pantierra/efast-phenocam-validation
1
0
Fork 0
Code Issues Pull requests Projects Releases Packages Wiki Activity

Handle cloud-coverage.

Browse source
This commit is contained in:
Felix Delattre 2025-12-22 13:54:14 +01:00
parent 6f347d04dd
commit 04f0ab334d
3 changed files with 88 additions and 8 deletions
Download patch file Download diff file Expand all files Collapse all files

43
clouds.py Normal file
View file

@ -0,0 +1,43 @@
import json
from pathlib import Path
from datetime import datetime
def detect_clouds(year, site_name):
output_file = Path(f"data/{site_name}/{year}/clouds.json")
clouds = {"s2": [], "s3": []}
for source in ["s2", "s3"]:
timeseries_file = Path(f"data/{site_name}/{year}/ndvi/{source}/timeseries.json")
if not timeseries_file.exists():
print(f"[CLOUDS-{source.upper()}] No timeseries.json found")
continue
print(f"[CLOUDS-{source.upper()}] Processing {timeseries_file}...")
with open(timeseries_file) as f:
timeseries = json.load(f)
entries = [(e, datetime.fromisoformat(e["date"].replace("Z", "+00:00"))) for e in timeseries if e["ndvi"] is not None]
for entry, entry_date in entries:
# Use 14-day window for seasonal context, require NDVI < 0.3 and >0.15 below max
window_ndvi = [e["ndvi"] for e, d in entries if abs((d - entry_date).days) <= 14]
if len(window_ndvi) < 3:
continue
max_ndvi = max(window_ndvi)
threshold = max_ndvi - 0.15
if entry["ndvi"] < threshold and entry["ndvi"] < 0.3:
clouds[source].append(entry["filename"])
print(f"[CLOUDS-{source.upper()}] Found {len(clouds[source])} cloud-covered files")
output_file.parent.mkdir(parents=True, exist_ok=True)
with open(output_file, "w") as f:
json.dump(clouds, f, indent=2)
print(f"[CLOUDS] Saved: {output_file}")

11
run.py
View file

@ -1,6 +1,7 @@
from download_s2 import download_s2
from download_s3 import download_s3
from ndvi import generate_ndvi, create_ndvi_timeseries
from clouds import detect_clouds
year = 2024
site_position = (47.116171, 11.320308)
@ -11,7 +12,11 @@ site_name = "innsbruck"
# download_s3(year, site_position, site_name)
# print("All downloads completed")
print(f"Generating NDVI for {site_name}, {year}")
# print(f"Generating NDVI for {site_name}, {year}")
# generate_ndvi(year, site_position, site_name)
create_ndvi_timeseries(year, site_position, site_name)
print("All NDVI generation completed")
# create_ndvi_timeseries(year, site_position, site_name)
# print("All NDVI generation completed")
print(f"Detecting clouds for {site_name}, {year}")
detect_clouds(year, site_name)
print("Cloud detection completed")

42
webapp/index.html
View file

@ -18,6 +18,7 @@
.timeseries-label { font-size: 12px; margin-bottom: 5px; color: #666; }
.timeseries { width: 100%; height: 120px; border: 1px solid #ccc; margin-bottom: 10px; }
.map-label { font-size: 12px; margin-bottom: 5px; color: #666; }
.map-date { font-size: 11px; margin-top: 5px; color: #999; }
.map { height: 500px; border: 1px solid #ccc; }
.leaflet-image-layer { image-rendering: pixelated; }
</style>
@ -27,6 +28,10 @@
<div class="slider-container">
<input type="range" id="dateSlider" min="0" max="365" value="0">
<div id="dateDisplay">2024-01-01</div>
<label style="display: flex; align-items: center; justify-content: center; gap: 8px; margin-top: 10px;">
<input type="checkbox" id="showClouds" checked>
<span>Show cloud-covered data</span>
</label>
</div>
<div class="maps">
<div class="map-container">
@ -34,8 +39,10 @@
<div class="timeseries-label">NDVI Timeseries</div>
<canvas id="s2timeseries" class="timeseries"></canvas>
<div class="map-label">RGB Imagery</div>
<div id="s2rgbdate" class="map-date"></div>
<div id="s2map" class="map"></div>
<div class="map-label">NDVI Imagery</div>
<div id="s2ndvidate" class="map-date"></div>
<div id="s2ndvimap" class="map"></div>
</div>
<div class="map-container">
@ -43,8 +50,10 @@
<div class="timeseries-label">NDVI Timeseries</div>
<canvas id="s3timeseries" class="timeseries"></canvas>
<div class="map-label">RGB Imagery</div>
<div id="s3rgbdate" class="map-date"></div>
<div id="s3map" class="map"></div>
<div class="map-label">NDVI Imagery</div>
<div id="s3ndvidate" class="map-date"></div>
<div id="s3ndvimap" class="map"></div>
</div>
</div>
@ -70,13 +79,17 @@
const overlays = { s2: null, s3: null };
const ndviOverlays = { s2: null, s3: null };
let timeseries = { s2: [], s3: [] };
let clouds = { s2: new Set(), s3: new Set() };
const showCloudsCheckbox = document.getElementById("showClouds");
async function loadTimeseries() {
const [s2, s3] = await Promise.all([
const [s2, s3, cloudData] = await Promise.all([
fetch("../data/innsbruck/2024/ndvi/s2/timeseries.json").then(r => r.json()),
fetch("../data/innsbruck/2024/ndvi/s3/timeseries.json").then(r => r.json())
fetch("../data/innsbruck/2024/ndvi/s3/timeseries.json").then(r => r.json()),
fetch("../data/innsbruck/2024/clouds.json").then(r => r.json()).catch(() => ({ s2: [], s3: [] }))
]);
timeseries = { s2, s3 };
clouds = { s2: new Set(cloudData.s2 || []), s3: new Set(cloudData.s3 || []) };
drawTimeseries();
}
@ -92,7 +105,10 @@
const plotW = w - pad * 2, plotH = h - pad * 2;
ctx.clearRect(0, 0, w, h);
const data = timeseries[source].filter(t => t.ndvi !== null);
let data = timeseries[source].filter(t => t.ndvi !== null);
if (!showCloudsCheckbox.checked) {
data = data.filter(t => !clouds[source].has(t.filename));
}
if (!data.length) continue;
const dates = data.map(t => new Date(t.date));
@ -159,6 +175,7 @@
const date = d.toISOString().split("T")[0].replace(/-/g, "");
for (let i = 0; i < 3; i++) {
const filename = `${date}_${i}.geotiff`;
if (!showCloudsCheckbox.checked && clouds[source].has(filename)) continue;
try {
const res = await fetch(`../data/innsbruck/2024/${source}/${filename}`);
if (res.ok) return filename;
@ -218,6 +235,10 @@
if (overlays[source]) maps[source].removeLayer(overlays[source]);
overlays[source] = L.imageOverlay(canvas.toDataURL(), bounds, { opacity: 0.95 }).addTo(maps[source]);
maps[source].fitBounds(bounds);
const dateStr = filename.split("_")[0];
const date = `${dateStr.slice(0,4)}-${dateStr.slice(4,6)}-${dateStr.slice(6,8)}`;
document.getElementById(`${source}rgbdate`).textContent = date;
}
async function loadNDVI(source, filename) {
@ -256,6 +277,10 @@
if (ndviOverlays[source]) ndvimaps[source].removeLayer(ndviOverlays[source]);
ndviOverlays[source] = L.imageOverlay(canvas.toDataURL(), bounds, { opacity: 0.95 }).addTo(ndvimaps[source]);
ndvimaps[source].fitBounds(bounds);
const dateStr = filename.split("_")[0];
const date = `${dateStr.slice(0,4)}-${dateStr.slice(4,6)}-${dateStr.slice(6,8)}`;
document.getElementById(`${source}ndvidate`).textContent = date;
}
const fmtDate = (d) => `${d.getFullYear()}-${String(d.getMonth() + 1).padStart(2, "0")}-${String(d.getDate()).padStart(2, "0")}`;
@ -274,6 +299,7 @@
const date = d.toISOString().split("T")[0].replace(/-/g, "");
for (let i = 0; i < 3; i++) {
const filename = `${date}_${i}.geotiff`;
if (!showCloudsCheckbox.checked && clouds[source].has(filename)) continue;
try {
const res = await fetch(`../data/innsbruck/2024/ndvi/${source}/${filename}`);
if (res.ok) return filename;
@ -287,7 +313,10 @@
async function updateImages() {
const date = dateFromDays(parseInt(slider.value));
dateDisplay.textContent = date;
history.replaceState({}, "", `?date=${date}`);
const params = new URLSearchParams();
params.set("date", date);
if (!showCloudsCheckbox.checked) params.set("hideClouds", "1");
history.replaceState({}, "", `?${params}`);
drawTimeseries();
for (const source of ["s2", "s3"]) {
const filename = await findFile(date, source);
@ -309,9 +338,12 @@
}
}
const urlDate = new URLSearchParams(location.search).get("date");
const urlParams = new URLSearchParams(location.search);
const urlDate = urlParams.get("date");
if (urlDate) slider.value = daysFromDate(urlDate);
if (urlParams.get("hideClouds") === "1") showCloudsCheckbox.checked = false;
slider.addEventListener("input", updateImages);
showCloudsCheckbox.addEventListener("change", updateImages);
loadTimeseries().then(updateImages);
</script>
</body>