danhammer

danhammer

import requests
import multiprocessing
from datetime import datetime

ALERT_URL = 'http://forma-cs-validation.elasticbeanstalk.com/api/alerts'


def _screener(x):
    try:
        not_cached = x['cached'] is not True

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import scipy
from scipy import ndimage
import copy
import matplotlib
matplotlib.use('Agg') # Must be before importing matplotlib.pyplot or pylab!
import matplotlib.pyplot as plt
import numpy as np
from spaceknow.horik import tools

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from bs4 import BeautifulSoup
import requests
import urllib
import pandas
import json
import itertools
import os

BASE = "https://2014.spaceappschallenge.org/awards/#globalnom"
GOOGLE_GEOCODE_URL = 'https://maps.googleapis.com/maps/api/geocode/json'

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import requests
from StringIO import StringIO
from pprint import pprint
from PIL import Image
from numpy import array

base = "https://api.data.gov/nasa/planetary/earth"

payload = {
    "lon": -122.066133,

danhammer

import requests
import urllib

BASE = "http://beta.gfw-apis.appspot.com/forest-change/forma-alerts"
period = "2008-01-01,2012-09-24"

sample_area = {
    "geometry": {
        "type": "Polygon",
        "coordinates": [

danhammer

danhammer

# Sample code to demonstrate the vegetation extraction from satellite imagery.
# The example region is a small plot in the central valley:

# https://gist.github.com/danhammer/47590518ece27c2ef0ab

# Specifically, this reports the mean and standard deviation EVI score for all 
# 30m pixels within the supplied polygon. To install the requests package on a
# Mac, type `sudo pip install requests` or visit this page for more comprehensive 
# install instructions:

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# Sample code to identify buildings withing a supplied bounding box.
import requests


def grabber(bbox, residential=True):
    BASE = "http://wolak.enviro-service.appspot.com/buildings"
    payload = bbox
    payload['residential'] = residential
    res = requests.get(BASE, params=payload).json()
    return res

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