Geo Spatial Analysis Of Forest Landscape For Wildlife Management

This book presents research on landscape ecology and the relationship between humans and wildlife. It helps readers understand how ecological patterns and processes are interconnected. This research illustrates and proposes (practicable) management strategies toward long-term ecological restoration and mitigation of consequences of conflict. Increasing wildlife activities in localities and forest fringes are an alarming issue. Ecological processes like movement, colonization, extinction and conflict issues depend on the landscape and ecological activities, the movement for example of migratory elephants and their colonization not only affects society but the wildlife and biodiversity too. Strategic management measures can contribute to enriching the biodiversity, habitat quality as well as landscape, while minimizing human-wildlife conflicts. This book describes landscape ecological patterns and processes, habitat dominancy, habitat dependency, suitability, connectivity and corridor selection. To synthesize these patterns and processes, several ecological indices are used. Use of geo-spatial techniques improves future management strategies for similar circumstances, especially, related to forest regeneration and forest restoration. This book provides a concise overview to a wide range of readers including postgraduate students, researcher, academics, landscape planners, decision makers and even local populations. The techniques and management strategies described should help planners to improve forest management, by implementing quality enhancement programs such as plantation area selection and corridor selection.

The book "Landscape Ecology Brief Concept, Scale, and Analysis" is thoughtfully crafted to cater to both beginners and scholars, facilitating an easy grasp of the recently emerged discipline of 'Landscape Ecology.' The book briefly covers the fundamental concepts, scaling processes, and pattern analysis of landscapes from an ecological perspective. The chapters are seamlessly organized to provide a logical flow of information. Throughout the book, simple illustrations and reliable graphical examples enhance understanding. The text is rich with information and draws examples from local environments, particularly focusing on forestry and elephants in southwest Bengal, aligning with the author's professional interests. Serving as a synthesis of both concepts and applications in landscape ecology, I anticipate that this book will enhance and also contribute to the development of knowledge and perceptual ideas for students and researchers interested in Landscape Ecology.

Geotechnologies and the Environment: Environmental Applications and Mana- ment presents an engaging and diverse array of physically-oriented GIScience applications that have been organized using four broad themes. While the book’s themes are by no means mutually exclusive, Hoalst-Pullen and Patterson provide an elegant overview of the eld that frames the collection’s subsequent thematic str- ture – Wilderness and Wildlife Response; Glaciers; Wetlands and Watersheds; and Human Health and the Environment. Over the course of the volume, the contrib- ing authors move beyond basic (and in some respects clichéd) landscape ecology of land use change to explore human-environment dynamics heretofore not emp- sized in the applied literature. In doing so, the collection presents a compelling case for the importance of developing new physically-oriented GIScience applications that reside at the nexus of social and natural systems with the explicit intent of informing public policy and/or the decision making practices of resource managers. Individually, the chapters themselves are intentionally diverse. The diversity of the approaches, their spatial context, and emphases on management applications demonstrate the many ways in which geotechnologies can be used to address small and big problems in both developed and developing regions. The collection’s int- nal coherence is derived – like the book series – from its explicit appeal to a wide variety of human-environment interactions with potential policy linkages.

The Latest Advances in Remote Sensing for Biodiversity This state-of-the-art volume provides fundamental information on and practical applications of remote sensing technologies in wildlife management, habitat studies, and biodiversity assessment and monitoring. The book reviews image analysis, interpretation techniques, and key geospatial tools, including field-based, aerial, and satellite remote sensing, GIS, GPS, and spatial modeling. Remote Sensing for Biodiversity and Wildlife Management emphasizes transdisciplinary collaboration, technological innovations, and new applications in this emerging field. Landmark case studies and illustrative examples of best practices in biodiversity and wildlife management remote sensing at multiple scales are featured in this pioneering work. COVERAGE INCLUDES: Management information requirements Geospatial data collection and processing Thermal, passive and active microwave, and passive and active optical sensing Integrated remote sensing, GIS, GPS, and spatial models Remote sensing of ecosystem process and structure Proven methods for acquiring, interpreting, and analyzing remotely sensed data Habitat suitability and quality analysis Mapping anthropogenic disturbances and modeling species distribution Biodiversity indicators, including species richness mapping and productivity modeling Habitat quality and dynamics Indicators and processes Invasive alien species Species prediction models Food and resources Biodiversity monitoring Fragmentation and spatial heterogeneity

Geographic Information Systems (GIS) provide a powerful tool for the investigation of species-habitat relationships and the development of wildlife management and conservation programs. However, the relative ease of data manipulation and analysis using GIS, associated landscape metrics packages, and sophisticated statistical tests may sometimes cause investigators to overlook important species-habitat functional relationships. Additionally, underlying assumptions of the study design or technology may have unrecognized consequences. This volume examines how initial researcher choices of image resolution, scale(s) of analysis, response and explanatory variables, and location and area of samples can influence analysis results, interpretation, predictive capability, and study-derived management prescriptions. Overall, most studies in this realm employ relatively low resolution imagery that allows neither identification nor accurate classification of habitat components. Additionally, the landscape metrics typically employed do not adequately quantify component spatial arrangement associated with species occupation. To address this latter issue, the authors introduce two novel landscape metrics that measure the functional size and location in the landscape of taxon-specific ‘solid’ and ‘edge’ habitat types. Keller and Smith conclude that investigators conducting GIS-based analyses of species-habitat relationships should more carefully 1) match the resolution of remotely sensed imagery to the scale of habitat functional relationships of the focal taxon, 2) identify attributes (explanatory variables) of habitat architecture, size, configuration, quality, and context that reflect the way the focal taxon uses the subset of the landscape it occupies, and 3) match the location and scale of habitat samples, whether GIS- or ground-based, to corresponding species’ detection locations and scales of habitat use.

This book demonstrates the measurement, monitoring, mapping, and modeling of forest resources. It explores state-of-the-art techniques based on open-source software & R statistical programming and modeling specifically, with a focus on the recent trends in data mining/machine learning techniques and robust modeling in forest resources. Discusses major topics such as forest health assessment, estimating forest biomass & carbon stock, land use forest cover (LUFC), dynamic vegetation modeling (DVM) approaches, forest-based rural livelihood, habitat suitability analysis, biodiversity and ecology, and biodiversity, the book presents novel advances and applications of RS-GIS and R in a precise and clear manner. By offering insights into various concepts and their importance for real-world applications, it equips researchers, professionals, and policy-makers with the knowledge and skills to tackle a wide range of issues related to geographic data, including those with scientific, societal, and environmental implications.

Spatially explicit maps of habitat relationships have proven to be valuable tools for conservation and management applications including evaluating how and which species may be impacted by large scale climate change, ongoing fragmentation of habitat, and local land-use practices. Studies have turned to remote sensing datasets as a way to characterize vegetation for the examination of habitat selection and for mapping realized relationships across the landscape. Although the use of remote sensing in wildlife studies has increased in recent years, the use of these datasets is still limited and some data sources and methods are yet to be explored. The overall goal of this dissertation was to look at the state of the wildlife ecology discipline in the use of geospatial data for habitat mapping, and to advance this area through the fusion of remote sensing tools for the mapping of previously difficult to characterize forest metrics for inclusion in avian cavity-nester habitat models. Chapter 2 reviewed over 60 years of selected wildlife literature to examine the wildlife ecology disciple through historic trends and recent advances in the use of remote sensing for habitat characterization focusing on aspects of scale and the use of available technology. We discuss commonly used remote sensing data sources, point out recent advances in the use of geospatial data for characterizing forest wildlife habitat (the use of lidar data and the creation of spatially explicit habitat prediction maps), and provide future suggestions for increased utilization of available datasets (secondary lidar metrics and time series Landsat data). In chapters 3 and 4 we explored the use of remote sensing for characterizing forest components previously difficult to map across landscapes at scales relevant to local wildlife habitat selection. Chapter 3 found promise in the fusion of lidar structure and Landsat time series disturbance products in the modeling and mapping of post-fire snag and shrub distributions at fine scales and at size/cover thresholds relevant for habitat mapping applications for many wildlife species. The study was conducted within the 2003 B & B Fire Complex in central Oregon. Using 164 field calibration plots and remote sensing predictors, we modeled the presence/absence of snag classes (dbh e"0cm, e"0cm, and e"5cm) and woody shrub cover resulting in 10m output predictive grid maps. Remote sensing predictors included various lidar structure and topography variables and Landsat time series products representing the pre-fire forest, disturbance magnitude, and current forest conditions. We were able to model and map all habitat metrics with acceptable predictive performance and low-moderate errors. The utility of these snag and shrub metrics for representing important nesting habitat features for a cavity-nesting species of conservation concern, the Lewis's Woodpecker (Melanerpes lewis), was demonstrated in Chapter 4. We were able to model nesting habitat with good accuracies according to multiple performance measures and then map realized relationships for this species of conservation concern in an identified source habitat type, providing a potential resource for local scale conservation and management efforts and adding to the regional knowledge of habitat selection for the Lewis's Woodpecker. To our knowledge, these chapters represent first attempts to fuse lidar and time series Landsat disturbance metrics in a post-fire landscape and for the mapping of snag and shrub distributions at scales relevant to avian cavity nesting habitat.