MapSnap System to Perform Vector-to-Raster Fusion

As the availability of geospatial data increases, there is a growing need to match these datasets together. However, since these datasets often vary in their origins and spatial accuracy, they frequently do not correspond well to each other, which create multiple problems. To accurately align with imagery, analysts currently either: 1) manually move the vectors, 2) perform a labor-intensive spatial registration of vectors to imagery, 3) move imagery to vectors, or 4) redigitize the vectors from scratch and transfer the attributes. All of these are time consuming and labor-intensive operations. Automated matching and fusing vector datasets has been a subject of research for years, and strides are being made. However, much less has been done with matching or fusing vector and raster data. While there are initial forays into this research area, the approaches are not robust. The objective of this work is to design and build robust software called MapSnap to conflate vector and image data in an automated/semi-automated manner. This paper reports the status of the MapSnap project that includes: (i) the overall algorithmic approach and system architecture, (ii) a tiling approach to deal with large datasets to tune MapSnap parameters, (iii) time comparison of MapSnap with re-digitizing the vectors from scratch and transfer the attributes, and (iv) accuracy comparison of MapSnap with manual adjustment of vectors. The paper concludes with the discussion of future work including addressing the general problem of continuous and rapid updating vector data, and fusing vector data with other data

Evaluation of Cumulative Ecosystem Response to Restoration Projects in the Lower Columbia River and Estuary, 2010

This is the seventh and final annual report of a project (2004–2010) addressing evaluation of the cumulative effects of habitat restoration actions in the 235-km-long lower Columbia River and estuary. The project, called the Cumulative Effects (CE) study, was conducted for the U.S. Army Corps of Engineers Portland District by a collaboration of research agencies led by the Pacific Northwest National Laboratory. We achieved the primary goal of the CE study to develop a methodology to evaluate the cumulative effects of habitat actions in the Columbia Estuary Ecosystem Restoration Program. We delivered 1) standard monitoring protocols and methods to prioritize monitoring activities; 2) the theoretical and empirical basis for a CE methodology using levels-of-evidence; 3) evaluations of cumulative effects using ecological relationships, geo-referenced data, hydrodynamic modeling, and meta-analyses; and 4) an adaptive management process to coordinate and coalesce restoration efforts in the LCRE. A solid foundation has been laid for future comprehensive evaluations of progress made by the Columbia Estuary Ecosystem Restoration Program to understand, conserve, and restore ecosystems in the lower Columbia River and estuary

Analysis and Mapping of Vegetation and Habitat for the Sheldon National Wildlife Refuge

The Lakeview, Oregon, office of the U.S. Fish and Wildlife Service (USFWS) contracted Pacific Northwest National Laboratory to classify vegetation communities on Sheldon National Wildlife Refuge in northeastern Nevada. The objective of the mapping project was to provide USFWS refuge biologists and planners with detailed vegetation and habitat information that can be referenced to make better decisions regarding wildlife resources, fuels and fire risk, and land management. This letter report describes the datasets and methods used to develop vegetation cover type and shrub canopy cover maps for the Sheldon National Wildlife Refuge. The two map products described in this report are (1) a vegetation cover classification that provides updated information on the vegetation associations occurring on the refuge and (2) a map of shrub canopy cover based on high-resolution images and field data

Analysis and Mapping of Vegetation and Habitat for the Hart Mountain National Antelope Refuge

The Lakeview, Oregon, office of the U.S. Fish and Wildlife Service (USFWS) contracted Pacific Northwest National Laboratory to classify vegetation communities on Hart Mountain National Antelope Refuge in northeastern Nevada. The objective of the mapping project was to provide USFWS refuge biologists and planners with detailed vegetation and habitat information that can be referenced to make better decisions regarding wildlife resources, fuels and fire risk, and land management. This letter report describes the datasets and methods used to develop vegetation cover type and shrub canopy cover maps for the Hart Mountain National Antelope Refuge. The two map products described in this report are 1) a vegetation cover classification that provides updated information on the vegetation associations occurring on the refuge and 2) a map of shrub canopy cover based on high-resolution images and field data

Landscape Measures of Rangeland Condition in the BLM Owyhee Pilot Project: Shrub Canopy Mapping, Vegetation Classification, and Detection of Anomalous Land Areas

In 2006, the BLM tasked PNNL to collaborate in research being conducted under the Owyhee Uplands Pilot Project to assess rangeland condition. The objective of this effort was to provide Owyhee Uplands Pilot Project with a sophisticated suite of data and tools to assist in evaluating the health and condition of the Owyhee Uplands study area. We focused on three technical areas. The first involved enhancing existing algorithms to estimate shrub canopy cover in the Lower Reynolds Creek Watershed. The second task involved developing and applying a strategy to assess and compare three vegetation map products for the Idaho portion of the Owyhee study area. The third task developed techniques and data that can be used to identify areas exhibiting anomalous rangeland conditions (for example exotic plants or excessive bare soil exposure). This report documents the methods used, results obtained, and conclusions drawn

Rapid Spaceborne Mapping of Wildfire Retardant Drops for Active Wildfire Management

Aerial application of fire retardant is a critical tool for managing wildland fire spread. Retardant applications are carefully planned to maximize fire line effectiveness, improve firefighter safety, protect high-value resources and assets, and limit environmental impact. However, topography, wind, visibility, and aircraft orientation can lead to differences between planned drop locations and the actual placement of the retardant. Information on the precise placement and areal extent of the dropped retardant can provide wildland fire managers with key information to (1) adaptively manage event resources, (2) assess the effectiveness of retardant slowing or stopping fire spread, (3) document location in relation to ecologically sensitive areas; and perform or validate cost-accounting for drop services. This study uses Sentinel-2 satellite data and commonly used machine learning classifiers to test an automated approach for detecting and mapping retardant application. We show that a multiclass model (retardant, burned, unburned, and cloud artifact classes) outperforms a single-class retardant model and that image differencing (post-application minus pre-application) outperforms single-image models. Compared to the random forest and support vector machine, the gradient boosting model performed the best with an overall accuracy of 0.88 and an F1 Score of 0.76 for fire retardant, though results were comparable for all three models. Our approach maps the full areal extent of the dropped retardant within minutes of image availability, rather than linear representations currently mapped by aerial GPS surveys. The development of this capability allows for the rapid assessment of retardant effectiveness and documentation of placement in relation to sensitive environments

Assessment of Technologies Used to Characterize Wildlife Populations in the Offshore Environment

Wind energy development in the offshore environment can have both direct and indirect effects on wildlife, yet little is known about most species that use near-shore and offshore waters due in part to the difficulty involved in studying animals in remote, challenging environments. Traditional methods to characterize offshore wildlife populations include shipboard observations. Technological advances have provided researches with an array of technologies to gather information about fauna from afar. This report describes the use and application of radar, thermal and optical imagery, and acoustic detection technologies for monitoring birds, bats, and marine mammals in offshore environments

High-Resolution Image Products Acquired from Mid-Sized Uncrewed Aerial Systems for Land–Atmosphere Studies

We assess the viability of deploying commercially available multispectral and thermal imagers designed for integration on small uncrewed aerial systems (sUASs, <25 kg) on a mid-size Group-3-classification UAS (weight: 25–600 kg, maximum altitude: 5486 m MSL, maximum speed: 128 m/s) for the purpose of collecting a higher spatial resolution dataset that can be used for evaluating the surface energy budget and effects of surface heterogeneity on atmospheric processes than those datasets traditionally collected by instrumentation deployed on satellites and eddy covariance towers. A MicaSense Altum multispectral imager was deployed on two very similar mid-sized UASs operated by the Atmospheric Radiation Measurement (ARM) Aviation Facility. This paper evaluates the effects of flight on imaging systems mounted on UASs flying at higher altitudes and faster speeds for extended durations. We assess optimal calibration methods, acquisition rates, and flight plans for maximizing land surface area measurements. We developed, in-house, an automated workflow to correct the raw image frames and produce final data products, which we assess against known spectral ground targets and independent sources. We intend this manuscript to be used as a reference for collecting similar datasets in the future and for the datasets described within this manuscript to be used as launching points for future research

PACIFIC NORTHWEST REGIONAL COLLABORATORY ANNUAL REPORT FOR SYNERGY VII (2007)

During this final year of the Pacific Northwest Regional Collaboratory we focused significantly on continuing the relationship between technical teams and government end-users. The main theme of the year was integration. This took the form of data integration via our web portal and integration of our technologies with the end users. The PNWRC's technical portfolio is based on EOS strategies, and focuses on 'applications of national priority: water management, invasive species, coastal management and ecological forecasting.' The products of our technical approaches have been well received by the community of focused end-users. The objective this year was to broaden that community and develop external support to continue and operationalize product development