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.

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).

In a rapidly changing world, there is an ever-increasing need to monitor the Earth’s resources and manage it sustainably for future generations. Earth observation from satellites is critical to provide information required for informed and timely decision making in this regard. Satellite-based earth observation has advanced rapidly over the last 50 years, and there is a plethora of satellite sensors imaging the Earth at finer spatial and spectral resolutions as well as high temporal resolutions. The amount of data available for any single location on the Earth is now at the petabyte-scale. An ever-increasing capacity and computing power is needed to handle such large datasets. The Google Earth Engine (GEE) is a cloud-based computing platform that was established by Google to support such data processing. This facility allows for the storage, processing and analysis of spatial data using centralized high-power computing resources, allowing scientists, researchers, hobbyists and anyone else interested in such fields to mine this data and understand the changes occurring on the Earth’s surface. This book presents research that applies the Google Earth Engine in mining, storing, retrieving and processing spatial data for a variety of applications that include vegetation monitoring, cropland mapping, ecosystem assessment, and gross primary productivity, among others. Datasets used range from coarse spatial resolution data, such as MODIS, to medium resolution datasets (Worldview -2), and the studies cover the entire globe at varying spatial and temporal scales.

Advanced Remote Sensing is an application-based reference that provides a single source of mathematical concepts necessary for remote sensing data gathering and assimilation. It presents state-of-the-art techniques for estimating land surface variables from a variety of data types, including optical sensors such as RADAR and LIDAR. Scientists in a number of different fields including geography, geology, atmospheric science, environmental science, planetary science and ecology will have access to critically-important data extraction techniques and their virtually unlimited applications. While rigorous enough for the most experienced of scientists, the techniques are well designed and integrated, making the book’s content intuitive, clearly presented, and practical in its implementation. Comprehensive overview of various practical methods and algorithms Detailed description of the principles and procedures of the state-of-the-art algorithms Real-world case studies open several chapters More than 500 full-color figures and tables Edited by top remote sensing experts with contributions from authors across the geosciences

This book provides a coherent review of NDVI including its origin, its availability, its associated advantages and disadvantages, and its possible applications in ecology, environmental monitoring, wildlife management, and conservation.

A. W. KOCHLER The intimate intercourse between two or more 2. vegetation maps are scientific tools for ana fields of knowledge often bears interesting and lyzing the environment and the relation valuable fruit. Vegetation maps are such fruit, ships between vegetation and the site on resulting from the union of botany and geogra which it occurs. This helps to explain the phy. The work of botanists can be comprehen distribution of plant communities on the sive only if it includes a consideration of plants basis of the physical and chemical features in space, i. e. in different types of landscapes. At of the landscape. On the other hand, plant this point, the work of geographers becomes communities allow conclusions on the natu important through their development of maps re of the environment; as tools to determine and to analyze distribu 3. vegetation maps are valuable standards of tions in space. Our highly developed knowledge reference for observing and measuring of vegetation is matched by the refinement of changes in the vegetation, their direction cartographic techniques, and maps can now be and their speed, i. e. the rate of change. This is important because the character ofvegeta made that will show the extent and geographical distribution of vegetation anywhere on the sur tion is dynamic and is increasingly affected face of our planet with a remarkable degree of by man; accuracy. 4.