Литература по ESRI ArcGIS Опции

[yuansw]

ESRI ArcGIS 9 ArcMap Руководство пользователя
 arcedit_sm.jpg ( 9.15 килобайт ) Кол-во скачиваний: 7

Автор: ESRI&Data+
Год: 2004
Страниц: 546
Формат: PDF
Размер: 31.3 MB
Качество: супер
Язык: русский

ESRI АгсМар – это одно из интегрированных приложений ArcGIS Desktop - ArcInfo , ArcEditor и ArcView , предназначенное для отображения карт и построения запросов к картам, создания твердых копий карт высокого полиграфического качества, разработки пользовательских картографических приложений, а также для решения широкого спектра других картографических задач. В АгсМар также входит полный набор инструментов редактирования, которые могут работать как с данными в формате корпоративных СУБД, так и с персональными базами геоданных и шейп-файлами. В АгсМар органично связаны режимы просмотра карты и редактирования ее данных.

Руководство попьзователя АгсМар поможет вам сразу приступить к работе. Независимо от уровня ваших знаний в области работы с ГИС, вы можете использовать эту книгу как справочник: в ней просто находить задачи, которые вам необходимо решить, а также подробные описания их выполнения.

Вы узнаете как

Представить ваши географические данные в виде карты
Эффективно отображать географические данные
Создавать и обновлять географические данные
Создавать карты высокого качества, предназначенные для публикаций
Строить интерактивные изображения, связывающие с вашим данными таблицы, диаграммы, отчеты, фотографии и Интернет-сайты
Понимать отношения, такие как "Где?", "Сколько?" и "Что если?"
Разрабатывать пользовательские картографические приложения, соответствующие вашим потребностям
Начните с выполнения упражнений вводного курса. Они позволят оценить круг задач, которые вы сможете решать с помощью АгсМар, и помогут вам создать свою первую карту. Или вы можете начать экспериментировать с АгсМар самостоятельно. Если у вас возникнут вопросы, вы найдете подробные пошаговые инструкции, которые помогут вам в выполнении ваших задач.

_http://rapidshare.de/files/27212731/ag9uam_ru.rap.html
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Сообщение отредактировал yuansw - 2.08.2006 - 10:25

[Williams]

Jay Gao - Remote Sensing of Natural Hazards

CRC Press, 2023
pdf, 464 pages, english
ISBN: 978-1-032-40690-9



This book presents a comprehensive coverage of remote sensing technology used to gather information on 12 types of natural hazards in the terrestrial sphere, biosphere, hydrosphere, and atmosphere. It clarifies in detail how to yield spatial and quantitative data on a natural hazard, including its spatial distribution, severity, causes, and the likelihood of occurrence. The author explains multiple methods of attaining data, describes the pros and cons of each method, and encourages readers to choose the best method applicable to their case. The author offers a practical approach to data analysis using the most appropriate methods and software.

1. Covers all major natural hazards including hurricanes, tornadoes, wildfires, and avalanches.
2. Studies each natural hazard holistically, ranging from spatial extent, severity, impact assessment, causes, and prediction of occurrence.
3. Explains different remotely sensed data and the most appropriate method used.
4. Compares different ways of sensing and clarifies the pros and cons of any selected data or their analysis.
5. Provides ample examples of each aspect of a natural hazard studied augmented with graphic illustrations and quality assurance information.

All professionals working in the field of natural hazards, senior undergraduate, and graduate students, will find in-depth approaches and sufficient information to become knowledgeable in the methods of yielding and analyzing data provided with remote sensing technology, ultimately providing a deeper understanding of natural hazards.

https://www.upload.ee/files/15271930/it9841.7z.html

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Marcelo de Carvalho Alves, Luciana Sanches - Remote Sensing and Digital Image Processing with R — Lab Manual

CRC Press, 2023
pdf, 188 pages, english
ISBN: 978-1-032-46124-3



This Lab Manual is a companion to the textbook Remote Sensing and Digital Image Processing with R. It covers examples of natural resource data analysis applications including numerous, practical problem-solving exercises, and case studies that use the free and open-source platform R. The intuitive, structural workflow helps students better understand a scientific approach to each case study in the book and learn how to replicate, transplant, and expand the workflow for further exploration with new data, models, and areas of interest. 　

Features
- Aims to expand theoretical approaches of remote sensing and digital image processing through multidisciplinary applications using R and R packages.
- Engages students in learning theory through hands-on real-life projects.
- All chapters are structured with solved exercises and homework and encourage readers to understand the potential and the limitations of the environments.
- Covers data analysis in the free and open-source R platform, which makes remote sensing accessible to anyone with a computer.
- Explores current trends and developments in remote sensing in homework assignments with data to further explore the use of free multispectral remote sensing data, including very high spatial resolution information.
- Undergraduate- and graduate-level students will benefit from the exercises in this Lab Manual, because they are applicable to a variety of subjects including environmental science, agriculture engineering, as well as natural and social sciences. Students will gain a deeper understanding and first-hand experience with remote sensing and digital processing, with a learn-by-doing methodology using applicable examples in natural resources.

https://www.upload.ee/files/15275922/Remote_Sensing_and_Digital_Image_Processing_with_R_-_Lab_Manual.rar.html

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Guo Q., Su Y., Hu T. - LiDAR Principles, Processing and Applications in Forest Ecology

Academic Press, 2023
pdf, 509 pages, english
ISBN: 978-0-12-823894-3



LiDAR Principles, Processing and Applications in Forest Ecology introduces the principles of LiDAR technology and explains how to collect and process LiDAR data from different platforms based on real-world experience. The book provides state-of the-art algorithms on how to extract forest parameters from LiDAR and explains how to use them in forest ecology. It gives an interdisciplinary view, from the perspective of remote sensing and forest ecology. Because LiDAR is still rapidly developing, researchers must use programming languages to understand and process LiDAR data instead of established software. In response, this book provides Python code examples and sample data. Sections give a brief history and introduce the principles of LiDAR, as well as three commonly seen LiDAR platforms. The book lays out step-by-step coverage of LiDAR data processing and forest structure parameter extraction, complete with Python examples. Given the increasing usefulness of LiDAR in forest ecology, this volume represents an important resource for researchers, students and forest managers to better understand LiDAR technology and its use in forest ecology across the world. The title contains over 15 years of research, as well as contributions from scientists across the world.

https://www.upload.ee/files/15336185/LiDAR_Principles__Processing_and_Applications_in_Forest_Ecology.rar.html

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