richpsharp

import pandas as pd

datasets={
    "PH_Top 10% of service overlap for _PH conservation": {
        'fig_title' :"Top 10% of service overlap for , PH conservation",
        'country' :"PH",
        'labels' :["1 service","2 services","3 services","4 services"],
        'visParams':{
            'min':1,
            'max':4,

richpsharp

"""Script to process Danny's RDS file into something that can be analyzed by the PCLD."""

import pyreadr
import geopandas as gpd

PROJECTION_EPSG = 32610
FILE_PATH = "Karp_LU_UseCase.RDS"


def main():

richpsharp

var grassland_fragmentation = function(aoi, year)
{
  var global_pasture_watch = ee.ImageCollection('projects/global-pasture-watch/assets/ggc-30m/v1/grassland_c');
  
  var clipped_gpw = global_pasture_watch.filterDate(year + '-01-01', (year + 1) + '-01-01').first().clip(aoi);
  // Anything > 1 is grassland "i.e. rangeland"
  var grassland = clipped_gpw.gte(1);
  //original code made a 7x7 square kernel on 10m, so we're doing a 3x3 for 30m as close enough