Download or read book Random Forests Applied as a Soil Spatial Predictive Model in Arid Utah written by Alexander Knell Stum and published by . This book was released on 2010 with total page 147 pages. Available in PDF, EPUB and Kindle. Book excerpt: Initial soil surveys are incomplete for large tracts of public land in the western USA. Digital soil mapping offers a quantitative approach as an alternative to traditional soil mapping. I sought to predict soil classes across an arid to semiarid watershed of western Utah by applying random forests (RF) and using environmental covariates derived from Landsat 7 Enhanced Thematic Mapper Plus (ETM+) and digital elevation models (DEM). Random forests are similar to classification and regression trees (CART). However, RF is doubly random. Many (e.g., 500) weak trees are grown (trained) independently because each tree is trained with a new randomly selected bootstrap sample, and a random subset of variables is used to split each node. To train and validate the RF trees, 561 soil descriptions were made in the field. An additional 111 points were added by case-based reasoning using aerial photo interpretation. As RF makes classification decisions from the mode of many independently grown trees, model uncertainty can be derived. The overall out of the bag (OOB) error was lower without weighting of classes; weighting increased the overall OOB error and the resulting output did not reflect soil-landscape relationships observed in the field. The final RF model had an OOB error of 55.2% and predicted soils on landforms consistent with soil-landscape relationships. The OOB error for individual classes typically decreased with increasing class size. In addition to the final classification, I determined the second and third most likely classification, model confidence, and the hypothetical extent of individual classes. Pixels that had high possibility of belonging to multiple soil classes were aggregated using a minimum confidence value based on limiting soil features, which is an effective and objective method of determining membership in soil map unit associations and complexes mapped at the 1:24,000 scale. Variables derived from both DEM and Landsat 7 ETM+ sources were important for predicting soil classes based on Gini and standard measures of variable importance and OOB errors from groves grown with exclusively DEM- or Landsat-derived data. Random forests was a powerful predictor of soil classes and produced outputs that facilitated further understanding of soil-landscape relationships.

Download or read book Digital Soil Mapping Using Landscape Stratification for Arid Rangelands in the Eastern Great Basin Central Utah written by Brook B. Fonnesbeck and published by . This book was released on 2015 with total page pages. Available in PDF, EPUB and Kindle. Book excerpt: Digital soil mapping typically involves inputs of digital elevation models, remotely sensed imagery, and other spatially explicit digital data as environmental covariates to predict soil classes and attributes over a landscape using statistical models. Digital imagery from Landsat 5, a digital elevation model, and a digital geology map were used as environmental covariates in a 67,000-ha study area of the Great Basin west of Fillmore, UT. A 0́−pre-map0́+ was created for selecting sampling locations. Several indices were derived from the Landsat imagery, including a normalized difference vegetation index, normalized difference ratios from bands 5/2, bands 5/7, bands 4/7, and bands 5/4. Slope, topographic curvature, inverse wetness index, and area solar radiation were calculated from the digital elevation model. The greatest variation across the study area was found by calculating the Optimum Index Factor of covariates, choosing band 7, normalized difference ratio bands 5/2, normalized difference vegetation index, slope, profile curvature, and area solar radiation. A 20-class ISODATA unsupervised classification of these six data layers was reduced to 12. Comparing the 12-class map to a geologic map, 166 sites were chosen weighted by areal extent; 158 sites were visited. Twelve points were added using case-based reasoning to total 170 points for model training. A validation set of 50 sites was selected using conditioned Latin Hypercube Sampling. Density plots of sample sets compared to raw data produced comparable results. Geology was used to stratify the study area into areas above and below the Lake Bonneville highstand shoreline. Raster data were subset to these areas, and predictions were made on each area. Spatial modeling was performed with three different models: random forests, support vector machines, and bagged classification trees. A set of covariates selected by random forests variable importance and the set of Optimum Index Factor covariates were used in the models. The Optimum Index Factor covariates produced the best classification using random forests. Classification accuracy was 45.7%. The predictive rasters may not be useful for soil map unit delineation, but using a hybrid method to guide further sampling using the pre-map and standard sampling techniques can produce a reasonable soil map.

Download or read book Alternative Sampling and Analysis Methods for Digital Soil Mapping in Southwestern Utah written by Colby W. Brungard and published by . This book was released on 2009 with total page 262 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digital soil mapping (DSM) relies on quantitative relationships between easily measured environmental covariates and field and laboratory data. We applied innovative sampling and inference techniques to predict the distribution of soil properties, soil attributes, taxonomic classes, and dominant vegetation across a 30,000-ha complex Great Basin landscape in southwestern Utah. This arid rangeland was characterized by rugged topography, diverse vegetation, and intricate geology. Environmental covariates calculated from digital elevation models (DEM) and spectral satellite data were used to represent factors controlling soil development and distribution. We investigated optimal sample size and sampled the environmental covariates using conditioned Latin Hypercube Sampling (cLHS). We demonstrated that cLHS, a type of stratified random sampling, closely approximated the full range of variability of environmental covariates in feature and geographic space with small sample sizes. Site and soil data were collected at 300 locations identified by cLHS. Random forests was used to generate spatial predictions and associated probabilities of site and soil characteristics. Balanced random forests and balanced and weighted random forests were investigated for their use in producing an overall soil map. Overall and class errors (referred to as out-of-bag [OOB] error) were within acceptable levels. Quantitative covariate importance was useful in determining what factors were important for soil distribution. Random forest spatial predictions were evaluated based on the conceptual framework developed during field sampling.

Download or read book Digital Soil Assessments and Beyond written by Budiman Minasny and published by CRC Press. This book was released on 2012-07-24 with total page 482 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digital soil assessments and beyond contains papers presented at the 5th Global Workshop on Digital Soil Mapping, held 10-13 April 2012 at the University of Sydney, Australia. The contributions demonstrate the latest developments in digital soil mapping as a discipline with a special focus on the use of map products to drive policy decisions partic

Download or read book Digital Soil Mapping written by Janis L. Boettinger and published by Springer Science & Business Media. This book was released on 2010-06-28 with total page 435 pages. Available in PDF, EPUB and Kindle. Book excerpt: Digital Soil Mapping is the creation and the population of a geographically referenced soil database. It is generated at a given resolution by using field and laboratory observation methods coupled with environmental data through quantitative relationships. Digital soil mapping is advancing on different fronts at different rates all across the world. This book presents the state-of-the art and explores strategies for bridging research, production, and environmental application of digital soil mapping.It includes examples from North America, South America, Europe, Asia, and Australia. The chapters address the following topics: - evaluating and using legacy soil data - exploring new environmental covariates and sampling schemes - using integrated sensors to infer soil properties or status - innovative inference systems predicting soil classes, properties, and estimating their uncertainties - using digital soil mapping and techniques for soil assessment and environmental application - protocol and capacity building for making digital soil mapping operational around the globe.

Download or read book Predicting the Spatial Variability in Soil Properties Using DSM Across Malheur National Forest written by Elizabeth A. Seeno and published by . This book was released on 2015 with total page 160 pages. Available in PDF, EPUB and Kindle. Book excerpt: Soil properties may hold the key to improved predictions of soils during digital soil mapping (DSM), which has developed with a focus on environmental factors external to soil. The spatial variability in soil properties was modeled across Malheur National Forest in eastern Oregon as an approach to improve DSM. The resulting preliminary maps are to be used as a potential source of information to support soil survey efforts in the region. Soil properties predicted using DSM included surface and subsurface soil pH, cation exchange capacity (CEC), base saturation, organic matter content, and percent clay content. A Random Forest (RF) classification model, a data mining algorithm that uses many rule-based decision trees to generate predictions, was used to generate predictive maps for each of the listed soil properties from a limited training dataset. Regression kriging was also attempted using the same dataset, but the distribution and density of sample locations made for a more complicated process and the procedure was only successful when applied to log-transformed subsurface organic matter content data in a smaller area within the forest. Random Forest classification models of soil pH, organic matter content, clay content, and CEC performed reasonably well, although the models could not reliably predict base saturation variability. However, the RF modeling process provides a place to begin determining new avenues for improving our understanding of how soil properties vary across the landscape, and the resulting predictive maps highlight areas in the region that should be more heavily sampled during future soil survey mapping.

Download or read book Digital Mapping of Soil Landscape Parameters written by Pradeep Kumar Garg and published by Springer Nature. This book was released on 2020-02-20 with total page 159 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book addresses the mapping of soil-landscape parameters in the geospatial domain. It begins by discussing the fundamental concepts, and then explains how machine learning and geomatics can be applied for more efficient mapping and to improve our understanding and management of ‘soil’. The judicious utilization of a piece of land is one of the biggest and most important current challenges, especially in light of the rapid global urbanization, which requires continuous monitoring of resource consumption. The book provides a clear overview of how machine learning can be used to analyze remote sensing data to monitor the key parameters, below, at, and above the surface. It not only offers insights into the approaches, but also allows readers to learn about the challenges and issues associated with the digital mapping of these parameters and to gain a better understanding of the selection of data to represent soil-landscape relationships as well as the complex and interconnected links between soil-landscape parameters under a range of soil and climatic conditions. Lastly, the book sheds light on using the network of satellite-based Earth observations to provide solutions toward smart farming and smart land management.

Download or read book Artificial Intelligence and Smart Agriculture Applications written by Utku Kose and published by CRC Press. This book was released on 2022-09-07 with total page 380 pages. Available in PDF, EPUB and Kindle. Book excerpt: An essential resource work for understanding how to design and develop smart applications for present and future problems of the field of agriculture.— Dr. Deepak Gupta, Maharaja Agrasen Institute of Technology, Delhi, India As a result of the advances in Artificial Intelligence (AI), many aspects of daily life have been transformed by smart digital technology. Advanced intelligent algorithms can provide powerful solutions to real-world problems. Smart applications have become commonplace. All areas of life are being changed by smart tools developed to deal with complex issues challenging both humanity and the earth. Artificial Intelligence and Smart Agriculture Applications presents the latest smart agriculture applications developed across the globe. It covers a broad array of solutions using data science and AI to attack problems facing agriculture worldwide. Features: Application of drones and sensors in advanced farming A cloud-computing model for implementing smart agriculture Conversational AI for farmer's advisory communications Intelligent fuzzy logic to predict global warming’s effect on agriculture Machine learning algorithms for mapping soil macronutrient elements variability A smart IoT framework for soil fertility enhancement AI applications in pest management A model using Python for predicting rainfall The book examines not only present solutions but also potential future outcomes. It looks at the role of AI-based algorithms and the almost infinite combinations of variables for agricultural applications. Researchers, public and private sector representatives, agriculture scientists, and students can use this book to develop sustainable and solutions for smart agriculture. This book’s findings are especially important as the planet is facing unprecedented environmental challenges from over-farming and climate change due to global warming.

Download or read book Soil Survey Manual written by United States. Bureau of Plant Industry, Soils, and Agricultural Engineering and published by Government Printing Office. This book was released on 1951 with total page 640 pages. Available in PDF, EPUB and Kindle. Book excerpt:

Download or read book Mitigating Land Degradation and Improving Livelihoods written by Feras Ziadat and published by Routledge. This book was released on 2015-07-16 with total page 281 pages. Available in PDF, EPUB and Kindle. Book excerpt: The research presented in this book demonstrates how an integrated ‘systems’ approach to farming in the watershed context increases the effectiveness of a production system and improves people’s livelihoods. It takes an integrated approach, using one watershed in Ethiopia as a ‘laboratory’ or model case study to focus on the interaction and interdependence between land, water, crops, soil, water harvesting, supplemental irrigation, forestry, socio-economic aspects, livestock and farm tools. A range of linked studies was conducted with active participation of the farming community and other relevant stakeholders, such as the local offices of agriculture and extension services. The starting point for the work was the premise that previous efforts to solve farming system constraints using a piecemeal approach or discipline-specific focus have not been successful. Thus, addressing agricultural and environmental constraints through a holistic approach enables the generation of comprehensive technologies to sustainably improve the natural resource base and livelihoods of communities. The authors discuss trade-offs and resource allocation, demonstrating how the environment can be protected while also improving productivity. A unique feature is the methodology developed for the selection of suitable fields and farmers to implement new approaches or improved technologies, to achieve production increases while reducing degradation of sensitive agro-ecosystems. It is also shown how the watershed scale is a valuable basis for assessing the protection of fragile lands.

Download or read book Computing Ethics written by Don Gotterbarn and published by CRC Press. This book was released on 2016-03-01 with total page 484 pages. Available in PDF, EPUB and Kindle. Book excerpt: This textbook emphasizes a diversity of values from different cultures, religions, and geographical locations. The book is designed to assist students, computing professionals, and faculty members to act in a more professional and ethical manner. Compelling case studies, ethical reasoning, and cultural perspectives will be included throughout the book, and the authors will apply lessons learned over many years of intense involvement in computing ethics. The text is appropriate either as a main text in a stand-alone ethics course or as a supplementary text for other related courses.

Download or read book Object Based Image Analysis written by Thomas Blaschke and published by Springer Science & Business Media. This book was released on 2008-08-09 with total page 804 pages. Available in PDF, EPUB and Kindle. Book excerpt: This book brings together a collection of invited interdisciplinary persp- tives on the recent topic of Object-based Image Analysis (OBIA). Its c- st tent is based on select papers from the 1 OBIA International Conference held in Salzburg in July 2006, and is enriched by several invited chapters. All submissions have passed through a blind peer-review process resulting in what we believe is a timely volume of the highest scientific, theoretical and technical standards. The concept of OBIA first gained widespread interest within the GIScience (Geographic Information Science) community circa 2000, with the advent of the first commercial software for what was then termed ‘obje- oriented image analysis’. However, it is widely agreed that OBIA builds on older segmentation, edge-detection and classification concepts that have been used in remote sensing image analysis for several decades. Nevert- less, its emergence has provided a new critical bridge to spatial concepts applied in multiscale landscape analysis, Geographic Information Systems (GIS) and the synergy between image-objects and their radiometric char- teristics and analyses in Earth Observation data (EO).

Download or read book Soil Organic Carbon Mapping Cookbook written by Food and Agriculture Organization of the United Nations and published by Food & Agriculture Org.. This book was released on 2018-05-21 with total page 222 pages. Available in PDF, EPUB and Kindle. Book excerpt: The Soil Organic Carbon Mapping cookbook provides a step-by-step guidance for developing 1 km grids for soil carbon stocks. It includes the preparation of local soil data, the compilation and pre-processing of ancillary spatial data sets, upscaling methodologies, and uncertainty assessments. Guidance is mainly specific to soil carbon data, but also contains many generic sections on soil grid development, as it is relevant for other soil properties. This second edition of the cookbook provides generic methodologies and technical steps to produce SOC maps and has been updated with knowledge and practical experiences gained during the implementation process of GSOCmap V1.0 throughout 2017. Guidance is mainly specific to SOC data, but as this cookbook contains generic sections on soil grid development it can be applicable to map various soil properties.

Download or read book Sensing Approaches for Precision Agriculture written by Ruth Kerry and published by Springer Nature. This book was released on 2021-11-23 with total page 425 pages. Available in PDF, EPUB and Kindle. Book excerpt: Sensing Approaches for Precision Agriculture aims to bring together the ‘state of the art’ of the most popular sensing techniques and the current state of research on the application of sensors in Precision Agriculture (PA). Sensing is of great value in PA because it provides cheap and immediate data for management. This book gives a broad overview of sensing in PA and a coherent introduction for new professionals and research scientists. Readers are introduced to the potential applications of a range of different sensors, how they should be used properly and their limitations for use in PA. Chapters on specific topics and case studies provide depth and enable implementation of the methods by users. A general introduction about sensing techniques in PA is followed by Chapters 2–9 on the most important specific techniques in sensing and Chapters 10–13 include mini-case studies, each showing cutting-edge applications for different sensing methods. Finally, there is an Epilogue on how we expect sensors and analysis to develop.

Download or read book Digital Soil Mapping with Limited Data written by Alfred E. Hartemink and published by Springer Science & Business Media. This book was released on 2008-07-11 with total page 448 pages. Available in PDF, EPUB and Kindle. Book excerpt: Signi?cant technological advances have been few and far between in the past approximately one hundred years of soil survey activities. Perhaps one of the most innovative techniques in the history of soil survey was the introduction of aerial photographs as base maps for ?eld mapping, which replaced the conventional base map laboriously prepared by planetable and alidade. Such a relatively simple idea by today’s standards revolutionized soil surveys by vastly increasing the accuracy and ef?ciently. Yet, even this innovative approach did not gain universal acceptance immediately and was hampered by a lack of aerial coverage of the world, funds to cover the costs, and in some cases a reluctance by some soil mappers and cartog- phers to change. Digital Soil Mapping (DSM), which is already being used and tested by groups of dedicated and innovative pedologists, is perhaps the next great advancement in delivering soil survey information. However, like many new technologies, it too has yet to gain universal acceptance and is hampered by ignorance on the part of some pedologists and other scientists. DSM is a spatial soil information system created by numerical models that - count for the spatial and temporal variations of soil properties based on soil - formation and related environmental variables (Lagacheric and McBratney, 2007).

Download or read book Rangeland Health written by National Research Council and published by National Academies Press. This book was released on 1994-02-01 with total page 201 pages. Available in PDF, EPUB and Kindle. Book excerpt: Rangelands comprise between 40 and 50 percent of all U.S. land and serve the nation both as productive areas for wildlife, recreational use, and livestock grazing and as watersheds. The health and management of rangelands have been matters for scientific inquiry and public debate since the 1880s, when reports of widespread range degradation and livestock losses led to the first attempts to inventory and classify rangelands. Scientists are now questioning the utility of current methods of rangeland classification and inventory, as well as the data available to determine whether rangelands are being degraded. These experts, who are using the same methods and data, have come to different conclusions. This book examines the scientific basis of methods used by federal agencies to inventory, classify, and monitor rangelands; it assesses the success of these methods; and it recommends improvements. The book's findings and recommendations are of interest to the public; scientists; ranchers; and local, state, and federal policymakers.

Download or read book GlobalSoilMap written by Dominique Arrouays and published by CRC Press. This book was released on 2014-01-27 with total page 496 pages. Available in PDF, EPUB and Kindle. Book excerpt: GlobalSoilMap: Basis of the global spatial soil information system contains contributions that were presented at the 1st GlobalSoilMap conference, held 7-9 October 2013 in Orléans, France. These contributions demonstrate the latest developments in the GlobalSoilMap project and digital soil mapping technology for which the ultimate aim is to produce a high resolution digital spatial soil information system of selected soil properties and their uncertainties for the entire world. GlobalSoilMap: Basis of the global spatial soil information system aims to stimulate capacity building and new incentives to develop full GlobalSoilMap products in all parts of the world.