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+{
+ "cells": [
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "# Detecting Bare Soil\n",
+ "\n",
+ "In today’s world of precision agriculture and environmental monitoring, the ability to detect and track bare soil periods is becoming increasingly important. This script leverages satellite data to illustrate the process of identifying these periods in agricultural fields, showcasing the capabilities of our platform. Please note that while this notebook uses a straightforward approach to demonstrate key concepts, our [Area Monitoring](https://area-monitoring.sinergise.com/) system employs more sophisticated models designed for robust, large-scale analysis. This notebook serves as an introductory example to help users understand the basic methodology and potential of our platform.\n",
+ "\n",
+ "## Why Detecting Bare Soil Matters\n",
+ "\n",
+ "Identifying periods of bare soil is crucial for several reasons:\n",
+ "\n",
+ "1. Soil Health: Bare soil is more susceptible to erosion, nutrient loss, and degradation. By knowing when soil is exposed, farmers can take protective measures.\n",
+ "\n",
+ "2. Water Management: Bare soil affects water retention and runoff patterns. Understanding these periods helps in planning irrigation and managing water resources more effectively.\n",
+ "\n",
+ "3. Carbon Sequestration: Soil exposed to the atmosphere releases carbon. Minimizing bare soil periods can help in carbon sequestration efforts, contributing to climate change mitigation.\n",
+ "\n",
+ "4. Crop Rotation Planning: Knowledge of bare soil periods aids in planning optimal crop rotations and cover crop strategies, enhancing overall soil fertility and crop yields.\n",
+ "\n",
+ "5. Compliance and Sustainability: Many agricultural policies and sustainability certifications require minimizing bare soil exposure. This tool helps in monitoring and compliance.\n",
+ "\n",
+ "6. Biodiversity: Bare soil periods can impact local ecosystems. Understanding these periods helps in managing biodiversity in agricultural landscapes.\n",
+ "\n",
+ "## From Data to Action\n",
+ "\n",
+ "By visualizing bare soil probabilities over time and clearly identifying bare soil periods, farmers and land managers can:\n",
+ "\n",
+ "1. Plan timely interventions to protect exposed soil\n",
+ "\n",
+ "2. Optimize planting and harvesting schedules\n",
+ "\n",
+ "3. Implement targeted conservation practices\n",
+ "\n",
+ "4. Make data-driven decisions about land use and crop management"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "## Overview\n",
+ "In this playbook, we combine several powerful tools to analyze agricultural fields over time:\n",
+ "\n",
+ "1. Data Retrieval: We use the Sentinel Hub API to fetch satellite imagery data for a specific field over a given time range.\n",
+ "\n",
+ "2. Index Calculation: The script calculates various spectral indices, including MSAVI (Modified Soil Adjusted Vegetation Index), BSI (Bare Soil Index), NDTI (Normalized Difference Tillage Index), TI (Tillage Index), and NDBI (Normalized Difference Built-up Index).\n",
+ "\n",
+ "3. Bare Soil Probability: Using a combination of these indices, we estimate the probability of bare soil for each data point.\n",
+ "\n",
+ "4. Time Series Analysis: The script processes this data into a time series, allowing us to track changes over time.\n",
+ "\n",
+ "5. Bare Soil Period Identification: We identify continuous periods where the bare soil probability exceeds a certain threshold.\n",
+ "\n",
+ "6. Visualization: The results are visualized in two graphs: one showing all indices over time, and another focusing specifically on bare soil probability."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 338,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "import folium\n",
+ "import getpass\n",
+ "\n",
+ "import pandas as pd\n",
+ "import matplotlib.pyplot as plt\n",
+ "from shapely.geometry import Polygon\n",
+ "\n",
+ "from sentinelhub import (\n",
+ " SHConfig,\n",
+ " Geometry,\n",
+ " CRS,\n",
+ " SentinelHubStatistical,\n",
+ " DataCollection,\n",
+ " SentinelHubDownloadClient,\n",
+ ")"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Credentials\n",
+ "\n",
+ "The Sentinel Hub Python SDK requires a ```client_id``` and a ```client_secret``` which can be created in the [Dashboard app user settings](https://apps.sentinel-hub.com/dashboard/#/account/settings). You can find full instructions on setting up the client credentials in this SDK from the [SDK documentation](https://sentinelhub-py.readthedocs.io/en/latest/configure.html). The following code will check if you have a local profile already created, and if not it will ask for the credentials and save the profile."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 339,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "Connected to Sentinel Hub\n"
+ ]
+ }
+ ],
+ "source": [
+ "config = SHConfig()\n",
+ "\n",
+ "if not config.sh_client_id or not config.sh_client_secret:\n",
+ " print(\"No credentials found, please provide the OAuth client ID and secret.\")\n",
+ " config.sh_client_id = getpass.getpass(\"Client ID: \")\n",
+ " config.sh_client_secret = getpass.getpass(\"Client Secret: \")\n",
+ " config.save()\n",
+ " print(f\"Credentials saved to {SHConfig.get_config_location()}\")\n",
+ "else:\n",
+ " print(f\"Connected to Sentinel Hub\")"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 340,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "foi_json = {\n",
+ " \"type\": \"FeatureCollection\",\n",
+ " \"features\": [\n",
+ " {\n",
+ " \"type\": \"Feature\",\n",
+ " \"properties\": {},\n",
+ " \"geometry\": {\n",
+ " \"coordinates\": [\n",
+ " [\n",
+ " [\n",
+ " -0.558261016622879,\n",
+ " 45.967967918251816\n",
+ " ],\n",
+ " [\n",
+ " -0.5583688254861556,\n",
+ " 45.967580759585644\n",
+ " ],\n",
+ " [\n",
+ " -0.5585485069244385,\n",
+ " 45.967143641710436\n",
+ " ],\n",
+ " [\n",
+ " -0.5588180290806406,\n",
+ " 45.9666940311547\n",
+ " ],\n",
+ " [\n",
+ " -0.5594648822587658,\n",
+ " 45.96663158495545\n",
+ " ],\n",
+ " [\n",
+ " -0.5596984681280901,\n",
+ " 45.96297211475388\n",
+ " ],\n",
+ " [\n",
+ " -0.5581352396168313,\n",
+ " 45.96289717427143\n",
+ " ],\n",
+ " [\n",
+ " -0.5570212147001143,\n",
+ " 45.96289717427143\n",
+ " ],\n",
+ " [\n",
+ " -0.5561048393657586,\n",
+ " 45.96293464452532\n",
+ " ],\n",
+ " [\n",
+ " -0.5548650374429371,\n",
+ " 45.96330934566902\n",
+ " ],\n",
+ " [\n",
+ " -0.5540924072599864,\n",
+ " 45.96403376069415\n",
+ " ],\n",
+ " [\n",
+ " -0.5539666302526598,\n",
+ " 45.964770655914435\n",
+ " ],\n",
+ " [\n",
+ " -0.5549189418751723,\n",
+ " 45.965407625240545\n",
+ " ],\n",
+ " [\n",
+ " -0.5565720111055725,\n",
+ " 45.96645673522326\n",
+ " ],\n",
+ " [\n",
+ " -0.5569313739809445,\n",
+ " 45.96685639094292\n",
+ " ],\n",
+ " [\n",
+ " -0.558261016622879,\n",
+ " 45.967967918251816\n",
+ " ]\n",
+ " ]\n",
+ " ],\n",
+ " \"type\": \"Polygon\"\n",
+ " }\n",
+ " }\n",
+ " ]\n",
+ "}"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 341,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Load GeoJSON into a shapely polygon\n",
+ "foi_polygon = Polygon(foi_json[\"features\"][0][\"geometry\"][\"coordinates\"][0])\n",
+ "\n",
+ "# Convert shapely polygon to a Sentinel Hub geometry\n",
+ "foi = Geometry(foi_polygon, crs=CRS(4326))"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 342,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "text/html": [
+ "
Make this Notebook Trusted to load map: File -> Trust Notebook
"
+ ],
+ "text/plain": [
+ ""
+ ]
+ },
+ "execution_count": 342,
+ "metadata": {},
+ "output_type": "execute_result"
+ }
+ ],
+ "source": [
+ "# Plot the field on an interactive map\n",
+ "m = folium.Map(\n",
+ " location=[\n",
+ " foi_polygon.centroid.coords.xy[1][0],\n",
+ " foi_polygon.centroid.coords.xy[0][0],\n",
+ " ],\n",
+ " zoom_start=15,\n",
+ " tiles=\"OpenStreetMap\",\n",
+ ")\n",
+ "geo_j = folium.GeoJson(data=foi_polygon, style_function=lambda x: {\"fillColor\": \"blue\"})\n",
+ "geo_j.add_to(m)\n",
+ "m"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Prepare the evalscscript for Bare Soil Calculation\n",
+ "\n",
+ "The script calculates various spectral indices:\n",
+ "- NDVI (Normalized Difference Vegetation Index) [reference](https://www.sciencedirect.com/science/article/abs/pii/S0034425797001041)\n",
+ "- BSI (Bare Soil Index) [reference](https://custom-scripts.sentinel-hub.com/custom-scripts/sentinel-2/barren_soil/)\n",
+ "- NDBI (Normalized Difference Built-up Index) [reference](https://www.tandfonline.com/doi/pdf/10.1080/01431160304987)\n",
+ "- TI (Tillage Index) [reference](https://www.asprs.org/wp-content/uploads/pers/1997journal/jan/1997_jan_87-93.pdf)\n",
+ "- NDTI (Normalized Difference Tillage Index) [reference](https://www.asprs.org/wp-content/uploads/pers/1997journal/jan/1997_jan_87-93.pdf)\n"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 343,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "evalscript = \"\"\"//VERSION=3\n",
+ "\n",
+ "function setup() {\n",
+ " return {\n",
+ " input: [{\n",
+ " bands: [\"B03\", \"B04\", \"B08\", \"B11\", \"B12\", \"SCL\", \"dataMask\"],\n",
+ " }],\n",
+ " output: [\n",
+ " { id: \"msavi\", bands: 1, sampleType: \"FLOAT32\" },\n",
+ " { id: \"bsi\", bands: 1, sampleType: \"FLOAT32\" },\n",
+ " { id: \"ndti\", bands: 1, sampleType: \"FLOAT32\" },\n",
+ " { id: \"ti\", bands: 1, sampleType: \"FLOAT32\"},\n",
+ " { id: \"ndbi\", bands: 1, sampleType: \"FLOAT32\"},\n",
+ " { id: \"bareSoil_Prob\", bands: 1, sampleType: \"FLOAT32\" },\n",
+ " { id: \"dataMask\", bands: 1 },\n",
+ " ]\n",
+ " }\n",
+ "}\n",
+ "\n",
+ "function isCloud(scl) {\n",
+ " // Compute clouds based on SCL layer\n",
+ " const cloudValues = [1, 3, 8, 9, 10];\n",
+ " return cloudValues.includes(scl);\n",
+ "}\n",
+ "function evaluatePixel(sample) {\n",
+ " // Modified Soil Adjusted Vegetation Index (abbrv. MSAVI)\n",
+ " // https://doi.org/10.1016/0034-4257(94)90134-1 and https://www.indexdatabase.de/db/i-single.php?id=44\n",
+ " let msavi = (2.0 * sample.B08 + 1.0 - Math.sqrt(Math.pow((2.0 * sample.B08 + 1.0), 2.0) - 8.0 * (sample.B08 - sample.B04))) / 2.0;\n",
+ "\n",
+ " // Bare Soil Index (BSI)\n",
+ " let bsi = ((sample.B11 + sample.B04) - (sample.B08 + sample.B04)) / ((sample.B11 + sample.B04) + (sample.B08 + sample.B04));\n",
+ "\n",
+ " // Normalized Difference Built-up Index (NDBI)\n",
+ " let ndbi = index(sample.B11, sample.B08);\n",
+ " \n",
+ " // Tillage Index (TI)\n",
+ " // https://www.asprs.org/wp-content/uploads/pers/1997journal/jan/1997_jan_87-93.pdf\n",
+ " let ti = sample.B11 / sample.B12;\n",
+ "\n",
+ " // Normalized Difference Tillage Index (NDTI)\n",
+ " // https://www.asprs.org/wp-content/uploads/pers/1997journal/jan/1997_jan_87-93.pdf\n",
+ " let ndti = (sample.B11 - sample.B12)/(sample.B11 + sample.B12)\n",
+ "\n",
+ " // Simple bare soil probability (example threshold-based approach)\n",
+ " let bareSoil_Prob = (msavi < 0.2 && bsi > 0 && ndbi > 0) ? 1.0 : 0.0;\n",
+ " \n",
+ " let is_cloud = isCloud(sample.SCL);\n",
+ " let is_water = (sample.SCL == 6);\n",
+ " let mask = sample.dataMask && !is_cloud ? 1 : 0 && !is_water ? 1 : 0;\n",
+ "\n",
+ " return {\n",
+ " msavi: [msavi],\n",
+ " bsi: [bsi],\n",
+ " ndti: [ndti],\n",
+ " ti: [ti],\n",
+ " ndbi: [ndbi],\n",
+ " bareSoil_Prob: [bareSoil_Prob],\n",
+ " dataMask: [mask],\n",
+ " };\n",
+ "}\n",
+ "\"\"\""
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### SentinelHub Statistical\n",
+ "We will generate the time series for the average of the these indices using Sentinel Hub Statistics API with the following parameters:\n",
+ "\n",
+ "- Sentinel 2 Level 2A data\n",
+ "- Evalscript defined above\n",
+ "- Time of interest from January 1st, 2019 to November 1st, 2024\n",
+ "- At the native resolution (`0.0001` degree -> ±10m)\n",
+ "- Calculated for each day `(P1D)`\n",
+ "- Over the geometry our field of interest `(foi)`"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "\n",
+ "Processing Units: The following code block will consume processing units.\n",
+ "
"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 344,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "time_of_interest = \"2019-01-01\", \"2024-11-01\"\n",
+ "input_data = SentinelHubStatistical.input_data(DataCollection.SENTINEL2_L2A)\n",
+ "\n",
+ "# Set up Sentinel Hub request\n",
+ "request = SentinelHubStatistical(\n",
+ " aggregation=SentinelHubStatistical.aggregation(evalscript=evalscript, \n",
+ " time_interval=time_of_interest, \n",
+ " aggregation_interval=\"P1D\", \n",
+ " resolution=(0.0001, 0.0001)), \n",
+ " input_data=[input_data],\n",
+ " geometry=foi,\n",
+ " config=config,\n",
+ " )\n",
+ "\n",
+ "# Make request and download response\n",
+ "download_requests = [request.download_list[0]]\n",
+ "client = SentinelHubDownloadClient(config=config)\n",
+ "response = client.download(download_requests)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Outputs retrieval"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 345,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# JSON data to DataFrame\n",
+ "series = pd.json_normalize(response[0][\"data\"])\n",
+ "\n",
+ "# Convert 'interval.from' to datetime and set it as the index\n",
+ "series['date'] = pd.to_datetime(series['interval.from'])\n",
+ "series['date'] = series['date'].dt.date\n",
+ "series.set_index('date', inplace=True)\n",
+ "\n",
+ "# Drop unnecessary columns\n",
+ "series.drop(columns=['interval.from', 'interval.to'], inplace=True)\n",
+ "\n",
+ "# Convert all columns to numeric, coercing errors to NaN\n",
+ "series = series.apply(pd.to_numeric, errors='coerce')"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Calculate the coverage \n",
+ "Cloud cover in satellite images can obscure ground features, reducing the reliability of spectral indices (e.g., NDVI, NDBI) and the accuracy outputs. By calculating the coverage, we can identify and filter out cloudy date to ensures that analysis focuses on clear, unobstructed information."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 346,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Calculate the percentage coverage\n",
+ "variable = \"msavi\"\n",
+ "min_coverage = 0.8 # 80% coverage\n",
+ "\n",
+ "# Retrieve the noDataCount\n",
+ "no_data_count = series[f\"outputs.{variable}.bands.B0.stats.noDataCount\"]\n",
+ "\n",
+ "# Retrieve the total number of pixels\n",
+ "total_pixels = series[f\"outputs.{variable}.bands.B0.stats.sampleCount\"].unique()[0] - no_data_count.min()\n",
+ "\n",
+ "series[\"coverage\"]=percentage_coverage = (1 - (no_data_count - no_data_count.min()) / total_pixels)\n",
+ "series = series[series[\"coverage\"]>=min_coverage]"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Time series of indices requested"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 347,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plt.rcParams.update({'font.size': 16})\n",
+ "indices = [\"msavi\", \"bsi\", \"ndbi\", \"bareSoil_Prob\"]\n",
+ "fig, ax = plt.subplots(figsize=(15, 5))\n",
+ "for index in indices:\n",
+ " series[f\"outputs.{index}.bands.B0.stats.mean\"].plot(ax=ax, style=\"o\", label=index)\n",
+ "plt.grid()\n",
+ "plt.legend(ncols=len(indices))\n",
+ "plt.title(\"Bare Soil Indices\")\n",
+ "plt.legend(ncols=len(indices))\n",
+ "plt.xlabel(\"\")\n",
+ "plt.tight_layout()"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Converting Bare Soil Probability to periods of Bare Soil\n",
+ "\n",
+ "Because the data is not continous, the bare soil probability index is backward filled. \n",
+ "\n",
+ "- **Backward Fill (bfill):**\n",
+ "The bfill method is used to fill missing values in the DataFrame by propagating the next valid observation backward.\n",
+ "For example, if you have a sequence [0.1, None, None, 0.4], after applying bfill, it becomes [0.1, 0.4, 0.4, 0.4].\n",
+ "\n",
+ "- **Storing Periods with Bare Soil:**\n",
+ "We initialize an empty dictionary bare_soil_periods.\n",
+ "We iterate over each row in the DataFrame using iterrows().\n",
+ "If the bare_soil_prob value is greater than 0.2, we store the date and the probability in the bare_soil_periods dictionary."
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 348,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "full_date_range = pd.date_range(start=series.index.min(), end=series.index.max(), freq='D')\n",
+ "bareSoil_Prob = series[\"outputs.bareSoil_Prob.bands.B0.stats.mean\"].reindex(full_date_range)\n",
+ "bareSoil_Prob = bareSoil_Prob.bfill() >= 0.1\n",
+ "\n",
+ "# Initialize variables\n",
+ "periods = []\n",
+ "start_date = None\n",
+ "\n",
+ "# Iterate through the series to identify True periods\n",
+ "for date, value in bareSoil_Prob.items():\n",
+ " if value and start_date is None:\n",
+ " start_date = date\n",
+ " elif not value and start_date is not None:\n",
+ " periods.append({\"start_date\": start_date, \"end_date\": date - pd.Timedelta(days=1)})\n",
+ " start_date = None\n",
+ "\n",
+ "# Handle the case where the series ends with a True period\n",
+ "if start_date is not None:\n",
+ " periods.append({\"start_date\": start_date, \"end_date\": bareSoil_Prob.index[-1]})"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Results in Numbers"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 349,
+ "metadata": {},
+ "outputs": [
+ {
+ "name": "stdout",
+ "output_type": "stream",
+ "text": [
+ "For the period 2019-01-04 to 2024-10-24:\n",
+ "--------------------------------------------\n",
+ "Number of bare soil periods: 12\n",
+ "Number of days with bare soil: 810 (38.19%)\n",
+ "Number of days with vegetation: 1311 (61.81%)\n"
+ ]
+ }
+ ],
+ "source": [
+ "# Calculate the number of periods\n",
+ "num_periods = len(periods)\n",
+ "\n",
+ "# Calculate the number of days of bare soil and days with vegetation\n",
+ "days_bare_soil = sum((period[\"end_date\"] - period[\"start_date\"]).days + 1 for period in periods)\n",
+ "total_days = len(bareSoil_Prob)\n",
+ "days_with_vegetation = total_days - days_bare_soil\n",
+ "\n",
+ "# Calculate the percentages\n",
+ "percentage_bare_soil = (days_bare_soil / total_days) * 100\n",
+ "percentage_with_vegetation = (days_with_vegetation / total_days) * 100\n",
+ "\n",
+ "# Print the results\n",
+ "print(f\"For the period {full_date_range[0].date()} to {full_date_range[-1].date()}:\")\n",
+ "print(f\"--------------------------------------------\")\n",
+ "print(f\"Number of bare soil periods: {num_periods}\")\n",
+ "print(f\"Number of days with bare soil: {days_bare_soil} ({percentage_bare_soil:.2f}%)\")\n",
+ "print(f\"Number of days with vegetation: {days_with_vegetation} ({percentage_with_vegetation:.2f}%)\")\n"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Bonus Tillage events\n",
+ "https://www.mdpi.com/2072-4292/12/16/2665"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 350,
+ "metadata": {},
+ "outputs": [],
+ "source": [
+ "# Set thresholds for detecting bare soil and tillage events\n",
+ "tillage_spike_threshold = 0.1 # Adjust based on expected spike size for tillage\n",
+ "\n",
+ "# Define a tillage event as a significant increase in both TI and NDTI during bare soil\n",
+ "series['tillage_event'] = (\n",
+ " (series[\"outputs.bareSoil_Prob.bands.B0.stats.mean\"] >= 0.1) & \n",
+ " (series[\"outputs.ti.bands.B0.stats.mean\"].diff() > tillage_spike_threshold) & \n",
+ " (series[\"outputs.ndti.bands.B0.stats.mean\"].diff() > tillage_spike_threshold)\n",
+ ")\n",
+ "# Extract dates and values where tillage events occur\n",
+ "tillage_events = list(series[series['tillage_event']].index)"
+ ]
+ },
+ {
+ "cell_type": "markdown",
+ "metadata": {},
+ "source": [
+ "### Visual representation"
+ ]
+ },
+ {
+ "cell_type": "code",
+ "execution_count": 351,
+ "metadata": {},
+ "outputs": [
+ {
+ "data": {
+ "image/png": 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",
+ "text/plain": [
+ ""
+ ]
+ },
+ "metadata": {},
+ "output_type": "display_data"
+ }
+ ],
+ "source": [
+ "plt.rcParams.update({'font.size': 16})\n",
+ "fig, ax = plt.subplots(figsize=(15, 5))\n",
+ "series[f\"outputs.msavi.bands.B0.stats.mean\"].plot(ax=ax, style=\"o\", color=\"#59A14F\", label=\"msavi\")\n",
+ "handled_labels = set()\n",
+ "for period in periods:\n",
+ " # Convert start and end of season to datetime\n",
+ " start_of_season = pd.to_datetime(period['start_date'])\n",
+ " end_of_season = pd.to_datetime(period['end_date'])\n",
+ "\n",
+ " label = 'Bare Soil Period'\n",
+ " if label not in handled_labels:\n",
+ " ax.axvspan(start_of_season, end_of_season, color='#B66353', alpha=0.1, label=label)\n",
+ " handled_labels.add(label)\n",
+ " else:\n",
+ " ax.axvspan(start_of_season, end_of_season, color='#B66353', alpha=0.1)\n",
+ "\n",
+ "# Plot vertical lines for tillage events detected\n",
+ "for date in tillage_events:\n",
+ " label = 'Tillage Events'\n",
+ " if label not in handled_labels:\n",
+ " ax.axvline(pd.to_datetime(date), color='k', linestyle='--', linewidth=1, label=label)\n",
+ " handled_labels.add(label)\n",
+ " else:\n",
+ " ax.axvline(pd.to_datetime(date), color='k', linestyle='--', linewidth=1)\n",
+ "\n",
+ "plt.legend(ncols=3, bbox_to_anchor=(1, 1.15))\n",
+ "plt.ylabel(\"vegetation index\")\n",
+ "plt.xlabel(\"\")\n",
+ "plt.grid(axis=\"y\")\n",
+ "plt.tight_layout()"
+ ]
+ }
+ ],
+ "metadata": {
+ "kernelspec": {
+ "display_name": "sentinelhub",
+ "language": "python",
+ "name": "python3"
+ },
+ "language_info": {
+ "codemirror_mode": {
+ "name": "ipython",
+ "version": 3
+ },
+ "file_extension": ".py",
+ "mimetype": "text/x-python",
+ "name": "python",
+ "nbconvert_exporter": "python",
+ "pygments_lexer": "ipython3",
+ "version": "3.12.0"
+ }
+ },
+ "nbformat": 4,
+ "nbformat_minor": 2
+}