Digitalization in ArcGIS is the process of converting geographic data from a hardcopy or a scanned image into vector data by tracing the features. It can help distinguish very small objects, depending on the resolution and accuracy of the source image and the digitizing method. There are three types of digitizing methods in ArcGIS: manual, heads-up, and automatic.

· Manual digitizing involves using a digitizer puck to trace features on a paper map or image. It has high accuracy, but it is time-consuming and requires a digitizing tablet.

· Heads-up digitizing involves scanning a paper map or image and displaying it on-screen as a base map, then drawing features on top of it. It is faster and easier than manual digitizing, but it may introduce errors due to misalignment or distortion of the base map.

· Automatic digitizing involves using image processing techniques to convert raster data (such as satellite imagery) into vector data. It is the fastest and most efficient method, but it may not capture all the details or nuances of the features.

Therefore, digitalization in ArcGIS can help distinguish very small objects, but the quality of the output depends on the quality of the input and the choice of the digitizing method.

How 'small' is 'small'?

Dear Nora,

It depends on you, as you will start digitizing and creating the shape files.

You have a choice, of which object you want to digitize or for which object you want to create a shape file.

The smaller object may be missed on the map scale (without zooming) but you can create the shape file and digitize it for more accuracy.

Eshim Ahmed Nora Firstly, let's consider the heart of digitization in ArcGIS. When I first began using ArcGIS, the potential it held for transforming our understanding of geographical features was immediately apparent. It's like opening a new window to view the world, where each layer you add offers a fresh perspective.

Now, regarding your objective of distinguishing between geological and artificial features, digitization in ArcGIS is indeed a powerful tool. The beauty of this process lies in its precision and flexibility. Imagine you're painting a detailed landscape, but instead of a brush, you have a plethora of digital tools at your disposal. Each tool allows you to capture the intricacies of the terrain, down to the smallest rock or man-made structure.

The key here is the resolution and quality of the data you're working with. High-resolution satellite imagery or aerial photographs are like the fine strokes of a master painter, revealing subtle details that might otherwise be overlooked. When you digitize these images in ArcGIS, you create shapefiles – essentially digital drawings – that accurately represent these features.

I recall a project where we had to distinguish between natural riverbeds and artificially modified water channels. At first glance, it seemed daunting, but as we zoomed in with our high-resolution imagery and began the careful process of digitization, the differences became starkly clear. The natural riverbeds had irregular, winding paths, shaped by centuries of water flow, whereas the artificial channels were more uniform and linear – the unmistakable imprint of human design.

In your case, to distinguish geological features from artificial ones, you'll need to pay close attention to patterns, shapes, and textures. Geological features often have a more random, natural appearance, showing the chaotic yet beautiful hand of nature. Artificial features, on the other hand, tend to exhibit regularity and symmetry, a reflection of human logic and planning.

Dear Eshim

Sorry, your question is very difficult to understand because before digitizing an object with ArcGIS, you naturally need to recognize it.

But if the digital data was previously generated by a specific sensor or capture system with geospatial data format, it will probably be used to recognize small objects through the use of different algorithms. But the success of the process will depend on the type of data you are processing and the nature of the object you intend to detect. ArcGIS as a general-purpose GIS platform can probably help detect small objects, but object detection techniques do not belong exclusively to geospatial GIS techniques. The methodologies are broad and as I said before they will depend on the characteristics of the object to be detected and the capabilities of the capture system.

Eshim Ahmed Nora, identification of small objects is matter of spatial resolution of remote sensing data, not a technology. You have enough resolution, you could identify small objects.