def test_Landsat_get_lst(red, nir, bt, expected, tol=0.001):
"""Test that different emissivity values (from NDVI & LAI) change LST"""
input_img = ee.Image.constant([0.2, 0.2, red, nir, 0.2, 0.2, bt, 0]) \
.rename(['B2', 'B3', 'B4', 'B5', 'B6', 'B7', 'B10', 'BQA']) \
.setMulti(l8_properties)
lst = ee.Image(landsat.Landsat(input_img)._get_lst())
assert abs(utils.image_value(lst)['lst'] - expected) <= tol
def test_Landsat_prep(img_id):
"""Test that the prepped image has the target bands and properties"""
l_info = ee.Image(img_id).getInfo()['properties']
prepped_img = landsat.Landsat(ee.Image(img_id)).prep()
prepped_info = ee.Image(prepped_img).getInfo()
assert [b['id'] for b in prepped_info['bands']
] == ['albedo', 'cfmask', 'lai', 'lst', 'ndvi']
assert prepped_info['properties']['SCENE_ID'] == img_id.split('/')[-1]
assert prepped_info['properties']['system:time_start'] == l_info[
'system:time_start']
def test_Landsat_init(img_id):
"""Test that the Landsat bands are renamed and properties are copied"""
l_info = ee.Image(img_id).getInfo()['properties']
input_img = landsat.Landsat(ee.Image(img_id)).input_image
input_info = ee.Image(input_img).getInfo()
assert [b['id'] for b in input_info['bands']] == [
'blue', 'green', 'red', 'nir', 'swir1', 'swir2', 'lst', 'bqa'
]
assert input_info['properties']['system:time_start'] == l_info[
'system:time_start']
assert input_info['properties']['k1_constant']
assert input_info['properties']['k2_constant']
def test_Landsat_get_albedo(blue, green, red, nir, swir1, swir2, tol=0.000001):
"""Test the albedo calculation
Ensure that the Green band is not being used to compute albedo
"""
expected = sum([
a * b for a, b in zip([blue, red, nir, swir1, swir2, 1],
[0.356, 0.130, 0.373, 0.085, 0.072, -0.0018])
])
input_img = ee.Image.constant([blue, green, red, nir, swir1, swir2, 300, 0]) \
.rename(['B2', 'B3', 'B4', 'B5', 'B6', 'B7', 'B10', 'BQA']) \
.setMulti(l8_properties)
albedo = ee.Image(landsat.Landsat(ee.Image(input_img))._get_albedo())
assert abs(utils.image_value(albedo)['albedo'] - expected) <= tol
def test_Landsat_get_lai(red=0.2, nir=0.7, expected=1.200, tol=0.001):
input_img = ee.Image.constant([0.2, 0.2, red, nir, 0.2, 0.2, 300, 0]) \
.rename(['B2', 'B3', 'B4', 'B5', 'B6', 'B7', 'B10', 'BQA']) \
.setMulti(l8_properties)
lai = ee.Image(landsat.Landsat(input_img)._get_lai())
assert abs(utils.image_value(lai)['lai'] - expected) <= tol
def test_Landsat_get_bqa_cfmask(bqa, expected):
input_img = ee.Image.constant([0.2, 0, 0, 0, 0, 0, 300, int(bqa, 2)]) \
.rename(['B2', 'B3', 'B4', 'B5', 'B6', 'B7', 'B10', 'BQA']) \
.setMulti(l8_properties)
cfmask = ee.Image(landsat.Landsat(input_img)._get_bqa_cfmask())
assert utils.image_value(cfmask)['cfmask'] == expected