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remote-sensing/deafrica_tools/app/wetlandsinsighttool.py
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"""
Wetlands insight tool widget, which can be used to run an interactive
version of the wetlands insight tool.
"""
# Import required packages
# Force GeoPandas to use Shapely instead of PyGEOS
# In a future release, GeoPandas will switch to using Shapely by default.
import os
os.environ['USE_PYGEOS'] = '0'
import datacube
import warnings
import seaborn as sns
import matplotlib.pyplot as plt
from datacube.utils.geometry import CRS
from ipyleaflet import (
WMSLayer,
basemaps,
basemap_to_tiles,
Map,
DrawControl,
WidgetControl,
LayerGroup,
LayersControl,
)
from traitlets import Unicode
from ipywidgets import (
GridspecLayout,
Button,
Layout,
HBox,
VBox,
HTML,
Output,
)
import json
import geopandas as gpd
from io import BytesIO
from dask.diagnostics import ProgressBar
import deafrica_tools
from deafrica_tools.dask import create_local_dask_cluster
from deafrica_tools.wetlands import WIT_drill
import deafrica_tools.app.widgetconstructors as deawidgets
def make_box_layout():
return Layout(
#border='solid 1px black',
margin='0px 10px 10px 0px',
padding='5px 5px 5px 5px',
width='100%',
height='100%',
)
def create_expanded_button(description, button_style):
return Button(
description=description,
button_style=button_style,
layout=Layout(width="auto", height="auto"),
)
class wit_app(HBox):
def __init__(self, lang=None):
super().__init__()
deafrica_tools.set_lang(lang)
##########################################################
# INITIAL ATTRIBUTES #
self.startdate = "2020-01-01"
self.enddate = "2020-03-01"
self.mingooddata = 0.0
self.resamplingfreq = "1M"
self.out_csv = "example_WIT.csv"
self.out_plot = "example_WIT.png"
self.product_list = [
(_("None"), "none"),
(_("ESRI World Imagery"), "esri_world_imagery"),
(_("Sentinel-2 Geomedian"), "gm_s2_annual"),
(_("Water Observations from Space"), "wofs_ls_summary_annual"),
]
self.product = self.product_list[0][1]
self.product_year = "2020-01-01"
self.target = None
self.action = None
self.gdf_drawn = None
##########################################################
# HEADER FOR APP #
# Create the Header widget
header_title_text = _("Wetlands Insight Tool")
instruction_text = _("Select parameters and AOI")
self.header = deawidgets.create_html(f"<h3>{header_title_text}</h3><p>{instruction_text}</p>")
self.header.layout = make_box_layout()
##########################################################
# HANDLER FUNCTION FOR DRAW CONTROL #
# Define the action to take once something is drawn on the map
def update_geojson(target, action, geo_json):
self.action = action
json_data = json.dumps(geo_json)
binary_data = json_data.encode()
io = BytesIO(binary_data)
io.seek(0)
gdf = gpd.read_file(io)
gdf.crs = "EPSG:4326"
self.gdf_drawn = gdf
gdf_drawn_epsg6933 = gdf.copy().to_crs("EPSG:6933")
m2_per_km2 = 10 ** 6
area = gdf_drawn_epsg6933.area.values[0] / m2_per_km2
polyarea_label = _('Total polygon area')
polyarea_text = f"<p><b>{polyarea_label}</b>: {area:.2f} km<sup>2</sup></p>"
if area <= 3000:
confirmation_text = '<p style="color:#33cc33;">' + _('Area falls within recommended limit') + '</p>'
self.header.value = header_title_text + polyarea_text + confirmation_text
else:
warning_text = '<p style="color:#ff5050;">' + _('Area is too large, please update your polygon') + '</p>'
self.header.value = header_title_text + polyarea_text + warning_text
##########################################################
# WIDGETS FOR APP OUTPUTS #
self.dask_client = Output(layout=make_box_layout())
self.progress_bar = Output(layout=make_box_layout())
self.wit_plot = Output(layout=make_box_layout())
self.progress_header = deawidgets.create_html("")
##########################################################
# MAP WIDGET, DRAWING TOOLS, WMS LAYERS #
# Create drawing tools
desired_drawtools = ['rectangle', 'polygon']
draw_control = deawidgets.create_drawcontrol(desired_drawtools)
# Begin by displaying an empty layer group, and update the group with desired WMS on interaction.
self.deafrica_layers = LayerGroup(layers=())
self.deafrica_layers.name = _('Map Overlays')
# Create map widget
self.m = deawidgets.create_map()
self.m.layout = make_box_layout()
# Add tools to map widget
self.m.add_control(draw_control)
self.m.add_layer(self.deafrica_layers)
# Store current basemap for future use
self.basemap = self.m.basemap
##########################################################
# WIDGETS FOR APP CONTROLS #
# Create parameter widgets
startdate_picker = deawidgets.create_datepicker()
enddate_picker = deawidgets.create_datepicker()
min_good_data = deawidgets.create_boundedfloattext(self.mingooddata, 0.0, 1.0, 0.05)
resampling_freq = deawidgets.create_inputtext(self.resamplingfreq, self.resamplingfreq)
output_csv = deawidgets.create_inputtext(self.out_csv, self.out_csv)
output_plot = deawidgets.create_inputtext(self.out_plot, self.out_plot)
deaoverlay_dropdown = deawidgets.create_dropdown(self.product_list, self.product_list[0][1])
run_button = create_expanded_button(_("Run"), "info")
##########################################################
# COLLECTION OF ALL APP CONTROLS #
parameter_selection = VBox(
[
HTML("<b>" + _("Map Overlay:") + "</b>"),
deaoverlay_dropdown,
HTML("<b>" + _("Start Date:") + "</b>"),
startdate_picker,
HTML("<b>" + _("End Date:") + "</b>"),
enddate_picker,
HTML("<b>" + _("Minimum Good Data:") + "</b>"),
min_good_data,
HTML("<b>" + _("Resampling Frequency:") + "</b>"),
resampling_freq,
HTML("<b>" + _("Output CSV:") + "</b>"),
output_csv,
HTML("<b>" + _("Output Plot:") + "</b>"),
output_plot,
]
)
parameter_selection.layout = make_box_layout()
##########################################################
# SPECIFICATION OF APP LAYOUT #
# Create the layout #[rowspan, colspan]
grid = GridspecLayout(11, 10, height="1100px", width="auto")
# Controls and Status
grid[0, :] = self.header
grid[1:6, 0:2] = parameter_selection
grid[6, 0:2] = run_button
# Dask and Progress info
grid[1, 7:] = self.dask_client
grid[2:7, 7:] = self.progress_bar
# Map
grid[1:7, 2:7] = self.m
# Plot
grid[7:, :] = self.wit_plot
# Display using HBox children attribute
self.children = [grid]
##########################################################
# SPECIFICATION UPDATE FUNCTIONS FOR EACH WIDGET #
# Run update functions whenever various widgets are changed.
startdate_picker.observe(self.update_startdate, "value")
enddate_picker.observe(self.update_enddate, "value")
min_good_data.observe(self.update_mingooddata, "value")
resampling_freq.observe(self.update_resamplingfreq, "value")
output_csv.observe(self.update_outputcsv, "value")
output_plot.observe(self.update_outputplot, "value")
deaoverlay_dropdown.observe(self.update_deaoverlay, "value")
run_button.on_click(self.run_app)
draw_control.on_draw(update_geojson)
##############################################################
# DEFINITION OF ALL UPDATE FUNCTIONS #
# set the start date to the new edited date
def update_startdate(self, change):
self.startdate = change.new
# set the end date to the new edited date
def update_enddate(self, change):
self.enddate = change.new
# set the min good data
def update_mingooddata(self, change):
self.mingooddata = change.new
# set the resampling frequency
def update_resamplingfreq(self, change):
self.resamplingfreq = change.new
# set the output csv
def update_outputcsv(self, change):
self.out_csv = change.new
# set the output plot
def update_outputplot(self, change):
self.out_plot = change.new
# Update product
def update_deaoverlay(self, change):
self.product = change.new
if self.product == "none":
self.deafrica_layers.clear_layers()
elif self.product == "esri_world_imagery":
self.deafrica_layers.clear_layers()
layer = basemap_to_tiles(basemaps.Esri.WorldImagery)
self.deafrica_layers.add_layer(layer)
else:
self.deafrica_layers.clear_layers()
layer = deawidgets.create_dea_wms_layer(self.product, self.product_year)
self.deafrica_layers.add_layer(layer)
def run_app(self, change):
# Clear progress bar and output areas before running
self.dask_client.clear_output()
self.progress_bar.clear_output()
self.wit_plot.clear_output()
# Connect to datacube database
dc = datacube.Datacube(app="wetland_app")
# Configure local dask cluster
with self.dask_client:
client = create_local_dask_cluster(
return_client=True, display_client=True
)
# Set any defaults
TCW_threshold = -0.035
dask_chunks = dict(x=1000, y=1000, time=1)
#check resampling freq
if self.resamplingfreq == 'None':
rsf = None
else:
rsf = self.resamplingfreq
self.progress_header.value = f"<h3>"+_("Progress")+"</h3>"
# run wetlands polygon drill
with self.progress_bar:
# with ProgressBar():
warnings.filterwarnings("ignore")
try:
df = WIT_drill(
gdf=self.gdf_drawn,
time=(self.startdate, self.enddate),
min_gooddata=self.mingooddata,
resample_frequency=rsf,
TCW_threshold=TCW_threshold,
export_csv=self.out_csv,
dask_chunks=dask_chunks,
verbose=False,
verbose_progress=True,
)
print(_("WIT complete"))
except AttributeError:
print(_("No polygon selected"))
# close down the dask client
client.shutdown()
# save the csv
if self.out_csv:
df.to_csv(self.out_csv, index_label="Datetime")
# ---Plotting------------------------------
with self.wit_plot:
fontsize = 17
plt.rcParams.update({"font.size": fontsize})
# set up color palette
pal = [
sns.xkcd_rgb["cobalt blue"],
sns.xkcd_rgb["neon blue"],
sns.xkcd_rgb["grass"],
sns.xkcd_rgb["beige"],
sns.xkcd_rgb["brown"],
]
# make a stacked area plot
plt.close("all")
fig, ax = plt.subplots(constrained_layout=True, figsize=(20, 6))
ax.stackplot(
df.index,
df.wofs_area_percent,
df.wet_percent,
df.green_veg_percent,
df.dry_veg_percent,
df.bare_soil_percent,
labels=[
_("open water"),
_("wet"),
_("green veg"),
_("dry veg"),
_("bare soil"),
],
colors=pal,
alpha=0.6,
)
# set axis limits to the min and max
ax.set_ylim(0, 100)
ax.set_xlim(df.index[0], df.index[-1])
ax.tick_params(axis="x", labelsize=fontsize)
# add a legend and a tight plot box
ax.legend(loc="lower left", framealpha=0.6)
ax.set_title(_("Percentage Fractional Cover, Wetness, and Water"))
# plt.tight_layout()
plt.show()
if self.out_plot:
# save the figure
fig.savefig(f"{self.out_plot}")
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