Department of Forest Resources and Environmental Conservation

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Browsing Department of Forest Resources and Environmental Conservation by Department "Forest Resources and Environmental Conservation"

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    The 1972 Virginia Outdoor Recreation Inventory
    Leuschner, William A.; Groves, David L.; Bolger, William T.; Stokes, Gerald L. (Virginia Tech. Division of Forestry and Wildlife Resources, 1974)
    The Virginia Commission of Outdoor Recreation coordinated the inventorying of outdoor recreation facilities in the state between June and December, 1972. The inventory is an integral part of the Virginia Outdoors Plan Information System. Its primary purpose was to provide data for the Commission to formulate and write the statewide comprehensive outdoor recreation plan. However, the intended use of these data was much broader. It was envisaged that they would be useful for other planning activities, such as those conducted by federal and state agencies or the 22 Planning District Commissions in Virginia, as well as for various research activities, special studies, and teaching. The purpose of this publication is threefold. The first is to encourage further use of the data by informing the public of its existence and the specific variables contained therein. The second is to present a limited but comprehensive set of data which can be used to answer general inquiries and which will save interested parties the trouble of writing to obtain it. Finally, we wish to inform the public of the availability of the data in other forms which may better suit individual needs but which would be too numerous to publish in this bulletin.
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    The 1977 Virginia Outdoor Recreation Demand Survey
    Roggenbuck, Joseph W. (Virginia Tech. Division of Forestry and Wildlife Resources, 1978)
    Knowledge of the present and projected public demand for outdoor recreation is a key element in the planning of a comprehensive system of outdoor recreation opportunities throughout Virginia. Public preferences for outdoor recreation experiences have changed dramatically in recent years, and formal measures of demand at any point in time remain only approximate. Nevertheless, demand analyses that are based upon the premise of satisfying public needs--as the public defines them--have a solid basis in the traditions and policies of governmental service agencies, and do provide a general guide for the planning, acquisition and development of outdoor recreation lands and facilities. This outdoor recreation demand booklet, published by the School of Forestry and Wildlife Resources, Virginia Polytechnic Institute and State University, in cooperation with the Virginia Commission of Outdoor Recreation, has three general purposes. The first is to provide federal, state and local agencies and organizations with responsibilities for the provision of outdoor recreation services with guidelines on current and projected demand for recreation activities by state, region, and locality. The second is to make the demand estimates easily available to agencies and organizations whose responsibilities do not include outdoor recreation but whose activities may impinge upon that system. Finally, the data contained here should be useful in various research activities, special studies, and teaching regarding the Virginia outdoor recreation system.
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    The 1977 Virginia Outdoor Recreation Needs Assessment
    Roggenbuck, Joseph W. (Virginia Tech. Division of Forestry and Wildlife Resources, 1978)
    This outdoor recreation needs assessment booklet, published by the School of Forestry and Wildlife Resources, Virginia Polytechnic Institute and State University, in cooperation with the Virginia Commission of Outdoor Recreation, has three general purposes. Its primary purpose is to provide guidelines on the amount and location of current and projected needs for additional outdoor recreational opportunities to federal, state, and local agencies and organizations with responsibilities for the provision of outdoor recreation services. The second is to make the needs estimates easily available to agencies and organizations whose responsibilities do not include outdoor recreation, but whose activities may impinge upon that system. Finally, the data contained here should be useful in various research activities, special studies, and teaching regarding the Virginia outdoor recreation system. Need for outdoor recreation land and facilities, as defined in this booklet, represents the difference between demand for and supply of outdoor recreation opportunities. As such, a needs assessment requires the previous calculation of present and projected recreation demand and a thorough inventory of existing recreation supply. These analyses were accomplished in 1977 and have been published as the 1977 Virginia Outdoor Recreation Demand Survey and the 1977 Virginia Outdoor Recreation Inventory. Copies of these booklets are available from the Virginia Commission of Outdoor Recreation. Since the needs estimates are dependent upon the ever-changing demand for and supply of outdoor recreation lands and facilities, the figures contained in this booklet are only approximate. The estimates should be viewed as providing general guidelines for decision-making, and not as precise measures of current deficiencies in the state's outdoor recreation system.
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    The 1977 Virginia Outdoor Recreation Survey
    Spittle, Gerald D.; Buhyoff, Gregory J.; Davy, John R. Jr.; McElwee, Robert L. (Virginia Tech. Division of Forestry and Wildlife Resources, 1978)
    The Virginia Commission of Outdoor Recreation coordinated through the Planning District Commissions an inventory of statewide recreation resources between April, 1977 and September, 1977. The School of Forestry and Wildlife Resources, Virginia Polytechnic Institute and State University, transferred the data into a computerized retrieval system from which this summary booklet was derived. This inventory is an integral part of the Virginia Outdoors Plan Information System. Its primary purpose is to provide information enabling the Commission to formulate and write the statewide comprehensive outdoor recreation plan. It is also envisaged that this data be used for other planning activities, such as those conducted by federal and state agencies or the 22 Planning District Commissions in Virginia, as well as for various research activities, special studies, and teaching. The purpose of this publication is threefold. The first is to encourage further use of the data it contains by informing the public of the specific type of information available. The second is to present a comprehensive set of data which can be used to answer general inquiries about the nature and distribution of recreation resources in the Commonwealth of Virginia. Finally, it is to advise that this data is available in other forms which may better suit individual needs but which would be too numerous to publish in this bulletin.
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    2018 Annual Report: Virginia Big Tree Program
    Wiseman, P. Eric (Virginia Tech. Department of Forest Resources and Environmental Conservation, 2018)
    The Virginia Big Tree Program is a public outreach program coordinated by Virginia Cooperative Extension and the Department of Forest Resources and Environmental Conservation at Virginia Tech. The program maintains a register of the 3 largest specimens of over 300 native, non-native, and naturalized tree species. This annual report details program accomplishments in 2018, including Big Tree reports, national rankings, and student intern contributions.
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    Above- and Below-Ground Carbon Sequestration in Shelterbelt Trees in Canada: A Review
    Mayrinck, Rafaella C.; Laroque, Colin P.; Amichev, Beyhan Y.; Van Rees, Ken (MDPI, 2019-10-19)
    Shelterbelts have been planted around the world for many reasons. Recently, due to increasing awareness of climate change risks, shelterbelt agroforestry systems have received special attention because of the environmental services they provide, including their greenhouse gas (GHG) mitigation potential. This paper aims to discuss shelterbelt history in Canada, and the environmental benefits they provide, focusing on carbon sequestration potential, above- and below-ground. Shelterbelt establishment in Canada dates back to more than a century ago, when their main use was protecting the soil, farm infrastructure and livestock from the elements. As minimal-and no-till systems have become more prevalent among agricultural producers, soil has been less exposed and less vulnerable to wind erosion, so the practice of planting and maintaining shelterbelts has declined in recent decades. In addition, as farm equipment has grown in size to meet the demands of larger landowners, shelterbelts are being removed to increase efficiency and machine maneuverability in the field. This trend of shelterbelt removal prevents shelterbelt’s climate change mitigation potential to be fully achieved. For example, in the last century, shelterbelts have sequestered 4.85 Tg C in Saskatchewan. To increase our understanding of carbon sequestration by shelterbelts, in 2013, the Government of Canada launched the Agricultural Greenhouse Gases Program (AGGP). In five years, 27 million dollars were spent supporting technologies and practices to mitigate GHG release on agricultural land, including understanding shelterbelt carbon sequestration and to encourage planting on farms. All these topics are further explained in this paper as an attempt to inform and promote shelterbelts as a climate change mitigation tool on agricultural lands.
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    Accuracy of Visible and Ultraviolet Light for Estimating Live Root Proportions with Minirhizotrons
    Wang, Z. Q.; Burch, W. H.; Mou, P.; Jones, R. H.; Mitchell, R. J. (Ecological Society of America, 1995-10)
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    Advancing lake and reservoir water quality management with near-term, iterative ecological forecasting
    Carey, Cayelan C.; Woelmer, Whitney M.; Lofton, Mary E.; Figueiredo, Renato J.; Bookout, Bethany J.; Corrigan, Rachel S.; Daneshmand, Vahid; Hounshell, Alexandria G.; Howard, Dexter W.; Lewis, Abigail S. L.; McClure, Ryan P.; Wander, Heather L.; Ward, Nicole K.; Thomas, R. Quinn (2021-01-18)
    Near-term, iterative ecological forecasts with quantified uncertainty have great potential for improving lake and reservoir management. For example, if managers received a forecast indicating a high likelihood of impending impairment, they could make decisions today to prevent or mitigate poor water quality in the future. Increasing the number of automated, real-time freshwater forecasts used for management requires integrating interdisciplinary expertise to develop a framework that seamlessly links data, models, and cyberinfrastructure, as well as collaborations with managers to ensure that forecasts are embedded into decision-making workflows. The goal of this study is to advance the implementation of near-term, iterative ecological forecasts for freshwater management. We first provide an overview of FLARE (Forecasting Lake And Reservoir Ecosystems), a forecasting framework we developed and applied to a drinking water reservoir to assist water quality management, as a potential open-source option for interested users. We used FLARE to develop scenario forecasts simulating different water quality interventions to inform manager decision-making. Second, we share lessons learned from our experience developing and running FLARE over 2 years to inform other forecasting projects. We specifically focus on how to develop, implement, and maintain a forecasting system used for active management. Our goal is to break down the barriers to forecasting for freshwater researchers, with the aim of improving lake and reservoir management globally.
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    Aids for Unit Planning on the Appalachian National Forests
    Burkhart, Harold E.; Leuschner, William A.; Stuck, R. Dean; Porter, John R.; Reynolds, Marion R. Jr. (Virginia Tech. Division of Forestry and Wildlife Resources, 1976)
    This report summarizes the results of studies conducted in response to a cooperative agreement between the Southern Region, U.S. Forest Service and the Department of Forestry and Forest Products, Virginia Polytechnic Institute and State University. The objective of the agreement was to improve National Forest management planning techniques. The agreement covered the period July 1, 1973 to June 30, 1975. Literature citations are given for those who desire additional detail.
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    Alternate Trait-Based Leaf Respiration Schemes Evaluated at Ecosystem-Scale Through Carbon Optimization Modeling and Canopy Property Data
    Thomas, R. Quinn; Williams, M.; Cavaleri, M. A.; Exbrayat, J. -F.; Smallman, T. L.; Street, L. E. (American Geophysical Union, 2019-12-25)
    Leaf maintenance respiration (Rleaf,m) is a major but poorly understood component of the terrestrial carbon cycle (C). Earth systems models (ESMs) use simple sub-models relating Rleaf,m to leaf traits, applied at canopy scale. Rleaf,m models vary depending on which leaf N traits they incorporate (e.g., mass or area based) and the form of relationship (linear or nonlinear). To simulate vegetation responses to global change, some ESMs include ecological optimization to identify canopy structures that maximize net C accumulation. However, the implications for optimization of using alternate leaf-scale empirical Rleaf,m models are undetermined. Here we combine alternate well-known empirical models of Rleaf,m with a process model of canopy photosynthesis. We quantify how net canopy exports of C vary with leaf area index (LAI) and total canopy N (TCN). Using data from tropical and arctic canopies, we show that estimates of canopy Rleaf,m vary widely among the three models. Using an optimization framework, we show that the LAI and TCN values maximizing C export depends strongly on the Rleaf,m model used. No single model could match observed arctic and tropical LAI-TCN patterns with predictions of optimal LAI-TCN. We recommend caution in using leaf-scale empirical models for components of ESMs at canopy-scale. Rleaf,m models may produce reasonable results for a specified LAI, but, due to their varied representations of Rleaf,mfoliar N sensitivity, are associated with different and potentially unrealistic optimization dynamics at canopy scale. We recommend ESMs to be evaluated using response surfaces of canopy C export in LAI-TCN space to understand and mitigate these risks.
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    Analysis of a lidar voxel-derived vertical profile at the plot and individual tree scales for the estimation of forest canopy layer characteristics
    Sumnall, Matthew; Peduzzi, Alicia; Fox, Thomas R.; Wynne, Randolph H.; Thomas, Valerie A. (2016)
    The goal of the current study was to develop methods of estimating the height of vertical components within plantation coniferous forest using airborne discrete multiple return lidar. In the summer of 2008, airborne lidar and field data were acquired for Loblolly pine forest locations in North Carolina and Virginia, USA, which comprised a variety of stand conditions (e.g. stand age, nutrient regime, and stem density). The methods here implement both field plot-scale analysis and an automated approach for the delineation of individual tree crown (ITC) locations and horizontal extents through a marker-based region growing process applied to a lidar derived canopy height model. The estimation of vertical features was accomplished through aggregating lidar return height measurements into vertical height bins, of a given horizontal extent (plot or ITC), creating a vertical 'stack' of bins describing the frequency of returns by height. Once height bins were created the resulting vertical distributions were smoothed with a regression curve-line function and canopy layers were identified through the detection of local maxima and minima. Estimates from Lorey's mean canopy height was estimated from plot-level curve-fitting with an overall accuracy of 5.9% coefficient of variation (CV) and the coefficient of determination (R-2) value of 0.93. Estimates of height to the living canopy produced an overall R-2 value of 0.91 (11.0% CV). The presence of vertical features within the sub-canopy component of the fitted vertical function also corresponded to areas of known understory presence and absence. Estimates from ITC data were averaged to the plot level. Estimates of field Lorey's mean canopy top height from average ITC data produced an R-2 value of 0.96 (7.9% CV). Average ITC estimates of height to the living canopy produced the closest correspondence to the field data, producing an R-2 value of 0.97 (6.2% CV). These results were similar to estimates produced by a statistical regression method, where R-2 values were 0.99 (2.4% CV) and 0.98 (4.9% CV) for plot average top canopy height and height to the living canopy, respectively. These results indicate that the characteristics of the dominant canopy can be estimated accurately using airborne lidar without the development of regression models, in a variety of intensively managed coniferous stand conditions.
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    An Analysis of Several Alternatives to Oil As an Industrial Fuel
    Kluender, Richard A.; Reisinger, Thomas W.; Farrar, Kenneth D.; Stuart, William B. (Virginia Tech. Division of Forestry and Wildlife Resources, 1981-10)
    This paper presents an analysis of some significant factors that should be evaluated when considering alternatives to oil burning boilers. Managers contemplating using or increasing the use of wood for energy should find the analysis particularly pertinent. A fundamental assumption of the analysis is that additional boiler capacity is to be added to an existing power generating facility. The method of analysis provides a yearly cash flow stream that tells how much better off the installation would be with an alternative to oil. A logical extension of this is the ran king of alternatives from most to least attractive.
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    Analyzing Trade-Offs, Synergies, and Drivers among Timber Production, Carbon Sequestration, and Water Yield in Pinus elliotii Forests in Southeastern USA
    Cademus, Ronald; Escobedo, Francisco J.; McLaughlin, Daniel L.; Abd-Elrahman, Amr (MDPI, 2014-06-20)
    Managing Pinus elliotii forests for timber production and/or carbon sequestration is a common management objective, but can negatively affect water yield due to high losses from evapotranspiration. Thus, understanding the trade-offs and potential synergies among multiple ecosystem goods services, as well as the drivers influencing these interactions, can help identify effective forest management practices. We used available data from 377 permanent plots from the USDA Forest Service Forest Inventory and Analysis Program for 2002–2011, and a forest water yield model to quantify provision levels and spatial distribution and patterns of carbon sequestration, timber volume and water yield for Pinus elliotii ecosystems in North Florida, USA. A ranking-classification framework and statistical analyses were used to better understand the interactions among ecosystem services and the effect of biophysical drivers on ecosystem service bundles. Results indicate that increased biomass reduced water yield but this trade-off varied across space. Specific synergies, or acceptable provision levels, among carbon sequestration, timber volume and water yield were identified and mapped. Additionally, stand age, silvicultural treatment, and site quality significantly affected the provision level of, and interactions among, the three ecosystem goods and services. The framework developed in this study can be used to assess, map, and manage subtropical forests for optimal provision of ecosystem services.
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    Approximating Prediction Uncertainty for Random Forest Regression Models
    Coulston, John W.; Blinn, Christine E.; Thomas, Valerie A.; Wynne, Randolph H. (2016-03)
    Machine learning approaches such as random forest have increased for the spatial modeling and mapping of continuous variables. Random forest is a non-parametric ensemble approach, and unlike traditional regression approaches there is no direct quantification of prediction error. Understanding prediction uncertainty is important when using model-based continuous maps as inputs to other modeling applications such as fire modeling. Here we use a Monte Carlo approach to quantify prediction uncertainty for random forest regression models. We test the approach by simulating maps of dependent and independent variables with known characteristics and comparing actual errors with prediction errors. Our approach produced conservative prediction intervals across most of the range of predicted values. However, because the Monte Carlo approach was data driven, prediction intervals were either too wide or too narrow in sparse parts of the prediction distribution. Overall, our approach provides reasonable estimates of prediction uncertainty for random forest regression models.
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    Assessing Biotic and Abiotic Effects on Biodiversity Index Using Machine Learning
    Bayat, Mahmoud; Burkhart, Harold E.; Namiranian, Manouchehr; Hamidi, Seyedeh Kosar; Heidari, Sahar; Hassani, Majid (MDPI, 2021-04-10)
    Forest ecosystems play multiple important roles in meeting the habitat needs of different organisms and providing a variety of services to humans. Biodiversity is one of the structural features in dynamic and complex forest ecosystems. One of the most challenging issues in assessing forest ecosystems is understanding the relationship between biodiversity and environmental factors. The aim of this study was to investigate the effect of biotic and abiotic factors on tree diversity of Hyrcanian forests in northern Iran. For this purpose, we analyzed tree diversity in 8 forest sites in different locations from east to west of the Caspian Sea. 15,988 trees were measured in 655 circular permanent sample plots (0.1 ha). A combination of machine learning methods was used for modeling and investigating the relationship between tree diversity and biotic and abiotic factors. Machine learning models included generalized additive models (GAMs), support vector machine (SVM), random forest (RF) and K-nearest–neighbor (KNN). To determine the most important factors related to tree diversity we used from variables such as the average diameter at breast height (DBH) in the plot, basal area in largest trees (BAL), basal area (BA), number of trees per hectare, tree species, slope, aspect and elevation. A comparison of RMSEs, relative RMSEs, and the coefficients of determination of the different methods, showed that the random forest (RF) method resulted in the best models among all those tested. Based on the results of the RF method, elevation, BA and BAL were recognized as the most influential factors defining variation of tree diversity.
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    Assessing methods for comparing species diversity from disparate data sources: the case of urban and peri-urban forests
    Staudhammer, Christina L.; Escobedo, Francisco J.; Blood, Amy (Ecological Society of America, 2018-10)
    Multi-scale forest inventory and monitoring data are increasingly being used in studies assessing forest diversity, structure, disturbance, and carbon dynamics. Also, local-level urban forest inventories are providing plot data and protocols to study tree diversity and ecosystem services in urban forests worldwide. But, differences in the sampling methods underlying these disparate protocols and data sources is a non-trivial concern in formulating comparative analyses. We assess commonly used methods for comparing tree diversity in peri-urban and urban forests when available data have different sample sizes, plot sizes, and sampling intensities. We present methods for appropriately evaluating species richness, as well as methods for comparing species distributions via community data matrices. Using permanent plot data from the southeastern United States, we present a case study comparing urban and peri-urban forests along a north-south gradient, and assessing species richness and the ecological homogenization hypothesis. Our findings indicate that comparisons of tree species richness among communities, or forest types, are often inconclusive since commonly used sample sizes do not provide precise estimates of the number of species present. While the ecological homogenization hypotheses can be tested under conditions of unequal sampling effort, we suggest robust methods such as PERMANOVA and the Raup-Crick dissimilarity index. A framework for selecting appropriate methods is also discussed. As forests are increasingly being altered by anthropogenic drivers, future studies using disparate data sources must account for differences in measurements and sampling protocols in order to produce results that are both statistically defensible and useful for science-based management.
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    Assessing patterns of oak regeneration and C storage in relation to restoration-focused management, historical land use, and potential trade-offs
    Carter, David R.; Fahey, Robert T.; Dreisilker, Kurt; Bialecki, Margaret B.; Bowles, Marlin (2015-01-29)
    Restoration of composition, structure, and function in oak dominated ecosystems is the focus of management in temperate forests around the world. Land managers focused on oak ecosystem restoration are challenged by the legacy effects of complex land-use histories, urbanization, climate change, and potential stakeholder response to management. Trade-offs may exist between managing forests for climate mitigation (e.g., maximizing C storage or sequestration) and promoting shade-intolerant species historically associated with frequent or high-severity disturbances. This study assessed the potentially conflicting goals of sustained live biomass accrual and increased oak regeneration in the East Woods Natural Area at The Morton Arboretum in Lisle, IL, USA. We evaluated how biomass trends and oak regeneration were related to management regimes, land-use history, current stand structure and composition, and topoedaphic factors. Our results indicated no significant trade-off between sustained live biomass accrual and oak regeneration. Live biomass was increasing across the landscape (biomass increment averaged 18,186 kg ha-1 yr-1) and was not strongly related to differences in management or land-use history. Oak regeneration was rare, especially beyond the seedling stage (~226 seedlings and 9 saplings ha-11) and was also not strongly related to recent management. Our results indicate that even 20+ years of annual prescribed burning combined with understory thinning has failed to produce the open canopy conditions and high light availability that are necessary for successful oak recruitment. The absence of any trade-offs between biomass accrual and oak regeneration may, therefore, be largely related to the ineffectiveness of current management for promoting oak regeneration. More intensive management utilizing canopy manipulations could produce greater trade-offs, but is likely necessary to establish and release oak regeneration.
  • Assessing the extent and drivers of forest plantation establishment in Andhra Pradesh
    Wynne, Randolph H.; Thomas, Valerie A.; Gundimeda, Haripriya; Amacher, Gregory S.; Cobourn, Kelly M.; Köhlin, Gunnar (2017-07)
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    Assessing the transferability of statistical predictive models for leaf area index between two airborne discrete return LiDAR sensor designs within multiple intensely managed Loblolly pine forest locations in the south-eastern USA
    Sumnall, Matthew; Peduzzi, Alicia; Fox, Thomas R.; Wynne, Randolph H.; Thomas, Valerie A.; Cook, Bruce (2016-04)
    Leaf area is an important forest structural variable which serves as the primary means of mass and energy exchange within vegetated ecosystems. The objective of the current study was to determine if leaf area index (LAI) could be estimated accurately and consistently in five intensively managed pine plantation forests using two multiple-return airborne LiDAR datasets. Field measurements of LAI were made using the LiCOR LAI2000 and LAI2200 instruments within 116 plots were established of varying size and within a variety of stand conditions (i.e. stand age, nutrient regime and stem density) in North Carolina and Virginia in 2008 and 2013. A number of common LiDAR return height and intensity distribution metrics were calculated (e.g. average return height), in addition to ten indices, with two additional variants, utilized in the surrounding literature which have been used to estimate LAI and fractional cover, were calculated from return heights and intensity, for each plot extent. Each of the indices was assessed for correlation with each other, and was used as independent variables in linear regression analysis with field LAI as the dependent variable. All LiDAR derived metrics were also entered into a forward stepwise linear regression. The results from each of the indices varied from an R-2 of 0.33 (S.E. 0.87) to 0.89 (S.E. 0.36). Those indices calculated using ratios of all returns produced the strongest correlations, such as the Above and Below Ratio Index (ABRI) and Laser Penetration Index 1 ( LPI1). The regression model produced from a combination of three metrics did not improve correlations greatly (R-2 0.90; S.E. 0.35). The results indicate that LAI can be predicted over a range of intensively managed pine plantation forest environments accurately when using different LiDAR sensor designs. Those indices which incorporated counts of specific return numbers (e.g. first returns) or return intensity correlated poorly with field measurements. There were disparities between the number of different types of returns and intensity values when comparing the results from two LiDAR sensors, indicating that predictive models developed using such metrics are not transferable between datasets with different acquisition parameters. Each of the indices were significantly correlated with one another, with one exception (LAI proxy), in particular those indices calculated from all returns, which indicates similarities in information content for those indices. It can then be argued that LiDAR indices have reached a similar stage in development to those calculated from optical-spectral sensors, but which offer a number of advantages, such as the reduction or removal of saturation issues in areas of high biomass.
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    Automated Mapping of Typical Cropland Strips in the North China Plain Using Small Unmanned Aircraft Systems (sUAS) Photogrammetry
    Zhang, Jianyong; Zhao, Yanling; Abbott, A. Lynn; Wynne, Randolph H.; Hu, Zhenqi; Zou, Yuzhu; Tian, Shuaishuai (MDPI, 2019-10-10)
    Accurate mapping of agricultural fields is needed for many purposes, including irrigation decisions and cadastral management. This paper is concerned with the automated mapping of cropland strips that are common in the North China Plain. These strips are commonly 3–8 m in width and 50–300 m in length, and are separated by small ridges that assist with irrigation. Conventional surveying methods are labor-intensive and time-consuming for this application, and only limited performance is possible with very high resolution satellite images. Small Unmanned Aircraft System (sUAS) images could provide an alternative approach to ridge detection and strip mapping. This paper presents a novel method for detecting cropland strips, utilizing centimeter spatial resolution imagery captured by sUAS flying at low altitude (60 m). Using digital surface models (DSM) and ortho-rectified imagery from sUAS data, this method extracts candidate ridge locations by surface roughness segmentation in combination with geometric constraints. This method then exploits vegetation removal and morphological operations to refine candidate ridge elements, leading to polyline-based representations of cropland strip boundaries. This procedure has been tested using sUAS data from four typical cropland plots located approximately 60 km west of Jinan, China. The plots contained early winter wheat. The results indicated an ability to detect ridges with comparatively high recall and precision (96.8% and 95.4%, respectively). Cropland strips were extracted with over 98.9% agreement relative to ground truth, with kappa coefficients over 97.4%. To our knowledge, this method is the first to attempt cropland strip mapping using centimeter spatial resolution sUAS images. These results have demonstrated that sUAS mapping is a viable approach for data collection to assist in agricultural land management in the North China Plain.