#41 Water_app how to load only 1 layer to filter?

[msahajar]

I am trying to work on calculating surface water area and vegetation area for catchments layers.

I made some changes to the original code. Which doesn't run into errors but does not even work when you submit. Also, it is not allowing to apply the filters.

Here are the changes I made to the code (:

Add Earth Engine data

fc = ee.FeatureCollection('users/msahajar/Catchments')
Map.addLayer(fc, {}, 'NSW catchments')
Map

#Design Interactive widgets (admin1 is removed and only admin 2 is retained for catchments)
admin2_widget = widgets.Text(
description='Catchment:',
value='Lachlan',
width=300,
style=style
)

def aoi_change(change):
Map.layers = Map.layers[:4]
Map.user_roi = None
Map.user_rois = None
Map.draw_count = 0
admin2_widget.value = ''
output_widget.clear_output()

full_widget = widgets.VBox([
widgets.HBox([admin2_widget, aoi_widget, download_widget]),
widgets.HBox([band_combo, year_widget, fmask_widget]),
widgets.HBox([nd_indices, first_band, second_band, nd_threshold, nd_color]),
submit
])

full_widget

Capture user interaction with the map

def handle_interaction(**kwargs):
latlon = kwargs.get('coordinates')
if kwargs.get('type') == 'click' and not aoi_widget.value:
Map.default_style = {'cursor': 'wait'}
xy = ee.Geometry.Point(latlon[::-1])
selected_fc = fc.filterBounds(xy)

    with output_widget:
        output_widget.clear_output()
    
        try:
            feature = selected_fc.first()
            admin2_id = feature.get('NAME').getInfo()
            statefp = feature.get('TAG')
            admin2_widget.value = admin2_id
            Map.layers = Map.layers[:4]        
            geom = selected_fc.geometry()
            layer_name = admin2_id
            Map.addLayer(ee.Image().paint(geom, 0, 2), {'palette': 'red'}, layer_name)  
            print(layer_name)
        except:
            print('No feature could be found')
            Map.layers = Map.layers[:4]        
        
    Map.default_style = {'cursor': 'pointer'}
else:
    Map.draw_count = 0

Map.on_interaction(handle_interaction)

Click event handler

def submit_clicked(b):

with output_widget:
    output_widget.clear_output()
    print('Computing...')
    Map.default_style = {'cursor': 'wait'}

    try:
        #admin1_id = admin1_widget.value
        admin2_id = admin2_widget.value
        band1 = first_band.value
        band2 = second_band.value
        selected_year = year_widget.value
        threshold = nd_threshold.value
        bands = band_combo.value.split('/')
        apply_fmask = fmask_widget.value
        palette = nd_color.value
        use_aoi = aoi_widget.value
        download = download_widget.value
        
        if use_aoi:
            if Map.user_roi is not None:
                roi = Map.user_roi
                layer_name = 'User drawn AOI'
                geom = roi
            else:
                output_widget.clear_output() 
                print('No user AOI could be found.')
                return
        else:
            
            roi = fc.filter(ee.Filter.eq('NAME', admin2_id), ee.Filter.eq('TAG', statefp))
            layer_name = admin2_id
            geom = roi.geometry()

I am just posting only the relevant code section where layer interaction is involved.
I am having trouble applying filters for the layer mostly. Also, I have trouble understanding the data formats, how is the catchment layer I am using is different from the US Counties file? US counties layer has metadata displayed in the attribute section whereas the layer I am using is in a tabular format.

How to address this in the code? PFA shp files of the catchment layer I am using for your reference.
lachlan_boundary.zip

I appreciate your time and support.

Thank you.

[giswqs]

You need to provide a complete notebook that can produce the errors. Make sure all private datasets are also accessible directly through the notebook. A question that makes it easier for others to debug is more likely to get an answer.

[msahajar]

How do I make the dataset accessible directly through the notebook?
I have uploaded the dataset as a file to GEE, is this sufficient?

Here's the complete code

import subprocess
try:
import geemap
except ImportError:
print('geemap package is not installed. Installing ...')
subprocess.check_call(["python", '-m', 'pip', 'install', 'geemap'])
import os
import ee
import geemap
import ipywidgets as widgets
from bqplot import pyplot as plt
from ipyleaflet import WidgetControl
import geopandas as gpd
import pandas as pd
from geopandas import GeoDataFrame
from shapely.geometry import Point,Polygon
import numpy as np
from functools import reduce

Map = geemap.Map(center=[40, -100], zoom=4, add_google_map=False)
Map.add_basemap('HYBRID')
Map.add_basemap('ROADMAP')
fc = ee.FeatureCollection('users/msahajar/Catchments')
Map.addLayer(fc, {}, 'NSW catchments')
Map

style = {'description_width': 'initial'}
output_widget = widgets.Output(layout={'border': '1px solid black'})
output_control = WidgetControl(widget=output_widget, position='bottomright')
Map.add_control(output_control)

admin2_widget = widgets.Text(
description='Catchment:',
value='Lachlan',
width=300,
style=style
)

aoi_widget = widgets.Checkbox(
value=False,
description='Use user-drawn AOI',
style=style
)

download_widget = widgets.Checkbox(
value=False,
description='Download chart data',
style=style
)

def aoi_change(change):
Map.layers = Map.layers[:4]
Map.user_roi = None
Map.user_rois = None
Map.draw_count = 0
admin2_widget.value = ''
output_widget.clear_output()

aoi_widget.observe(aoi_change, names='value')

band_combo = widgets.Dropdown(
description='Band combo:',
options=['Red/Green/Blue', 'NIR/Red/Green', 'SWIR2/SWIR1/NIR', 'NIR/SWIR1/Red','SWIR2/NIR/Red',
'SWIR2/SWIR1/Red', 'SWIR1/NIR/Blue', 'NIR/SWIR1/Blue', 'SWIR2/NIR/Green', 'SWIR1/NIR/Red'],
value='NIR/Red/Green',
style=style
)

year_widget = widgets.IntSlider(min=1984, max=2021, value=2010, description='Selected year:', width=400, style=style)

fmask_widget = widgets.Checkbox(
value=True,
description='Apply fmask(remove cloud, shadow, snow)',
style=style
)

Normalized Satellite Indices: https://www.usna.edu/Users/oceano/pguth/md_help/html/norm_sat.htm

nd_options = ['Vegetation Index (NDVI)',
'Water Index (NDWI)',
'Modified Water Index (MNDWI)',
'Snow Index (NDSI)',
'Soil Index (NDSI)',
'Burn Ratio (NBR)',
'Customized']
nd_indices = widgets.Dropdown(options=nd_options, value='Modified Water Index (MNDWI)', description='Normalized Difference Indes:', style=style)

first_band = widgets.Dropdown(
description='1st band:',
options=['Blue', 'Green','Red','NIR', 'SWIR1', 'SWIR2'],
value='Green',
style=style
)

second_band = widgets.Dropdown(
description='2nd band:',
options=['Blue', 'Green','Red','NIR', 'SWIR1', 'SWIR2'],
value='SWIR1',
style=style
)

nd_threshold = widgets.FloatSlider(
value=0,
min=-1,
max=1,
step=0.01,
description='Threshold:',
orientation='horizontal',
style=style
)

nd_color = widgets.ColorPicker(
concise=False,
description='Color:',
value='blue',
style=style
)

def nd_index_change(change):
if nd_indices.value == 'Vegetation Index (NDVI)':
first_band.value = 'NIR'
second_band.value = 'Red'
elif nd_indices.value == 'Water Index (NDWI)':
first_band.value = 'NIR'
second_band.value = 'SWIR1'
elif nd_indices.value == 'Modified Water Index (MNDWI)':
first_band.value = 'Green'
second_band.value = 'SWIR1'
elif nd_indices.value == 'Snow Index (NDSI)':
first_band.value = 'Green'
second_band.value = 'SWIR1'
elif nd_indices.value == 'Soil Index (NDSI)':
first_band.value = 'SWIR1'
second_band.value = 'NIR'
elif nd_indices.value == 'Burn Ratio (NBR)':
first_band.value = 'NIR'
second_band.value = 'SWIR2'
elif nd_indices.value == 'Customized':
first_band.value = None
second_band.value = None

nd_indices.observe(nd_index_change, names='value')

submit = widgets.Button(
description='Submit',
button_style='primary',
tooltip='Click me',
style=style
)

full_widget = widgets.VBox([
widgets.HBox([admin2_widget, aoi_widget, download_widget]),
widgets.HBox([band_combo, year_widget, fmask_widget]),
widgets.HBox([nd_indices, first_band, second_band, nd_threshold, nd_color]),
submit
])

full_widget

def handle_interaction(**kwargs):
latlon = kwargs.get('coordinates')
if kwargs.get('type') == 'click' and not aoi_widget.value:
Map.default_style = {'cursor': 'wait'}
xy = ee.Geometry.Point(latlon[::-1])
selected_fc = fc.filterBounds(xy)

    with output_widget:
        output_widget.clear_output()
    
        try:
            feature = selected_fc.first()
            admin2_id = feature.get('NAME').getInfo()
            statefp = feature.get('TAG')
            admin2_widget.value = admin2_id
            Map.layers = Map.layers[:4]        
            geom = selected_fc.geometry()
            layer_name = admin2_id
            Map.addLayer(ee.Image().paint(geom, 0, 2), {'palette': 'red'}, layer_name)  
            print(layer_name)
        except:
            print('No feature could be found')
            Map.layers = Map.layers[:4]        
        
    Map.default_style = {'cursor': 'pointer'}
else:
    Map.draw_count = 0

Map.on_interaction(handle_interaction)

def submit_clicked(b):

with output_widget:
    output_widget.clear_output()
    print('Computing...')
    Map.default_style = {'cursor': 'wait'}

    try:
        admin2_id = admin2_widget.value
        band1 = first_band.value
        band2 = second_band.value
        selected_year = year_widget.value
        threshold = nd_threshold.value
        bands = band_combo.value.split('/')
        apply_fmask = fmask_widget.value
        palette = nd_color.value
        use_aoi = aoi_widget.value
        download = download_widget.value
        
        if use_aoi:
            if Map.user_roi is not None:
                roi = Map.user_roi
                layer_name = 'User drawn AOI'
                geom = roi
            else:
                output_widget.clear_output() 
                print('No user AOI could be found.')
                return
        else:
        
            roi = fc.filter(ee.Filter.eq('NAME', admin2_id), ee.Filter.eq('TAG', statefp))
            layer_name = admin2_id
            geom = roi.geometry()


        Map.layers = Map.layers[:4]        
        Map.addLayer(ee.Image().paint(geom, 0, 2), {'palette': 'red'}, layer_name)  
        
        images = geemap.landsat_timeseries(roi=roi, start_year=1984, end_year=2021, start_date='01-01', end_date='03-31', apply_fmask=apply_fmask)
        nd_images = images.map(lambda img: img.normalizedDifference([band1, band2]))
        result_images = nd_images.map(lambda img: img.gt(threshold))

        selected_image = ee.Image(images.toList(images.size()).get(selected_year - 1984))
        selected_result_image = ee.Image(result_images.toList(result_images.size()).get(selected_year - 1984)).selfMask()
        
        vis_params = {
            'bands': bands,
            'min': 0,
            'max': 3000
        }
        
        Map.addLayer(selected_image, vis_params, 'Landsat ' + str(selected_year))
        Map.addLayer(selected_result_image, {'palette': palette}, 'Result ' + str(selected_year))

        
        def cal_area(img):
            pixel_area = img.multiply(ee.Image.pixelArea()).divide(1e4)
            img_area = pixel_area.reduceRegion(**{
                'geometry': geom,
                'reducer': ee.Reducer.sum(),
                'scale': 1000,
                'maxPixels': 1e12,
                'bestEffort': True
            })
            return img.set({'area': img_area})
        
        areas = result_images.map(cal_area)
        stats = areas.aggregate_array('area').getInfo()
        x = list(range(1984, 2021))
        y = [item.get('nd') for item in stats]
        
        fig = plt.figure(1)
        fig.layout.height = '270px'
        plt.clear()
        plt.plot(x, y)
        plt.title('Temporal trend (1984-2020)')
        plt.xlabel('Year')
        plt.ylabel('Area (ha)')
        
        output_widget.clear_output()            

        plt.show()
        
        if download:
            out_dir = os.path.join(os.path.expanduser('~'), 'Downloads')
            out_name = 'chart_' + geemap.random_string() + '.csv'
            out_csv = os.path.join(out_dir, out_name)
            if not os.path.exists(out_dir):
                os.makedirs(out_dir)
            with open(out_csv, 'w') as f:
                f.write('year, area (ha)\n')
                for index, item in enumerate(x):
                    line = '{},{:.2f}\n'.format(item, y[index])
                    f.write(line) 
            link = geemap.create_download_link(
                out_csv, title="Click here to download the chart data: ")
            display(link)

    except Exception as e:
        print(e)
        print('An error occurred during computation.')        

    Map.default_style = {'cursor': 'default'}

submit.on_click(submit_clicked)

Pretty much changed only the part where I thought it appropriate to generate the app for only 1 layer of dataset.
I am attaching the dataset in zip folder for your reference.
lachlan_boundary.zip

Thank you so much for your help. _/_