diff --git a/.gitignore b/.gitignore
index 08a5a6e..c89374f 100644
--- a/.gitignore
+++ b/.gitignore
@@ -13,6 +13,9 @@ googlemaps-api-key.txt
 bin
 
 cachedir
+
+sample_annotator/cache/
+
 examples/outputs
 
 temp/
diff --git a/poetry.lock b/poetry.lock
index 2acf9a0..5146272 100644
--- a/poetry.lock
+++ b/poetry.lock
@@ -1,4 +1,19 @@
-# This file is automatically @generated by Poetry 1.7.1 and should not be changed by hand.
+# This file is automatically @generated by Poetry 1.8.2 and should not be changed by hand.
+
+[[package]]
+name = "affine"
+version = "2.4.0"
+description = "Matrices describing affine transformation of the plane"
+optional = false
+python-versions = ">=3.7"
+files = [
+    {file = "affine-2.4.0-py3-none-any.whl", hash = "sha256:8a3df80e2b2378aef598a83c1392efd47967afec4242021a0b06b4c7cbc61a92"},
+    {file = "affine-2.4.0.tar.gz", hash = "sha256:a24d818d6a836c131976d22f8c27b8d3ca32d0af64c1d8d29deb7bafa4da1eea"},
+]
+
+[package.extras]
+dev = ["coveralls", "flake8", "pydocstyle"]
+test = ["pytest (>=4.6)", "pytest-cov"]
 
 [[package]]
 name = "alabaster"
@@ -72,13 +87,13 @@ tests-mypy = ["mypy (>=1.11.1)", "pytest-mypy-plugins"]
 
 [[package]]
 name = "autopep8"
-version = "2.3.1"
+version = "2.3.2"
 description = "A tool that automatically formats Python code to conform to the PEP 8 style guide"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
-    {file = "autopep8-2.3.1-py2.py3-none-any.whl", hash = "sha256:a203fe0fcad7939987422140ab17a930f684763bf7335bdb6709991dd7ef6c2d"},
-    {file = "autopep8-2.3.1.tar.gz", hash = "sha256:8d6c87eba648fdcfc83e29b788910b8643171c395d9c4bcf115ece035b9c9dda"},
+    {file = "autopep8-2.3.2-py2.py3-none-any.whl", hash = "sha256:ce8ad498672c845a0c3de2629c15b635ec2b05ef8177a6e7c91c74f3e9b51128"},
+    {file = "autopep8-2.3.2.tar.gz", hash = "sha256:89440a4f969197b69a995e4ce0661b031f455a9f776d2c5ba3dbd83466931758"},
 ]
 
 [package.dependencies]
@@ -122,13 +137,13 @@ lxml = ["lxml"]
 
 [[package]]
 name = "bioregistry"
-version = "0.11.29"
+version = "0.11.33"
 description = "Integrated registry of biological databases and nomenclatures"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "bioregistry-0.11.29-py3-none-any.whl", hash = "sha256:f4d8b9130297b505c186a51aa5451a355f29e9fef25fd358441b6c95bb5606e4"},
-    {file = "bioregistry-0.11.29.tar.gz", hash = "sha256:6d6b1c9943bb80eea4fee699d1f9f86b13a260151468db53e70c557b9a0538ef"},
+    {file = "bioregistry-0.11.33-py3-none-any.whl", hash = "sha256:d3b87d34871288240a555ec4de6231a36c232d24114a05e57f0e6f59c4a8ebbe"},
+    {file = "bioregistry-0.11.33.tar.gz", hash = "sha256:3e955d41c39423fdc80b1cc75dfe5f8086c960757305b01f01499b0d2043a87e"},
 ]
 
 [package.dependencies]
@@ -371,6 +386,40 @@ files = [
 [package.dependencies]
 click = "*"
 
+[[package]]
+name = "click-plugins"
+version = "1.1.1"
+description = "An extension module for click to enable registering CLI commands via setuptools entry-points."
+optional = false
+python-versions = "*"
+files = [
+    {file = "click-plugins-1.1.1.tar.gz", hash = "sha256:46ab999744a9d831159c3411bb0c79346d94a444df9a3a3742e9ed63645f264b"},
+    {file = "click_plugins-1.1.1-py2.py3-none-any.whl", hash = "sha256:5d262006d3222f5057fd81e1623d4443e41dcda5dc815c06b442aa3c02889fc8"},
+]
+
+[package.dependencies]
+click = ">=4.0"
+
+[package.extras]
+dev = ["coveralls", "pytest (>=3.6)", "pytest-cov", "wheel"]
+
+[[package]]
+name = "cligj"
+version = "0.7.2"
+description = "Click params for commmand line interfaces to GeoJSON"
+optional = false
+python-versions = ">=2.7, !=3.0.*, !=3.1.*, !=3.2.*, <4"
+files = [
+    {file = "cligj-0.7.2-py3-none-any.whl", hash = "sha256:c1ca117dbce1fe20a5809dc96f01e1c2840f6dcc939b3ddbb1111bf330ba82df"},
+    {file = "cligj-0.7.2.tar.gz", hash = "sha256:a4bc13d623356b373c2c27c53dbd9c68cae5d526270bfa71f6c6fa69669c6b27"},
+]
+
+[package.dependencies]
+click = ">=4.0"
+
+[package.extras]
+test = ["pytest-cov"]
+
 [[package]]
 name = "colorama"
 version = "0.4.6"
@@ -471,13 +520,13 @@ test-no-images = ["pytest", "pytest-cov", "pytest-rerunfailures", "pytest-xdist"
 
 [[package]]
 name = "curies"
-version = "0.10.1"
+version = "0.10.2"
 description = "Idiomatic conversion between URIs and compact URIs (CURIEs)"
 optional = false
 python-versions = ">=3.9"
 files = [
-    {file = "curies-0.10.1-py3-none-any.whl", hash = "sha256:48a4da42bfaf778e9d8ec68cdca72a7aee3ee2b0800a1988df7d52067e8a32ba"},
-    {file = "curies-0.10.1.tar.gz", hash = "sha256:28fb1c4dcf19e4ff924095c92a61ba03179ce1313e234a8e422f3062315d15c1"},
+    {file = "curies-0.10.2-py3-none-any.whl", hash = "sha256:5320232c9d399dda9822c2a358436dc3e808c76a017b8195dd17b097735efc7b"},
+    {file = "curies-0.10.2.tar.gz", hash = "sha256:3e416bbf578b0c9f94cbdf92b7432536962da2b8a90a05fbaa42cbcbad3fd61a"},
 ]
 
 [package.dependencies]
@@ -756,6 +805,29 @@ files = [
     {file = "fqdn-1.5.1.tar.gz", hash = "sha256:105ed3677e767fb5ca086a0c1f4bb66ebc3c100be518f0e0d755d9eae164d89f"},
 ]
 
+[[package]]
+name = "geopandas"
+version = "1.0.1"
+description = "Geographic pandas extensions"
+optional = false
+python-versions = ">=3.9"
+files = [
+    {file = "geopandas-1.0.1-py3-none-any.whl", hash = "sha256:01e147d9420cc374d26f51fc23716ac307f32b49406e4bd8462c07e82ed1d3d6"},
+    {file = "geopandas-1.0.1.tar.gz", hash = "sha256:b8bf70a5534588205b7a56646e2082fb1de9a03599651b3d80c99ea4c2ca08ab"},
+]
+
+[package.dependencies]
+numpy = ">=1.22"
+packaging = "*"
+pandas = ">=1.4.0"
+pyogrio = ">=0.7.2"
+pyproj = ">=3.3.0"
+shapely = ">=2.0.0"
+
+[package.extras]
+all = ["GeoAlchemy2", "SQLAlchemy (>=1.3)", "folium", "geopy", "mapclassify", "matplotlib (>=3.5.0)", "psycopg-binary (>=3.1.0)", "pyarrow (>=8.0.0)", "xyzservices"]
+dev = ["black", "codecov", "pre-commit", "pytest (>=3.1.0)", "pytest-cov", "pytest-xdist"]
+
 [[package]]
 name = "ghp-import"
 version = "2.1.0"
@@ -937,17 +1009,17 @@ files = [
 
 [[package]]
 name = "inflect"
-version = "7.4.0"
+version = "7.5.0"
 description = "Correctly generate plurals, singular nouns, ordinals, indefinite articles"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
-    {file = "inflect-7.4.0-py3-none-any.whl", hash = "sha256:85af0997ee2bda942b1c1eed8c8a827abda91aa3e22d1efaa0eea817f9350ce7"},
-    {file = "inflect-7.4.0.tar.gz", hash = "sha256:904baa17cc2cb74827a6c27b95692e95670dadc72b208b3e8c1c05aeed47026b"},
+    {file = "inflect-7.5.0-py3-none-any.whl", hash = "sha256:2aea70e5e70c35d8350b8097396ec155ffd68def678c7ff97f51aa69c1d92344"},
+    {file = "inflect-7.5.0.tar.gz", hash = "sha256:faf19801c3742ed5a05a8ce388e0d8fe1a07f8d095c82201eb904f5d27ad571f"},
 ]
 
 [package.dependencies]
-more-itertools = ">=8.5.0"
+more_itertools = ">=8.5.0"
 typeguard = ">=4.0.1"
 
 [package.extras]
@@ -1248,13 +1320,13 @@ files = [
 
 [[package]]
 name = "linkml"
-version = "1.8.5"
+version = "1.8.6"
 description = "Linked Open Data Modeling Language"
 optional = false
 python-versions = "<4.0.0,>=3.8.1"
 files = [
-    {file = "linkml-1.8.5-py3-none-any.whl", hash = "sha256:5a45577a4bb380f3a128f45764545cb2da92dd3310a110de7dc5355796d5ac43"},
-    {file = "linkml-1.8.5.tar.gz", hash = "sha256:8f31834560ade4b7f1aebc973d22b31951d7061643d32bdcba258a650db9b140"},
+    {file = "linkml-1.8.6-py3-none-any.whl", hash = "sha256:17e222cbbf8873508fbcc6c39d1ce06b6b14a372adc73bbaffe3d328d1af59ea"},
+    {file = "linkml-1.8.6.tar.gz", hash = "sha256:81da9eb75a1cdbe050eaa421fbe4c1e035be9f5f05c154ec667a2ec711839bc5"},
 ]
 
 [package.dependencies]
@@ -1281,6 +1353,7 @@ pyyaml = "*"
 rdflib = ">=6.0.0"
 requests = ">=2.22"
 sqlalchemy = ">=1.4.31"
+typing-extensions = {version = ">=4.6.0", markers = "python_version < \"3.12\""}
 watchdog = ">=0.9.0"
 
 [package.extras]
@@ -1626,13 +1699,13 @@ tests = ["coverage", "pytest"]
 
 [[package]]
 name = "more-itertools"
-version = "10.5.0"
+version = "10.6.0"
 description = "More routines for operating on iterables, beyond itertools"
 optional = false
-python-versions = ">=3.8"
+python-versions = ">=3.9"
 files = [
-    {file = "more-itertools-10.5.0.tar.gz", hash = "sha256:5482bfef7849c25dc3c6dd53a6173ae4795da2a41a80faea6700d9f5846c5da6"},
-    {file = "more_itertools-10.5.0-py3-none-any.whl", hash = "sha256:037b0d3203ce90cca8ab1defbbdac29d5f993fc20131f3664dc8d6acfa872aef"},
+    {file = "more-itertools-10.6.0.tar.gz", hash = "sha256:2cd7fad1009c31cc9fb6a035108509e6547547a7a738374f10bd49a09eb3ee3b"},
+    {file = "more_itertools-10.6.0-py3-none-any.whl", hash = "sha256:6eb054cb4b6db1473f6e15fcc676a08e4732548acd47c708f0e179c2c7c01e89"},
 ]
 
 [[package]]
@@ -1646,6 +1719,25 @@ files = [
     {file = "mypy_extensions-1.0.0.tar.gz", hash = "sha256:75dbf8955dc00442a438fc4d0666508a9a97b6bd41aa2f0ffe9d2f2725af0782"},
 ]
 
+[[package]]
+name = "networkx"
+version = "3.4.2"
+description = "Python package for creating and manipulating graphs and networks"
+optional = false
+python-versions = ">=3.10"
+files = [
+    {file = "networkx-3.4.2-py3-none-any.whl", hash = "sha256:df5d4365b724cf81b8c6a7312509d0c22386097011ad1abe274afd5e9d3bbc5f"},
+    {file = "networkx-3.4.2.tar.gz", hash = "sha256:307c3669428c5362aab27c8a1260aa8f47c4e91d3891f48be0141738d8d053e1"},
+]
+
+[package.extras]
+default = ["matplotlib (>=3.7)", "numpy (>=1.24)", "pandas (>=2.0)", "scipy (>=1.10,!=1.11.0,!=1.11.1)"]
+developer = ["changelist (==0.5)", "mypy (>=1.1)", "pre-commit (>=3.2)", "rtoml"]
+doc = ["intersphinx-registry", "myst-nb (>=1.1)", "numpydoc (>=1.8.0)", "pillow (>=9.4)", "pydata-sphinx-theme (>=0.15)", "sphinx (>=7.3)", "sphinx-gallery (>=0.16)", "texext (>=0.6.7)"]
+example = ["cairocffi (>=1.7)", "contextily (>=1.6)", "igraph (>=0.11)", "momepy (>=0.7.2)", "osmnx (>=1.9)", "scikit-learn (>=1.5)", "seaborn (>=0.13)"]
+extra = ["lxml (>=4.6)", "pydot (>=3.0.1)", "pygraphviz (>=1.14)", "sympy (>=1.10)"]
+test = ["pytest (>=7.2)", "pytest-cov (>=4.0)"]
+
 [[package]]
 name = "nltk"
 version = "3.9.1"
@@ -1786,6 +1878,31 @@ files = [
 [package.dependencies]
 et-xmlfile = "*"
 
+[[package]]
+name = "osmnx"
+version = "2.0.1"
+description = "Download, model, analyze, and visualize street networks and other geospatial features from OpenStreetMap"
+optional = false
+python-versions = ">=3.9"
+files = [
+    {file = "osmnx-2.0.1-py3-none-any.whl", hash = "sha256:6532b28f4eaf0c7621f03f77873e64c2e4de5bf46aeafb4faa84413bc9f34f62"},
+    {file = "osmnx-2.0.1.tar.gz", hash = "sha256:24bb7dc4c0d548ce11a61a79de08bdeea7d74f2d1889a93b60da825051c0e374"},
+]
+
+[package.dependencies]
+geopandas = ">=1.0"
+networkx = ">=2.5"
+numpy = ">=1.22"
+pandas = ">=1.4"
+requests = ">=2.27"
+shapely = ">=2.0"
+
+[package.extras]
+entropy = ["scipy (>=1.5)"]
+neighbors = ["scikit-learn (>=0.23)", "scipy (>=1.5)"]
+raster = ["rasterio (>=1.3)", "rio-vrt (>=0.3)"]
+visualization = ["matplotlib (>=3.5)"]
+
 [[package]]
 name = "packaging"
 version = "24.2"
@@ -1922,93 +2039,89 @@ files = [
 
 [[package]]
 name = "pillow"
-version = "11.0.0"
+version = "11.1.0"
 description = "Python Imaging Library (Fork)"
 optional = false
 python-versions = ">=3.9"
 files = [
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 pyyaml = "*"
 
 [package.extras]
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 zstd = ["zstandard"]
 
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+
+[package.dependencies]
+certifi = "*"
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 [[package]]
 name = "pyproject-api"
 version = "1.8.0"
@@ -2644,25 +2845,73 @@ wikipedia = {version = "*", optional = true, markers = "extra == \"classifier\""
 [package.extras]
 classifier = ["joblib", "numpy", "scikit-learn", "scipy", "stemming", "wikipedia"]
 
+[[package]]
+name = "rasterio"
+version = "1.4.3"
+description = "Fast and direct raster I/O for use with Numpy and SciPy"
+optional = false
+python-versions = ">=3.9"
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+plot = ["matplotlib"]
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 [[package]]
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 description = "RDFLib is a Python library for working with RDF, a simple yet powerful language for representing information."
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 isodate = {version = ">=0.7.2,<1.0.0", markers = "python_version < \"3.11\""}
-pyparsing = ">=2.1.0,<4"
+pyparsing = ">=3.2.0,<4"
 
 [package.extras]
-berkeleydb = ["berkeleydb (>=18.1.0,<19.0.0)"]
-html = ["html5rdf (>=1.2,<2)"]
-lxml = ["lxml (>=4.3,<6.0)"]
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+html = ["html5rdf (>=1.2.1,<2)"]
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 networkx = ["networkx (>=2,<4)"]
 orjson = ["orjson (>=3.9.14,<4)"]
 
@@ -3004,13 +3253,13 @@ files = [
 
 [[package]]
 name = "ruamel-yaml"
-version = "0.18.6"
+version = "0.18.10"
 description = "ruamel.yaml is a YAML parser/emitter that supports roundtrip preservation of comments, seq/map flow style, and map key order"
 optional = false
 python-versions = ">=3.7"
 files = [
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 ]
 
 [package.dependencies]
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 description = "A set of python modules for machine learning and data mining"
 optional = false
 python-versions = ">=3.9"
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 [[package]]
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 [[package]]
 name = "shexjsg"
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 ]
 
 [metadata]
 lock-version = "2.0"
 python-versions = "^3.10"
-content-hash = "09a1d2fb25b2ca2ae64ed1bb26bd0bc4296137b133cf5d82d19bff2aca527c52"
+content-hash = "3320cc90aadd1081ad17a36491b8adc1e8a174923b5bd95b8a5bbae69d3e9af5"
diff --git a/pyproject.toml b/pyproject.toml
index 5f37678..36ff203 100644
--- a/pyproject.toml
+++ b/pyproject.toml
@@ -48,6 +48,9 @@ pyyaml = "^6.0" # to humor deptry
 quantulum3 = { extras = ["classifier"], version = "^0.9.2" }
 recommonmark = "^0.7.1"
 sphinx-rtd-theme = "3.0"
+rasterio = "^1.4.3"
+pyproj = "^3.7.0"
+osmnx = "^2.0.1"
 
 
 [tool.poetry.dev-dependencies]
diff --git a/sample_annotator/alaska_air_nlcds.py b/sample_annotator/alaska_air_nlcds.py
new file mode 100644
index 0000000..c9c7fe5
--- /dev/null
+++ b/sample_annotator/alaska_air_nlcds.py
@@ -0,0 +1,76 @@
+import pandas as pd
+import rasterio
+from pyproj import Transformer
+
+# NLCD Land Cover Classification Dictionary
+NLCD_CLASSES = {
+    11: "Open Water",
+    12: "Perennial Ice/Snow",
+    21: "Developed, Open Space",
+    22: "Developed, Low Intensity",
+    23: "Developed, Medium Intensity",
+    24: "Developed, High Intensity",
+    31: "Barren Land",
+    41: "Deciduous Forest",
+    42: "Evergreen Forest",
+    43: "Mixed Forest",
+    51: "Dwarf Scrub",
+    52: "Shrub/Scrub",
+    71: "Grassland/Herbaceous",
+    72: "Sedge/Herbaceous",
+    73: "Lichens",
+    74: "Moss",
+    81: "Pasture/Hay",
+    82: "Cultivated Crops",
+    90: "Woody Wetlands",
+    95: "Emergent Herbaceous Wetlands"
+}
+# Path to the NLCD .img file
+nlcd_file = "../downloads/NLCD_2016_Land_Cover_AK_20200724.img"
+
+# Path to the TSV file containing coordinates
+tsv_file = "../downloads/Marina Nieto-Caballero air study proposed local scale - merged and curated (1).tsv"
+
+output_filename = "../local/nlcd_land_cover_results.tsv"
+
+# Read the TSV file
+df = pd.read_csv(tsv_file, sep='\t')
+
+# Open the NLCD .img file
+with rasterio.open(nlcd_file) as src:
+    # Initialize coordinate transformer
+    transformer = Transformer.from_crs("EPSG:4326", src.crs, always_xy=True)
+
+    # Prepare lists to collect results
+    sample_names = []
+    nlcd_codes = []
+    nlcd_descriptions = []
+
+    # Iterate over the DataFrame rows
+    for _, row in df.iterrows():
+        lon, lat = row['lon val'], row['lat val']
+        sample_name = row['sample name']
+
+        # Transform coordinates to raster CRS
+        transformed_coord = transformer.transform(lon, lat)
+
+        # Extract NLCD land cover class
+        land_cover_value = [val for val in src.sample([transformed_coord])][0][0]
+        land_cover_description = NLCD_CLASSES.get(land_cover_value, "Unknown Class")
+
+        # Store the results
+        sample_names.append(sample_name)
+        nlcd_codes.append(land_cover_value)
+        nlcd_descriptions.append(land_cover_description)
+
+# Create a results DataFrame
+results_df = pd.DataFrame({
+    'Sample Name': sample_names,
+    'NLCD Code': nlcd_codes,
+    'NLCD Description': nlcd_descriptions
+})
+
+# Save results to a new TSV file
+results_df.to_csv(output_filename, sep='\t', index=False)
+
+print(f"Land cover classification completed. Results saved to '{output_filename}'.")
diff --git a/sample_annotator/alaska_air_osm.py b/sample_annotator/alaska_air_osm.py
new file mode 100644
index 0000000..30bbb45
--- /dev/null
+++ b/sample_annotator/alaska_air_osm.py
@@ -0,0 +1,119 @@
+import osmnx as ox
+import pandas as pd
+import time
+from typing import List, Dict, Any
+
+# Path to the TSV file containing coordinates
+tsv_file: str = "../downloads/Marina Nieto-Caballero air study proposed local scale - merged and curated (1).tsv"
+
+output_filename: str = "../local/osm_all_features_results.tsv"
+
+# Threshold for flagging uncommon features (e.g., less than 20% of samples)
+uncommon_threshold: float = 0.2
+
+# Read the TSV file
+df: pd.DataFrame = pd.read_csv(tsv_file, sep='\t')
+
+
+def fetch_osm_features(lat: float, lon: float, dist: int = 1000) -> pd.DataFrame:
+    """
+    Fetch OpenStreetMap (OSM) features near a specified latitude and longitude.
+
+    Args:
+        lat (float): Latitude of the location.
+        lon (float): Longitude of the location.
+        dist (int): Search radius in meters (default is 1000).
+
+    Returns:
+        pd.DataFrame: A DataFrame containing the fetched OSM features.
+    """
+    tags: Dict[str, bool] = {
+        'aeroway': True,
+        'amenity': True,
+        'barrier': True,
+        'boundary': True,
+        'building': True,
+        'emergency': True,
+        'geological': True,
+        'highway': True,
+        'historic': True,
+        'landuse': True,
+        'leisure': True,
+        'man_made': True,
+        'military': True,
+        'natural': True,
+        'place': True,
+        'surface': True,
+        'tourism': True,
+        'water': True,
+        'waterway': True,
+        'wetland': True
+    }
+    features: pd.DataFrame = ox.features_from_point((lat, lon), tags=tags, dist=dist)
+    return features
+
+
+# Prepare a list to collect results
+results: List[Dict[str, Any]] = []
+
+# Iterate over each coordinate and fetch OSM features
+for idx, row in df.iterrows():
+    lat, lon = row['lat val'], row['lon val']
+    sample_name = row['sample name']
+
+    print(f"Processing {idx + 1}/{len(df)}: Sample '{sample_name}' at ({lat}, {lon})")
+
+    try:
+        features: pd.DataFrame = fetch_osm_features(lat, lon)
+
+        if features.empty:
+            print(f"No features found for Sample '{sample_name}' at ({lat}, {lon})")
+            results.append({
+                'sample_name': sample_name,
+                'latitude': lat,
+                'longitude': lon,
+                'feature_info': 'No features found'
+            })
+        else:
+            for _, feature in features.iterrows():
+                feature_info: str = ", ".join(
+                    f"{k}: {v}" for k, v in feature.items()
+                    if pd.notnull(v) and k != 'geometry' and (
+                            k in ['name', 'name:en', 'old_name', 'old_name:en'] or (
+                            not k.startswith('name:') and not k.startswith('old_name:')
+                    )
+                    )
+                )
+                results.append({
+                    'sample_name': sample_name,
+                    'latitude': lat,
+                    'longitude': lon,
+                    'feature_info': feature_info if feature_info else 'No English name found'
+                })
+    except Exception as e:
+        print(f"Error fetching data for Sample '{sample_name}': {e}")
+        results.append({
+            'sample_name': sample_name,
+            'latitude': lat,
+            'longitude': lon,
+            'feature_info': f"Error fetching data: {e}"
+        })
+
+    time.sleep(1)  # 1-second delay between requests
+
+# Convert results to DataFrame
+results_df: pd.DataFrame = pd.DataFrame(results)
+
+# Identify and flag uncommon features across samples
+feature_counts: pd.Series = results_df['feature_info'].value_counts()
+total_samples: int = len(df)
+
+dynamic_column_name: str = f"lt_{int(uncommon_threshold * 100)}_pct_of_samples"
+results_df[dynamic_column_name] = results_df['feature_info'].apply(
+    lambda x: True if feature_counts[x] / total_samples < uncommon_threshold else False
+)
+
+# Save the results to a TSV file
+results_df.to_csv(output_filename, sep='\t', index=False)
+
+print(f"OSM feature extraction completed. Results saved to '{output_filename}'.")