feat(DEM_SuPER): 添加对ALOS 12.5m DEM的下载支持.

DATA_SuPER/DEM_SuPER.py

@@ -4,25 +4,35 @@
 This module contains functions related to preprocessing DEM data.
 For example, elevation, slope, aspect
 
-Step1: Use earthaccess search and download NASADEM Data
+Step1: Use earthaccess search and download DEM Data
 - NASADEM_HGT
     - includes 30m DEM, based on SRTM data
     - https://lpdaac.usgs.gov/products/nasadem_hgtv001/
 - NASADEM_SC
     - includes 30m slope, aspect, based on NASADEM_HGT
     - https://lpdaac.usgs.gov/products/nasadem_scv001/
+- ALOS PALSAR RTC Project
+    - includes 12.5, 30m DEM, based on ALOS PALSAR data
+    - https://www.earthdata.nasa.gov/data/projects/alos-palsar-rtc-project
 
-Step2: Process DEM data
+Step2a: Process NASADEM data
 - 下载的 NASADEM 均为 *.zip 文件, 需先进行解压
 - NASADEM 文件名称结构为: NASADEM_类型_网格编号/网格编号.数据类型
     - 高程示例: NASADEM_HGT_n30e113/n30e113.hgt
     - 坡度示例: NASADEM_SC_n30e113/n30e113.slope
     - 坡向示例: NASADEM_SC_n30e113/n30e113.aspect
-- 读取文件按网格进行裁剪并镶嵌, 坡度和坡向数据需要进行缩放处理, 将网格范围的结果保存为 *.tif 文件
+- 读取文件按指定范围进行裁剪并镶嵌, 坡度和坡向数据需要进行缩放处理, 将网格范围的结果保存为 *.tif 文件
+
+Step2b: Process ALOS PALSAR RTC Project data
+- 下载的 ALOS PALSAR RTC Project 均为 *.zip 文件, 需先进行解压
+- ALOS PALSAR RTC Project 文件名称结构为: AP_轨道号_CCC_DDDD_RT1.数据类型.tif
+    - 高程示例: AP_16112_FBS_F0620_RT1.dem.tif
+- 读取文件按指定范围进行裁剪并镶嵌, 坡度和坡向数据需要进行缩放处理, 将网格范围的结果保存为 *.tif 文件
+
 
 -------------------------------------------------------------------------------                        
 Authors: Hong Xie
-Last Updated: 2025-08-05
+Last Updated: 2025-10-10
 ===============================================================================
 """
 
@@ -41,7 +51,12 @@ from rioxarray import open_rasterio
 
 sys.path.append(os.path.dirname(os.path.dirname(os.path.abspath(__file__))))
 
-from utils.common_utils import setup_dask_environment, clip_image, mosaic_images
+from utils.common_utils import (
+    setup_dask_environment,
+    setup_logging,
+    clip_image,
+    mosaic_images,
+)
 from HLS_SuPER.HLS_Su import earthdata_search
 
 
@@ -103,53 +118,88 @@ def download_granule(granule_urls: list[str], output_dir: str) -> bool:
     return True
 
 
-def unzip_nasadem_files(zip_file_list: list[str], unzip_dir: str):
+def unzip_dem_files(
+    zip_file_list: list[str], unzip_dir: str, mode_str: str = "NASADEM"
+) -> None:
     """
-    解压下载的 NASADEM ZIP 文件, 并将解压后的文件统一为可读写的 .hgt 格式
+    解压下载的 DEM ZIP 文件,
+
+    若为 NASADEM, 则将其解压后的文件统一为可读写的 .hgt 格式;
+    若为 ALOSDEM, 则将其解压后的文件统一为可读写的 .tif 格式.
+
+    Parameters
+    ----------
+    zip_file_list: list
+        待解压的 ZIP 文件列表
+    unzip_dir: str
+        解压目录
+    mode_str: str, optional
+        解压模式, 默认为 "NASADEM", 可选 "NASADEM", "ALOSDEM"
     """
     try:
         for zip_path in zip_file_list:
             if not zipfile.is_zipfile(zip_path):
                 continue
             with zipfile.ZipFile(zip_path, "r") as zip_ref:
-                # 仅解压包含 .hgt, .slope, .aspect 的文件
+                if mode_str == "NASADEM":
-                for hgt_file in [f for f in zip_ref.namelist() if f.endswith((".hgt", ".slope", ".aspect"))]:
+                    # 示例文件名称: NASADEM_HGT_n30e113.zip
-                    # 解压时重命名文件
+                    # 仅解压包含 .hgt, .slope, .aspect 的文件
-                    new_name = (
+                    for hgt_file in [
-                        hgt_file.replace(".hgt", ".elevation.hgt")
+                        f
-                        if hgt_file.endswith(".hgt")
+                        for f in zip_ref.namelist()
-                        else f"{hgt_file}.hgt"
+                        if f.endswith((".hgt", ".slope", ".aspect"))
-                    )
+                    ]:
+                        # 解压时重命名文件
+                        new_name = (
+                            hgt_file.replace(".hgt", ".elevation.hgt")
+                            if hgt_file.endswith(".hgt")
+                            else f"{hgt_file}.hgt"
+                        )
                     unzip_file_path = os.path.join(unzip_dir, new_name)
                     if os.path.exists(unzip_file_path):
                         continue
                     with zip_ref.open(hgt_file) as source_file:
-                        with open(unzip_file_path, 'wb') as unzip_file:
+                        with open(unzip_file_path, "wb") as unzip_file:
                             unzip_file.write(source_file.read())
+                elif mode_str == "ALOSDEM":
+                    # 仅解压包含 dem.tif 的文件
+                    for tif_file in [
+                        f for f in zip_ref.namelist() if f.endswith("dem.tif")
+                    ]:
+                        new_name = tif_file.replace("dem.tif", "elevation.tif")
+                        unzip_file_path = os.path.join(unzip_dir, new_name)
+                        if os.path.exists(unzip_file_path):
+                            continue
+                        with zip_ref.open(tif_file) as source_file:
+                            with open(unzip_file_path, "wb") as unzip_file:
+                                unzip_file.write(source_file.read())
     except Exception as e:
-        logging.error(f"Error unzipping NASADEM to {unzip_dir}: {e}")
+        logging.error(f"Error unzipping {mode_str} to {unzip_dir}: {e}")
         return
 
 
 def process_granule(
     unzip_dir: str,
     output_dir: str,
+    mode_str: str,
     name: str,
     roi: list,
     clip=True,
     tile_id: str = None,
 ) -> bool:
     """
-    读取解压并重命名处理后的指定类型 NASADEM 数据并进行预处理, 包括读取, 裁剪, 镶嵌, 并对坡度坡向进行缩放
+    读取解压并重命名处理后的指定类型 DEM 数据并进行预处理, 包括读取, 裁剪, 镶嵌, 并对坡度坡向进行缩放
 
     Parameters
     ----------
     unzip_dir: str
-        解压后的 NASADEM 文件根目录
+        解压后的 DEM 文件根目录
     output_dir: str
         输出根目录
+    mode_str: str
+        数据模式, 可选 NASADEM, ALOSDEM
     name: str
-        数据类型, 包括 elevation, slope, aspect
+        数据类型, 可选 elevation, slope, aspect
     roi: list
         网格范围
     clip: bool
@@ -163,17 +213,19 @@ def process_granule(
         处理状态 True or False
     """
 
-    dem_file_list = glob.glob(os.path.join(unzip_dir, f"*{name}.hgt"))
+    if mode_str == "NASADEM":
-    out_tif_name = f"DEM.NASADEM.{tile_id}.2000.{name}.tif"
+        dem_file_list = glob.glob(os.path.join(unzip_dir, f"*{name}.hgt"))
+        out_tif_name = f"DEM.NASADEM.{tile_id}.2000.{name}.tif"
+    elif mode_str == "ALOSDEM":
+        dem_file_list = glob.glob(os.path.join(unzip_dir, f"*{name}.tif"))
+        out_tif_name = f"DEM.ALOSDEM.{tile_id}.2014.{name}.tif"
     output_file = os.path.join(output_dir, out_tif_name)
     if not os.path.isfile(output_file):
         try:
             dem_raster_list = []
             for dem_path in dem_file_list:
                 dem = (
-                    open_rasterio(dem_path)
+                    open_rasterio(dem_path).squeeze(dim="band", drop=True).rename(name)
-                    .squeeze(dim="band", drop=True)
-                    .rename(name)
                 )
                 if name == "slope" or name == "aspect":
                     org_attrs = dem.attrs
@@ -190,7 +242,9 @@ def process_granule(
                     dem_mosaiced = mosaic_images(dem_raster_list, nodata=-32768)
                 if roi is not None and clip:
                     dem_mosaiced = clip_image(dem_mosaiced, roi, clip_by_box=True)
-                dem_mosaiced.rio.to_raster(output_file, driver="COG", compress="DEFLATE")
+                dem_mosaiced.rio.to_raster(
+                    output_file, driver="COG", compress="DEFLATE"
+                )
         except Exception as e:
             logging.error(f"Error processing files in {name}: {e}")
             return False
@@ -200,54 +254,72 @@ def process_granule(
     return True
 
 
-def main(region: list, asset_name: list, tile_id: str):
+def main(
+    output_root_dir: str,
+    region: list,
+    asset_name: list,
+    tile_id: str,
+    mode_str: str = "NASADEM",
+):
     bbox = tuple(list(region.total_bounds))
-    # 示例文件名称: NASADEM_HGT_n30e113.zip
     results_urls = []
-    output_root_dir = ".\\data\\DEM\\NASADEM"
+    mode_str = mode_str.upper()
+    output_root_dir = os.path.join(output_root_dir, mode_str)
     # 放置下载的 ZIP 文件
     download_dir = os.path.join(output_root_dir, "ZIP")
     # 放置解压并预处理后的文件
     unzip_dir = os.path.join(download_dir, "UNZIP")
     output_dir = os.path.join(output_root_dir, "TIF", tile_id)
+    os.makedirs(download_dir, exist_ok=True)
     os.makedirs(unzip_dir, exist_ok=True)
     os.makedirs(output_dir, exist_ok=True)
-    results_urls_file = f"{output_root_dir}\\NASADEM_{tile_id}_results_urls.json"
+    results_urls_file = os.path.join(
+        output_root_dir, f"{mode_str}_{tile_id}_results_urls.json"
+    )
+
+    # 配置日志
+    logs_file = os.path.join(output_root_dir, f"{mode_str}_{tile_id}_SuPER.log")
+    setup_logging(logs_file)
+
     # 默认覆盖上一次检索记录
     results_urls = earthdata_search(asset_name, roi=bbox)
     with open(results_urls_file, "w") as f:
         json.dump(results_urls, f)
-    # 构造待解压的文件列表
+    logging.info(f"Found {len(results_urls)} {mode_str} granules.")
-    zip_file_list = [os.path.join(download_dir, os.path.basename(result[0])) for result in results_urls]
+    if len(results_urls) == 0:
+        return
 
-    # 配置日志
+    # 构造待解压的文件列表
-    logging.basicConfig(
+    zip_file_list = [
-        level=logging.INFO,
+        os.path.join(download_dir, os.path.basename(result[0]))
-        format="%(levelname)s:%(asctime)s ||| %(message)s",
+        for result in results_urls
-        handlers=[
+    ]
-            logging.StreamHandler(sys.stdout),
-            logging.FileHandler(f"{output_root_dir}\\NASADEM_SuPER.log"),
-        ],
-    )
-    logging.info(f"Found {len(results_urls)} NASADEM granules.")
 
     client = dask.distributed.Client(timeout=60, memory_limit="8GB")
     client.run(setup_dask_environment)
     all_start_time = time.time()
     client.scatter(results_urls)
 
-    logging.info(f"Start processing NASADEM ...")
+    logging.info(f"Start processing {mode_str} ...")
     download_tasks = [
         dask.delayed(download_granule)(granule_url, download_dir)
         for granule_url in results_urls
     ]
-    unzip_tasks = dask.delayed(unzip_nasadem_files)(zip_file_list, unzip_dir)
+    # 根据模式传递正确的解压标识
-    process_tasks = [
+    unzip_tasks = dask.delayed(unzip_dem_files)(zip_file_list, unzip_dir, mode_str)
-        dask.delayed(process_granule)(
+    if mode_str == "NASADEM":
-            unzip_dir, output_dir, name, region, True, tile_id
+        process_tasks = [
-        )
+            dask.delayed(process_granule)(
-        for name in ["elevation", "slope", "aspect"]
+                unzip_dir, output_dir, mode_str, name, region, True, tile_id
-    ]
+            )
+            for name in ["elevation", "slope", "aspect"]
+        ]
+    elif mode_str == "ALOSDEM":
+        process_tasks = [
+            dask.delayed(process_granule)(
+                unzip_dir, output_dir, mode_str, "elevation", region, True, tile_id
+            )
+        ]
 
     dask.compute(*download_tasks)
     dask.compute(unzip_tasks)
@@ -256,14 +328,19 @@ def main(region: list, asset_name: list, tile_id: str):
     client.close()
     all_total_time = time.time() - all_start_time
     logging.info(
-        f"All NASADEM Downloading complete and proccessed. Total time: {all_total_time} seconds"
+        f"All {mode_str} Downloading complete and processed. Total time: {all_total_time} seconds"
     )
 
 
 if __name__ == "__main__":
     earthaccess.login(persist=True)
     # region = gpd.read_file("./data/vectors/wuling_guanqu_polygon.geojson")
-    tile_id = "49REL"
+    # tile_id = "49REL"
+    tile_id = "Wuhan"
     region = gpd.read_file(f"./data/vectors/{tile_id}.geojson")
-    asset_name = ["NASADEM_HGT", "NASADEM_SC"]
+    # asset_name = ["NASADEM_HGT", "NASADEM_SC"]
-    main(region, asset_name, tile_id)
+    # mode_str = "NASADEM"
+    asset_name = ["ALOS_PSR_RTC_HIGH"]
+    mode_str = "ALOSDEM"
+    output_root_dir = ".\\data\\DEM"
+    main(output_root_dir, region, asset_name, tile_id, mode_str)