These protocols describe the application of remote sensing imagery for monitoring spatially explicit ecological indicators (vital signs) of landscape pattern that have been identified for the National Capital Region Network (NCRN). The protocols employ land-cover data from multiple remote sensing platforms, including aerial photography, IKONOS satellite imagery, SPOT Imagery, and Landsat ETM+ imagery. The multi-scale approach facilitates the acquisition of fine-scale data suitable for detailed analyses of small areas (1-m resolution or smaller) and coarser data (e.g., up to 15 and 30m resolution) for repeat characterization of larger areas. For most applications, the coarser scale data are adequate for characterizing landscape pattern, although ultimately data from multiple sensors may be appropriate or necessary based on different objectives of landscape monitoring (e.g., mapping single trees vs. forest stands) and the scale at which a resource of interest interacts with the larger landscape (e.g., birds vs. herptiles). Eight Standard Operating Procedures are provided that document methods for the acquisition (SOP 1) and pre-processing of satellite imagery (SOP 2), the development of land cover maps from remotely sensed data (SOP 3), the processing of those maps in preparation for analyses of landscape patterns (SOP 4), calculation of landscape pattern metrics (SOP 5), graph analysis of landscape connectivity (SOP 6), stream buffer delineation (SOP 7), and image-to-image or mapto- map change detection (SOP 8). SOPs have been tested for 4 parks in the NCRN, Antietam National Battlefield (ANTI), Rock Creek Park (ROCR), Prince William Park (PRWI) and Catoctin Mountain Park (CATO) and the results of these analyses are Townsend et al (2009).

Landscape dynamics refers to a large suite of ecological and geomorphological processes occurring across broad spatial scales. As part of Vital Signs Monitoring, the North Coast and Cascades Network (NCCN) of the National Park Service developed a protocol for monitoring landscape dynamics using remote sensing. Protocol implementation involves cooperative work with the Laboratory for Applications of Remote Sensing in Ecology (LARSE) at Oregon State University, leveraging their use of Landsat remotely sensed imagery to detect landscape change. LARSE has developed a set of algorithms called LandTrendr (Landsat-based Detection of Trends in Disturbance and Recovery).

Effective protocols for landscape-dynamics monitoring generally use remote sensing and Geographic Information Systems (GIS) to model broad-scale patterns and temporal changes occurring in and around national parks. Protocol development for long-term monitoring of land-scape dynamics of SODN parks involves identification of (1) appropriate remote-sensing data for monitoring, (2) image classification and processing schemes, and (3) statistical and spatial analysis techniques to describe change and pattern. The landscape dynamics monitoring protocol presented in this document includes phases of data acquisition, processing, classification, and accuracy assessment.

National parks, wildlife refuges and sanctuaries, natural reserves, conservation areas, frontier lands, and marine-protected areas are increasingly recognized as essential providers of ecosystem services and biological resources. As debates about climate change and sustainability intensify, protected areas become more important as indicators of eco

Part of an ongoing series of manuals covering the range of applications of remotely sensed imagery, Volume 4 addresses the use of this technology in natural resource management and environmental monitoring. Comprehensive, authoritative, and up-to-date, it covers terrestrial ecosystems, aquatic ecosystems, and agriculture ecosystems, as well as future directions in technology and research.

Filling the need for a comprehensive book that covers both theory and application, Remote Sensing of Land Use and Land Cover: Principles and Applications provides a synopsis of how remote sensing can be used for land-cover characterization, mapping, and monitoring from the local to the global scale. With contributions by leading scientists from aro