Well, the ones at Building 5 in State Office Campus like SAM, orthphotography, tax maps, etc … the DEC server is still working, although that’s probably because they are hosted in ESRI cloud.
I was reading the state GIS’ email list, and noticed that their Civil Boundaries ArcMap has linked to it Census population counts for 1990, 2000, 2010 and 2020 for those interested in population changes for counties and localities without having to download and link the Census data. Get it here:
https://gisservices.its.ny.gov/arcgis/rest/services/NYS_Civil_Boundaries/FeatureServer/
Get a Free Interactive GPS Map for your phone:
https://andyarthur.org/ny
https://andyarthur.org/pa
… shows your location as a blue dot in relationship to campsites, trails, state land. This online map requires cell service, won’t work in remote country, so also bring a paper map.
Earlier today I posted a Leaflet Map showing the current Satellite Image from NOAA’s GEOS-East derived product, the GeoColor. It’s nice but to look really attractive you need to increase the brightness and saturation. If you want a 1920×1080 image that looks nice that you can download, you can use this python code. This ARC GIS Image Server is relatively straightforward to work with — supply a bounding box in Web Mercator, size and a few other parameters and it will spit back the image you want.
import requests, io
from PIL import Image, ImageEnhance, ImageDraw, ImageFont
from datetime import datetime
# new york - new england
url = "https://satellitemaps.nesdis.noaa.gov/arcgis/rest/services/MERGED_GeoColor/ImageServer/exportImage/exportImage?bbox=-9011008.3905,4747656.7008,-7345292.6701,6195679.7647&size=1920%2C1080&format=jpgpng&transparent=false&bboxSR=3857&imageSR=3857&f=image"
# full usa
#url = "https://satellitemaps.nesdis.noaa.gov/arcgis/rest/services/MERGED_GeoColor/ImageServer/exportImage/exportImage?bbox=-14401959.1214%2C2974317.6446%2C-7367306.5342%2C6447616.2099&size=1920%2C1080&format=jpgpng&transparent=false&bboxSR=3857&imageSR=3857&f=image&fbclid=IwAR1HvlVi55Bd933eOhM-Cvou2JgPdKAlcp2go4f8B5pqcioAPvcJyfYT0BA"
response = requests.get(url)
image_bytes = io.BytesIO(response.content)
img = PIL.Image.open(image_bytes)
enhancer = ImageEnhance.Color(img)
img = enhancer.enhance(2.5)
enhancer = ImageEnhance.Brightness(img)
img = enhancer.enhance(1.2)
img.save('/tmp/latest_image.jpg')
When using a projected coordinate system, it turns out you can calculate distance with a very simple lambda function. Beats that ugly haversine formula you have to use with World Geodetic System 1984.
Here is the equalivent with WGS 84 (written as a Lambda):