I am pleased to share the updated context map DRAFT for your review and comments.Of course, review to note any obvious omissions or anomalies in the map. Also, please share your general thoughts on the look and feel of the map. The way we have it right now with the basemap labeled “Light Gray Canvas”, the building footprints show up as you zoom in. I find that very helpful to visually confirm the context.There are actually have many different criteria that can lead to classification. This detail was necessary to refine the map. You can check on and off the different criteria on the left to see how it impacts the map if you would like.There are many different considerations, but mostly context is defined by the development of buildings - how close the buildings are to the road, how densely they have been built together, and how large the building area is. Urban and Rural Village contexts tend to have more buildings close to the road and suburban contexts tend to have buildings further back. Here is the primary data considered: Immediate Building Density Immediate Building Area Density Immediate Building Count Wide Building Density Wide Building Area Density Wide Intersection Density Wide Segment Density Federal and State Urban Compact AreasThe “immediate” building information considers buildings that partially within 60 feet of the road centerline. For a sports analogy, that is about the distance from a baseball pitching rubber to home plate. The “wide” data looks at buildings, segments, and intersections in the general area 1/8 of a mile from centerline in all directions. That is about the distance of two football fields. Both types of data have value, especially when they are strategically used together.The Map is split into 5 contexts categories: Red - Urban Orange - Suburban Dark Green - Rural Village (Heavily Developed) Light Green - Rural Village (Moderately Developed) Blank – RuralThe red urban and the dark green village areas have exactly the same criteria except one is inside federal or state urban compact and one is outside both urban compacts. You will also notice some of the major arterial roads cutting through urban areas have been identified as suburban. Examples of this include William Clark Drive in Westbrook, Center Street and Minot Avenue in Auburn, and Pleasant Street in Brunswick. This typically occurs because the buildings are mostly built back further from the road.Important to note: We will need two “rural village” layers. We realized we need to separate how we treat the very densely developed villages like downtown Camden and the fringe villages like Searsmont and Jefferson.

Thank you for giving this map a look over and providing your feedback.

I am pleased to share the updated context map DRAFT for your review and comments.Of course, review to note any obvious omissions or anomalies in the map. Also, please share your general thoughts on the look and feel of the map. The way we have it right now with the basemap labeled “Light Gray Canvas”, the building footprints show up as you zoom in. I find that very helpful to visually confirm the context.There are actually have many different criteria that can lead to classification. This detail was necessary to refine the map. You can check on and off the different criteria on the left to see how it impacts the map if you would like.There are many different considerations, but mostly context is defined by the development of buildings - how close the buildings are to the road, how densely they have been built together, and how large the building area is. Urban and Rural Village contexts tend to have more buildings close to the road and suburban contexts tend to have buildings further back. Here is the primary data considered: Immediate Building Density Immediate Building Area Density Immediate Building Count Wide Building Density Wide Building Area Density Wide Intersection Density Wide Segment Density Federal and State Urban Compact AreasThe “immediate” building information considers buildings that partially within 60 feet of the road centerline. For a sports analogy, that is about the distance from a baseball pitching rubber to home plate. The “wide” data looks at buildings, segments, and intersections in the general area 1/8 of a mile from centerline in all directions. That is about the distance of two football fields. Both types of data have value, especially when they are strategically used together.The Map is split into 5 contexts categories: Red - Urban Orange - Suburban Dark Green - Rural Village (Heavily Developed) Light Green - Rural Village (Moderately Developed) Blank – RuralThe red urban and the dark green village areas have exactly the same criteria except one is inside federal or state urban compact and one is outside both urban compacts. You will also notice some of the major arterial roads cutting through urban areas have been identified as suburban. Examples of this include William Clark Drive in Westbrook, Center Street and Minot Avenue in Auburn, and Pleasant Street in Brunswick. This typically occurs because the buildings are mostly built back further from the road.Important to note: We will need two “rural village” layers. We realized we need to separate how we treat the very densely developed villages like downtown Camden and the fringe villages like Searsmont and Jefferson.

Thank you for giving this map a look over and providing your feedback.