From 5ca65747801f3c22acdd6911bf3b1eeb56a8da85 Mon Sep 17 00:00:00 2001
From: xhong <xhong_17@outlook.com>
Date: Sun, 12 Jan 2025 00:38:59 +0800
Subject: [PATCH] =?UTF-8?q?feat:=20=E5=AE=8C=E5=96=84=E4=BA=91=E7=AB=AF?=
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---
 HLS_SuPER/HLS_PER.py | 22 +++++++++++++---------
 1 file changed, 13 insertions(+), 9 deletions(-)

diff --git a/HLS_SuPER/HLS_PER.py b/HLS_SuPER/HLS_PER.py
index 5eed2a6..feb02ab 100644
--- a/HLS_SuPER/HLS_PER.py
+++ b/HLS_SuPER/HLS_PER.py
@@ -61,7 +61,11 @@ def open_hls(
     # (Add) 读取波段名称
     split_asset = url.split("/")[-1].split(".")
     asset_name = split_asset[1]
-    band_name = split_asset[-2]
+    band_name = split_asset[-2] if split_asset[-2] != "subset" else split_asset[-3]
+    # 判断是否为 Fmask 波段
+    is_fmask = True if (band_name in ["Fmask", "FMASK"]) else False
+    # 判断是否为 L30 独有的热红外波段
+    is_tir = True if (band_name in ["B10", "B11", "TIR1", "TIR2"]) and (asset_name == "L30") else False
 
     # Reproject ROI and Clip if ROI is provided and clip is True
     if roi is not None and clip:
@@ -70,15 +74,14 @@ def open_hls(
 
     # (Add) 即使大部分影像已经被缩放且填补了缺失值, 但可能仍然有些影像需要进行手动在本地GIS软件中进行缩放和填补缺失值
     # Apply Scale Factor if desired for non-quality layer
-    if band_name != "Fmask":
+    if not is_fmask:
         if scale:
             # Mask Fill Values
             da = xr.where(da == -9999, np.nan, da)
             # Scale Data
             # (Add) 除质量层, 以及 L30 的两个热红外波段外, 其他光谱波段缩放因子均为 0.0001
             # (Add) L30 的两个热红外波段缩放因子为 0.01
-            # NOTE: 需要注意的是热红外此时未被改名
-            if (band_name == "B10" or band_name == "B11") and (asset_name == "L30"):
+            if is_tir:
                 da = da * 0.01
             else:
                 da = da * 0.0001
@@ -96,12 +99,12 @@ def open_hls(
         # Add Scale Factor to Attributes Manually - This will overwrite/add if the data is missing.
         # (Add) 若要手动缩放, 则需要手动添加缩放因子
         else:
-            if (band_name == "B10" or band_name == "B11") and (asset_name == "L30"):
+            if is_tir:
                 da.attrs["scale_factor"] = 0.01
             else:
                 da.attrs["scale_factor"] = 0.0001
-    # 销毁源数据
-    del da_org
+    # 清除源数据
+    da_org = None
     return da
 
 
@@ -186,12 +189,13 @@ def process_granule(
             quality_output_name = create_output_name(quality_url, band_dict)
             quality_output_file = f"{output_dir}/{quality_output_name}"
             # Check if quality asset is already processed
-            # Open Quality Layer
-            qa_da = open_hls(quality_url, roi, clip, scale, chunk_size)
             if not os.path.isfile(quality_output_file):
+                # Open Quality Layer
+                qa_da = open_hls(quality_url, roi, clip, scale, chunk_size)
                 # Write Output
                 qa_da.rio.to_raster(raster_path=quality_output_file, driver="COG")
             else:
+                qa_da = open_hls(quality_output_file, roi, clip, scale, chunk_size)
                 logging.info(
                     f"Existing quality file {quality_output_name} found in {output_dir}."
                 )