Geographic Information Services (GIS) – Maps – Cartography

I am an amateur cartographer who designs maps and does a wide variety geospatial analysis using free and open-source geographic information software (GIS) and public sources of data to design quality maps, graphs, charts and datasets. I am looking for new and interesting projects to improve my skills, make connections and expand my portfolio.

Mapping Avaliable

• Tax/Property Mapping
• High Resolution Aerial Photography
• Recreational Maps – Hunting, Camping, Hiking
• Georeference addresses using State Address Mapping service, plot them on a map
• Wetlands, Topographic Contours, Land Cover
• Compare historical aerial photos or maps to current photography
• Web mapping using leaflet (HTML/Javascript file to embed on a website or use at home)

Example maps can found below.

Services Available

• A list of property owners within 1,000 feet of a proposed development
• How many cars per day pass a business?
• How many people who live within 5 miles of a business or park?
• How many African Americans and Hispanics live within 10 miles of Albany Pine Bush?
• What are wealthiest election districts?
• How many people ride public transit in a neighborhood?
• How much of an area is wetland or farm field?
• How big an interchange?
• What is the average slope and elevation of an area or trail?

Example data can found below.

Pricing and Cost

For most projects, there is no fee. I am looking for experience, references, mentors and connections in the geospatial community.

If you have a large project, let’s talk about it. I might be willing to do it for free, if it’s something really interesting
or important like fighting suburban sprawl and pollution. I don’t a business or taxes set up, so I can’t really charge at this point.

Data Avaliable

• US Census – 2019 American Community Survey, 2020 US Census
• NYS Tax and Assessment Rolls (2020)
• NYSDOT Traffic Counts and Road Data
• Historical Aerial Photography (primarily 1952, but earlier and later exist)
• ArcGIS REST/Services and WMS Services from state and local agencies
• LiDAR Elevation Profiles
• USGS Topographic Maps, historic and modern – with overlays if requested
• Data Repositories like CUGIR, DataNY.gov and NYSGIS
• Recreation data from NYSDEC

Software Used

• Quantum GIS (QGIS) including 3D Mapping
• Geodata Abstraction Library (GDAL, ogr2ogr)
• Python, including the data-science libraries PANDAS and GeoPANDAS
• LeafletJS Web Mapping Services

Geographies Avaliable

• Primary Capital Region and also much of New York State, also some for Pennsylvania, Vermont, West Virginia
• State, county, municipal, school districts – Most data sets
• Parks, highways, buffer (distance to) – Most data sets
• Election districts – Roughly 75% of NYS counties
• Census Tract or Blockgroup – 2019 American Community Survey
• Tabulation Block – 2020 US Census

Are printed maps avaliable at this time?

Not currently. I can send you a file based on your specifications to print at your local print shop.

How long do mapping projects take?

Depends on complexity of the project. Many projects only take minutes, however if a project requires georeferencing, data cleaning, or custom shapes or layouts, it might take significantly longer. More revisions lead to better quality output.

Do you make maps professionally?

No! This is just a hobby. But I’m interested in expanding my skills. I do a lot of mapping for my blog and in support of community organizations like Save the Pine Bush.

Are my maps of good quality?

Thats for you to decide. I don’t have formal education in map making, and I don’t have professional tools. But do take a look at the work I’ve done below.

Examples of Maps

Examples of Data and Code

Properties in Albany Pine Bush Study Area,Excel Files: Various Tax Rolls,Find coordinates and political districts,Look Up State Tax Records and aScript for Processing RPTL 1520 PDFs.

Querying state property database, political enrollments, PL 94-171 Census files, calculating population statistics, what address is a district in, converting old districts to new districts.

import pandas as pd
import geopandas as gpd
 
# path to overlay shapefile
overlayshp = r'/tmp/dis_to_albany.gpkg'
 
# summary level -- 750 is tabulation block, 150 is blockgroup
# large areas over about 50 miles much faster to use bg
summaryLevel = 150
#summaryLevel = 750
 
# path to block or blockgroup file
if summaryLevel == 150:
    blockshp = r'/home/andy/Documents/GIS.Data/census.tiger/36_New_York/tl_2020_36_bg20.shp.gpkg'
else:
    blockshp = r'/home/andy/Documents/GIS.Data/census.tiger/36_New_York/tl_2020_36_tabblock20.shp.gpkg'
 
# path to PL 94-171 redistricting geoheader file
pl94171File = '/home/andy/Desktop/nygeo2020.pl'
 
# field to categorize on (such as Ward -- required!)
catField = 'Name'
 
# geo header contains 2020 census population in column 90 
# per PL 94-171 documentation, low memory chunking disabled 
# as it causes issues with the geoid column being mixed types
df=pd.read_csv(pl94171File,delimiter='|',header=None, low_memory=False )
 
# column 2 is summary level 
population=df[(df.iloc[:,2] == summaryLevel)][[9,90]]
 
# load overlay
overlay = gpd.read_file(overlayshp).to_crs(epsg='3857')
 
# shapefile of nys 2020 blocks, IMPORTANT (!) mask by output file for speed
blocks = gpd.read_file(blockshp,mask=overlay).to_crs(epsg='3857')
 
# geoid for linking to shapefile is column 9
joinedBlocks=blocks.set_index('GEOID20').join(population.set_index(9))
 
# store the size of unbroken blocks
# in case overlay lines break blocks into two
joinedBlocks['area']=joinedBlocks.area
 
# run union
unionBlocks=gpd.overlay(overlay, joinedBlocks, how='union')
 
# drop blocks outside of overlay
unionBlocks=unionBlocks.dropna(subset=[catField])
 
# create population projection when a block crosses
# an overlay line -- avoid double counting -- this isn't perfect
# as we loose a 0.15 percent due to floating point errors
unionBlocks['sublock']=unionBlocks[90]*(unionBlocks.area/unionBlocks['area'])
 
# sum blocks in category
unionBlocks=pd.DataFrame(unionBlocks.groupby(catField).sum()['sublock'])
 
# rename columns
unionBlocks=unionBlocks.rename({'sublock': '2020 Census Population'},axis=1)
 
# calculate cumulative sum as you go out each ring
unionBlocks['millions']=unionBlocks.cumsum(axis=0)['2020 Census Population']/1000000
 
# each ring is 50 miles
unionBlocks['miles']=unionBlocks.index*50
 
# output
unionBlocks

Most highly assessed properties in Albany County …

from arcgis.features import FeatureLayer
lyr_url = 'https://gisservices.its.ny.gov/arcgis/rest/services/NYS_Tax_Parcel_Centroid_Points/MapServer/0'
layer = FeatureLayer(lyr_url)
query_result1 = layer.query(where="COUNTY_NAME='Albany' AND FULL_MARKET_VAL > 100000000", 
                                    out_fields='PARCEL_ADDR,CITYTOWN_NAME,FULL_MARKET_VAL,OWNER_TYPE', out_sr='4326')

df=query_result1.sdf.sort_values(by='FULL_MARKET_VAL', ascending=False)
df['Full Market Value'] = df['FULL_MARKET_VAL'].map('${:,.0f}'.format)

df

	OBJECTID	PARCEL_ADDR	CITYTOWN_NAME	FULL_MARKET_VAL	OWNER_TYPE	SHAPE	Full Market Value
11	26652	64 Eagle St	Albany	1204254925	2	{“x”: -73.75980312511581, “y”: 42.650469918250…	$1,204,254,925
3	9150	1200 Washington Ave	Albany	886298715	2	{“x”: -73.81092293494828, “y”: 42.679257168282…	$886,298,715
4	10208	1400 Washington Ave	Albany	642398287	2	{“x”: -73.82369286130952, “y”: 42.685845700657…	$642,398,287
0	885	251 Fuller Rd	Albany	440042827	2	{“x”: -73.83559002316825, “y”: 42.690208093507…	$440,042,827
5	18164	632 New Scotland Ave	Albany	377568201	8	{“x”: -73.80381341626146, “y”: 42.655758957669…	$377,568,201
1	906	141 Fuller Rd	Albany	321199143	2	{“x”: -73.83323986150171, “y”: 42.693189748928…	$321,199,143
19	108087	See Card 1067	Watervliet	280898876	1	{“x”: -73.70670724174552, “y”: 42.719628647232…	$280,898,876
15	65380	737 Alb Shaker Rd	Colonie	263916100	3	{“x”: -73.80365248218001, “y”: 42.747956678125…	$263,916,100
9	21923	304 Madison Ave	Albany	234265418	2	{“x”: -73.76227373289564, “y”: 42.648000674457…	$234,265,418
2	907	201 Fuller Rd	Albany	203426124	2	{“x”: -73.83362605353057, “y”: 42.692609131686…	$203,426,124
16	69999	515 Loudon Rd	Colonie	166065600	8	{“x”: -73.74958475282632, “y”: 42.719321807666…	$166,065,600
7	20592	47 New Scotland Ave	Albany	162276338	8	{“x”: -73.77597163421673, “y”: 42.653565689693…	$162,276,338
6	20574	132 S Lake Ave	Albany	146296360	2	{“x”: -73.77970918544908, “y”: 42.654390366929…	$146,296,360
8	20597	113 Holland Ave	Albany	143498501	2	{“x”: -73.77306688593143, “y”: 42.650762742870…	$143,498,501
17	78203	Mannsville	Colonie	142570400	1	{“x”: -73.71245452369443, “y”: 42.718124477080…	$142,570,400
18	95509	1 Crossgates Mall Rd	Guilderland	130554700	8	{“x”: -73.84702700595471, “y”: 42.687699053797…	$130,554,700
10	24521	86 S Swan St	Albany	128436403	2	{“x”: -73.75980563770365, “y”: 42.653931892804…	$128,436,403
13	46883	1916 US 9W	Coeymans	110000000	8	{“x”: -73.83388475575597, “y”: 42.488730743021…	$110,000,000
12	35152	380 River Rd	Bethlehem	105263158	8	{“x”: -73.76445503554325, “y”: 42.595925419330…	$105,263,158
14	65097	15 Wolf Rd	Colonie	101967213	8	{“x”: -73.81423716588279, “y”: 42.709939498581…	$101,967,213