lib.py

import os
import ee
import folium
import folium.plugins as plugins

# GEE Authentication
GEE_CREDENTIALS_FILE = "./data/key/geospatial.json"
if not os.path.exists(GEE_CREDENTIALS_FILE):
    credentials = ee.ServiceAccountCredentials(None, key_data=os.getenv("geospatial_api_key"))
else:
    credentials = ee.ServiceAccountCredentials(None, GEE_CREDENTIALS_FILE)

ee.Initialize(credentials)


# Constants
CLASSES = {
    "names": ["Water", "Trees", "Flooded Vegetation", "Crops", "Built Area", "Bare Ground", "Snow/Ice", "Clouds", "Rangeland"],
    "colors": ["1a5bab", "358221", "87d19e", "ffdb5c", "ed022a", "ede9e4", "f2faff", "c8c8c8", "c6ad8d"],
}

CLOUDY_PIXEL_PERCENTAGE = 12
S2_START_DATE = "2023-08-01"
S2_END_DATE = "2023-08-31"
S2_LULC_START_DATE = "2023-01-01"
S2_LULC_END_DATE = "2023-12-31"

S2_VIS_PARAMS = {"bands": ["B4", "B3", "B2"], "min": 0, "max": 3000, "gamma": [1, 1, 1]}


# UTILS
def ApplyBitwiseS2CloudMask(image):
    """QA60 bandı üzerinden bitwise bulut maskesi uygular."""
    qa = image.select("QA60")
    cloudBitMask = 1 << 10  # Bit 10: yoğun bulut
    cirrusBitMask = 1 << 11  # Bit 11: cirrus bulut
    mask = qa.bitwiseAnd(cloudBitMask).eq(0).And(qa.bitwiseAnd(cirrusBitMask).eq(0))
    return image.updateMask(mask)


def ReColormap(image, old_colors: list, new_colors: list):
    """LULC sınıf değerlerini yeniden eşler."""
    return image.remap(old_colors, new_colors)


def CalculateIntersectionArea(image, roi: ee.Geometry):
    """Görüntü geometrisi ile ROI arasındaki kesişim alanını hesaplar."""
    convex_hull = image.geometry().convexHull()
    intersection = convex_hull.intersection(roi)
    return image.set("INTERSECTION_AREA", intersection.area())


def FilterBestAreaOfMGRSJoin(image):
    """Aynı MGRS tile içinden en büyük kesişim alanına sahip görüntüyü seçer."""
    return ee.ImageCollection.fromImages(image.get("mgrs_tile_match")).sort("INTERSECTION_AREA", False).first()


def AddGEELayer(fmap: folium.Map, ee_image, vis_params: dict, name: str, show: bool = True):
    """GEE imajını folium haritasına tile katmanı olarak ekler."""
    map_id = ee_image.getMapId(vis_params)
    tile_url = map_id["tile_fetcher"].url_format
    folium.TileLayer(tiles=tile_url, attr="Google Earth Engine", name=name, overlay=True, control=True, show=show).add_to(fmap)


def RequestFunction(roi_coords: list) -> folium.Map:
    """
    Verilen koordinat listesinden Sentinel-2 ve ESRI LULC katmanlarını
    içeren bir Folium haritası döndürür.
    """
    if not roi_coords:
        return None

    roi = ee.Geometry.Polygon(roi_coords)

    # ROI merkezini hesapla (harita başlangıç konumu)
    centroid = roi.centroid().getInfo()["coordinates"]
    center_lat = centroid[1]
    center_lon = centroid[0]

    # Sentinel-2 koleksiyonu
    S2Collection = (
        ee.ImageCollection("COPERNICUS/S2_HARMONIZED")
        .filterBounds(roi)
        .filterDate(S2_START_DATE, S2_END_DATE)
        .filter(ee.Filter.lt("CLOUDY_PIXEL_PERCENTAGE", CLOUDY_PIXEL_PERCENTAGE))
        .sort("CLOUDY_PIXEL_PERCENTAGE", ascending=True)
    )

    # ESRI LULC koleksiyonu
    esriLULCCollection = ee.ImageCollection("projects/sat-io/open-datasets/landcover/ESRI_Global-LULC_10m_TS").filterDate(
        S2_LULC_START_DATE, S2_LULC_END_DATE
    )
    esriLULCCollection = ee.ImageCollection(esriLULCCollection.mosaic().clip(roi)).map(
        lambda img: ReColormap(img, [1, 2, 4, 5, 7, 8, 9, 10, 11], [1, 2, 3, 4, 5, 6, 7, 8, 9])
    )

    # Bulut maskeleme
    S2Collection = S2Collection.map(ApplyBitwiseS2CloudMask)

    # Alan hesaplama ve MGRS tile eşleştirme
    S2Collection = S2Collection.map(lambda img: CalculateIntersectionArea(img, roi)).sort("INTERSECTION_AREA", False)

    joinCol = ee.Join.saveAll("mgrs_tile_match").apply(
        primary=S2Collection.distinct("MGRS_TILE"),
        secondary=S2Collection,
        condition=ee.Filter.equals(leftField="MGRS_TILE", rightField="MGRS_TILE"),
    )

    bestCollection = ee.ImageCollection(joinCol.map(FilterBestAreaOfMGRSJoin))
    s2Image = bestCollection.mosaic().clip(roi)

    # LULC maskesi: yalnızca geçerli S2 piksellerini göster
    esriLULCImage = esriLULCCollection.first().updateMask(s2Image.select("B4").gt(0))

    # Folium MAP
    fmap = folium.Map(location=[center_lat, center_lon], zoom_start=10, tiles=None)

    # Temel katman
    folium.TileLayer(tiles="https://tile.openstreetmap.org/{z}/{x}/{y}.png", attr="OpenStreetMap", name="OpenStreetMap", show=True).add_to(
        fmap
    )

    folium.TileLayer(
        tiles="https://server.arcgisonline.com/ArcGIS/rest/services/World_Imagery/MapServer/tile/{z}/{y}/{x}", attr="Esri", name="Esri Uydu"
    ).add_to(fmap)

    # ROI sınırı
    roi_geojson = roi.getInfo()
    folium.GeoJson(roi_geojson, name="Pilot Bölge", style_function=lambda x: {"color": "black", "weight": 2, "fillOpacity": 0}).add_to(fmap)

    # GEE katmanları
    AddGEELayer(fmap, s2Image, S2_VIS_PARAMS, "Sentinel-2 RGB")
    AddGEELayer(fmap, esriLULCImage, {"min": 1, "max": 9, "palette": CLASSES["colors"]}, "ESRI LULC")

    folium.LayerControl(position="bottomleft").add_to(fmap)
    plugins.Fullscreen(position="topright").add_to(fmap)

    return fmap