes and their interrelationships with social and spatial factors. The Disentangling Disparities Data Warehouse, or D3W, is a population-based data resource that includes geotagged California Cancer Registry data linked to census, American Community Survey, and other curated sources of neighborhood-level contextual and environmental data. The D3W allows ecologic and/or multilevel statistical analysis and supports sophisticated analysis of the spatial dynamics of cancer in California. The HealthWebMapper is a highly interactive data visualization tool with a simple two-tier web geographic information systems (GIS) framework. This dynamic web GIS/mapping tool was created with open-source JavaScript library, Leaflet, and free web authoring tools (bootstrap, jquery, and Google Chart) to provide user-friendly maps and data-mining functions, including multiple classification methods, correlation analysis, data export, and side-by-side displays. HealthWebMapper is an open source application and available via a public Github repository, and it can be easily installed on any website without specialized GIS servers or databases. Finally, to promote ease of access to the D3W and HealthWebMapper as well as other research data resources, we are developing the Health Data Open Analytic Portal, with support from the newly established NIH-funded HealthLINK Center for Population Health and Health Disparities Research at San Diego State University. The key functions of the open data portal are to archive, manage, download, and integrate disease, environmental, socioeconomic, and health behavior data. The data portal will enable the sharing, archiving, and learning of research procedures and health data resources. The searchable and downloadable data portal will also provide comprehensive research investigator profiles and online training materials to facilitate transdisciplinary research collaborations in cancer population health and beyond. Citation Format: Caroline A. Thompson, Ming-Hsiang Tsou. Improving researcher accessibility to publicly available data through creative integration, geospatial visualization, and open data portals [abstract]. In: Proceedings of the AACR Special Conference on Modernizing Population Sciences in the Digital Age; 2019 Feb 19-22; San Diego, CA. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2020;29(9 Suppl):Abstract nr IA08.

Quantum GIS (QGIS): An introduction to a free alternative to more costly GIS platforms

Geographic information system (GIS) software packages can be prohibitively expensive, causing many to shy away from mapping and spatial analysis. This 7-page fact sheet written by Jeffry M. Flenniken, Steven Stuglik, and Basil V. Iannone III and published by the UF/IFAS School of Forest Resources and Conservation introduces the reader to a free GIS software package called Quantum GIS (QGIS), walking the reader through simple GIS processes that can be used to visualize spatial patterns of importance to a variety of fields, including natural resources, agriculture, and urban planning. Learn how to create a land-cover map for a county of interest and create heatmaps that illustrate the density of a given attribute (Florida Springs for this example). This publication will benefit those interested in incorporating GIS into their work but who are unable to afford expensive proprietary GIS software packages, as well as anyone interested in learning a new GIS software package. https://edis.ifas.ufl.edu/fr428

Locating residential on-street electric vehicle charging infrastructure: A practical methodology

Depending on the method of electricity generation, mass-market penetration of electric vehicles has the potential to reduce emissions of greenhouse gases and air pollutants considerably, and to reduce dependency on fossil fuels. This paper presents a novel methodology for Local Government Authorities (LGAs) to identify suitable locations for the initial provision of residential on-street Plug-in Electric Vehicle (PEV) charging infrastructure in urban areas to help remove barriers to PEV uptake. The methodology is practical for use by LGAs with limited financial resources as it is based on simple Geographic Information System (GIS) analysis of routinely available census and parking data to identify the spatial overlaps between areas where residents are most likely to be PEV users and areas where there is a high reliance on residential on-street parking. The methodology has been implemented in practice to determine a charging infrastructure installation strategy for Southampton, UK, where 128 streets (out of 1924 in total) were recommended as suitable locations. These streets were reviewed by a group of experts during a workshop and confirmed as suitable locations for the initial installation of residential on-street charge points in the city.

GIS-Based Rockfall Susceptibility Zoning in Greece

The assessment of rockfall risks on human activities and infrastructure is of great importance. Rock falls pose a significant risk to (a) transportation infrastructure, (b) inhabited areas, and (c) Cultural Heritage sites. The paper presents a method to assess rockfall susceptibility at national scale in Greece, using a simple rating approach and Geographic Information Systems (GIS) techniques. An extensive inventory of rockfalls for the entire country was compiled for the period between 1935 and 2019. The rockfall events that were recorded are those which have mainly occurred as distinct rockfall episodes in natural slopes and have impacted human activities, such as roads, inhabited areas, and archaeological sites. Through a detailed analysis of the recorded data, it was possible to define the factors which determine the occurrence of rockfalls. Based on this analysis, the susceptibility zoning against rockfalls at the national scale was prepared, using a simple rating approach and GIS techniques. The rockfall susceptibility zoning takes into account the following parameters: (a) the slope gradient, (b) the lithology, (c) the annual rainfall intensity, (d) the earthquake intensity, and (e) the active fault presence. Emphasis was given on the study of the earthquake effect as a triggering mechanism of rockfalls. Finally, the temporal and spatial frequency of the recorded events and the impact of rockfalls on infrastructure assets and human activities in Greece were evaluated.

Application opportunities of geographic information systems analysis to support achievement of the UNAIDS 90-90-90 targets in South Africa.

In an effort to achieve control of the HIV epidemic, 90-90-90 targets have been proposed whereby 90% of the HIV-infected population should know their status, 90% of those diagnosed should be receiving antiretroviral therapy, and 90% of those on treatment should be virologically suppressed. In this article we present approaches for using relatively simple geographic information systems (GIS) analyses of routinely available data to support HIV programme management towards achieving the 90-90-90 targets, with a focus on South Africa (SA) and other high-prevalence settings in low- and middle-income countries. We present programme-level GIS applications to map aggregated health data and individual-level applications to track distinct patients. We illustrate these applications using data from City of Johannesburg Region D, demonstrating that GIS has great potential to guide HIV programme operations and assist in achieving the 90-90-90 targets in SA.

A Combinatorial Reasoning Mechanism with Topological and Metric Relations for Change Detection in River Planforms: An Application to GlobeLand30’s Water Bodies

Changes in river plane shapes are called river planform changes (RPCs). Such changes can impact sustainable human development (e.g., human habitations, industrial and agricultural development, and national border security). RPCs can be identified through field surveys—a method that is highly precise but time-consuming, or through remote sensing (RS) and geographic information system (GIS), which are less precise but more efficient. Previous studies that have addressed RPCs often used RS, GIS, or digital elevation models (DEMs) and focused on only one or a few rivers in specific areas with the goal of identifying the reasons underlying these changes. In contrast, in this paper, we developed a combinatorial reasoning mechanism based on topological and metric relations that can be used to classify RPCs. This approach does not require DEMs and can eliminate most false-change information caused by varying river water levels. First, we present GIS models of river planforms based on their natural properties and, then, modify these models into simple GIS river planform models (SGRPMs) using straight lines rather than common lines to facilitate computational and human understanding. Second, we used double straight line 4-intersection models (DSL4IMs) and intersection and difference models (IDMs) of the regions to represent the topological relations between the SGRPMs and used double-start-point 8-distance models (DS8DMs) to express the metric relations between the SGRPMs. Then, we combined topological and metric relations to analyse the changes in the SGRPMs. Finally, to compensate for the complexity of common river planforms in nature, we proposed three segmentation rules to turn common river planforms into SGRPMs and used combinatorial reasoning mechanism tables (CRMTs) to describe the spatial relations among different river planforms. Based on our method, users can describe common river planforms and their changes in detail and confidently reject false changes. Future work should develop a method to automatically or semi-automatically adjust the segmentation rules and the combinatorial reasoning mechanism.

Spatial prediction of demersal fish diversity in the Baltic Sea: comparison of machine learning and regression-based techniques

Marine spatial planning (MSP) is considered a valuable tool in the ecosystem-based management of marine areas. Predictive modelling may be applied in the MSP framework to obtain spatially explicit information about biodiversity patterns. The growing number of statistical approaches used for this purpose implies the urgent need for comparisons between different predictive techniques. In this study, we evaluated the performance of selected machine learning and regression-based methods that were applied for modelling fish community indices. We hypothesized that habitat features can influence fish assemblage and investigated the effect of environmental gradients on demersal fish diversity (species richness and Shannon–Weaver Index). We used fish data from the Baltic International Trawl Surveys (2001–2014) and maps of six potential predictors: bottom salinity, depth, seabed slope, growth season bottom temperature, seabed sediments and annual mean bottom current velocity. We compared the performance of six alternative modelling approaches: generalized linear models, generalized additive models, multivariate adaptive regression splines, support vector machines, boosted regression trees and random forests. We applied repeated 10-fold cross-validation, using accuracy as the measure of model quality. Finally, we selected random forest as the best performing algorithm and implemented it for the spatial prediction of fish diversity from the Baltic Proper to the Kattegat. To obtain information on the data reliability and confidence of the developed models, which are essential for MSP, we estimated the uncertainty of predictions with standard deviation of predictions obtained from all the trees in the ensemble random forest method. We showed how state-of-the-art predictive techniques, based on easily available data and simple Geographic Information System tools, can be used to obtain reliable spatial information about fish diversity. Our comparative work highlighted the potential of machine learning method to reduce prediction error in modelling of demersal fish diversity in the framework of MSP.

The value of spatial analysis for tracking supply for family planning: the case of Kinshasa, DRC.

While geographic information systems (GIS) are frequently used to research accessibility issues for healthcare services around the world, sophisticated spatial analysis protocols and outputs often prove inappropriate and unsustainable to support evidence-based programme strategies in resource-constrained environments. This article examines how simple, open-source and interactive GIS tools have been used to locate family planning (FP) services delivery points in Kinshasa (Democratic Republic of Congo) and to identify underserved areas, determining the potential location of new service points, and to support advocacy for FP programmes. Using smartphone-based data collection applications (OpenDataKit), we conducted two surveys of FP facilities supported by partner organizations in 2012 and 2013 and used the results to assess gaps in FP services coverage, using both ratio of facilities per population and distance-based accessibility criteria. The cartographic outputs included both static analysis maps and interactive Google Earth displays, and sought to support advocacy and evidence-based planning for the placement of new service points. These maps, at the scale of Kinshasa or for each of the 35 health zones that cover the city, garnered a wide interest from the operational level of the health zones' Chief Medical Officers, who were consulted to contribute field knowledge on potential new service delivery points, to the FP programmes officers at the Ministry of Health, who could use the map to inform resources allocation decisions throughout the city.

Post-disaster Forest Management and Bark Beetle Outbreak in Tatra National Park, Slovakia

Abstract In November 2004, the Alžbeta windstorm hit the mountainous areas of northern and central Slovakia. The most affected area was Tatra National Park, where downslope wind damaged 12,000 ha of forest, mostly Norway spruce (Picea abies [L.] Karst.). In the areas with the highest level of nature conservation, about 165,000 m3 of damaged wood was left uncleared. These uncleared sites triggered a serious bark beetle outbreak, where Ips typographus (L.) was among the dominant species. The aim of our work was to quantify and map forest damage resulting from this windstorm and subsequent insect outbreak in Tatra National Park. The objective of this article is also to present simple geographic information system (GIS) techniques available to forest managers for the detection and mapping of bark beetle infestations. The infested areas were studied using GIS and a series of color-infrared aerial photographs taken in 2005–2009. More than 50% of all damage was recorded within 300 m, and more than 75% within 500...

Using geographical information systems and cartograms as a health service quality improvement tool

IntroductionDisease prevalence can be spatially analysed to provide support for service implementation and health care planning, these analyses often display geographic variation. A key challenge is to communicate these results to decision makers, with variable levels of Geographic Information Systems (GIS) knowledge, in a way that represents the data and allows for comprehension. The present research describes the combination of established GIS methods and software tools to produce a novel technique of visualising disease admissions and to help prevent misinterpretation of data and less optimal decision making. The aim of this paper is to provide a tool that supports the ability of decision makers and service teams within health care settings to develop services more efficiently and better cater to the population; this tool has the advantage of information on the position of populations, the size of populations and the severity of disease. MethodsA standard choropleth of the study region, London, is used to visualise total emergency admission values for Chronic Obstructive Pulmonary Disease and bronchiectasis using ESRI’s ArcGIS software. Population estimates of the Lower Super Output Areas (LSOAs) are then used with the ScapeToad cartogram software tool, with the aim of visualising geography at uniform population density. An interpolation surface, in this case ArcGIS’ spline tool, allows the creation of a smooth surface over the LSOA centroids for admission values on both standard and cartogram geographies. The final product of this research is the novel Cartogram Interpolation Surface (CartIS). ResultsThe method provides a series of outputs culminating in the CartIS, applying an interpolation surface to a uniform population density. The cartogram effectively equalises the population density to remove visual bias from areas with a smaller population, while maintaining contiguous borders. CartIS decreases the number of extreme positive values not present in the underlying data as can be found in interpolation surfaces. DiscussionThis methodology provides a technique for combining simple GIS tools to create a novel output, CartIS, in a health service context with the key aim of improving visualisation communication techniques which highlight variation in small scale geographies across large regions. CartIS more faithfully represents the data than interpolation, and visually highlights areas of extreme value more than cartograms, when either is used in isolation.

Mapping the Potential for Biofuel Production on Marginal Lands: Differences in Definitions, Data and Models across Scales

As energy policies mandate increases in bioenergy production, new research supports growing bioenergy feedstocks on marginal lands. Subsequently there has been an increase in published work that uses Geographic Information Systems (GIS) to map the availability of marginal land as a proxy for bioenergy crop potential. However, despite the similarity in stated intent among these works a number of inconsistencies remain across studies that make comparisons and standardization difficult. We reviewed a collection of recent literature that mapped bioenergy potential on marginal lands at varying scales, and found that there is no common working definition of marginal land across all of these works. Specifically, we found considerable differences in mapped results that are driven by dissimilarities in definitions, model framework, data inputs, scale and treatment of uncertainty. Most papers reviewed here employed relatively simple GIS overlays of input criteria, distinct thresholds identifying marginal land, and few details describing accuracy and uncertainty. These differences are likely to be major impediments to integration of studies mapping marginal lands for bioenergy production. We suggest that there is future need for spatial modeling of bioenergy, yet further scholarship is needed to compare across countries and scales to understand the global potential for bioenergy crops.

Development of Future Land Cover Change Scenarios in the Metropolitan Fringe, Oregon, U.S., with Stakeholder Involvement

We describe a future land cover scenario construction process developed under consultation with a group of stakeholders from our study area. We developed a simple geographic information system (GIS) method to modify a land cover dataset and then used qualitative data extracted from the stakeholder storyline to modify it. These identified variables related to our study area’s land use regulation system as the major driver in the placement of new urban growth on the landscape; and the accommodation of new population as the determinant of its growth rate. The outcome was a series of three scenario maps depicting a gradient of increased urbanization. The effort attempted to create a simple and transparent modeling framework that is easy to communicate. The incorporation of the regulatory context and rules and place-specific modeling for denser urban and sparse rural areas provide new insights of future land conversions. This relatively rapid mapping process provides useful information for spatial planning and projects for where and how much urban land will be present by the year 2050.

Investigating Changes in Coastal Environment Using Internet-Based Geospatial Data

The concerns of researchers and policy makers for the deteriorating condition of the coastal environments have increased in recent times. As the threats to the world today, such as, climate change, population pressure, urbanization and disasters are getting worse, it has become needful to give more attention to means of sustaining the human environment, especially the coastal areas. On the basis of this background, access to geospatial data through internet technology has become attractive, for investigating the impacts of dynamic processes on the coastal environment. This paper presents the result of investigation carried out in Okrika coastal areas of Rivers State, Nigeria. In particular, it discusses how internet-based geospatial data (for example; LandSat TM, ETM+ and Google Earth maps) of three epochs, were incorporated into open-source Geographic Information System (GIS), such as, Integrated Land and Water Information System (ILWIS), and applied to the investigation of land use/land cover (LU/LC) changes. The results obtained tend to show that between 1986 – 2007, 10.94% of the coastal areas was modified from water body to residential areas, 1.10% from residential areas to swamps, 0.42% from vegetation to water body and 0.93% from residential areas to water body. With these modifications, the economic mainstay of the people (marine, tourism and fishing activities) has been adversely affected. The research recommends that effective shoreline protection facility be put in place through government regulations in order to minimize further encroachment, particularly with regards to the water bodies. Also, high-resolution geospatial data as well as simple GIS applications should be made available on the internet, to enable more researchers contribute knowledge and solution to coastal crises, as well as improve collaboration within an interactive platform among policy and strategy formulators.Key Words: Coastal environment, Geospatial data, Remote Sensing, LandSat TM, ETM+, Internet, Open-source GIS.

Accessibility to primary health care in Belgium: an evaluation of policies awarding financial assistance in shortage areas.

BackgroundIn many countries, financial assistance is awarded to physicians who settle in an area that is designated as a shortage area to prevent unequal accessibility to primary health care. Today, however, policy makers use fairly simple methods to define health care accessibility, with physician-to-population ratios (PPRs) within predefined administrative boundaries being overwhelmingly favoured. Our purpose is to verify whether these simple methods are accurate enough for adequately designating medical shortage areas and explore how these perform relative to more advanced GIS-based methods.MethodsUsing a geographical information system (GIS), we conduct a nation-wide study of accessibility to primary care physicians in Belgium using four different methods: PPR, distance to closest physician, cumulative opportunity, and floating catchment area (FCA) methods.ResultsThe official method used by policy makers in Belgium (calculating PPR per physician zone) offers only a crude representation of health care accessibility, especially because large contiguous areas (physician zones) are considered. We found substantial differences in the number and spatial distribution of medical shortage areas when applying different methods.ConclusionsThe assessment of spatial health care accessibility and concomitant policy initiatives are affected by and dependent on the methodology used. The major disadvantage of PPR methods is its aggregated approach, masking subtle local variations. Some simple GIS methods overcome this issue, but have limitations in terms of conceptualisation of physician interaction and distance decay. Conceptually, the enhanced 2-step floating catchment area (E2SFCA) method, an advanced FCA method, was found to be most appropriate for supporting areal health care policies, since this method is able to calculate accessibility at a small scale (e.g. census tracts), takes interaction between physicians into account, and considers distance decay. While at present in health care research methodological differences and modifiable areal unit problems have remained largely overlooked, this manuscript shows that these aspects have a significant influence on the insights obtained. Hence, it is important for policy makers to ascertain to what extent their policy evaluations hold under different scales of analysis and when different methods are used.

Innovative Suffocation Management and the Effects of the Suffocation Concentrations Created by Shopping Malls in Urban Area

The suffocation is an innovative metric that can be used in Satellite City Design. Suffocation is a scalar magnitude which is proportional to the volumes of interacting buildings and cross proportional to the the distance between the outer contours of the buildings and is inspired from the theory of Gravitation and theory of Potential.By summing up the suffocations of each building in the area it is possible to calculate the “Total suffocation” affecting a single building. The total suffocation with relevant decision variables and constraint functions can be used as a design optimization metric for suburban or satellite city design processes.In this study the effect of the big shopping mall constructions over the total suffocation distribution for given area will be analyzed as a real case study for the satellite cities around the metropolitan areas. The change for the construction distribution will be retrieved from simple Geographic Information Systems applications such as “Google Earth”. The change in the total distribution of total suffocation over the area where there are huge shopping malls are computed and the results are discussed.

Developing a GIS for Rural Villages in the Philippines

This paper is an introduction to applying geographic information systems (GIS) technology specifically to rural villages in the Philippines. GIS is a relatively new and valuable tool in decision making that is useful in managing organizations and applicable in a wide range of disciplines including agriculture, public health, natural resource management, and local governance. Rural village governance, although well-established, has been largely untouched by GIS technology. This paper lays out steps to develop a GIS that is uniquely villagebased and home-grown. The ultimate goal is to empower villagers to set the direction and implementation of their own village’s development efforts. The steps discuss how to build an inexpensive GIS for rural villages with the help of a GIS expert-coach. Village participation, interest of GIS technician-trainees, and village financial capability are some important considerations in village GIS capability building. A simple GIS for an actual village is also hypothetically illustrated. Keywords - Geographic Information system, rural villages

Incorporating Wildlife Conservation into County Comprehensive Plans: A GIS Approach

Within the United States (U.S.), state wildlife agencies are required to identify Species of Greatest Conservation Need (SGCN), the factors that impact these species, and the conservation actions needed to conserve these species through documentation of a Comprehensive Wildlife Conservation Strategy (CWCS). While the identification of SGCN represents an essential first step towards a comprehensive management strategy at the state level, the incorporation of this information into county level comprehensive plans will likely increase conservation efforts needed statewide. Our objective for this study was to use spatial data to delineate areas of human activity overlapping with areas rich in biodiversity to provide state wildlife agencies and local county planners recommended conservation actions to reduce biodiversity loss by human activities. Using the state of Idaho as an example, we delineated areas within the state where biodiversity hotspots for terrestrial and aquatic SGCN and human activities may be conflicting. We then identified counties within the state where these areas of conflict occur and identified conservation actions that may mitigate human activities to benefit SGCN. Our study used available geospatial data and a simple geographical information system (GIS) based approach which could be applied to other areas to support county-level land use planning for wildlife conservation.