The year 2021 is looming over us and I am dying to have some sort of control over what I could be doing for the next 365 days. While 2020 had been a year of 'character building', I discover alot of things about everything around me and myself. For starters, I am an avid planner; surprisingly. But it does not mean that I follow through with them. See what I did right there? I am admitting the truth behind self-study and lifetime of learning.
With alot of things I have planned to breathe new life to my own progress and time management, I went hunting for some interesting stuff in the internet for inspiration and try-outs. And guess what? I found one and I think most people may have been using this already in full swing because the review is 5 ⭐!
🌑🌒🌓🌔🌕🌖🌗🌘🌑
Taskade is simply a project/team management tool. Ah ah ah...before you write me off, hear me out. Taskade is aimed to help teams to plan, organize or manage their tasks and prioritize output for decision-making. It is simply an interactive planner sans organizer sans dashboard that sees where you're at with your work, what you've managed to get done and communicate tasks among people in your team; IF you have a whole team working on some sort of project. Hence, the chat capability that is implemented in this tool.
At my job, I work in a team of only 2 people; me and another colleague, and we're the regional programme unit which is apart of the bigger unit of team mates spread elsewhere in other regions. So, just because your unit is small, it doesn't mean that your task load complements your pint-sized manpower. So, I've been looking for platforms that could help me organize our productivity and ensure high-quality output. Just because technology is more advanced, it doesn'e mean there isn't any learning curve, right? So I tried just about anything under the sun for project/team management; Asana, Slack, Discord, the pre-existing Google..., but none of them could nail all shortcomings precisely; due dates, assignment of tasks, progress, sub-tasks, interactive commenting, multiplatform sync, brainstorming etc. Channels in Slack gives me headache -- same with Discord, and Telegram channels is too 'static' and 'one-way street' for me to view everything.
I found Taskade after trying to find a complementary 'Forest: Focus' extension at the Google Chrome extensions marketplace. There are plenty of interesting high-quality extensions as of late and I am pleasantyl surprised because earlier this year, most of them were quite 'beta' in their functionality. I saw a 'Bullet Journal' extension that someone raved about and another individual commented: 'Isn't this Taskade?'. The curious cat I am, I googled it and was not disappointed. What are the main keywords that hooked me?:
FREE
Google-integrated
Remote work environment advocacy
Multi-platform
What features do Taskade actually have? ✨
Given that it is an All-in-One Collaboration tool, it is understandable if the GUI is pleasing on the eyes. I do understand that first-impression is everything; color, packaging, fore-front information and visual, but it was really the functionality that delivers me to salvation. If you're an active member of Dev.to, then you'll catch feels with this theme that Taskade delivers. Key features in Taskade that you should try out:
Task list
Collaborators invitation feature (no organizational handle required)
Chat feature (with a call feature!)
Workspace feature (nothing new but...I'll get back to this later)
5 interchangeable neural-forest task list templates; List, Board, Action, Mindmap and Org Chart -- seamless with no error.
The capability to utilize this very platform as a presentation or exported into PDF task list printout.
Safe to say, Taskade buried me alive with the curation of beautiful images for the background; again...not relevant but needed to be said.
The Live Demosandbo lets you try it out for yourself although, at first glance, you may be wondering what on earth you are looking at. But it won't take long before you discover that it is quite intuitive.
Did I mention you can download and access it from just about ANYWHERE? Laptops, browser extensions and even smartphone apps. I'm not kidding when I said Taskade is multiplatform; they work on Windows, Mac, Android, iOS and Linux. Currently, I am testing it out using the Chrome extension and installed the app in my Android phone. It works like I expect it to so far.
What is the difference between the FREE and PAID version? 💰💰💰
As I just mentioned, you can sign-up for it for free and use it for life...for free. The priced version is seemingly there to accommodate the file size per upload you require; as of now. For free plan, you can upload 5MB file per upload while the paid version increases the size to 50MB per upload. Both versions offer:
Unlimited storage
Unlimited tasks entry
Unlimited project creation
Unlimited collaborators addition
The development team is currently adding more functionalities such as Project Activity Tracking, Integration to Dropbox, Google Drive and One Drive as well as Email Integration -- available for free.
Although it is mentioned that the free version of Taskade includes unlimited tasks, collaborators and all essential features, it was also mentioned that you will need to upgrade if you exceed the workspace limits which doesn't actually have any entailing elaborations which I will try to dig soon enough. But safe to say that if you are a single person using this tool, you are considered a team of 'one' where your shared projects in workspace to your 'editors' are still considered free. Only workspace the addition of workspace members are billed. This may imply that there are certain limits to how many individuals you can add into your workspace before you are required to upgrade. So far, visually, I see that the limit may be 2 people that makes up to 3 people per workspace (including yourself). You can find some details to pricing and FAQs here:
Taskade | Simple Pricing
Personally, I don't think USD5 is a hard bargain if you're self-employed and work with external parties collaboratively. If you're apart of an organization, feel free to ask for demo from them. Discount is possible if you're from a nonprofit or educational institution.
How I use Taskade? ☕
Well, given that it was free to sign-up, I tried it out straight away and I'm happy to report that I successfully managed to use it without having to google nor view any how-tos. That is a good thing! In fact, I am quite elated with just how easy it is to use this tool that I have used my personal email to help centralize and manage my work and personal work side-by-side. If you prefer some satellite view of your progress and all the task you need to complete to clear off certain objective, this is not a bad organization.
So I created 2 workspace: one for work and one for my personal tasks. Then I just collate all my tasks into monthly projects.
My personal tasks involve me updating my study progress and curating stuff I like online into my Tumblr blog.
Create studyblr workspace
Create new project in the studyblr workspace to organize and brainstorm Tumblr contents I plan to create and post: Tumblr: 2021/01.
Utilize the Mindmap template from all the options of templates shared and start creating the and organizing the content I want and tasks I need to execute to develop them.
Et voila! There all there is to it! It is easy peasy and you can start adding due dates as reminders and links as resources as well as hashtags for filtering in future. Check out some drafting I did so far in the screenshots below!
For more updates, check out their Updates page that fully utilizes Taskade to share all the updates straight from December 2017 till present and the chat function is there available for you to ask the Taskade team about the feature updates directly. Now that's awesome cause you know something's good if the one who makes them, actually uses them.😎😎😎
There are alot of Python courses out there that we can jump into and get started with. But to a certain extent in that attempt to learn the language, the process becomes unbearably long and frustratingly slow. We all know the feeling of wanting to run before we could learn how to walk; we really wanna get started with some subtantial project but we do not know enough to even call the data into the terminal for viewing.
Back in August, freeCodeCamp in collaboration with Jovian.ai, organized a very interesting 6-week MOOC called Data Analysis with Python: Zero to Pandas and as a self-proclaimed Python groupie, I pledged my allegiance!
If there are any expectation that I've managed to whizz myself through the course and obtained a certificate, nothing of that sort happened; I missed the deadline cause I was busy testing out every single code I found and work had my brain on overdrive. I can't...I just...can't. Even with the extension, I was short of 2 Pythonic answers required to earn the certificate. But don't mistake my blunders for the quality of the content this course has to offer; is worth every gratitude of its graduates!
Zero to Pandas MOOC is a course that spans over 6 weeks with one lecture webinar per week that compacts the basics of Python modules that are relevant in executing data analysis. Like the play on its name, this course assumes no prior knowledge in Python language and aims to teach prospective students the basics on Python language structure AND the steps in analyzing real data. The course does not pretend that data analytics is easy and cut-corners to simplify anything. It is a very 'honest' demonstration that effectively gives overly ambitious future data analysts a flick on the forehead about data analysis. Who are we kidding? Data analysis using programming language requires sturdy knowledge in some nifty codes clean, splice and feature engineer the raw data and real critical thinking on figuring out 'Pythonic' ways to answer analytical questions. What does it even mean by Pythonic ways? Please refer to this article by Robert Clark, How to be Pythonic and Why You Should Care. We can discuss it somewhere down the line, when I am more experienced to understand it better. But for now, Packt Hub has the more comprehensive simple answer; it simply is an adjective coined to describe a way/code/structure of a code that utilizes or take advantage of the Python idioms well and displays the natural fluency in the language.
The bottom line is, we want to be able to fully utilize Python in its context and using its idioms to analyze data.
The course is conducted at Jovian.ai platform by its founder; Aakash and it takes advantage of Jupyter-like notebook format; Binder, in addition to making the synchronization available at Kaggle and Google's Colab. Each webinar in this course spans over close to 2 hours and each week, there are assignments on the lecture given. The assignments are due in a week but given the very disproportionate ratio of students and instructors, there were some extensions on the submission dates that I truly was grateful for. Forum for students is available at Jovian to engage students into discussing their ideas and question and the teaching body also conducts office hours where students can actively ask questions.
The instructor's method of teaching is something I believe to be effective for technical learners. In each lectures, he will be teaching the codes and module requires to execute certain tasks in the thorough procedure of the data analysis task itself. From importing the .csv formatted data into Python to establishing navigation to the data repository...from explaining what the hell loops are to touching base with creating functions. All in the controlled context of two most important module for the real objective of this course; Numpy and Pandas.
My gain from this course is immensely vast and that's why I truly think that freeCodeCamp and Jovian.ai really put the word 'tea' to 'teachers'. Taking advantage of the fact that people are involuntarily quarantined in their house, this course is something that should not be placed aside in the 'LATER' basket. I managed to clear my head to understand what 'loop' is! So I do think it can solve the world's problem!
In conclusion, this is the best course I have ever completed (90%!) on data analysis using Python. I look forward to attending it again and really finish up that last coursework.
Oh. Did I not mention why I got stuck? It was the last coursework. We are required to demonstrate all the steps of data analysis on data of our choice, create 5 questions and answer them using what we've learned throughout the course. Easy eh? Well, I've always had the tendency of digging my own grave everytime I get awesome cool assignments. But I'm not saying I did not do it :). Have a look-see at this notebook and consider the possibilities you can grasp after you've completed the course. And that's just my work...I'm a standard C-grade student.
And the exciting latest news from Jovian.ai is that they have upcoming course at Jovian for Deep Learning called Deep Learning with PyTorch: Zero to GANS! That's actually yesterday's news since they organized it earlier this year...so yeah...this is an impending second cohort! Tentatively, the course will start on Nov 14th. Click the link below to sign-up and get ready to attack the nitty-gritty. Don't say I didn't warn ya.
And that's me, reporting live from the confinement of COVID pandemic somewhere in a developing country at Southeast Asia....
There is a moment where base maps just couldn't or wouldn't cut it. And DEMs are not helping. The beautiful hillshade raster generated from the hillshade tool can't help it if the DEM isn't as crisp as you would want it to be. And to think that I've been hiding into hermitage to learn how to 'soften' and cook visual 'occlusion' to make maps look seamlessly smooth. Cartographers are the MUAs of the satellite image community.
I have always loved monochromatic maps where the visual is clean, the colors not harsh and easy for me to read. There was not much gig lately at work where map-making is concerned. The last one was back in April for some of our new strategy plans. So, when my pal wanted me to just 'edit' some maps she wanted to use, I can't stop myself with just changing the base map.
The result isn't as much as I'd like it to be but then, we are catering the population that actually uses this map. Inspired by the beautiful map produced by John M Nelson that he graciously presented at 2019 NACIS; An Absurdly Tall Hiking Map of the Appalachian Trail. What I found is absurd is how little views this presentation have. The simplicity of the map is personally spot-on for me. Similar to Daniel P. Huffman as he confessed in his NACIS 2018 talk; Mapping in Monochrome, I am in favor of monochromatic color scheme. I absolutely loathe chaotic map that looked like my niece's unicorn just barf the 70s color deco all across the screen. Maybe for practical purposes of differentiating values of an attribute is deemed justifiable but surely...we can do better than clashing orange, purple and green together, no?
So...a request to change some labels turn into a full-on make over. There are some things that I realized while making this map using ArcGIS Pro that I believe any ArcGIS Pro noob should know:
Sizing your symbols in Symbology should ideally be done in the Layout view. Trust me. It'll save you alot of time.
When making outlines of anything at all, consider using a tone or two lighter than the darkest of colors and make the line thinner than 1 pt.
Halo do matter for your labels or any textual elements of your map.
Sometimes, making borders for your map is justifiable goose chase. You don't particularly need it. Especially if the map is something you are going to compact together with articles or to be apart of a book etc.
Using blue all the way might have been something I preferred but they have the different zonations for the rivers, so that plan went out the window.
And speaking of window...the window for improvement in this map is as big as US and Europe combined.
Esri has been releasing more and more MOOC over the span of 2 years to accommodate its increasingly large expanse of products within the ArcGIS ecosystem.
But of all the MOOCs that I've participated in, 'Do-It-Yourself Geo App MOOC' must be the most underrated ones produced by Esri Training. The functionalities highlighted within the MOOC took the anthem right off their recent Esri UC 2020 that went virtual. The curriculum includes:
The creation of hosted feature layer (without utilizing any GIS software medium like ArcMap or ArcGIS Pro).
The basics of the ArcGIS Online platform ecosystem:
hosted feature layer > web map > web app
Basically, to view a hosted feature layer, you will need to drag it onto a 'Map' and save it as a web map.
Conventionally, web map suffices for the visualization and analytical work for the likes of any geospatialist who are familiar with Web GIS.
But this time, Esri is highlighting a brand new web map product called 'Map Viewer Beta'. Why beta? Cause it is still in beta version but so sleeky cool that they just had to let every have a shot at using it. Truth be told, Map Viewer Beta did not disappoint.
Even so, Map Viewer Beta still has some functionalities that have yet to be implemented.
Using web map to visualize data, configure pop-up, execute simple analysis and extending it to Map Viewer Beta interface
Utilizing Survey123 for crowdsourcing data; the first level of citizen science and creating a webmap out of it.
Creating native apps using AppStudio for ArcGIS; no coding required.
Some tidbits on accessing the ArcGIS API for JavaScript
I love how cool it is that this MOOC actually shows you step-by-step on how to use the new Map Viewer Beta and explain the hierarchy of formats for the published content in the ArcGIS Online platform
I have established my understanding of ArcGIS Online ecosystem 3 years back but I do find it awkward that such powerful information is not actually summarized in a way that is comprehensible for users that have every intention of delving into Web GIS. And Web GIS is the future with all the parallel servers that could handle the processing/analysis of large amount of data. ArcGIS Online is a simplified platform that provides interfaces for the fresh-eyed new geospatial professionals.
It is quite well-know for the fact that there has been some criticism as to the domination of Esri within the GIS tools/resources within the geospatial science industry, but I believe it is something we could take as a pinch of salt. Not everything in Esri's massive line of commercial products are superior to other platforms but it is a starting point for any new geospatialists who wants to explore technologies there are not familiar with.
All in all, this MOOC is heaven-sent. For me, I have been playing with the web apps and web maps for close to 4 years and I can attest to the fact that it covers all the basics. For the developer's bit, maybe not so much as going through it in a distinct step-by-step but it does stoke the curiosity as to how it works. The question is, how do we make it work. Now that's a mystery I am eager to solve.
I'm going to put this on my ever-expanding to-do list and think JavaScript for another few more months of testing out this ArcGIS API for JavaScript implementation. Tell me if you wanna know how this actually works and I'll share what I find out when I do.
For those who had missed out on this cohort, fear not. This MOOC runs twice a year and the next cohort is going to be from Feb 17 to March 17 2021. The registration is already open, so don’t hold back and click the link below:
Do-It-Yourself Geo Apps
Do register for a public account before signing up or just click 'Register' at the MOOC's page and it's open the open to either sign in or 'Create a public account'. It was a blast and I'm sure, if you've never used any of the feature I've mentioned above, you'll be as wide-eyed as I was 3 years ago. :D
Till then, stay spatially mappy comrades!
P/S: If you complete all the assignments and quizzes, you'll get a certificate of completion from Esri. Which is pretty rad!
To cater for my lack of knowledge in biological data sampling and analysis, I actually signed up for the 'Wildlife Study Design and Data Analysis' organized by Biodiversity Conservation Society Sarawak
So, this new year, I've decided to take it down a notch and systematically choose my battlefield. Wildlife species data has always been mystery at me. As we all know, biologists hold them close to their hearts to the point of annoyance sometimes (those movies with scientists blindly running after some rare orchids or snakes or something like that really wasn't kidding). Hey...I get it and I totally agree - the data that belongs to the organization has to be treated with utmost confidentiality and all by the experts that collects them. Especially since we all know that they are not something so easily retrieved. Even more so, I optimistically support for the enthusiasm to be extended to their data cleaning and storing too while they're at it. But it doesn't mean I have to like the repercussions. Especially not when someone expects a habitat suitability map from me and I have no data to work with and all I had is a ping-pong game of exchanging jargon in the air with the hopes that the other player gets what you mean cough up something you can work with. Yes...there is not a shred of shame here when I talk about how things work in the world, but it is what it is and I'm not mad. It's just how it works in the challenging world of academics and research.
To cater for my lack of knowledge in biological data sampling and analysis, I actually signed up for the 'Wildlife Study Design and Data Analysis' organized by
Biodiversity Conservation Society Sarawak (BCSS for short)
or
Pertubuhan Biodiversiti Konservasi Sarawak
It just ended yesterday and I can't say I did not cry internally. From pain and gratitude and accomplishment of the sort. 10 days of driving back and forth between the city center and UNIMAS was worth the traffic shennanigans.
It is one of those workshops where you really do get down to the nitty-gritty part of understanding probability distribution from scratch; how to use it for your wildlife study data sampling design and analyzing them to obtain species abundance, occupancy or survival. And most importantly, how Bayes has got anything to do with it. I've been hearing and seeing Bayesian stats, methods and network on almost anything that involves data science, R and spatial stats that I am quite piffed that I did not understand a thing. I am happy to inform that now, I do. Suffice to say that it was a bootcamp well-deserved of the 'limited seats' reputation and the certificate really does feel like receiving a degree. It dwindles down to me realizing a few things I don't know:
I did not know that we have been comparing probabilities instead of generating a 'combined' one based on a previous study all these years.
I did not know that Ronald Fisher had such strong influence that he could ban the usage of Bayesian inference by deeming it unscientific.
I did not know that, for Fisher, if the observation cannot be repeated many times and is uncertain, then, the probability cannot be determined - which is crazy! You can't expect to shoot virus into people many times and see them die to generate probability that it is deadly!
I did not know that Bayes theorem actually combines prior probability and the likelihood data you collected on the field for your current study to generate the posterior probability distribution!
I did not know that Thomas Bayes was a pastor and his theory was so opposed to during his time. It was only after Ronald Fisher died that Bayesian inference gain favor especially in medical field.
I did not know...well...almost anything at all about statistics!
It changed the way I look at statistics basically. But I self-taught myself into statistics for close to 9 years and of course I get it wrong most of the time; now I realize that for the umpph-th time. And for that, I hope the statistics power that be forgives me. Since this boot camp was so effective, I believe it is due to their effort in developing and executing the activities that demonstrates what probability distribution models we were observing. In fact, I wrote down the activities next to the topic just to remember what the deal was. Some of the stuffs covered are basics on Binomial Distribution, Poisson Distribution, Normal/Gaussian Distribution, Posterior probability, Maximum Likelihood Estimate (MLE), AIC, BACI, SECR, Occupancy and Survival probability. Yes...exhausting and I have to say, it wasn't easy. I could listen and distracted by paper falling for a fraction of time just to find myself lost in the barrage of information. What saved me was the fact that we have quizzes that we have to fill in to evaluate our understanding of the topic for the day and discuss them first thing in the next session. Best of all, we were using R with the following packages: wiqid, unmarked, rjags and rasters. Best locations for camera traps installation was discussed as well and all possible circumstances of your data; management and collection itself on the field, were covered rigorously.
For any of you guys out there who are doing wildlife study, I believe that this boot camp contains quintessential information for you to understand to design your study better. Because once the data is produced, all we can do it dance around finding justification of some common pitfalls that we could've countered quite easily.
In conclusion, not only that this workshop cast data analysis in a new light for me, but it also helps establishes the correct steps and enunciates the requirements to gain most out of your data. And in my case, it has not only let me understand what could be going on with my pals who go out into the jungle to observe the wildlife first hand, it has also given me ideas on looking for the resources that implements Bayesian statistics/methods on remote sensing and GI in general. Eventhough location analysis was not discussed beyond placing the locations of observation and occasions on the map, I am optimistic in further expanding what I understood into some of the stuff I'm planning; habitat suitability modeling and how to not start image classification from scratch...every single time if that's even possible.
For more information on more workshops by BCSS or wildlife study design and the tools involved, check out the links below:
Biodiversity Conservation Society Sarawak (BCSS) homepage: https://bcss.org.my/index.htm
BCSS statistical tutorials: https://bcss.org.my/tut/
Mike Meredith's home page: http://mikemeredith.net/
And do check out some of these cool websites that I have referred to for more information as well as practice. Just to keep those brain muscles in loop with these 'new' concepts:
Statistical Rethinking: A Bayesian Course with Examples in R and Stan: https://github.com/rmcelreath/statrethinking_winter2019
Probability Concepts Explained: Introduction by Jonny Brooks-Bartlett: https://towardsdatascience.com/probability-concepts-explained-introduction-a7c0316de465
Probability Concepts Explained: Maximum Likelihood Estimation by Jonny Brooks-Bartlett: https://towardsdatascience.com/probability-concepts-explained-maximum-likelihood-estimation-c7b4342fdbb1
Probability Concepts Explained: Bayesian Inference for Parameter Estimation by Jonny Brooks-Bartlett
I'll be posting some of the things I am working on while utilizing the Bayesian stats. I'd love to see yours too!
P/S: Some people prefer to use base R with its simple interface, but if you're the type who works better with everything within your focal-view, I suggest you install RStudio. It's an IDE for R that helps to ease the 'anxiety' of using base R.
P/S/S: Oh! Oh! This is the most important part of all. If you're using ArcGIS Pro like I do, did you know that it has R-Bridge that can enable the accessibility of R workspace in ArcGIS Pro? Supercool right?! If you want to know more on how to do that, check out this short 2 hour course on how to get the extension in and an example on how to use it:
Using the R-Bridge: https://www.esri.com/training/catalog/58b5e417b89b7e000d8bfe45/using-the-r-arcgis-bridge/
Survey123 for ArcGIS is perhaps, one of those applications that superficial nerds like me would like; it's easy to configure, kiddie-level degree of customization with 'coding' (for that fragile ego-stroke) and user-friendly template to use.
No app development/coding experience is required to publish a survey form and believe it or not, you can, personalize your survey to not look so meh.
It took me some time to stumble through the procedures of enabling this feature before I understand the 'ArcGIS Online' ecosystem to which this app is chained to.
So how do we do it? And why doesn't it work pronto?
This issue may be due to the fact that when we first start creating our forms, we go through the generic step-by-step procedures that leave little to imagination what was happening. Most of the time, we're too eager to find out how it really work.
When we publish a Survey123 form; be it from the Survey123 website portal or the Survey123 Connect for ArcGIS software, we are actually creating and publishing a folder that contains a hosted feature layer and a form. It is on that hosted feature layer that we add, delete, update or edit data it. From ArcGIS Online, it looks like any feature service that we publish out of ArcGIS Desktop or ArcGIS Pro, save for the special folder it is placed in with a 'Form' file.
To enable any offline function in any hosted feature layer in ArcGIS Online, you will need to enable the 'Sync' feature. So far, in many technical articles that I have gone through to learn how to enable this offline feature always goes back to 'Prepare basemaps for offline use'. It is a tad bit frustrating. But my experience when deal with 'Collector for ArcGIS' gave me the sense of epiphany when it comes to Survey123. So when you have prepared your Survey123 form for offline usage and it still doesn't work...do not be alarmed and let's see how to rectify the issue.
1. Locate your survey's hosted feature layer
At your ArcGIS Online home page, click 'Content' at the main tab. We're going to go directly to your hosted feature layer that was generated for your survey when you published.
Locate your survey folder. Click it open
In the survey folder, navigate to the survey's hosted feature layer and click 'Options' button; the triple ellipses icon
At at the dropdown, click 'View item details'. Please refer to the screenshot below:
2. Change the hosted feature layer settings
At the item details page, navigate to the 'Settings' button at the main header and click it. This will prompt open the settings page for the feature layer. Refer to the screenshot below:
At the 'Settings' page, there are two tabs at the subheader; 'General' and 'Feature layer (hosted)'. Click 'Feature layer (hosted)' to configure its settings.
At the 'Feature layer (hosted)' option, locate the 'Editing' section. Here, check the 'Enable sync' option. This is the option that will enable offline data editing. Please refer to the following screenshot:
Don't forget to click 'Save'
With this, your hosted feature layer which serves as the data model is enabled for synchronization. Synchronization helps to sync back any changes you've made when you're out on the field collecting data; editing, adding, deleting or update...depending on what feature editing you've configured.
It's pretty easy once you get the hang of it and just bear in mind that the data hierarchy in the ArcGIS Online universe are as follows:
Feature layer (hosted) > Web map > Web application
Once you get that out of the way, go crazy with your data collection without any worries!
Coding is one of the things I have aspired to do since like...forever! But finding a resource in-sync with my comprehension, schedule and able to retain my interest long enough is a challenge.
I have the attention span of a gnat so, I jumped everywhere! If I am not actively engaged with the learning, I just can't do it. And I know...we have DataCamp, Udemy, Khan Academy and even Kaggle...but I either can't keep up, too poor to pay for the full course or it couldn't sync with me enough. I believe I can say that most of the exercise doesn't 'vibe' with me.
Recently, I committed myself to my one passion; running. It's one of my favorite activities when I was back in school but the will to really run died a decade ago. I have recently picked up my running shoes and ran my little heart out despite having the speed of a running ant; aging perhaps? And I owe my hardcore will to the motivation of earning what I paid when I decided to join a 1-month long virtual run of 65km. It is called the 'Pave Your Path' virtual run organized by
Running Station
. Nailed it 2 days ago after 13 sessions of 5km - yes, you can accumulate the distance from multiple runs. It made me realize that...it's not that bad. The 'near-death' experience while running kinda turned me into a daredevil these days when it comes to undertaking some things I'd whine about doing a few months back.
"If I can go through dying every single evening for 5km long run...I can handle this,"
My thoughts exactly every time I feel so reluctant to finish some tasks I believe I could hold off for some time.
Naturally, I plan my work rigorously and despite the flexibility of my schedule and my detailed plans, I still have a hard time trying to nail the last coffin to my projects. Usually, it's due to my brain's exhaustion from overthinking or I am just truly tired physically. Which is a weird situation given I do not farm for a living. Even so, I was lethargic all the time.
But when I started running a month ago, things kind of fall into places for me. Maybe...just maybe...I've become more alert than I used to. I still have my ignorance of things that I believe do not concern my immediate attention but I seem to be able to network my thoughts faster than I used to.
It might be just me, feeling like a new person due to my sheer willpower to not burn my RM60 paid for the virtual run, but it did feel like there was a change.
For that, I managed to confirm what I have suspected all along - I am one of those people who love drills. I like things to be drilled into my head until I by-heart it into efficiency and then focus on polishing the effectiveness.
Thus...for coding, I committed myself to
freeCodeCamp
. By hook or by crook, I'll be coding by first quarter next year or someone's head is gonna roll!
It's an interactive learning experience simple enough for me to start, straightforward enough to not make me waste my time searching for answers and it's free. God bless Quincy Larson.
Going back to the program outlined in freeCodeCamp, I find it fascinating that they start off with HTML. I have no arguments there. My impatience made me learn my lesson - you run too fast, you're going to burn out painfully and drop dead before you halfway through. HTML is a very gentle introduction to coding for newbies since it's like LEGO building blocks where you arrange blocks and match two to create something. I didn't have to go crazy with frustration is I don't 'get' it. Yes, we would all want some Python lovin' and I think alot of coders I came to know have raved about how simple it is to learn. But I think, it is an opinion shared by 'experienced' coders who wished Python was there when they first started coding. Someone once told me, what you think is the best based on others' experiences may not be the best for you...and I agree with this. After alot of deliberations and patience at my end, starting over again this time feels, unlike the dreaded looming doom I've always had back then.
Are you into coding? What do you code and what's you're language preference? Where did you learn coding? Feel free to share with me!
Have you ever heard of the binning technique?
My favorite cartographer is John M. Nelson. In fact, he's the one who actually got me searching what 'cartography' really is. Fortunately, he's a mix of a storyteller/technical support analyst/designer. So, his techniques are the ones I have least trouble understanding. And this is by no means a comment meant to offend because really, I'm a little slow and John is a very 'generous' teacher when it comes to explaining things; even through replies in posts. You can witness his work first hand at his own blog posts here;
https://adventuresinmapping.com/
So, the first of his work that captured my attention is the Six Month Drought of the American Southeast map created using the binning method. I didn't even know what binning is, but the map was so pretty it had me announcing my loyalty to #cartography hashtags.
So what is binning? According to GIS Lounge, binning is a data modification technique where original data values is converted into a range of small intervals called bins. Bins will then be replaced with a values that is representative of that interval to reduce the number of data points.
Okay. It should be a no-brainer. But the data he used was the polygon shapefiles of droughts' extent and their severity. Although it is still unknown to me how USGS actually collect this data but his map is sang the deserving anthem to their hard work. But alas, I never had the chance to reproduce it. I do not have the knack of identifying interesting data of any sort, so I either am stuck with reproducing a redundant work or waste my time in a wild goose chase for data; I'm a noob with a tunnel-vision focus. I won't even vote myself if we have a jungle excursion that requires mapping cause we'll be stuck longer than necessary.
Even so, one year later, precisely this moment...I found a valid reason to attempt this. And it's all because I need to validate satellite imagery classification some colleagues made to show hot spots of global deforestation. I am not a remote sensing wizard, but vector data...now that I can work with.
Using the same binning technique, I can summarize the steps as follows:
Merge all the data of deforestation variables Generate hexagonal tessellation Create the hexagon centroids Use 'Spatial Join' to sum up the weights of overlapping polygon features of the merged data and join it with the hexagonal centroids Then configure symbology
Visualizing was a herculean effort for my brain. The map John made is a bivariate map. And compared to his data which has 2 numerical variables to enable that, mine only had one and it is the summation of the ranking weight I ensued on the deforestation variables. He merged all the shapefiles of weeks after weeks of drought severity readings. Me...I just manage this >>>
My first attempt was to just visualize the probability of the deforestation using the centroid point sizes.
That wasn't much of a success because visually, it doesn't actually appeal to my comprehension. It looks good when you zoom in closer because it gives off that newspaper print feel with that basemap. From this whole extent, it's not helpful.
So, after I tried to no avail to make it work with toggling the size and the colors, I found that instead of trying to make it look nice, I better opt on answering the questions posed by my colleague; could you identify the areas of high likeliness of prolonged deforestation? For that purpose, only hexagonal mesh would do the trick. So based on the 10 km sq size of their hexagons that depicts the areas of deforestation based on image classification, I used 'Spatial Join' too again and join the centroids back their predecessor hexagons to carry the binned values.
Et voila!
The weight summation was of the degree of prolonged deforestation likeliness and the values range all the way to 24. I made 4 intervals which gave a practical visualization. Eight intervals were pushing it and 6 was not pleasant. It could be my color palette choice that made them unappealing but too many intervals will defeat my purpose.
Yay or nay...I'm not too sure about it. But I do believe that this summarizes the areas where conservationists should be on the alert with.
After having a discussion with a colleague, yeah...this technique has a lot of gaps.
ONE; this is not a point feature. Using the values where the centroid touches/overlays ONLY is not exactly a precise method. Although, it is not wrong either.
TWO; The merged polygonal data came off as OVERLAPPING polygonal features.
Overlooking the shortcomings and just using it to visually aid cross-checking...yea maybe. Even then...it's not as laser-point precise as one would aspire. I stand humbled.
Story Map is a web application template product that has been popularized in ArcGIS Online for a user-friendly and comprehensive narrative of maps. The ‘Cascade’ template has become the seamless interface of choice due to it’s ribbon transitions and availability of content streaming from external sources.
Please refer to the following link for resources used in this webinar:
Story Map for Noobs: Cascade web application
📌 Availability: Retracted in 2021