<jupyter_start><jupyter_text>Uncomment the following line to install [geemap](https://geemap.org) if needed.<jupyter_code># !pip install geemap
import ee
import geemap
from ipyleaflet import ImageOverlay
Map = geemap.Map()
Map
collection = ee.ImageCollection("USGS/NLCD")
print(collection.aggregate_array('system:id').getInfo())
dataset = ee.Image('USGS/NLCD/NLCD2016')
landcover = ee.Image(dataset.select('landcover'))
Map.addLayer(landcover, {}, 'NLCD land cover')
url = 'https://www.mrlc.gov/sites/default/files/NLCD_Colour_Classification_Update.jpg'
bounds = [(28, -128), (35, -123)]
io = ImageOverlay(url=url, bounds=bounds, name='NLCD legend')
Map.add_layer(io)<jupyter_output><empty_output>
{'fraction_non_alphanumeric': 0.15351506456241032, 'fraction_numerical': 0.020086083213773313, 'mean_word_length': 7.512195121951219, 'pattern_counts': {'":': 0, '<': 5, '<?xml version=': 0, '>': 5, 'https://': 2, 'lorem ipsum': 0, 'www.': 1, 'xml': 0}, 'pii_count': 0, 'substrings_counts': 0, 'word_list_counts': {'cursed_substrings.json': 0, 'profanity_word_list.json': 0, 'sexual_word_list.json': 0, 'zh_pornsignals.json': 0}}
{'chain_length': '1', 'dir': 'jupyter-structured-clean-dedup', 'id': '461931', 'license': 'MIT', 'n_tokens_mistral': 266, 'n_tokens_neox': 253, 'n_words': 47, 'path': 'examples/notebooks/image_overlay.ipynb', 'repo_name': 'Yisheng-Li/geemap', 'size': '697'}