Floating...in The Mid Of It

The devil in the details

I have started to post some videos demonstrating some tools in ArcGIS Pro. Short ones and pretty quick ones which I strived for since I absolutely am frightened with the idea of irritating people with unnecessary voice-over. It has no garnered much response and it's cool with me. Although, the lack of traction does things to my insides, I go back to the real reason I am doing thing, which is to stash the tools that I managed to learn on my own by trials and errors and keep them somewhere I can refer back to it to remember how it works.

Creating maps involves a number of iterative processes made to suit the intended output. Although creating maps itself is a form of art; heavily reliant on target audience's knowledge and aesthetical preference, it is still an inherently democratic science. Thus, knowing the mainstream technology and tools in the industry to express your vision or message is given. So for those just starting out with using geographical information software (GIS) for your final year project or research, this videos are meant for you. The purpose is not to overwhelm you with too many information, or distract you with my narration, but to follow in real-time the process from the start up of the software to the running of tools that generates the information needed.

Knowing fully well that there is an endless variety of GIS software or tools out there, processes that you need to execute to make things happen may vary in name and functionalities. Forget the beef between ArcGIS and QGIS, of which one is the better tool; if it serves your needs, then use it. You're not obliged to pledge loyalty to software or brands although you are encouraged to maintain integrity in your beliefs when it comes to corporate versus open source tools in the industry. Both choices come with their advantages and disadvantages. Yours truly uses QGIS and ArcGIS Pro interchangeably. If it doesn't work in ArcGIS Pro, which I use primarily, I'll jump to using QGIS. It's not a big deal. If it works painlessly, there is no reason to feel bad about using it.

So far, the content I have made emphasizes mostly on ArcGIS Pro or Esri products since using them is how I come to learn more about geology and geography. QGIS was a name I did not learn of in my university years when ArcGIS versions start with the digit 9️⃣, so you can catch my drift.

We can go on and on about theoretical stuff and our smarter pals usually knows what to do when faced with the tools. Unfortunately, I fall in the percentile that needed to land on the job to understand what on earth I am supposed to do. This series of videos are for those who have the same problem as I do and need to see the magic actually happening before knowing what to do. And for the most part, there are so many things to read and try out before you get it right. So hopefully, the demos can kickstart some thoughts or observation in the logic within the software's ecosystem and become more than just a technical power-user.

This week, I touched on some tools that I found helpful when dealing with point vector data, so feel free to check it out 👇🏻

Next week, I'm thinking of exploring some series of point analysis and space time cube is beckoning for me to test it out. Until then, stay cool and drop a word if you need any clarifications on the demos!

Eyes on the Forest Sarawak | WWF-Malaysia

The ‘Eyes on the Forest’ Sarawak web application is developed with the joint effort of WWF-Malaysia and WWF-Japan. Emulating the successful ‘Eyes on the Forest’ Sumatra database, this web app intends to provide an undiluted information on the rich diversity of Sarawak’s unique wildlife, forests and land uses as well as increasing the transparency on the threats; deforestation, infrastructure developments and urbanization, as well as its drivers; concessions, agricultural activities and unsupervised resource harvesting.

Identifying where the threats, the drivers and the conservation targets are located will help in making a concrete point at the policy level and push for more boots on the ground to ensure that the protected areas stay protected. The baseline information provided are essential in the prompt intervention for biodiversity protection.

Data collected and consolidated from dispersed public sources and engineered for simple and direct visualization. Values are generated based on verified legislated information provided by stakeholders and state agencies to the Sarawak Conservation Programme (SCP) for WWF-Malaysia.

Developed and maintained by:

Azalea Kamellia

GIS Officer (SCP) | WWF- Malaysia

June 2018 - Present

🌱 Google Earth Pro 101

Google Earth Pro is one of the most powerful freely available software one can use for location investigation. If you're a non-tech GIS user who needs to know just enough to get your work going, then let's hit the ground running with this tutorial for starters.

🟢 Beginner-friendly.

🆓 Free with no hidden monetary cost.

🖥️ Available for Windows, Mac and Linux.

train on water

Peta Gunatanah Malaysia 2014 - 2018

Peta Gunatanah Malaysia 2014 -2018 ("Malaysia's Land Cover 2014 - 2018") web application is a platform generated for the Quality Assessment activity organized by Forest Research Institute Malaysia (FRIM) on 23rd June 2024.

The workshop aims to collect field/reference data from Malaysian's state agencies in the effort to verify the quality of the land cover classification output generated in support of CO2 release measurement from converted agricultural lands.

Participants are able access the app via conventional browsers from their mobile devices and submit drawings/sketches that they have captured within interactive data layers.

This web app aims to support direct input from source onto the task of improving the accuracy of the generated land cover maps. Vectors generated from this exercise are readily standardized with the required data scheme from quality assessment, making full use of the ArcGIS Online ecosystem full to a produce concrete output and actionable information.

Community Empowerment Strategy Dashboard 2021 | WWF-Malaysia

Tool: Operations Dashboard ArcGIS, Survey123 for ArcGIS, ArcGIS Online Technique: XLSForm programming, web application development

The northern highland communities of Lun Bawang have been collaborating with WWF-Malaysia under the Sarawak Conservation Programme (SCP) to empower sustainable economies and managing their natural biodiversity through the Community Empowerment Strategy (formerly known as Community Engagement and Education Strategy).

Since 2016, the communities have been actively mapping out their land uses and culturally important locations to delineate their areas of settlement and source of livelihood. Given the close vicinity of their communities to the licensed timber concessions, producing a definitive map is important to preserve and conserve their surrounding natural capitals.

Several outreach has been done and the community mapping effort has been shifted to implement citizen science via the Survey123 for ArcGIS mobile application which is apart of the ArcGIS ecosystem. This enables the local community to collect information despite the lack of network reception and the data can still be synchronized upon availability automatically or manually shared with the field officers.

📌 Availability: Retracted in 2021

Story Map for Noobs: Cascade | WWF Network

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

[2022] 30 Day Map Challenge -- FAILED

Last year, I participated once again in the 30 Day Map Challenge that was going around in Twitter-ville come November. It is the 3rd attempt at the marathon and 2022 served as a reminder that progressed too despite getting stuck at Day 3 as life caught up with me.

I don't like the idea that I have left the challenge incomplete, again. It was not my priority and I work better with clear goals or visions of expected output. If it does not add to my need to learn something new ...it will be a task bound to head straight to the backburner. Let's resolve to make it a long-term routine instead of a spurt of stress trying to make the deadline.

As a consequence, I am attuning this task into one that actually gives me the benefit out putting into record the techniques and tools I used to make the maps in writing. I believe that will serve more purpose and added value other than visuals. And perhaps, have some stock ready for submission this year instead.

Anyone else participated in this challenge back in November? How did you do and what would you like to do better for the next one? Don't be shy and do drop a word or two.

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.