A talk I gave at the 2014 MAC URISA Conference in Atlantic City. Often, GIS users have little exposure to SQL. This talk gives a brief overview to SQL from a GIS users' perspective, and provides some examples of how it can be used in place of common ArcGIS/desktop GIS tasks to improve efficiency.
Presented by Patrick Woerner and John Reiser at the Northeast Arc Users Group, November 10, 2015.
Wildlife habitat change trend information is a necessary and fundamental component for successful assessment and management of wildlife species. Habitat loss and fragmentation continue to be the two most serious threats to wildlife populations. To effectively protect endangered and threatened species populations and to evaluate protection and management efforts, it is important for wildlife agencies to actively identify and monitor habitat for each listed species. New Jersey’s Division of Fish and Wildlife adopted a habitat change analysis approach to track wildlife habitat transition and fragmentation trends over time. The programmatic GIS analysis approach extracts potential habitat from available Land Use/Land Cover (LULC) data based on species habitat associations and range extents. The analysis spans four time periods between 1986 and 2012. Analysis outputs provide readily available, up-to-date, multi-level, species-specific habitat change information to support agency initiatives. Resulting maps and data serve as a guide to help prioritize work for particular species and their habitats and provide baseline information for the development of species status assessments and recovery plans. Outputs also provide a basis for additional analyses such as evaluating habitat change in regulated vs. unregulated areas, evaluating habitat conservation planning efforts, and other land-use planning, land management and preservation efforts.
Presented by Patrick Woerner and John Reiser at the Northeast Arc Users Group, November 10, 2015.
Wildlife habitat change trend information is a necessary and fundamental component for successful assessment and management of wildlife species. Habitat loss and fragmentation continue to be the two most serious threats to wildlife populations. To effectively protect endangered and threatened species populations and to evaluate protection and management efforts, it is important for wildlife agencies to actively identify and monitor habitat for each listed species. New Jersey’s Division of Fish and Wildlife adopted a habitat change analysis approach to track wildlife habitat transition and fragmentation trends over time. The programmatic GIS analysis approach extracts potential habitat from available Land Use/Land Cover (LULC) data based on species habitat associations and range extents. The analysis spans four time periods between 1986 and 2012. Analysis outputs provide readily available, up-to-date, multi-level, species-specific habitat change information to support agency initiatives. Resulting maps and data serve as a guide to help prioritize work for particular species and their habitats and provide baseline information for the development of species status assessments and recovery plans. Outputs also provide a basis for additional analyses such as evaluating habitat change in regulated vs. unregulated areas, evaluating habitat conservation planning efforts, and other land-use planning, land management and preservation efforts.
This PPT File, helps with the Basic Interview Questions specially for DataBase Domain.. For more questions , please log in to www.rekruitin.com
By ReKruiTIn.com
Strata 2014: Design Challenges for Real Predictive Platforms Max Gasner
The first databases were tightly coupled to their implementation details and use cases, until the relational revolution opened up the field and made database systems flexible enough to support a wide variety of applications with minimal configuration. What will it take to make predictive systems as ubiquitous and easy to use as databases? We’ll discuss the crucial design criteria for future predictive platforms and the kinds of interfaces they need to be able to support, as well as the challenges that lie between the state of the art and the future we envision.
This PPT File, helps with the Basic Interview Questions specially for DataBase Domain.. For more questions , please log in to www.rekruitin.com
By ReKruiTIn.com
Strata 2014: Design Challenges for Real Predictive Platforms Max Gasner
The first databases were tightly coupled to their implementation details and use cases, until the relational revolution opened up the field and made database systems flexible enough to support a wide variety of applications with minimal configuration. What will it take to make predictive systems as ubiquitous and easy to use as databases? We’ll discuss the crucial design criteria for future predictive platforms and the kinds of interfaces they need to be able to support, as well as the challenges that lie between the state of the art and the future we envision.
SQL is an ANSI (American National Standards Institute) standard computer language for accessing and manipulating database systems. SQL statements are used to retrieve and update data in a database. SQL works with database programs like MS Access, DB2, Informix, MS SQL Server, Oracle, Sybase, etc.
NewyorkSys is one of the leading top Training and Consulting Company in US. Newyorksys have certified trainers. We will provide Online Training, Fast Track online training, with job assistance. We are providing excellent Training in all courses.
SQL is a language that provides an interface to a relational database system.
SQL is developed by IBM in 1970s and it is a defacto standard as well as ISO & ANSI standard
SQL also supports DML for insert, update & delete operations and DDL for creating and modifying tables and other database structures.
Excel Tutorials - VLOOKUP and HLOOKUP FunctionsMerve Nur Taş
Excel Tutorials with screenshots.
Reference and lookup functions in Excel: How to use VLOOKUP and HLOOKUP functions. VLOOKUP function example.
MS Excel 2016 for Mac
Real-time Data De-duplication using Locality-sensitive Hashing powered by Sto...DECK36
Data de-duplication, in our case also called "Entity Matching", is not just about reducing multiple instances of the same item to one in order to save some space. It is a challenging task with many practical applications from health care to fraud prevention: "Is this person the same patient as ten years ago, but has moved in the meantime?", "Is this personalized spam mail the same email that was sent to many others, yet customized in each case?", or "Was there a spike resp. what is the base level of similar looking account creations?". In the age of Big Data, we do have the data to answer such questions, but heuristically comparing each item to all other items quickly becomes technically prohibitive for huge data sets.
In this session, we will have a look at past practises and current developments in the world of data de-duplication. After that, we will look at how to leverage locality-sensitive hashing algorithmically to reduce the amount of comparisons to a workable level. A demonstration will feature our implementation of that algorithm on top of Riak and Storm. The session will then finish with an overview of experiments and results using that system on different datasets, including browser fingerprints, tweets, and news articles.
A "M"ind Bending Experience. Power Query for Power BI and Beyond.Alex Powers
Power Query is quickly becoming the number one skill your employees NEED TO HAVE working in a modern workplace. Join Alex Powers as he demystifies the Power Query M Language, writing your own custom solutions and how to approach the language in a way that makes sense to both technical and non-technical users.
Python and GIS: Improving Your WorkflowJohn Reiser
A 40 minute talk on using Python with GIS software. Integration with ArcGIS and open source software is demonstrated. Includes links to several Python-based projects on Github. Presented at the Delaware Valley Regional Planning Commission's Information Resource Exchange Group on December 9th, 2015.
A MAC URISA event. This talk is oriented to GIS users looking to learn more about the Python programming language. The Python language is incorporated into many GIS applications. Python also has a considerable installation base, with many freely available modules that help developers extend their software to do more.
The beginning third of the talk discusses the history and syntax of the language, along with why a GIS specialist would want to learn how to use the language. The middle of the talk discusses how Python is integrated with the ESRI ArcGIS Desktop suite. The final portion of the talk discusses two Python projects and how they can be used to extend your GIS capabilities and improve efficiency.
Recording of the talk: https://www.youtube.com/watch?v=F1_FqvbXHb4
An introduction to GIS Data Types. Strengths and weaknesses of raster and vector data are discussed. Also covered is the importance of topology. Concludes with a discussion of the vector-based format of OpenStreetMap data.
First unit lecture for John Reiser's GIS II course offered Spring 2011 at Rowan University, Glassboro, NJ.
Materials are released under a CC BY-NC-SA 3.0 license: http://creativecommons.org/licenses/by-nc-sa/3.0/
A presentation and workshop presented at the 2009 Annual Conference of the American Planning Association, New Jersey Chapter. Originally presented at the Bloustein School, Rutgers-New Brunswick. Workshop materials available at http://njgeo.org/presentations/
This is a presentation by Dada Robert in a Your Skill Boost masterclass organised by the Excellence Foundation for South Sudan (EFSS) on Saturday, the 25th and Sunday, the 26th of May 2024.
He discussed the concept of quality improvement, emphasizing its applicability to various aspects of life, including personal, project, and program improvements. He defined quality as doing the right thing at the right time in the right way to achieve the best possible results and discussed the concept of the "gap" between what we know and what we do, and how this gap represents the areas we need to improve. He explained the scientific approach to quality improvement, which involves systematic performance analysis, testing and learning, and implementing change ideas. He also highlighted the importance of client focus and a team approach to quality improvement.
The French Revolution, which began in 1789, was a period of radical social and political upheaval in France. It marked the decline of absolute monarchies, the rise of secular and democratic republics, and the eventual rise of Napoleon Bonaparte. This revolutionary period is crucial in understanding the transition from feudalism to modernity in Europe.
For more information, visit-www.vavaclasses.com
Operation “Blue Star” is the only event in the history of Independent India where the state went into war with its own people. Even after about 40 years it is not clear if it was culmination of states anger over people of the region, a political game of power or start of dictatorial chapter in the democratic setup.
The people of Punjab felt alienated from main stream due to denial of their just demands during a long democratic struggle since independence. As it happen all over the word, it led to militant struggle with great loss of lives of military, police and civilian personnel. Killing of Indira Gandhi and massacre of innocent Sikhs in Delhi and other India cities was also associated with this movement.
How to Split Bills in the Odoo 17 POS ModuleCeline George
Bills have a main role in point of sale procedure. It will help to track sales, handling payments and giving receipts to customers. Bill splitting also has an important role in POS. For example, If some friends come together for dinner and if they want to divide the bill then it is possible by POS bill splitting. This slide will show how to split bills in odoo 17 POS.
Students, digital devices and success - Andreas Schleicher - 27 May 2024..pptxEduSkills OECD
Andreas Schleicher presents at the OECD webinar ‘Digital devices in schools: detrimental distraction or secret to success?’ on 27 May 2024. The presentation was based on findings from PISA 2022 results and the webinar helped launch the PISA in Focus ‘Managing screen time: How to protect and equip students against distraction’ https://www.oecd-ilibrary.org/education/managing-screen-time_7c225af4-en and the OECD Education Policy Perspective ‘Students, digital devices and success’ can be found here - https://oe.cd/il/5yV
2024.06.01 Introducing a competency framework for languag learning materials ...Sandy Millin
http://sandymillin.wordpress.com/iateflwebinar2024
Published classroom materials form the basis of syllabuses, drive teacher professional development, and have a potentially huge influence on learners, teachers and education systems. All teachers also create their own materials, whether a few sentences on a blackboard, a highly-structured fully-realised online course, or anything in between. Despite this, the knowledge and skills needed to create effective language learning materials are rarely part of teacher training, and are mostly learnt by trial and error.
Knowledge and skills frameworks, generally called competency frameworks, for ELT teachers, trainers and managers have existed for a few years now. However, until I created one for my MA dissertation, there wasn’t one drawing together what we need to know and do to be able to effectively produce language learning materials.
This webinar will introduce you to my framework, highlighting the key competencies I identified from my research. It will also show how anybody involved in language teaching (any language, not just English!), teacher training, managing schools or developing language learning materials can benefit from using the framework.
Ethnobotany and Ethnopharmacology:
Ethnobotany in herbal drug evaluation,
Impact of Ethnobotany in traditional medicine,
New development in herbals,
Bio-prospecting tools for drug discovery,
Role of Ethnopharmacology in drug evaluation,
Reverse Pharmacology.
How to Make a Field invisible in Odoo 17Celine George
It is possible to hide or invisible some fields in odoo. Commonly using “invisible” attribute in the field definition to invisible the fields. This slide will show how to make a field invisible in odoo 17.
Welcome to TechSoup New Member Orientation and Q&A (May 2024).pdfTechSoup
In this webinar you will learn how your organization can access TechSoup's wide variety of product discount and donation programs. From hardware to software, we'll give you a tour of the tools available to help your nonprofit with productivity, collaboration, financial management, donor tracking, security, and more.
Model Attribute Check Company Auto PropertyCeline George
In Odoo, the multi-company feature allows you to manage multiple companies within a single Odoo database instance. Each company can have its own configurations while still sharing common resources such as products, customers, and suppliers.
The Indian economy is classified into different sectors to simplify the analysis and understanding of economic activities. For Class 10, it's essential to grasp the sectors of the Indian economy, understand their characteristics, and recognize their importance. This guide will provide detailed notes on the Sectors of the Indian Economy Class 10, using specific long-tail keywords to enhance comprehension.
For more information, visit-www.vavaclasses.com
The Art Pastor's Guide to Sabbath | Steve ThomasonSteve Thomason
What is the purpose of the Sabbath Law in the Torah. It is interesting to compare how the context of the law shifts from Exodus to Deuteronomy. Who gets to rest, and why?
2. #MACURISA2014
DBMS Systems
! Many of the modern DBMSs support spatial data.
! Oracle, MS SQL, PostgreSQL are most often used.
! PostgreSQL is
! open source/free to use and modify
! incredibly reliable, extensible, powerful
! provides spatial capabilities through PostGIS
! DBMSs allow for “enterprise” functionality, like
multiple users/concurrency, high output, etc.
3. #MACURISA2014
Structured Query Language
! SQL is the standardized method of interacting with
a database
! Even Access allows you to use SQL
! Common, hopefully familiar, statements:
! Select (read from database)
! Insert (new records into a DBMS)
! Update (existing records in DBMS)
! Delete (remove records from DBMS)
! Where (limits your results)
4. #MACURISA2014
Select Statements
! Most common SQL
query you will
encounter
! “Select By Attributes”
has this as the
foundation
! Nothing more than
“SELECT * FROM
gis_layer WHERE…”
5.
6. #MACURISA2014
Joins
! In ArcGIS or Access, you join two (or more) tables
together using a primary key.
! If the keys match, the secondary tables are tacked
on to the first
! Again, geospatial is special, so GIS has another
type of join
7. #MACURISA2014
Combining Tables
! The simplest combination of two tables would be to
combine each record from table A with each record
from table B.
! The Cartesian Product.
! Example: A has 2 records, B has 3.
! A ✕ B: {(A1, B1), (A1, B2), (A1, B3),
(A2, B1), (A2, B2), (A2, B3)}
! Let’s take a deck of cards as an example.
8.
9.
10. #MACURISA2014
Joins
! Think of a Join as limiting the Cartesian Product of
two tables down to just the specific records desired.
! The manner in which you form your SELECT … JOIN
will be important:
! Ensure the desired records and columns are returned.
! Speed of the JOIN performed.
11. #MACURISA2014
Spatial Joins
! Relationship not determined by key, but by
proximity or connectivity
! Contains/Within/Overlaps
! One feature falls entirely within another
! Touches/Intersects/Crosses
! One feature touches another
! Equals or Disjoint
12. #MACURISA2014
Set Theory
! General terms first, because these concepts are
used across GIS and not just in SQL.
! Union
! Intersection
! Relative Complement
! Symmetric Difference
! Terms should be
somewhat familiar…
13. #MACURISA2014
Union
! ArcToolbox: returns a set where all features are
returned, however new features created where they
intersect.
! SQL: Set of all values from both tables.
! Join: An FULL JOIN – all values from two tables,
with NULL values where there are not shared values.
! Venn:
14. #MACURISA2014
Unions are not Cartesian
! Union / FULL JOIN will leave NULLs where there
are not matches across tables. All records will be
returned, however the records will not be “shuffled”
together like the cards example.
! FULL JOINs still require a WHERE or ON predicate
to create the join.
18. #MACURISA2014
Intersection
! ArcToolbox: returns a set where the geometries of
two different feature classes overlap.
! SQL: Only where the two tables share values.
! Join: An INNER JOIN – intersection of two tables.
! Venn:
19. #MACURISA2014
LEFT & RIGHT JOINs
! ArcToolbox: called Update.
! SQL: All records in Table A, along with some columns/
records from Table B.
! Join: A LEFT JOIN – columns from B will contain NULL if
there is no match. All records from A returned. (A RIGHT
JOIN is just an easy way of writing the reverse.)
! Venn:
! Examples?
20. #MACURISA2014
Symmetric Difference
! ArcToolbox: returns a set where the geometries
feature class A do not overlap feature class B.
! SQL: Only where the two tables do not share
values.
! Join: An FULL JOIN, WHERE a.value <> b.value
! Venn:
! Examples?
21. #MACURISA2014
Many types of Joins
! INNER and OUTER (LEFT, RIGHT, FULL)
! Different from Cartesian Product because some
comparison value needs to be tested for truth.
! Truth testing can be =, <>, <, > can also be the
result of a function.
! Spatial Joins in SQL:
! ST_Intersects(a.shape, b.shape)
! ST_Contains(a.shape, b.shape), ST_Within()
! ST_Overlaps(a.shape, b.shape)
! ST_Touches(a.shape, b.shape)
23. #MACURISA2014
Fire Stations in Town
! How can we calculate
the number of fire
stations within a
municipality?
! Can we find the most?
! Can we find the least?
! How about those towns
with no fire stations?
! How about those with a
specific number of fire
stations?
30. #MACURISA2014
Bus Routes
! How can we find the towns
that are along a given bus
route?
! How do we find the routes
that cross through a town?
! How do we find the towns
without service?
! bus.line = 553
AND
ST_Intersects(
bus.shape,
mun.shape)
31. #MACURISA2014
Self-Joins
! A table can be referenced
twice in the same query.
! How could we use this to
generate a “neighbor” list?
! How would we generate
that list of towns?
! FROM nj_munis m,
njmunis x
WHERE m.mun <>
x.mun AND
ST_Touches(m.shape
, x.shape)
32. #MACURISA2014
Denny's & La Quinta
! Using SQL to remove
the humor from jokes…
SELECT d.city, d.state,
ST_Transform(d.shape,2163) <->
ST_Transform(l.shape,2163) as
distance
FROM dennys d, laquinta l
WHERE (ST_Transform(d.shape,2163)
<-> ST_Transform(l.shape,2163))
< 150
ORDER BY 3;
34. #MACURISA2014
Power of SQL
! Speed.
! Flexibility.
! Data integrity and control.
! Automated reports as data changes.
! Views and functions can help automate and
streamline your GIS workflow.
! A bit of a learning curve, but SQL is a standard
and is supported and understood by a wide variety
of applications and data stores.
35. #MACURISA2014
More Info and Thanks!
! John Reiser
email: jreiser@njgeo.org
twitter: @johnjreiser
code: github.com/johnjreiser
! Articles on New Jersey Geographer:
http://njgeo.org/
! "Mitch Hedberg & GIS" (using PostgreSQL):
http://njgeo.org/2014/01/30/mitch-hedberg-and-gis/