Land Use/ Land Cover Classification Pascagoula, MS

 The map below illustrates Level 2 Land Use/ Land Cover in Pascagoula, Mississippi. The classifications are stratified into sub-classes denoting their broader schemes of urban development, agricultural land, forest land, water, and wetland. I assigned each class a different color for ease of reference. The points on the map represent a random sample of coordinates where an accuracy assessment was applied to my designated classifications to test if my delineating was correct. The results of the assessment were entered into an error matrix to deduce the producers accuracy (for my own edification) and the total accuracy of the sample on the map. 

The assignment required that we manually create polygons in a feature class that represented our own designation of classification boundaries. It was imperative to maintain a consistent scale throughout the exercise as to not confuse the demarcation of these boundaries. I was satisfied with the scale of 1:2,500 throughout my creation of the polygons though I often had to zoom in and out to make sure I was not missing any geometric areas and subsequently leaving them unmarked.

I encountered a major issue with my 'Clip' tool while attempting to separate the islands of non-forested wetlands from the bay and surrounding rivers. With office hours cancelled and needing to present an acceptable product, I exported each classification as its own features class and subsequently changed their symbology so the non-forested wetlands would be visible over the large singular bay/estuary polygon.

Upon completion of the project, I do feel that there may be a more spatially accurate methodology to produce our desired map. If one selects the entire study area as a polygon and then clips each internal feature from it, there would be no need to snap polygons together and it would prevent small and difficult to see areas from being missed. Since the entire study area is a polygon, all areas within it would be entirely accounted for. It was rather difficult performing the exercise attempting to snap together polygons and I do know that there is likely some overlap and minute (several pixels in squared area) regions that were missed. 

Below is my map:


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