This dataset is about book subjects. It has 3 rows and is filtered where the books is OpenStreetMap : be your own cartographer. It features 10 columns including number of authors, number of books, earliest publication date, and latest publication date.

FRUC Datasets (Forest environment dataset)

This dataset was collected as part of the work conducted by the Forestry Robotics @ University of Coimbra team (https://www.youtube.com/@forestryroboticsuc; part of the Institute of Systems and Robotics, https://www.isr.uc.pt/) within the scope of the Safety, Exploration and Maintenance of Forests with Ecological Robotics (SEMFIRE, ref. CENTRO-01-0247-FEDER-03269; http://semfire.ingeniarius.pt/) and the Semi-Autonomous Robotic System for Forest Cleaning and Fire Prevention (SafeForest, CENTRO-01-0247-FEDER-045931) research projects. Its purpose is to allow researchers in forestry robotics to have an in-depth analysis of a florests environment; obtain an a priori map for robot operations (e.g. path plannning, landscaping, etc…) and to train segmentation algorithms;

The dataset in question includes data from multiple sensors and absolute, map-referenced localization which can be used to register the sensor data to a fixed coordinate system. It was collected at the Choupal National Woods, Coimbra, Portugal (40◦13′13.3′′N;8◦26′38.1′′W). The dataset was collected during a partly clouded day in a forest environment by performing two circular loop laps amounting to a total distance of approximately 800m, with a total duration of 14 minutes and 22 seconds. The scenario is rich in features relevant to forestry robotics applications, including trees, bushes, tree trunks, etc. To better handle the multimodal nature of the acquired data, the dataset is bundled into rosbags, a file format used by the ROS (Robot Operating System) to record and play back data.

More specifically, the datasets include:

RGB Images from an Intel Realsense D435i

Aligned Depth Images from an Intel Realsense D435i

Left and Right Mono Images from a Mynt Eye s1030

Point Clouds from a Livox Mid-70 LiDAR

Unfiltered acceleration, gyroscopic and magnetic data from a Xsens MTi IMU

Unfiltered acceleration, gyroscopic data from an Intel Realsense D435i

GNSS Fix data from a Xiaomi Mi Mix 3 device

Description of files:

The dataset is contain in choupal.bag.

The rosbag_info.txt contains the information of each rosbag;

The sensor_box.urdf contains all the required transforms;

The sensor_box.stl contains the 3D model of the apparatus;

The choupal.launch publishes the sensor transforms and plays the dataset;

The localization.bag contains the final graph of poses extracted with Cartographer republished as nav_msgs/odom at 4.98Hz.

The localization_15Hz.bag contains a map-referenced localization extracted with Cartographer at a higher frequency, but the poses are interpolated. If you don't require a high frame rate, please use the localization.bag instead.

Usage:

Extract the fruc_dataset_choupal_launch.zip into a catkin workspace

Install the necessary dependencies of the package:

cd [/path/to/catkin_ws]

rosdep install --from-paths src --ignore-src -y -r

Copy the rosbags into the fruc_dataset_choupal_launch/rosbag/

Edit the fruc_dataset_choupal_launch/launch/choupal.launch file to your use case:

Change the file_path argument if the rosbags are not in the default location;

Set localization_file to the path of the desired localization bag, leave it empty to run the dataset without localization.

Compile the package and source the environment:

catkin_make [/your_catkin_workspace/]

source [/your_catkin_workspace/devel/setup.bash]

Launch the files:

roslaunch fruc_dataset_choupal_launch choupal.launch

The topographical images of this map book for the former Prussian territory east of the Weser in scale 1: 50,000 took place between 1767 and 1787. with the significant participation of Friedrich Wilhelm Karl Graf von Schmettau. The Prussian officer and cartographer created the work against the concerns of Frederick II. However, in consultation with the then Crown Prince Friedrich Wilhelm II on his own initiative and with the support of the Minister Friedrich Wilhelm Graf von der Schulenburg-Kehnert. According to sources, scope and content, the work is the culmination of pre-official Prussian cartography. The individual sheets were hand-drawn unique pieces and not intended for publication. The originals of the 270-section map work are in the possession of the Staatsbibliothek zu Berlin - Preußischer Kulturbesitz. The cards are available as multicolour prints and have a size of 97 cm x 64 cm. You will be given plano.

Continuing the tradition of the best-selling Getting to Know series, Getting to Know ArcGIS Pro 2.6 teaches new and existing GIS users how to get started solving problems using ArcGIS Pro. Using ArcGIS Pro for these tasks allows you to understand complex data with the leading GIS software that many businesses and organizations use every day.Getting to Know ArcGIS Pro 2.6 introduces the basic tools and capabilities of ArcGIS Pro through practical project workflows that demonstrate best practices for productivity. Explore spatial relationships, building a geodatabase, 3D GIS, project presentation, and more. Learn how to navigate ArcGIS Pro and ArcGIS Online by visualizing, querying, creating, editing, analyzing, and presenting geospatial data in both 2D and 3D environments. Using figures to show each step, Getting to Know ArcGIS Pro 2.6 demystifies complicated process like developing a geoprocessing model, using Python to write a script tool, and the creation of space-time cubes. Cartographic techniques for both web and physical maps are included.Each chapter begins with a prompt using a real-world scenario in a different industry to help you explore how ArcGIS Pro can be applied for operational efficiency, analysis, and problem solving. A summary and glossary terms at the end of every chapter help reinforce the lessons and skills learned.Ideal for students, self-learners, and seasoned professionals looking to learn a new GIS product, Getting to Know ArcGIS Pro 2.6 is a broad textbook and desk reference designed to leave users feeling confident in using ArcGIS Pro on their own.AUDIENCEProfessional and scholarly. Higher education.AUTHOR BIOMichael Law is a cartographer and GIS professional with more than a decade of experience. He was a cartographer for Esri, where he developed cartography for books, edited and tested GIS workbooks, and was the editor of the Esri Map Book. He continues to work with GIS software, writing technical documentation, teaching training courses, and designing and optimizing user interfaces.Amy Collins is a writer and editor who has worked with GIS for over 16 years. She was a technical editor for Esri, where she honed her GIS skills and cultivated an interest in designing effective instructional materials. She continues to develop books on GIS education, among other projects.Pub Date: Print: 10/6/2020 Digital: 8/18/2020 ISBN: Print: 9781589486355 Digital: 9781589486362 Price: Print: $84.99 USD Digital: $84.99 USD Pages: 420 Trim: 7.5 x 9.25 in.Table of ContentsPrefaceChapter 1 Introducing GISExercise 1a: Explore ArcGIS OnlineChapter 2 A first look at ArcGIS Pro Exercise 2a: Learn some basics Exercise 2b: Go beyond the basics Exercise 2c: Experience 3D GISChapter 3 Exploring geospatial relationshipsExercise 3a: Extract part of a dataset Exercise 3b: Incorporate tabular data Exercise 3c: Calculate data statistics Exercise 3d: Connect spatial datasetsChapter 4 Creating and editing spatial data Exercise 4a: Build a geodatabase Exercise 4b: Create features Exercise 4c: Modify featuresChapter 5 Facilitating workflows Exercise 5a: Manage a repeatable workflow using tasks Exercise 5b: Create a geoprocessing model Exercise 5c: Run a Python command and script toolChapter 6 Collaborative mapping Exercise 6a: Prepare a database for data collection Exercise 6b: Prepare a map for data collection Exercise 6c: Collect data using ArcGIS CollectorChapter 7 Geoenabling your projectExercise 7a: Prepare project data Exercise 7b: Geocode location data Exercise 7c: Use geoprocessing tools to analyze vector dataChapter 8 Analyzing spatial and temporal patternsExercise 8a: Create a kernel density map Exercise 8b: Perform a hot spot analysis Exercise 8c: Explore the results in 3D Exercise 8d: Animate the dataChapter 9 Determining suitability Exercise 9a: Prepare project data Exercise 9b: Derive new surfaces Exercise 9c: Create a weighted suitability modelChapter 10 Presenting your project Exercise 10a: Apply detailed symbology Exercise 10b: Label features Exercise 10c: Create a page layout Exercise 10d: Share your projectAppendix Image and data source credits Data license agreement GlossaryGetting to Know ArcGIS Pro 2.6 | Official Trailer | 2020-08-10 | 00:57