From 5baeb2227f60378febcdc6753ba4b772cb16738d Mon Sep 17 00:00:00 2001 From: Charlie Marshak Date: Thu, 20 Jun 2024 13:08:16 -0700 Subject: [PATCH 1/5] update readme for glad --- README.md | 9 ++++++--- 1 file changed, 6 insertions(+), 3 deletions(-) diff --git a/README.md b/README.md index c2d9767..10237b1 100644 --- a/README.md +++ b/README.md @@ -81,7 +81,9 @@ Out[2]: 'pekel_water_occ_2021', 's1_coherence_2020', 'cop_100_lulc_discrete', 'radd_deforestation_alerts_2022', - 'hand' + 'hand', + 'glad_landcover', + 'glad_change' ``` More information about these datasets can be found below + Pekel water occurence: https://global-surface-water.appspot.com/download @@ -89,8 +91,9 @@ More information about these datasets can be found below + Hansen annual mosaic, treecover 2000, gain, and loss year: https://data.globalforestwatch.org/documents/941f17325a494ed78c4817f9bb20f33a/explore + S1 Coherence from December 2019 - Nov 2020: https://aws.amazon.com/marketplace/pp/prodview-iz6lnjbdlgcwa#resources + The copernicus 100 m LULC dataset from 2015 - 2019: https://land.copernicus.eu/global/content/annual-100m-global-land-cover-maps-available -+ Height above nearest drainage (distributed and generated by ASF) in 2021: https://github.com/asjohnston-asf/agu-2022-notebooks/blob/main/hand-notebook.ipynb (and their [tool](https://github.com/HydroSAR/HydroSAR/blob/develop/src/hydrosar/hand/prepare.py) to do the exact same thing) -+ RADD Deforestation alerts: https://data.globalforestwatch.org/datasets/gfw::deforestation-alerts-radd/about ++ Height above nearest drainage (distributed and generated by ASF) in 2021 derived from Copernicus Global DEM: https://github.com/asjohnston-asf/agu-2022-notebooks/blob/main/hand-notebook.ipynb (and their [tool](https://github.com/HydroSAR/HydroSAR/blob/develop/src/hydrosar/hand/prepare.py) to do the exact same thing) ++ RADD Deforestation alerts (ongoing): https://data.globalforestwatch.org/datasets/gfw::deforestation-alerts-radd/about ++ Glad landcover maps (2000, 2005, 2010, 2015, 2020) and change map (2020 changes when compared to 2000): https://storage.googleapis.com/earthenginepartners-hansen/GLCLU2000-2020/v2/download.html See these [notebooks](notebooks/tile_creation) to see how these tiles are generated and organized. From 7f08501baf0476d5f478507f7e339c598aa2e80e Mon Sep 17 00:00:00 2001 From: scott Date: Sat, 22 Jun 2024 13:37:21 -0400 Subject: [PATCH 2/5] Add option to download Sentinel-1 `rho` and `tau` The implementation is a bit hacky- rather than redo the pandas model and geojson data, I'm just swapping the `COH12` name in the urls for `rho`, `tau` or `rmse`. --- src/tile_mate/stitcher.py | 41 +++++++++++++++++++++++++++++---------- 1 file changed, 31 insertions(+), 10 deletions(-) diff --git a/src/tile_mate/stitcher.py b/src/tile_mate/stitcher.py index f26a772..de6d686 100644 --- a/src/tile_mate/stitcher.py +++ b/src/tile_mate/stitcher.py @@ -36,6 +36,7 @@ CURRENT_HANSEN_YEAR = 2022 SEASONS = ['fall', 'winter', 'spring', 'summer'] S1_TEMPORAL_BASELINE_DAYS = [6, 12, 18, 24, 36, 48] +S1_VARIABLES = ['rho', 'tau', 'rmse'] GLAD_LANDCOVER_YEARS = [2000, 2005, 2010, 2015, 2020] @@ -55,6 +56,7 @@ def get_tile_data( year: int = None, season: str = None, temporal_baseline_days: int = None, + variable: str = None ) -> gpd.GeoDataFrame: # Because tile data is cached - we need to copy it. df_tiles = get_all_tile_data(tile_key).copy() @@ -102,16 +104,33 @@ def update_glad_landcover_url(url: str, year: int = year) -> str: raise ValueError('Year is required for tile lookup') if tile_key == 's1_coherence_2020': - if any([var is None for var in [temporal_baseline_days, season]]): - raise ValueError(f'{tile_key} requires season and temporal baseline ' 'to be specified') + if season is None: + raise ValueError(f'{tile_key} requires season to be specified') + if variable is None and temporal_baseline_days is None: + raise ValueError(f'{tile_key} requires either variable or temporal baseline to be specified') + if season not in SEASONS: raise ValueError(f'season keyword must be in {", ".join(SEASONS)}') - if temporal_baseline_days not in S1_TEMPORAL_BASELINE_DAYS: + if temporal_baseline_days not in [None, *S1_TEMPORAL_BASELINE_DAYS]: tb_days_str = list(map(str, S1_TEMPORAL_BASELINE_DAYS)) raise ValueError(f'temporal_baseline_days must be in {", ".join(tb_days_str)}') + if variable not in [None, *S1_VARIABLES]: + raise ValueError(f'variable keyword must be in {", ".join(S1_VARIABLES)}') + # we need season, but we can either do temporal baseline, or variable ind_season = df_tiles.season == season - ind_tb = df_tiles.temporal_baseline_days == temporal_baseline_days - df_tiles = df_tiles[ind_tb & ind_season].reset_index(drop=True) + if temporal_baseline_days is not None: + ind_tb = df_tiles.temporal_baseline_days == temporal_baseline_days + total_ind = ind_tb & ind_season + df_tiles = df_tiles[total_ind].reset_index(drop=True) + else: + # ind_variable = df_tiles.variable == variable + # HACK: there is not a "variable" for now. + # So instead, we pick the 12day rasters, the manipulate the URL to get the variable we want + ind_tb = df_tiles.temporal_baseline_days == 12 + total_ind = ind_tb & ind_season + df_tiles = df_tiles[total_ind].reset_index(drop=True) + df_tiles.loc[:, 'url'] = df_tiles.loc[:, 'url'].str.replace('_COH12', f'_{variable}') + if df_tiles.empty: raise NoTileCoverage(f'{tile_key} has no global tiles with the parameters provided') return df_tiles @@ -177,11 +196,12 @@ def get_additional_tile_metadata(urls: list[str], max_tile_tries: int = 10) -> d def get_raster_from_tiles( extent: list[float], - tile_shortname: str = None, - df_tiles: gpd.GeoDataFrame = None, - year: int = None, - season: str = None, - temporal_baseline_days: int = None, + tile_shortname: str | None = None, + df_tiles: gpd.GeoDataFrame | None = None, + year: int | None = None, + season: str | None = None, + temporal_baseline_days: int | None = None, + variable: str | None = None ) -> tuple: if (tile_shortname is None) and (df_tiles is None): raise ValueError('Either "tile_shortname" or "df_tiles" must be provided') @@ -195,6 +215,7 @@ def get_raster_from_tiles( year=year, temporal_baseline_days=temporal_baseline_days, season=season, + variable=variable, ) df_tiles = TILE_SCHEMA.validate(df_tiles) From 1c7667cf22fbec6ccd333b46a3f59f300a2a8dcf Mon Sep 17 00:00:00 2001 From: Charlie Marshak Date: Mon, 24 Jun 2024 10:31:24 -0700 Subject: [PATCH 3/5] update scotts pr --- CHANGELOG.md | 3 ++ README.md | 6 ++- notebooks/Basic_Demo.ipynb | 98 +++++++++++++++++++++++++++++++++++--- src/tile_mate/stitcher.py | 43 +++++++++-------- tests/test_stitch_api.py | 27 +++++++++++ 5 files changed, 148 insertions(+), 29 deletions(-) diff --git a/CHANGELOG.md b/CHANGELOG.md index 1aee03a..16156eb 100644 --- a/CHANGELOG.md +++ b/CHANGELOG.md @@ -6,6 +6,9 @@ The format is based on [Keep a Changelog](https://keepachangelog.com/en/1.0.0/), and this project adheres to [PEP 440](https://www.python.org/dev/peps/pep-0440/) and uses [Semantic Versioning](https://semver.org/spec/v2.0.0.html). +## [0.0.11] +* Added `rho`, `tau` and `rmse` variables for VV polarization from Sentinel-1 Global coherence. See: http://sentinel-1-global-coherence-earthbigdata.s3-website-us-west-2.amazonaws.com/ + ## [0.0.10] ### Added diff --git a/README.md b/README.md index 10237b1..cdb5101 100644 --- a/README.md +++ b/README.md @@ -65,7 +65,7 @@ We have notebooks to demonstrate common usage: # Datasets Supported -The datasets supported are: +There are numerous tile sets. There are keyword arguments for many of the tiles. For example, for `hansen_annual_mosaic` the years 2013-2022 can be specified. The easiest way to see what is possible is to look at the [Basic Demo](notebooks/Basic_Demo.ipynb). The datasets supported are: ``` In [1]: from tile_mate.stitcher import DATASET_SHORTNAMES @@ -90,12 +90,14 @@ More information about these datasets can be found below + ESA World Cover (10 m) for 2020 and 2021: https://aws.amazon.com/marketplace/pp/prodview-7oorylcamixxc + Hansen annual mosaic, treecover 2000, gain, and loss year: https://data.globalforestwatch.org/documents/941f17325a494ed78c4817f9bb20f33a/explore + S1 Coherence from December 2019 - Nov 2020: https://aws.amazon.com/marketplace/pp/prodview-iz6lnjbdlgcwa#resources + + Include all temporal baselines and seasons for VV coherence + + Include `rho`, `tau` and `rmse` seasonal decay modeling parameters + The copernicus 100 m LULC dataset from 2015 - 2019: https://land.copernicus.eu/global/content/annual-100m-global-land-cover-maps-available + Height above nearest drainage (distributed and generated by ASF) in 2021 derived from Copernicus Global DEM: https://github.com/asjohnston-asf/agu-2022-notebooks/blob/main/hand-notebook.ipynb (and their [tool](https://github.com/HydroSAR/HydroSAR/blob/develop/src/hydrosar/hand/prepare.py) to do the exact same thing) + RADD Deforestation alerts (ongoing): https://data.globalforestwatch.org/datasets/gfw::deforestation-alerts-radd/about + Glad landcover maps (2000, 2005, 2010, 2015, 2020) and change map (2020 changes when compared to 2000): https://storage.googleapis.com/earthenginepartners-hansen/GLCLU2000-2020/v2/download.html -See these [notebooks](notebooks/tile_creation) to see how these tiles are generated and organized. +See these [notebooks](notebooks/tile_creation) to see how these tiles are generated and organized. Feel free to open a issue ticket or PR if there are modifications or new tilesets you would like to see. # Dateline support diff --git a/notebooks/Basic_Demo.ipynb b/notebooks/Basic_Demo.ipynb index 6a6ca7c..3c43464 100644 --- a/notebooks/Basic_Demo.ipynb +++ b/notebooks/Basic_Demo.ipynb @@ -10,7 +10,7 @@ }, { "cell_type": "code", - "execution_count": 1, + "execution_count": 2, "id": "f37a02b3-55be-4ada-b22d-d13dbf8fd8cf", "metadata": {}, "outputs": [], @@ -21,7 +21,7 @@ }, { "cell_type": "code", - "execution_count": 2, + "execution_count": 3, "id": "3f910d14-4943-4a8e-a7c3-45fc65a50f24", "metadata": {}, "outputs": [], @@ -37,7 +37,7 @@ }, { "cell_type": "code", - "execution_count": 3, + "execution_count": 4, "id": "67b4528a-4aa8-4100-9195-1ee909e8edcb", "metadata": {}, "outputs": [ @@ -59,7 +59,7 @@ " 'glad_change']" ] }, - "execution_count": 3, + "execution_count": 4, "metadata": {}, "output_type": "execute_result" } @@ -520,7 +520,7 @@ "bounds = [-120.35, 34.85, -120.25, 34.95]\n", "\n", "X_lossyear, p_lossyear = get_raster_from_tiles(bounds, \n", - " tile_shortname='hansen_lossyear')\n", + " tile_shortname='hansen_lossyear')\n", "np.unique(X_lossyear)" ] }, @@ -766,6 +766,58 @@ "X_coh.shape" ] }, + { + "cell_type": "code", + "execution_count": 8, + "id": "744bc8a4-95a0-4152-a241-572b36ae1cde", + "metadata": {}, + "outputs": [ + { + "name": "stderr", + "output_type": "stream", + "text": [ + "Reading tile metadata: 100%|█████████████████████████████████████████████| 1/1 [00:00<00:00, 8004.40it/s]\n", + "Reading tile imagery: 100%|████████████████████████████████████████████████| 1/1 [00:00<00:00, 2.76it/s]" + ] + }, + { + "name": "stdout", + "output_type": "stream", + "text": [ + "CPU times: user 6.65 s, sys: 111 ms, total: 6.76 s\n", + "Wall time: 9.73 s\n" + ] + }, + { + "name": "stderr", + "output_type": "stream", + "text": [ + "\n" + ] + }, + { + "data": { + "text/plain": [ + "(1, 721, 361)" + ] + }, + "execution_count": 8, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "%%time\n", + "\n", + "bounds = [-120.8, 34.4, -120.5, 35]\n", + "\n", + "X_rmse, p_rmse = get_raster_from_tiles(bounds, \n", + " tile_shortname='s1_coherence_2020',\n", + " variable='rmse',\n", + " season='fall')\n", + "X_rmse.shape" + ] + }, { "cell_type": "code", "execution_count": 20, @@ -800,6 +852,40 @@ " vmin=0, vmax=100)" ] }, + { + "cell_type": "code", + "execution_count": 10, + "id": "299c57ab-e593-4b4e-82d7-3f46142ed0d7", + "metadata": {}, + "outputs": [ + { + "data": { + "image/png": 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", + "text/plain": [ + "
" + ] + }, + "metadata": {}, + "output_type": "display_data" + }, + { + "data": { + "text/plain": [ + "" + ] + }, + "execution_count": 10, + "metadata": {}, + "output_type": "execute_result" + } + ], + "source": [ + "show(X_rmse, \n", + " transform=p_rmse['transform'], \n", + " interpolation='none', \n", + " vmin=0, vmax=100)" + ] + }, { "cell_type": "markdown", "id": "a0a0ec0a-0666-4b96-9d25-ae2202d55121", @@ -1389,7 +1475,7 @@ "name": "python", "nbconvert_exporter": "python", "pygments_lexer": "ipython3", - "version": "3.12.1" + "version": "3.12.4" } }, "nbformat": 4, diff --git a/src/tile_mate/stitcher.py b/src/tile_mate/stitcher.py index de6d686..9353ac4 100644 --- a/src/tile_mate/stitcher.py +++ b/src/tile_mate/stitcher.py @@ -1,5 +1,6 @@ from functools import lru_cache from pathlib import Path +from typing import Optional import geopandas as gpd import rasterio @@ -36,7 +37,7 @@ CURRENT_HANSEN_YEAR = 2022 SEASONS = ['fall', 'winter', 'spring', 'summer'] S1_TEMPORAL_BASELINE_DAYS = [6, 12, 18, 24, 36, 48] -S1_VARIABLES = ['rho', 'tau', 'rmse'] +S1_MODEL_VARIABLES = ['rho', 'tau', 'rmse'] GLAD_LANDCOVER_YEARS = [2000, 2005, 2010, 2015, 2020] @@ -53,10 +54,10 @@ def get_all_tile_data(tile_key: str) -> gpd.GeoDataFrame: @lru_cache def get_tile_data( tile_key: str, - year: int = None, - season: str = None, - temporal_baseline_days: int = None, - variable: str = None + year: Optional[int] = None, + season: Optional[str] = None, + temporal_baseline_days: Optional[str] = None, + s1_decay_model_param: Optional[str] = None ) -> gpd.GeoDataFrame: # Because tile data is cached - we need to copy it. df_tiles = get_all_tile_data(tile_key).copy() @@ -104,32 +105,32 @@ def update_glad_landcover_url(url: str, year: int = year) -> str: raise ValueError('Year is required for tile lookup') if tile_key == 's1_coherence_2020': - if season is None: - raise ValueError(f'{tile_key} requires season to be specified') - if variable is None and temporal_baseline_days is None: - raise ValueError(f'{tile_key} requires either variable or temporal baseline to be specified') - + if (season is None) and (s1_decay_model_param is None): + raise ValueError(f'{tile_key} requires *both* season or s1_decay_model_param to be specified') + # XOR of variables + if (temporal_baseline_days is None) == (s1_decay_model_param is None): + raise ValueError(f'{tile_key} requires either s1_decay_model_param or temporal baseline to be specified') if season not in SEASONS: raise ValueError(f'season keyword must be in {", ".join(SEASONS)}') if temporal_baseline_days not in [None, *S1_TEMPORAL_BASELINE_DAYS]: tb_days_str = list(map(str, S1_TEMPORAL_BASELINE_DAYS)) raise ValueError(f'temporal_baseline_days must be in {", ".join(tb_days_str)}') - if variable not in [None, *S1_VARIABLES]: - raise ValueError(f'variable keyword must be in {", ".join(S1_VARIABLES)}') + if s1_decay_model_param not in [None, *S1_MODEL_VARIABLES]: + raise ValueError(f's1_decay_model_param keyword must be in {", ".join(S1_MODEL_VARIABLES)}') # we need season, but we can either do temporal baseline, or variable ind_season = df_tiles.season == season + # temporal baseline and season if temporal_baseline_days is not None: ind_tb = df_tiles.temporal_baseline_days == temporal_baseline_days total_ind = ind_tb & ind_season df_tiles = df_tiles[total_ind].reset_index(drop=True) + # s1_decay_model_param else: - # ind_variable = df_tiles.variable == variable - # HACK: there is not a "variable" for now. - # So instead, we pick the 12day rasters, the manipulate the URL to get the variable we want + # use 12 day temporal baseline to replace with s1_decay_model_param ind_tb = df_tiles.temporal_baseline_days == 12 total_ind = ind_tb & ind_season df_tiles = df_tiles[total_ind].reset_index(drop=True) - df_tiles.loc[:, 'url'] = df_tiles.loc[:, 'url'].str.replace('_COH12', f'_{variable}') + df_tiles.loc[:, 'url'] = df_tiles.loc[:, 'url'].str.replace('_COH12', f'_{s1_decay_model_param}') if df_tiles.empty: raise NoTileCoverage(f'{tile_key} has no global tiles with the parameters provided') @@ -198,10 +199,10 @@ def get_raster_from_tiles( extent: list[float], tile_shortname: str | None = None, df_tiles: gpd.GeoDataFrame | None = None, - year: int | None = None, - season: str | None = None, - temporal_baseline_days: int | None = None, - variable: str | None = None + year: Optional[int] = None, + season: Optional[str] = None, + temporal_baseline_days: Optional[int] = None, + s1_decay_model_param: Optional[str] = None ) -> tuple: if (tile_shortname is None) and (df_tiles is None): raise ValueError('Either "tile_shortname" or "df_tiles" must be provided') @@ -215,7 +216,7 @@ def get_raster_from_tiles( year=year, temporal_baseline_days=temporal_baseline_days, season=season, - variable=variable, + s1_decay_model_param=s1_decay_model_param, ) df_tiles = TILE_SCHEMA.validate(df_tiles) diff --git a/tests/test_stitch_api.py b/tests/test_stitch_api.py index e7056d8..5cb1a91 100644 --- a/tests/test_stitch_api.py +++ b/tests/test_stitch_api.py @@ -9,6 +9,7 @@ HANSEN_MOSAIC_YEARS, S1_TEMPORAL_BASELINE_DAYS, SEASONS, + S1_MODEL_VARIABLES, ) @@ -69,6 +70,22 @@ def test_coherence_dataset(season, temporal_baseline_days): tile_shortname='s1_coherence_2020', season=season, temporal_baseline_days=temporal_baseline_days, + s1_decay_model_param=None, + ) + assert len(X.shape) == 3 + + +@pytest.mark.parametrize('season', SEASONS) +@pytest.mark.parametrize('s1_var', S1_MODEL_VARIABLES) +def test_s1_model_tiles(season, s1_var): + # Note only getting 1 tile + bounds = [-120.45, 34.85, -120.15, 34.95] + X, _ = get_raster_from_tiles( + bounds, + tile_shortname='s1_coherence_2020', + season=season, + temporal_baseline_days=None, + s1_decay_model_param=s1_var, ) assert len(X.shape) == 3 @@ -132,3 +149,13 @@ def test_s1_coherence_exceptions(): X, _ = get_raster_from_tiles( bounds, tile_shortname='s1_coherence_2020', season='fall', temporal_baseline_days=5 ) + + # No temporal baseline when using model param + with pytest.raises(ValueError): + X, _ = get_raster_from_tiles( + bounds, + tile_shortname='s1_coherence_2020', + season='fall', + temporal_baseline_days=12, + s1_decay_model_param='rmse', + ) From e688572ec2d28d11c37f6b70a6f6079f2eba7d85 Mon Sep 17 00:00:00 2001 From: Charlie Marshak Date: Mon, 24 Jun 2024 10:33:46 -0700 Subject: [PATCH 4/5] lint --- src/tile_mate/stitcher.py | 4 ++-- tests/test_stitch_api.py | 2 +- 2 files changed, 3 insertions(+), 3 deletions(-) diff --git a/src/tile_mate/stitcher.py b/src/tile_mate/stitcher.py index 9353ac4..272e156 100644 --- a/src/tile_mate/stitcher.py +++ b/src/tile_mate/stitcher.py @@ -57,7 +57,7 @@ def get_tile_data( year: Optional[int] = None, season: Optional[str] = None, temporal_baseline_days: Optional[str] = None, - s1_decay_model_param: Optional[str] = None + s1_decay_model_param: Optional[str] = None, ) -> gpd.GeoDataFrame: # Because tile data is cached - we need to copy it. df_tiles = get_all_tile_data(tile_key).copy() @@ -202,7 +202,7 @@ def get_raster_from_tiles( year: Optional[int] = None, season: Optional[str] = None, temporal_baseline_days: Optional[int] = None, - s1_decay_model_param: Optional[str] = None + s1_decay_model_param: Optional[str] = None, ) -> tuple: if (tile_shortname is None) and (df_tiles is None): raise ValueError('Either "tile_shortname" or "df_tiles" must be provided') diff --git a/tests/test_stitch_api.py b/tests/test_stitch_api.py index 5cb1a91..9166378 100644 --- a/tests/test_stitch_api.py +++ b/tests/test_stitch_api.py @@ -7,9 +7,9 @@ DATASETS_WITH_YEAR, GLAD_LANDCOVER_YEARS, HANSEN_MOSAIC_YEARS, + S1_MODEL_VARIABLES, S1_TEMPORAL_BASELINE_DAYS, SEASONS, - S1_MODEL_VARIABLES, ) From 18502a78caea3c5265eae3951edd7e3413bb4aba Mon Sep 17 00:00:00 2001 From: Charlie Marshak Date: Mon, 24 Jun 2024 10:36:23 -0700 Subject: [PATCH 5/5] more optional typing --- src/tile_mate/stitcher.py | 4 ++-- 1 file changed, 2 insertions(+), 2 deletions(-) diff --git a/src/tile_mate/stitcher.py b/src/tile_mate/stitcher.py index 272e156..a7f2f36 100644 --- a/src/tile_mate/stitcher.py +++ b/src/tile_mate/stitcher.py @@ -197,8 +197,8 @@ def get_additional_tile_metadata(urls: list[str], max_tile_tries: int = 10) -> d def get_raster_from_tiles( extent: list[float], - tile_shortname: str | None = None, - df_tiles: gpd.GeoDataFrame | None = None, + tile_shortname: Optional[str] = None, + df_tiles: Optional[gpd.GeoDataFrame] = None, year: Optional[int] = None, season: Optional[str] = None, temporal_baseline_days: Optional[int] = None,