@article {49876, title = {Hierarchial analysis of vegetation dynamics over 71 years: soil-rainfall interactions in a Chihuahuan Desert ecosystem}, journal = {Ecological Applications}, volume = {22}, year = {2012}, month = {04/2012}, pages = {909-926}, chapter = {909}, abstract = {

Proliferation of woody plants in grasslands and savannas is a persistent problem globally. This widely observed shift from grass to shrub dominance in rangelands worldwide has been heterogeneous in space and time largely due to cross-scale interactions among soils, climate, and land-use history. Our objective was to use a hierarchical framework to evaluate the relationship between spatial patterns in soil properties and long-term shrub dynamics in the northern Chihuahuan Desert of New Mexico, USA. To meet this objective, shrub patch dynamics from 1937 to 2008 were characterized at patch and landscape scales using historical imagery and a recent digital soils map. Effects of annual precipitation on patch dynamics on two soils revealed strong correlations between shrub growth on deep sandy soils and above-average rainfall years (r = 0.671, P = 0.034) and shrub colonization and below-average rainfall years on shallow sandy soils (r = 0.705, P = 0.023). Patch-level analysis of demographic patterns revealed significant differences between shrub patches on deep and shallow sandy soils during periods of above- and below-average rainfall. Both deep and shallow sandy soils exhibited low shrub cover in 1937 (1.0\% {\textpm} 2.3\% and 0.3\% {\textpm} 1.3\%, respectively [mean {\textpm} SD]) and were characterized by colonization or appearance of new patches until 1960. However, different demographic responses to the cessation of severe drought on the two soils and increased frequency of wet years after 1960 have resulted in very different endpoints. In 2008 a shrubland occupied the deep sandy soils with cover at 19.8\% {\textpm} 9.1\%, while a shrub-dominated grassland occurred on the shallow sandy soils with cover at 9.3\% {\textpm} 7.2\%. Present-day shrub vegetation constitutes a shifting mosaic marked by the coexistence of patches at different stages of development. Management implications of this long-term multi-scale assessment of vegetation dynamics support the notion that soil properties may constrain grassland remediation. Such efforts on sandy soils should be focused on sites characterized by near-surface water-holding capacity, as those lacking available water-holding capacity in the shallow root zone pose challenges to grass recovery and survival.

}, keywords = {aerial photography, Chihuahuan Desert, cross-scale linkages, ecological-state mapping, hierarchy theory, Jornada Basin LTER, New Mexico USA, object-based change detection, petrocalcic soil, prosopis glandulosa, shrub patch dynamics, shrub proliferation, soil depth}, doi = {10.1890/11-1193.1}, url = {/files/bibliography/12-026.pdf}, author = {Dawn M. Browning and Danielle Duni and Andrea S. Laliberte and A. Rango} } @article {49879, title = {Rangeland and pasture monitoring: an approach to interpretation of high-resolution imagery focused on observer calibration for repeatability}, journal = {Environmental Monitoring and Assessment}, volume = {184}, year = {2012}, month = {07/23/2011}, pages = {3789-3804}, chapter = {3789}, abstract = {

Collection of standardized assessment and monitoring data is critically important for supporting policy and management at local to continental scales. Remote sensing techniques, including image interpretation, have shown promise for collecting plant community composition and ground cover data efficiently. More work needs to be done, however, evaluating whether these techniques are sufficiently feasible, cost-effective, and repeatable to be applied in large programs. The goal of this study was to design and test an image-interpretation approach for collecting plant community composition and ground cover data appropriate for local and continental-scale assessment and monitoring of grassland, shrubland, savanna, and pasture ecosystems. We developed a geographic information system image-interpretation tool that uses points classified by experts to calibrate observers, including point-by-point training and quantitative quality control limits. To test this approach, field data and high-resolution imagery (\~{}3 cm ground sampling distance) were collected concurrently at 54 plots located around the USA. Seven observers with little prior experience used the system to classify 300 points in each plot into ten cover types (grass, shrub, soil, etc.). Good agreement among observers was achieved, with little detectable bias and low variability among observers (coefficient of variation in most plots \<0.5). There was a predictable relationship between field and image-interpreter data (R (2) \> 0.9), suggesting regression-based adjustments can be used to relate image and field data. This approach could extend the utility of expensive-to-collect field data by allowing it to serve as a validation data source for data collected via image interpretation.

}, keywords = {aerial photography, assessment and monitoring, image interpretation, large-scale, remote sensing, repeatability}, doi = {10.1007/s10661-011-2224-2}, url = {/files/bibliography/12-005.pdf}, author = {Danielle Duni and Jason W. Karl and Scott T. Schrader and Noemi Baquera and Jeffrey E. Herrick} } @proceedings {50045, title = {Feature selection methods for object-based classification of sub-decimeter resolution digital aerial imagery}, volume = {XXXVIII}, year = {2010}, pages = {4/C7}, address = {Ghent, Belgium}, abstract = {Due to the availability of numerous spectral, spatial, and contextual features, the determination of optimal features and class separabilities can be a time consuming process in object-based image analysis (OBIA). While several feature selection methods have been developed to assist OBIA, a robust comparison of the utility and efficiency of approaches could facilitate broader application. In this study, we tested feature selection methods and assessments of class separability for object-based classifications of arid land vegetation in the southwestern U.S. using sub-decimeter digital aerial imagery with a 6 cm ground resolved distance. Using Definiens Developer software, we evaluated 1) classification tree analysis (CTA), 2) feature space optimization (FSO), and 3) SEparability and THreshold (SEaTH). We assessed strengths, weaknesses and best uses for each approach using the criteria of ease of use, ability to rank and/or reduce input features, ability to obtain feature thresholds and class separation distances, and underlying statistical assumptions. We conclude that CTA is best suited for reducing a large number of input features, either for nearest neighbor classification or for deriving rules for rule-based classification. FSO is most appropriate for determining a suitable group of features relatively quickly, because it operates within the Definiens software. However, the features are not ranked and feature thresholds cannot be determined. SEaTH interfaces well with outputs from Definiens and is most appropriate for ranking input features based on class separation distances for two-class comparisons, but has the disadvantage of assuming normality, unlike the non-parametric CTA. All methods offered an objective approach for determining suitable features for classifications of hyperspatial aerial imagery. Limitations, assumptions, and appropriate uses for this and other datasets are discussed.}, keywords = {accuracy, aerial photography, classification, feature selection, high resolution, object-based image analysis (OBIA), vegetation}, url = {/files/bibliography/10-048.pdf}, author = {Andrea S. Laliberte and Dawn M. Browning and A. Rango} } @article {50044, title = {Hierarchical object-based classification of ultra-high-resolution digital mapping camera (DMC) imagery for rangeland monitoring and assessment}, journal = {Journal of Spatial Science}, volume = {55}, year = {2010}, month = {June 2010}, pages = {101-115}, chapter = {101}, abstract = {Ultra high resolution digital aerial photography has great potential to complement or replace ground measurements of vegetation cover for rangeland monitoring and assessment. We investigated object-based image analysis (OBIA) techniques for classifying vegetation in southwestern U.S. arid rangelands with 4 cm resolution digital aerial photography. We obtained high r-square values for image- and ground-based measures of percent cover (r-square values: 0.82-0.92). OBIA enabled us to automate the classification process and demonstrated potential for quantifying fine-scale land cover attributes with ultra high resolution imagery. This approach exhibits promise for nationwide application for monitoring grazing lands.}, keywords = {aerial photography, object-based image analysis, rangelands, vegetation classifications, very high resolution}, doi = {10.1080/14498596.2010.487853}, url = {/files/bibliography/10-023.pdf}, author = {Andrea S. Laliberte and Dawn M. Browning and Jeffrey E. Herrick and Peg Gronemeyer} } @conference {50042, title = {Object-based classification of hyperspatial digital mapping camera (DMC) imagery for potential integration into the National Resource Inventory (NRI) of grazing lands}, booktitle = {American Society for Photogrammetry and Remote Sensing (ASPRS) Annual Meeting}, year = {2010}, month = {April 26-30,2010}, address = {San Diego, CA}, abstract = {Land management agencies such as the Bureau of Land Management (BLM) and the Natural Resources Conservation Service (NRCS) are required to monitor and assess vegetation conditions across millions of acres of rangelands and grazing lands. Field-based assessments are very costly and inefficient over large areas; remote sensing offers the potential to increase the number of monitoring locations, automate the image classification process, and reduce monitoring costs. Hyperspatial digital aerial photography has great potential to complement or replace ground measurements of vegetation cover. We investigated object-based image analysis (OBIA) techniques for classifying vegetation in southwestern U.S. arid rangelands with 4 cm resolution digital aerial photography. We obtained high r-square values for image- and ground-based measures of percent cover (r-square values: 0.82-0.92). OBIA enabled us to automate the classification process by applying a process tree developed on one image iteratively to subsequent images of the same vegetation community. The ability to classify multiple images efficiently offers the potential to increase the precision of national level inventories by increasing sample locations and to reduce costs by requiring fewer personnel to obtain ground measurements. This approach has demonstrated potential for quantifying fine-scale land cover attributes with very high resolution digital imagery, and exhibits promise for nationwide application for monitoring grazing lands.}, keywords = {aerial photography, digital mapping camera, grazing lands, National Resource Inventory, object-based classification}, author = {Andrea S. Laliberte and Dawn M. Browning and Jeffrey E. Herrick and Peg Gronemeyer} } @article {50057, title = {Impact of flight regulations on effective use of unmanned aerial vehicles for natural resources applications}, journal = {Journal of Applied Remote Sensing}, volume = {4}, year = {2010}, pages = {043539}, abstract = {Unmanned Aerial Vehicles (UAVs) have great potential for rangeland assessment, monitoring, and management as has been shown by prior studies. Additionally, numerous other applications in natural resources have shown the value of using UAVs. In order to have UAVs become a dependable tool for public land management agencies in carrying out their government-mandated responsibilities, it is necessary to integrate UAVs into the National Airspace System (NAS). To achieve this, Federal Aviation Administration (FAA) regulations have to be followed to assure public safety. UAV operators need to know that the safety regulations which incorporate line of sight restrictions will slow progress towards an operational system and plan accordingly for the extra time necessary to prepare and complete flight missions. In the long term by following approved safety procedures, you will develop a UAV flight team that is capable of accomplishing missions anywhere in the United States and contribute to a totally integrated NAS comprised of manned and unmanned aircraft systems that can be used jointly for natural resources management. At the same time, it is hoped that FAA regulations will change with time based on the locale in which operations take place, especially when they include large, remote, sparsely populated areas, and based on the capabilities and experience of the UAV flight team being used.}, keywords = {aerial photography, civilian applications, FAA regulations, National Airspace System, rangeland management, Small unmanned aerial vehicles}, url = {/files/bibliography/10-021.pdf}, author = {A. Rango and Andrea S. Laliberte} } @article {50137, title = {Unmanned aerial vehicle-based remote sensing for rangeland assessment, monitoring, and management}, journal = {Journal of Applied Remote Sensing}, volume = {3}, year = {2009}, month = {08/2009}, pages = {033542}, abstract = {

Rangeland comprises as much as 70\% of the Earth\’s land surface area. Much of this vast space is in very remote areas that are expensive and often impossible to access on the ground. Unmanned Aerial Vehicles (UAVs) have great potential for rangeland management. UAVs have several advantages over satellites and piloted aircraft: they can be deployed quickly and repeatedly; they are less costly and safer than piloted aircraft; they are flexible in terms of flying height and timing of missions; and they can obtain imagery at sub-decimeter resolution. This hyperspatial imagery allows for quantification of plant cover, composition, and structure at multiple spatial scales. Our experiments have shown that this capability, from an off-the-shelf mini-UAV, is directly applicable to operational agency needs for measuring and monitoring. For use by operational agencies to carry out their mandated responsibilities, various requirements must be met: an affordable and reliable platform; a capability for autonomous, low altitude flights; takeoff and landing in small areas surrounded by rugged terrain; and an easily applied data analysis methodology. A number of image processing and orthorectification challenges have been or are currently being addressed, but the potential to depict the land surface commensurate with field data perspectives across broader spatial extents is unrivaled.

}, keywords = {aerial photography, autonomous flight, indicators, rangeland applications, Small unmanned aerial vehicles}, doi = {10.1117/1.3216822}, url = {/files/bibliography/09-025.pdf}, author = {A. Rango and Andrea S. Laliberte and Jeffrey E. Herrick and Craig Winters and Kris Havstad and Caitriana Steele and Dawn M. Browning} } @proceedings {50233, title = {A procedure for orthorectification of sub-decimeter resolution imagery obtained with an unmanned aerial vehicle (UAV)}, year = {2008}, month = {April 28, 2009}, address = {Portland, OR}, abstract = {Digital aerial photography acquired with unmanned aerial vehicles (UAVs) has great value for resource management due to the flexibility and relatively low cost for image acquisition, and very high resolution imagery (5 cm) which allows for mapping bare soil and vegetation types, structure and patterns in great detail. While image acquisition is relatively straightforward, the creation of orthorectified, GIS-ready image mosaics presents multiple challenges. Those include relatively small image footprints, image distortion due to the use of low-cost digital cameras, difficulty in locating ground control points and in automatic generation of tie points, and relatively large errors in exterior orientation (camera position and attitude information from the UAV{\textquoteright}s GPS/IMU). We developed an automated procedure to improve the accuracy of the exterior orientation by matching the UAV images to an orthorectified reference image. Using the UAV reported exterior orientation and camera geometry, combined with the reference image and DEM, the algorithm simulates image acquisition and then computes the covariance between camera image and simulated image pixels. With this evaluation function, a heuristic search algorithm finds successive improvements to the external orientation, ultimately producing a corrected exterior orientation that allows orthorectification with minimal input of tie points and/or ground control points. The RMS error for a 5-cm resolution, 257-image mosaic was 48 cm. Cost and turnaround time for production of orthorectified mosaics from UAV imagery are considerable reduced due to less time and money spent on ground control point and manual tie point collection.}, keywords = {aerial photography, digital, high resolution, imagery, UAV}, url = {/files/bibliography/08-047.pdf}, author = {Andrea S. Laliberte and Craig Winters and A. Rango} } @article {50260, title = {Role of aerial photos in compiling a long-term remote sensing data set}, journal = {Journal of Applied Remote Sensing}, volume = {2}, year = {2008}, month = {10/2008}, pages = {023541}, abstract = {

Long-term data sets are important in the fields of ecology, hydrology, rangeland science, and geography. Remote sensing is an especially important component of such studies when spatial and temporal capabilities are important considerations. In many cases, satellite remote sensing is not adequate because of resolution or length of observation considerations. However, aerial photography, which extends back into the mid 1930s, is often overlooked. In order to find relevant imagery, considerable effort needs to be expended because the aerial photos over a particular study area can be scattered in a large number of archives across the country. Once the photos are assembled, digital scanning, proper documentation, storage, and a searchable data base are necessary to make easy and effective use of the aerial photos. The aerial photo data are of immense value to researchers, natural resource managers, students, and the general public.

}, keywords = {aerial photography, ecology, historic landscape legacies, rangelands, vegetation change}, doi = {10.1117/1.3009225}, url = {/files/bibliography/08-043.pdf}, author = {A. Rango and Andrea S. Laliberte and Craig Winters} } @conference {50280, title = {Bulldozers, mental models, and aerial photography: Geographies of long-term private restoration on semi-arid rangelands}, booktitle = {Association of American Geographers Annual Meeting}, series = {Association of American Geographers}, year = {2008}, month = {April 14-19, 200}, pages = {18115}, abstract = {Private efforts to restore degraded Southwestern desert grasslands have been under way at least since the 1920s, but their effects are little studied and poorly understood. Most are considered simply to have failed, or to have been swamped by the effects of climate and fire suppression. These judgments may need to be reevaluated on longer temporal scales, however, in light of evidence that semiarid rangeland systems are strongly determined by "slow" variables and thresholds of nonlinear change. Drought, erosion, fire, grazing and other disturbances may leave historical legacies that persist on scales of decades or longer, and management interventions may require comparable periods of time to show significant responses in target organisms. Long-term data have been collected for a handful of government research sites, and repeat photography and aerial photographs have enabled analysis of broader patterns of vegetation change, but historical information about management of private ranches has been almost wholly lacking. We use a combination of interviews, archival records, aerial photography, remote sensing and GIS to evaluate restoration efforts on the Elbrock Ranch in southwestern New Mexico over the past seventy years. This research contributes to efforts to historicize state-and-transition models in rangeland ecology, and to understand ranchers{\textquoteright}"mental models" as slow variables in their own right. It also enables us to see beyond dualisms of human/natural and pristine/degraded to geographies of restoration on very large spatial and temporal scales.}, keywords = {aerial photography, bulldozers, private, restoration}, author = {N. F. Sayre and Whelan, M. and E.L. Fredrickson and Brandon T Bestelmeyer} } @article {50683, title = {Object-oriented image analysis for mapping shrub encroachment from 1937-2003 in southern New Mexico}, journal = {Remote Sensing of Environment}, volume = {93}, year = {2004}, month = {September 20, 20}, pages = {198-210}, abstract = {

Shrub encroachment into arid and semiarid grasslands in the southwestern United States is of concern because increased shrub cover leads to declines in species diversity, water availability, grazing capacity, and soil organic matter. Although it is well known that shrubs have increased over time, we have little quantitative information related to the nonlinear nature of this vegetation change over a particular time period. On the USDA-ARS Jornada Experimental Range and the adjacent Chihuahuan Desert Rangeland Research Center (CDRRC)(New Mexico State University) in southern New Mexico, shrub increase has been measured with various ground survey techniques extending back to 1858. For this study, we used 11 aerial photos taken between 1937 and 1996 that covered a 150-ha study area and had sufficient resolution for shrub detection. A QuickBird satellite image provided coverage for 2003. We used image segmentation and object-based classification to monitor vegetation changes over time. Shrub cover increased from 0.9\% in 1937 to 13.1\% in 2003, while grass cover declined from 18.5\% to 1.9\%. Vegetation dynamics reflected changes in precipitation patterns, in particular effects of the 1951-1956 drought. Accuracy assessment showed that shrub and grass cover was underestimated due to the constraint of the pixel size. Eighty-seven percent of all shrubs \>2m2 were detected. The use of object-based classification has advantages over pixel-based classification for the extraction of shrubs from panchromatic aerial and high-resolution satellite imagery. Incorporating both spectral and spatial image information approximates the way humans interpret information visually from aerial photos but has the benefit of an automated classification routine. Combining several scales of analysis in a hierarchical segmentation method is appropriate in an ecological sense and allowed for determining shrub density in coarser level classes. Despite encountering difficulties in analyzing a greatly varying aerial photo dataset, including variability in spectral and spatial resolutions, moisture conditions, time of year of observation, and appearance of grass cover, aerial photos provide an invaluable historic record for monitoring shrub encroachment into a desert grassland.

}, keywords = {aerial photography, desert grassland, mapping, object-based classification, satellite image, segmentation, shrub encroachment}, doi = {10.1016/j.rse.2004.07.011}, url = {/files/bibliography/04-053.pdf}, author = {Andrea S. Laliberte and A. Rango and Kris Havstad and Paris, J.F. and Reldon F. Beck and R.P. McNeely and Amy L. Gonzalez} } @article {50812, title = {The utility of historical aerial photographs for detecting and judging the effectiveness of rangeland remediation treatments}, journal = {Environmental Practice}, volume = {5}, number = {2}, year = {2003}, month = {June 1, 2003}, pages = {107-118}, abstract = {

Aerial photos are a type of remote sensing data especially valuable for rangeland applications. This type of data has advantages that include relative ease of interpretation and acquisition, inexpensiveness, high resolution (1-2m), and providing a common reference for communication among those involved in rangeland management. Additionally, air photos are especially well suited for analysis of historical rangeland remediation treatments because acquisition of widespread aerial photographic coverage began during the 1930{\textquoteright}s. Several types of treatments are easily identified and monitored over time, including contour terraces, brush water spreaders, rootplow seeding, water ponding dikes, shrub removal by grubbing, and grazing restrictions. The use of aerial photos allows us the opportunity to recreate the management history of rangeland and to serve as a point of departure for involvement in more sophisticated satellite-based remote sensing systems.

}, keywords = {aerial photography, air photo archives, Civilian Conservation Corps, Jornada Basin, rangeland, remediation treatments, remote sensing}, doi = {10.1017/S1466046603031065}, url = {/files/bibliography/03-020.pdf}, author = {A. Rango and Kris Havstad} } @article {50934, title = {Remote sensing documentation of historic rangeland remediation treatments in southern New Mexico}, journal = {Journal of Arid Environments}, volume = {50}, number = {4}, year = {2002}, note = {Entered in ARIS at Beltsville July 7, 2001}, month = {April 1, 2002}, pages = {549-572}, abstract = {

The Jornada Experimental Range and the New Mexico State University Chihuahuan Desert Rangeland Research Center are fruitful areas to study the long term effects of rangeland remediation treatments which started in the 1930s. A number of diverse manipulations were completed under the direction of federal agency and university scientist, and abundant remote sensing imagery is available to assist in relocating the treatments and evaluating their success. This is particularly important because few of the treatments were maintained following the loss of scientific personnel coinciding with the start of World War II, and most records of Civilian Conservation Corps scientific work were lost with the disbanding of the agency in 1942. Aerial photography, which was systematically used to image the United States beginning in the 1930s, can be used to identify types of treatments, measure area coverage, estimate longevity, and help contour terraces, brush hwater spreaders, strips grubbed free of shrubs (despite the fact that thes strips have remained visible for 65 years), and mechanical rootplowing and seeding. Distinct positive, long-term vegetation responses could be seen in aerial photos and existing conventional records that experimental manipulation of rangelands has often been ineffective on the landscape scale because treatments are not performed over large enough contiguous area and hydrological and ecological processes overwhelm the treatments. In addition, treatments are not maintained over time, treatment evaluation periods are sometimes too short, multipurpose treatments are not used to maximize effects, and treatments are often not located in appropriate sites.

}, keywords = {aerial photography, New Mexico, rangeland remediation, remote sensing, shrub removal, water spreading}, doi = {10.1006/jare.2001.0865}, url = {/files/bibliography/02-070.pdf}, author = {A. Rango and Sarah Goslee and Jeffrey E. Herrick and M. Chopping and Kris Havstad and L. Huenneke and Gibbens, Robert P. and Reldon F. Beck and R.P. McNeely} } @article {JRN54841, title = {Assessment of a method for mapping woody plant density in a grassland matrix}, journal = {Journal of Arid Environments}, volume = {38}, year = {1998}, month = {February 1998}, pages = {269-282}, chapter = {269}, abstract = {

Determining patterns of land degradation, and by inference the ecological processes at play, is critical to designing and implementing strategies and tactics to halt degrading practices and restore already degraded areas. In this paper we describe the application of a new image analysis technique to determine the presence and density of shrubs in a grassland matrix and evaluate its use for assessing rates and patterns of shrub increase, a common form of land degradation in rangelands throughout the world. By analysing a series of images derived from aerial photography to identify and separate objects (shrubs) in progressive steps, we were able to detect accurately individual shrubs with canopies greater than 9\ m2(about 85\% of the sample population). The method also was moderately successful in predicting canopy area of individual trees. This approach offers land managers and policy-makers a tool for defining both temporal patterns and rates of shrub increase as well as for defining the current extent of an invasion as a basis for targeting control technologies.

}, keywords = {aerial photography, density slicing, Geographic Information System, image analysis, remote sensing, shrub invasion}, doi = {10.1006/jare.1997.0325}, url = {/files/bibliography/770.pdf}, author = {Grant Whiteman and Joel R. Brown} }