This book explores the concepts, premises, advancements, and challenges in quantifying natural forest landscape patterns through mapping techniques. After several decades of development and use, these tools can now be examined for their foundations, intentions, scope, advancements, and limitations. When applied to natural forest landscapes, mapping techniques must address concepts such as stochasticity, heterogeneity, scale dependence, non-Euclidean geometry, continuity, non-linearity, and parsimony, as well as be explicit about the intended degree of abstraction and assumptions. These studies focus on quantifying natural (i.e., non-human engineered) forest landscape patterns, because those patterns are not planned, are relatively complex, and pose the greatest challenges in cartography, and landscape representation for further interpretation and analysis.

Remote sensing and GIS are increasingly used as tools for monitoring and managing forests. Remotely sensed and GIS data are now the data sources of choice for capturing, documenting, and understanding forest disturbance and landscape pattern. Sitting astride the fields of ecology, forestry, and remote sensing/GIS, Understanding Forest Disturbanc

Key researchers present newly emerging approaches to computer simulation models of large, forest landscapes.

Environmental information and systems play a major role in environmental decision making. As such, it is vital to understand the impact that they have on different aspects of sustainable environmental management, as well as to understand the opportunism they might present for further improvement. Environmental Information Systems: Concepts, Methodologies, Tools, and Applications is an innovative reference source containing the latest research on the use of information systems to track and organize environmental data for use in an overall environmental management system. Highlighting a range of topics such as environmental analysis, remote sensing, and geographic information science, this multi-volume book is designed for engineers, data scientists, practitioners, academicians, and researchers interested in all aspects of environmental information systems.

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.