Cristina Gómez

Bringing an ecological view of change to Landsat-based remote sensing

When characterizing the processes that shape ecosystems, ecologists increasingly use the unique perspective offered by repeat observations of remotely sensed imagery. However, the concept of change embodied in much of the traditional remote-sensing literature was primarily limited to capturing large or extreme changes occurring in natural systems, omitting many more subtle processes of interest to ecologists. Recent technical advances have led to a fundamental shift toward an ecological view of change. Although this conceptual shift began with coarser-scale global imagery, it has now reached users of Landsat imagery, since these datasets have temporal and spatial characteristics appropriate to many ecological questions. We argue that this ecologically relevant perspective of change allows the novel characterization of important dynamic processes, including disturbances, longterm trends, cyclical functions, and feedbacks, and that these improvements are already facilitating our understanding of critical driving forces, such as climate change, ecological interactions, and economic pressures.

A history of habitat dynamics: Characterizing 35 years of stand replacing disturbance

Landscape change, specifically habitat loss and modification, is thought to have an impact on the health, productivity, distribution, and survival of grizzly bears (Ursus arctos L.). Although grizzly bears may preferentially seek out areas of anthropogenic disturbances for foraging opportunities, research has found that grizzly bears experience greater mortality in these areas as a result of increased human access. Additional insights on the location and rates of anthropogenic-driven landscape change are required to better understand related impacts upon grizzly bears. In this study, a time series of 14 Landsat MSS, TM, and ETM+ images were used to retrospectively document and quantify the rate of landscape change over a 35-year period from 1973 to 2008 in a 13507km2 analysis area in western Alberta, Canada. The study area is located within a larger region that contains the highest density of grizzly bears in Alberta and has experienced increasingly intensive forest harvesting and oil and gas exploration activities during this period. To accommodate the differing spectral channels from MSS to TM/ETM+ sensors, the arctangent of the angle of the Tasseled Cap greenness-to-brightness components was computed for each image year, with sequential image pairs differenced and a threshold applied to identify stand-replacing disturbance events. Results indicated that 11% of the analysis area experienced some form of stand-replacing disturbance (e.g., cutblocks, roads, oil and gas well sites, seismic lines, power lines, pipelines, blowdown) between 1973 and 2008. The greatest proportion of this change (by area) occurred between 2004 and 2006 (24%), while the lowest proportion occurred between 2000 and 2001 (2%). Although the number of change events has fluctuated over time, with a minimum of 2888 change events between 1976 and 1978 (2%) and a maximum of 36623 change events between 2004 and 2006 (29%), the mean size of change events has decreased over time: prior to 1995, mean event size was greater than 1.5ha; after 1995, it was less than 1.5ha. The annual rate of change was greatest between 2004 and 2006 (−1.25%), and lowest between 1981 and 1990 (−0.04%). Consideration of changes within the context of units relevant to grizzly bear management (i.e., grizzly bear watershed units and core or secondary habitat areas) indicate that the amount and rate of change was not spatially or temporally uniform across the study area. While the average change event size has decreased over time, the increasing number of change events has resulted in a larger aggregate area of change in more recent years. Landsat imagery provided a large-area, synoptic, and consistent characterization of 35years of stand-replacing disturbance in our study area, providing information that enables an improved understanding of the complex interactions between grizzly bear distribution, abundance, health, survival, and habitat.

Modeling Forest Structural Parameters in the Mediterranean Pines of Central Spain using QuickBird-2 Imagery and Classification and Regression Tree Analysis (CART)

Forest structural parameters such as quadratic mean diameter, basal area, and number of trees per unit area are important for the assessment of wood volume and biomass and represent key forest inventory attributes. Forest inventory information is required to support sustainable management, carbon accounting, and policy development activities. Digital image processing of remotely sensed imagery is increasingly utilized to assist traditional, more manual, methods in the estimation of forest structural attributes over extensive areas, also enabling evaluation of change over time. Empirical attribute estimation with remotely sensed data is frequently employed, yet with known limitations, especially over complex environments such as Mediterranean forests. In this study, the capacity of high spatial resolution (HSR) imagery and related techniques to model structural parameters at the stand level (n = 490) in Mediterranean pines in Central Spain is tested using data from the commercial satellite QuickBird-2. Spectral and spatial information derived from multispectral and panchromatic imagery (2.4 m and 0.68 m sided pixels, respectively) served to model structural parameters. Classification and Regression Tree Analysis (CART) was selected for the modeling of attributes. Accurate models were produced of quadratic mean diameter (QMD) (R 2 = 0.8; RMSE = 0.13 m) with an average error of 17% while basal area (BA) models produced an average error of 22% (RMSE = 5.79 m 2 /ha).

Characterizing 25 years of change in the area, distribution, and carbon stock of Mediterranean pines in Central Spain

Mediterranean pines are subject to continuous change under the influence of natural and human factors. Remotely sensed data provide a means to characterize these changes over large areas. In this study we used a time series of Landsat imagery to capture 25 years (1984–2009) of change in the pine-dominated forests of the Central Range in Spain. Object-based image analysis methods were used to identify landscape-level changes in the area and the distribution of forests. We also propose that in the absence of disturbance, biomass accrual is occurring (or depletion in cases where removal is evident) and may be related to changes to the carbon stock; we describe the detected spectral changes in terms of biomass changes as the carbon stocking process. The primary inputs for the identification of changes in the area and distribution of pine stands were Landsat bands 3, 4 and 5 and the Tasseled Cap Angle (TCA) – a metric derived from the greenness and brightness components of the Tasseled Cap Transformation (TCT). In the identification of carbon stocking processes the temporal derivative of the TCA, the Process Indicator (PI), was used to inform on the rate and directionality of the change present. Our results show that the total area of pine forest has increased by 40%, from 1211 km2 to 1698 km2, during this period, with a variable rate of change. The distribution of pine-dominated forest has changed as well: there is an area of 765 km2 permanently covered with pines and 945 km2 found to be temporarily occupied. Following the logic of carbon stocking processes, our findings show that at the end of the analysis period, 20% of the potential pine area is increasing its carbon stock and 40% of this area is experiencing a decrease.

Forest structural diversity characterization in Mediterranean pines of central Spain with QuickBird-2 imagery and canonical correlation analysis

Variation in forest structure provides information on vegetation complexity and provides insights on biodiversity. Characterizing forest structural diversity with remotely sensed data supports reporting, monitoring, and policy development. We explored the relationship between forest structural diversity in Mediterranean pines of the Spanish Central Range and variables derived from imagery captured with a commercial high spatial resolution satellite (QuickBird-2; with pixels sided 2.4 m multispectral and 0.68 m panchromatic). To combine multiple aspects of tree conditions at a stand level, “structural diversity” was characterized at the plot level (N = 1022) as a linear combination of the median of absolute differences of individual trees’ bole diameter, height, and crown diameter measured on the field from the local median equivalents. Spectral reflectance variations in the visible and near-infrared, as well as image co-occurrence texture metrics from the panchromatic imagery at various window sizes were generated. All relationships to image-derived values were assessed against circular 0.3 ha areas corresponding with the field measured plots. Canonical correlation analysis aided in identification of combinations of reflectance and texture metrics most highly related with forest structural diversity (R = 0.89). Reflectance diversity was found to be more important than co-occurrence texture features in describing forest structural diversity when forest structure was limited (R = 0.47 vs. R = 0.39), whereas texture was more informative to the model when the forest structural diversity was high (R = 0.88 vs. R = 0.63), relating more complex forest conditions. Our results, although empirically defined by the local conditions and image acquisition characteristics, demonstrated the potential in high spatial resolution imagery for description of forest structural diversity in forests of the Mediterranean environment, especially important for Spain where a national high spatial resolution image data base has been collected.

Barrier island geomorphology, hydrodynamic modelling, and historical shoreline changes: an example from South Uist and Benbecula, Scottish Outer Hebrides

Abstract Dawson, A.G.; Gómez, C.; Ritchie, W.; Batstone, C.; Lawless, M.; Rowan, J.S.; Dawson, S.; Mcilveny, J.; Bates, R., and Muir, D., 2012. Barrier island geomorphology, hydrodynamic modelling, and historical shoreline changes: an example from South Uist and Benbecula, Scottish Outer Hebrides. A partly quantitative reconstruction is provided of the evolution of Gualan Island, a barrier island located between South Uist and Benbecula in the Scottish Outer Hebrides, using historical maps, aerial photographs, and Lidar (light detection and ranging) data. Geomorphological changes over the last approximately 200 years are described together with quantitative changes in the dimension of the barrier island, including rates of shoreline retreat. A series of digital terrain models (DTMs) provided the boundary conditions for a two-dimensional (2D) ocean circulation tide-surge model simulating water level and wave conditions associated with a highly destructive storm that took place during January 2005. During this storm event, the central part of the barrier island was overtopped by waves. Validating the hydrodynamic model against eye-witness and field evidence obtained after the 2005 storm allowed simulation of a range of potential future breaching scenarios. Thus with the same storm conditions a large barrier breach 500 m wide would result in wave heights rising by 0.8–0.9 m on hitherto sheltered shorelines.

Small unmanned airborne systems to support oil and gas pipeline monitoring and mapping

Oil and gas transmission pipelines require monitoring for maintenance and safety, to prevent equipment failure and accidents. Unmanned aerial vehicles (UAVs) technology is emerging as an opportunity to supplement current monitoring systems. Small UAV technological solutions are flexible and adaptable and with a demonstrated capacity to obtain valuable data at small to medium spatial scales. Systematic surveys of extensive areas are better completed with fixed-wing platforms and automatic flight design, whilst multirotor platforms provide flexibility in shorter and localized inspection missions. The type of sensor carried by an aerial platform determines the sort of data acquired and the obtainable information; sensors also determine the need for specific mechanical designs and the provision of energy on-board required from the system. UAV systems prototyped to monitor pipelines are reviewed in this paper, and a number of monitoring scenarios are proposed and illustrated. Notwithstanding difficulties encountered in the generalization of use for civilian applications, small UAVs have demonstrated, through research and operational cases, the capacity to support the inspection and monitoring of oil and gas pipelines.

Integrated object-based spatiotemporal characterization of forest change from an annual time series of Landsat image composites

Abstract Identifying and mapping the location, extent, severity, and causal agent of forest change events is necessary for obtaining a wide range of information. Using 6 ecologically representative test sites (each ∼ 800 km2) in the province of Saskatchewan, Canada, for the period 1998–2012, our objective was to prototype an object-based approach for identifying spectral change features, filling data gaps in Landsat reflectance annual best-available-pixel (BAP) composites, and attributing change processes to the derived stand-like spatial objects. The tasseled cap angle (TCA), which combines information from the visible, near-infrared, and midinfrared, enabled the description of landscape condition and its temporal derivative, the process indicator (PI), relates the rate and directionality of change at the landscape level. Data gaps, as well as anomalous values identified using time-series similarity analysis with dynamic time warping and cross-correlation measures, were replaced by spatiotemporal interpolation, resulting in annual proxy composites with no missing values. An assessment of proxy values against surface reflectance values indicated high agreement for reflectance bands (R = 0.79–0.96, RMSE = 0.005–0.021) and for TCA (R = 0.93, RMSE = 0.005), and a decrease in reliability of the proxy value as the size of the spatiotemporal gap increased, with longer temporal gaps having a greater impact on infill reliability than larger spatial gaps. Distinctive change dynamics of the sample sites were captured, demonstrating a capacity to simultaneously identify low and high magnitude changes as well as positive (e.g., growth) and negative (e.g., wildfire) trajectories using the PI. The approach presented herein provides a robust option for monitoring forest change by simultaneously describing state and ongoing change processes.

Shoreline Change and Coastal Vulnerability Characterization with Landsat Imagery: A Case Study in the Outer Hebrides, Scotland

Abstract Observation of cause–effect patterns of change in coastal environments provides insights into vulnerable areas and supports prediction and adaptation to flooding and erosion. Historic and periodic (6–8 year intervals) imagery from the Landsat archive is used to investigate transformations in the Atlantic coast of two Scottish islands over the period 1989–2011. Supervised classification of spectrally normalized images followed by change detection and spatial analysis reveals the patterns of change and the location of the most dynamic coastal areas. Quantitative measures of recent shifts and movement rates of relevant coastal lines, such as the lower limit of land-based vegetation, are assessed with the Digital Shoreline Analysis System. While very low rates are indicated for horizontal changes in the position of the lower limit of land-based vegetation (0.3 m y−1), specific areas have been subjected to high rates of coastal progradation as well as erosion (e.g. 2.5 m y−1 at Stilligarry). Information derived from satellite data supports the characterization of geomorphologically dynamic coasts at regional scales. With a rich and open access archive of imagery, a commitment to continuity, and compatibility with the Earth observation missions of other space programs, the Landsat mission offers useful and otherwise unavailable data for monitoring of coastal areas.

Changing Trends of Biomass and Carbon Pools in Mediterranean Pine Forests

The amount of biomass in forest ecosystems is critical information for global carbon cycle modelling. Determination of forest function as a sink or source of carbon is likewise relevant for both scientific applications and policy formulation. The quantity and function of forest biomass in the global carbon cycle is dynamic and changes as a result of natural and anthropogenic processes. This dynamism necessitates monitoring capacity that enables the characterization of changes in forest biomass over time and space. By combining field inventory and remotely sensed data, it is possible to characterize the quantity of biomass for a single date, or to characterize trends in quantity and function of forest biomass through time. Field inventory data provides accurate information for calibration of spatially extensive remotely sensed data models and for model validation as well. Historical, repeat measures of the same field plots facilitate the estimation of temporal trends in biomass accrual or removal, as well as carbon pooling processes. Remotely sensed data enable the inference of trends over large areas, and historical data archives can support retrospective analyses and the establishment of a baseline for future monitoring efforts. This chapter describes some of the opportunities provided by synergies between field measures and remotely sensed data for biomass and carbon assessment over large areas, and describes a case study in the Mediterranean pines of Spain, in which biomass and carbon pooling for the period 1984 to 2009 are estimated with a time series of Landsat imagery supported with data from the Spanish National Forest Inventory.