- Видео 44
- Просмотров 27 134
Ian Boles
Добавлен 18 фев 2014
Welcome to the personal RUclips channel of Ian Boles, Adjunct Professor of Geography at Cypress College. This video collection is a work in progress as I travel the world collecting material to supplement my geography courses.
GEOG 232, Week 14 Lecture: Python, Part 2
Welcome to GEOG 232: Analysis & Modeling at Cypress College. In week 14, I continue my discussion of Python scripting for GIS. In this, the second of two lectures on Python scripting, I discuss the key differences between programming and scripting languages, introduce Python libraries and modules, and continue my discussion of various data types used in Python.
This is part two of two lectures on Python for ArcGIS Pro. For part one, please see here: ruclips.net/video/HYXwzPGT0-4/видео.html
This is part two of two lectures on Python for ArcGIS Pro. For part one, please see here: ruclips.net/video/HYXwzPGT0-4/видео.html
Просмотров: 53
Видео
GEOG 232, Week 13 Lecture: Python, Part 1
Просмотров 682 года назад
Welcome to GEOG 232: Analysis & Modeling at Cypress College. In week 13, I introduce Python scripting for GIS. I discuss the fundamentals of Python scripting, including a brief overview of its history, proper syntax, and introductory scripting techniques. This is part one of two lectures on Python for ArcGIS Pro. Go here for part two: ruclips.net/video/g-ul6EBV6W4/видео.html
GEOG 232, Week 12 Lecture: ModelBuilder, Part 2
Просмотров 432 года назад
Welcome to GEOG 232: Analysis & Modeling at Cypress College. In week 12, I continue my discussion of ModelBuilder within the ArcGIS Pro platform. ModelBuilder is a visual programming language for building geoprocessing workflows in ArcGIS. The concepts and principles discussed in this lecture are applicable to ModelBuilder in ArcGIS Pro, as well as ArcMap. In this lecture, I dive deeper into Mo...
GEOG 232, Week 11 Lecture: ModelBuilder, Part 1
Просмотров 572 года назад
Welcome to GEOG 232: Analysis & Modeling at Cypress College. In week 11, I introduce the ModelBuilder interface. ModelBuilder is a visual programming language for building geoprocessing workflows in ArcGIS. The concepts and principles discussed in this lecture are applicable to ModelBuilder in ArcGIS Pro, as well as ArcMap. In this lecture, I discuss the steps involved with setting up and runni...
GEOG 232, Week 9 Lecture: LiDAR, Part 2
Просмотров 802 года назад
Welcome to GEOG 232: Analysis & Modeling at Cypress College. In week 9, I continue my discussion on LiDAR (Light Detection and Ranging) technology as it relates to remote sensing. LiDAR is a system for measuring surfaces at a distance using pulses of light and a sensor. In this lecture, I explain the role of reflective intensity in LiDAR; I discuss a handful of professional applications of LiDA...
GEOG 232, Week 8 Lecture: LiDAR, Part 1
Просмотров 892 года назад
Welcome to GEOG 232: Analysis & Modeling at Cypress College. In week 8, I introduce LiDAR (Light Detection and Ranging) technology as it relates to remote sensing. LiDAR is a system for measuring surfaces at a distance using pulses of light and a sensor. LiDAR point cloud data can be used for creating Digital Elevation Models (DEM) and Digital Surface Models (DSM), among other derivative produc...
GEOG 232, Week 7 Lecture: Digital Elevation and Surface Models
Просмотров 612 года назад
Welcome to GEOG 232: Analysis & Modeling at Cypress College. In week 7, I introduce Digital Elevation Models (DEM) and Digital Surface Models (DSM). I describe how the models are created - derived from LiDAR point clouds - and how they can be used to extract actionable intelligence.
GEOG 232, Week 6 Lecture: Deep Learning
Просмотров 682 года назад
Welcome to GEOG 232: Analysis & Modeling at Cypress College. In week 6, I discuss machine learning and deep learning applied to image classification and object extraction. Subfields of artificial intelligence, machine learning and deep learning rely on algorithms, training samples, varying degrees of human direction to extract features from imagery.
GEOG 232, Week 5 Lecture: Change Detection
Просмотров 2542 года назад
Welcome to GEOG 232: Analysis & Modeling at Cypress College. In week 5, I discuss multispectral imagery sources, criteria for imagery selection, and change detection techniques. Useful in monitoring and quantifying changes in forestry, land use, agriculture, and water resources, among many other domains, change detection is a method of understanding how an area has changed over time.
GEOG 232, Week 4 Lecture: Multispectral Imagery
Просмотров 992 года назад
Welcome to GEOG 232: Analysis & Modeling at Cypress College. In week 4, I discuss spectral and multispectral imagery. Multispectral imagery can be thought of as a hybrid of spectroscopy and aerial imagery. Spectroscopy tells us about the composition of an object or surface via its electromagnetic signature. Spectroscopy answers the question, "What?", while aerial imagery answers the question, "...
GEOG 232, Week 3 Lecture: Image Classification
Просмотров 692 года назад
Welcome to GEOG 232: Analysis & Modeling at Cypress College. In week 3, I introduce the concept of image classification. Image classification is the act of categorizing and organizing objects on the sensed landscape. In the context of remote sensing and GIS, we rely on a combination of computer algorithms and human direction to find patterns and make sense of raw data, leading to new spatial in...
GEOG 232, Week 2 Lecture: Intro to Remote Sensing
Просмотров 952 года назад
Welcome to GEOG 232: Analysis & Modeling at Cypress College. In week 2, I introduce the practice and history of remote sensing and discuss remote sensing techniques, including aerial and satellite imaging devices; two core methods for deriving information from imagery - image interpretation and photogrammetry; and the electromagnetic light spectrum.
GEOG 232, Week 1 Lecture: Intro to Imagery
Просмотров 912 года назад
Welcome to GEOG 232: Analysis & Modeling at Cypress College. In week 1, I introduce the core concepts of the class, including the key differences between vector and raster data, types of raster imagery, the importance of spatial resolution, how to apply spatial analysis techniques to raster data, and an overview of ArcGIS Pro software.
Data Prep for Population Pyramid Build
Просмотров 573 года назад
Using age-sex cohort data downloaded from the United Nations Population Dynamics website (population.un.org/wpp/DataQuery/), this video explains how to prepare your raw data for creating a population pyramid. This video does not explain how to build a population pyramid.
Raster Analysis
Просмотров 2013 года назад
In week 14, we explore the benefits and unique quirks of raster data. Raster data, in contrast to vector data, rely on grids of values that can represent visible or invisible light, elevation, temperature, or any number of observed or predicted values. Raster analysis techniques discussed include image classification and map algebra.
GEOG 231 Week 14 Tutorial, Raster Analysis
Просмотров 1543 года назад
GEOG 231 Week 14 Tutorial, Raster Analysis
GEOG 231 Week 12 Tutorial, OLS Regression
Просмотров 1,3 тыс.3 года назад
GEOG 231 Week 12 Tutorial, OLS Regression
GEOG 231 Week 9 Tutorial, Analyzing Patterns, Part 1
Просмотров 1603 года назад
GEOG 231 Week 9 Tutorial, Analyzing Patterns, Part 1
Mapping Density, Pt. 2: Data Classification
Просмотров 3023 года назад
Mapping Density, Pt. 2: Data Classification
GEOG 231 Week 6 Tutorial, Mapping Density
Просмотров 1603 года назад
GEOG 231 Week 6 Tutorial, Mapping Density
GEOG 231 Week 5 Tutorial, Working with Census Data: Part 2
Просмотров 1403 года назад
GEOG 231 Week 5 Tutorial, Working with Census Data: Part 2
GEOG 231 Week 4 Tutorial, Working with Census Data
Просмотров 2,3 тыс.4 года назад
GEOG 231 Week 4 Tutorial, Working with Census Data
I am in a Geography class right now, and I did not understand Data Classification. The University I am attending has a textbook with very little information and some classifications, but not all, and barely any of the maps are precisely explained, yet they want me to know most of them. Thanks to your video explaining each classification with pictures and definitions, I got a better understanding of them. Thank you!
Sir, I am starting a project on health data (based on years,or anything) for spatial modeling, predictions, analysis for this , I need dataset i didn't get any datasets.. can you provide any links or share please
Since GWR calculates coefficient for each region by considering its neighbour, does that means coeficients for region on map edges are less reliable?
What is the book that you show
Very impressive lecture vidoe, thanks. Can i get your address?
great! thanks so much and blessed u iJN
thank you so much teacher! awesome tutorial. god bless you and your family.
Azan means ... Allah is the Almighty GOD. Allah is the Greatest. Allah is the Greatest. I testify, there is none worthy of worship except Allah (Almighty God). I testify, there is none worthy of worship except Allah (Almighty God). I testify that Muhammad ( Peace be upon Him) is the Messenger of Allah. I testify that Muhammad ( Peace be upon Him) is the Messenger of Allah. Come to prayer. Come to prayer. Come to Salvation. Come to Salvation. Allah is the Greatest. Allah is the Greatest. There is no God but Allah.
Allah en Büyüktür. Allah en Büyüktür Allah en Büyüktür Allah en Büyüktür Şahitlik ederim ki Allah'tan başka ilah yoktur. Şahitlik ederim ki Allah'tan başka ilah yoktur. Şahitlik ederim ki Hz Muhammed Allah'ın elçisidir. Şahitlik ederim ki Hz Muhammed Allah'ın elçisidir. Haydi namaza Haydi namaza Haydi kurtuluşa gel Haydi kurtuluşa gel Allah en Büyüktür Allah en Büyüktür Allah'tan başka ilah yoktur.
Why I get null values after joining data?
I'm having the same problem :/
Your tutorial is so helpful!!! Thank you very much for your sharing!
Thank you
What does the std deviation mean on the map exactly? Is it just where population is above the mean?
The standard deviation displayed on the map is above/below the mean number of 911 calls by census block group. Say, for example, the mean number of calls is 28. The darkest brown color represents those block groups with a number of calls in the mid to high 30s. The light tan color represents those with a number in the teens.
Not your student, but great job explaining how to get this done. I do this analysis on a yearly basis and since American FindFinder is gone, I had a hard time last year (March 2020) getting this done. Thanks to you, I'll get it done faster and better this year. Cheers to you and Geography!
Thank you for posting this! I am a GIS student in Texas and this really helped me with an independent research project. Thanks!
You are very welcome. Glad you found it useful.
Hello professor is there any tutorial videos out there that show you how to create a map?
I use ArcGIS and QGIS to make maps. If you have access to ArcMap or ArcGIS Pro, you will find tons of videos on RUclips. QGIS is a free open source GIS program with a loyal following; plenty of videos on that too.
Thanks a lot professor Boles
You're very welcome!