Torres Strait Sentinel 2 Satellite Regional Maps and Imagery 2015 – 2021 (AIMS)

This dataset contains both large (A0) printable maps of the Torres Strait broken into six overlapping regions, based on a clear sky, clear water composite Sentinel 2 composite imagery and the imagery used to create these maps. These maps show satellite imagery of the region, overlaid with reef and island boundaries and names. Not all features are named, just the more prominent features. This also includes a vector map of Ashmore Reef and Boot Reef in Coral Sea as these were used in the same discussions that these maps were developed for. The map of Ashmore Reef includes the atoll platform, reef boundaries and depth polygons for 5 m and 10 m.This dataset contains all working files used in the development of these maps. This includes all a copy of all the source datasets and all derived satellite image tiles and QGIS files used to create the maps. This includes cloud free Sentinel 2 composite imagery of the Torres Strait region with alpha blended edges to allow the creation of a smooth high resolution basemap of the region. The base imagery is similar to the older base imagery dataset: Torres Strait clear sky, clear water Landsat 5 satellite composite (NERP TE 13.1 eAtlas, AIMS, source: NASA).Most of the imagery in the composite imagery from 2017 - 2021.Method:The Sentinel 2 basemap was produced by processing imagery from the World_AIMS_Marine-satellite-imagery dataset (01-data/World_AIMS_Marine-satellite-imagery in the data download) for the Torres Strait region. The TrueColour imagery for the scenes covering the mapped area were downloaded. Both the reference 1 imagery (R1) and reference 2 imagery (R2) was copied for processing. R1 imagery contains the lowest noise, most cloud free imagery, while R2 contains the next best set of imagery. Both R1 and R2 are typically composite images from multiple dates. The R2 images were selectively blended using manually created masks with the R1 images. This was done to get the best combination of both images and typically resulted in a reduction in some of the cloud artefacts in the R1 images. The mask creation and previewing of the blending was performed in Photoshop. The created masks were saved in 01-data/R2-R1-masks. To help with the blending of neighbouring images a feathered alpha channel was added to the imagery. The processing of the merging (using the masks) and the creation of the feathered borders on the images was performed using a Python script (src/local/03-merge-R2-R1-images.py) using the Pillow library and GDAL. The neighbouring image blending mask was created by applying a blurring of the original hard image mask. This allowed neighbouring image tiles to merge together. The imagery and reference datasets (reef boundaries, EEZ) were loaded into QGIS for the creation of the printable maps. To optimise the matching of the resulting map slight brightness adjustments were applied to each scene tile to match its neighbours. This was done in the setup of each image in QGIS. This adjustment was imperfect as each tile was made from a different combinations of days (to remove clouds) resulting in each scene having a different tonal gradients across the scene then its neighbours. Additionally Sentinel 2 has slight stripes (at 13 degrees off the vertical) due to the swath of each sensor having a slight sensitivity difference. This effect was uncorrected in this imagery. Single merged composite GeoTiff:The image tiles with alpha blended edges work well in QGIS, but not in ArcGIS Pro. To allow this imagery to be used across tools that don't support the alpha blending we merged and flattened the tiles into a single large GeoTiff with no alpha channel. This was done by rendering the map created in QGIS into a single large image. This was done in multiple steps to make the process manageable. The rendered map was cut into twenty 1 x 1 degree georeferenced PNG images using the Atlas feature of QGIS. This process baked in the alpha blending across neighbouring Sentinel 2 scenes. The PNG images were then merged back into a large GeoTiff image using GDAL (via QGIS), removing the alpha channel. The brightness of the image was adjusted so that the darkest pixels in the image were 1, saving the value 0 for nodata masking and the boundary was clipped, using a polygon boundary, to trim off the outer feathering. The image was then optimised for performance by using internal tiling and adding overviews. A full breakdown of these steps is provided in the README.md in the 'Browse and download all data files' link.The merged final image is available in `export\TS_AIMS_Torres Strait-Sentinel-2_Composite.tif`.Source datasets:Complete Great Barrier Reef (GBR) Island and Reef Feature boundaries including Torres Strait Version 1b (NESP TWQ 3.13, AIMS, TSRA, GBRMPA), https://eatlas.org.au/data/uuid/d2396b2c-68d4-4f4b-aab0-52f7bc4a81f5Geoscience Australia (2014b), Seas and Submerged Lands Act 1973 - Australian Maritime Boundaries 2014a - Geodatabase [Dataset]. Canberra, Australia: Author. https://creativecommons.org/licenses/by/4.0/ [license]. Sourced on 12 July 2017, https://dx.doi.org/10.4225/25/5539DFE87D895 Basemap/AU_GA_AMB_2014a/Exclusive_Economic_Zone_AMB2014a_Limit.shpThe original data was obtained from GA (Geoscience Australia, 2014a). The Geodatabase was loaded in ArcMap. The Exclusive_Economic_Zone_AMB2014a_Limit layer was loaded and exported as a shapefile. Since this file was small no clipping was applied to the data.Geoscience Australia (2014a), Treaties - Australian Maritime Boundaries (AMB) 2014a [Dataset]. Canberra, Australia: Author. https://creativecommons.org/licenses/by/4.0/ [license]. Sourced on 12 July 2017, http://dx.doi.org/10.4225/25/5539E01878302 Basemap/AU_GA_Treaties-AMB_2014a/Papua_New_Guinea_TSPZ_AMB2014a_Limit.shpThe original data was obtained from GA (Geoscience Australia, 2014b). The Geodatabase was loaded in ArcMap. The Papua_New_Guinea_TSPZ_AMB2014a_Limit layer was loaded and exported as a shapefile. Since this file was small no clipping was applied to the data.AIMS Coral Sea Features (2022) - DRAFTThis is a draft version of this dataset. The region for Ashmore and Boot reef was checked. The attributes in these datasets haven't been cleaned up. Note these files should not be considered finalised and are only suitable for maps around Ashmore Reef. Please source an updated version of this dataset for any other purpose.CS_AIMS_Coral-Sea-Features/CS_Names/Names.shpCS_AIMS_Coral-Sea-Features/CS_Platform_adj/CS_Platform.shpCS_AIMS_Coral-Sea-Features/CS_Reef_Boundaries_adj/CS_Reef_Boundaries.shpCS_AIMS_Coral-Sea-Features/CS_Depth/CS_AIMS_Coral-Sea-Features_Img_S2_R1_Depth5m_Coral-Sea.shpCS_AIMS_Coral-Sea-Features/CS_Depth/CS_AIMS_Coral-Sea-Features_Img_S2_R1_Depth10m_Coral-Sea.shpMurray Island 20 Sept 2011 15cm SISP aerial imagery, Queensland Spatial Imagery Services Program, Department of Resources, QueenslandThis is the high resolution imagery used to create the map of Mer.World_AIMS_Marine-satellite-imageryThe base image composites used in this dataset were based on an early version of Lawrey, E., Hammerton, M. (2024). Marine satellite imagery test collections (AIMS) [Data set]. eAtlas. https://doi.org/10.26274/zq26-a956. A snapshot of the code at the time this dataset was developed is made available in the 01-data/World_AIMS_Marine-satellite-imagery folder of the download of this dataset.Data Location:This dataset is filed in the eAtlas enduring data repository at: data\custodian\2020-2029-AIMS\TS_AIMS_Torres-Strait-Sentinel-2-regional-maps. On the eAtlas server it is stored at eAtlas GeoServer\data\2020-2029-AIMS.Change Log:2025-05-12: Eric LawreyAdded Torres-Strait-Region-Map-Masig-Ugar-Erub-45k-A0 and Torres-Strait-Eastern-Region-Map-Landscape-A0. These maps have a brighten satellite imagery to allow easier reading of writing on the maps. They also include markers for geo-referencing the maps for digitisation. 2025-02-04: Eric LawreyFixed up the reference to the World_AIMS_Marine-satellite-imagery dataset, clarifying where the source that was used in this dataset. Added ORCID and RORs to the record.2023-11-22: Eric LawreyAdded the data and maps for close up of Mer. - 01-data/TS_DNRM_Mer-aerial-imagery/ - preview/Torres-Strait-Mer-Map-Landscape-A0.jpeg - exports/Torres-Strait-Mer-Map-Landscape-A0.pdfUpdated 02-Torres-Strait-regional-maps.qgz to include the layout for the new map.2023-03-02: Eric LawreyCreated a merged version of the satellite imagery, with no alpha blending so that it can be used in ArcGIS Pro. It is now a single large GeoTiff image. The Google Earth Engine source code for the World_AIMS_Marine-satellite-imagery was included to improve the reproducibility and provenance of the dataset, along with a calculation of the distribution of image dates that went into the final composite image. A WMS service for the imagery was also setup and linked to from the metadata. A cross reference to the older Torres Strait clear sky clear water Landsat composite imagery was also added to the record.本数据集包含托雷斯海峡的大尺寸（A0幅面）可打印地图，共分为6个重叠分区，制图基础为晴朗天空、清澈水体条件下生成的哨兵2号（Sentinel 2）合成影像，以及用于制作上述地图的原始影像。地图内容为该区域的卫星影像，叠加了礁体与岛屿边界及名称，仅标注了较为显著的地物。本数据集还包含珊瑚海阿什莫尔礁与布特礁的矢量地图，因二者与本系列地图的研发讨论背景一致。阿什莫尔礁地图包含环礁平台、礁体边界，以及5米与10米深度的面要素。 本数据集包含上述地图研发过程中使用的全部工程文件，涵盖所有源数据集、所有衍生卫星影像瓦片，以及用于制作地图的QGIS（QGIS地理信息系统）工程文件。其中包含托雷斯海峡区域的无云哨兵2号合成影像，该影像采用alpha混合边缘处理，可用于制作该区域平滑的高分底图。该底图与旧版底图数据集风格一致：托雷斯海峡晴朗天空、清澈水体Landsat 5卫星合成影像（NERP TE 13.1 eAtlas，澳大利亚海洋科学研究所[AIMS]，来源：美国航空航天局[NASA]）。合成影像的大部分数据取自2017-2021年的影像。 **制作方法**：本数据集的哨兵2号底图，通过处理澳大利亚海洋科学研究所海洋卫星影像数据集（World_AIMS_Marine-satellite-imagery，数据下载路径为01-data/World_AIMS_Marine-satellite-imagery）中托雷斯海峡区域的影像生成。首先下载覆盖制图区域的真彩色影像，并复制参考1影像（R1）与参考2影像（R2）用于后续处理。其中R1影像为噪声最低、无云占比最高的影像，R2影像为次优的影像数据集。二者通常均为多日期合成影像。随后通过手动创建的蒙版，将R2影像选择性地与R1影像融合，以获取两者的最优组合，通常可减少R1影像中的部分云伪影。蒙版的创建与融合预览在Photoshop中完成，生成的蒙版保存于01-data/R2-R1-masks路径下。为便于相邻影像的融合，为影像添加了羽化alpha通道。上述蒙版融合与影像羽化边框的处理，通过Python脚本（src/local/03-merge-R2-R1-images.py）结合Pillow库与GDAL库完成。相邻影像融合蒙版通过对原始硬边缘蒙版进行模糊处理生成，以实现相邻影像瓦片的平滑融合。将处理后的影像与参考数据集（礁体边界、专属经济区[EEZ]）加载至QGIS中，用于制作可打印地图。为优化最终地图的匹配效果，对每个影像瓦片进行了小幅亮度调整，以匹配相邻瓦片的色调，该调整在QGIS的影像加载配置中完成。由于每个瓦片由不同日期的影像组合而成（以去除云量），各瓦片间存在色调梯度差异，因此该调整存在一定局限性。此外，哨兵2号传感器因扫描带灵敏度存在细微差异，会导致影像出现垂直方向偏移13度的条纹，该效应未在本影像中进行校正。 **单合并GeoTiff格式影像**：带alpha混合边缘的影像瓦片在QGIS中可正常使用，但在ArcGIS Pro中无法兼容。为使该影像可在不支持alpha混合的工具中使用，将所有瓦片合并并扁平化处理为无alpha通道的单幅大型GeoTiff格式影像。具体流程为：将QGIS中制作的地图渲染为单幅大型图像，该过程通过多个步骤完成以确保流程可管理。随后利用QGIS的Atlas功能，将渲染后的地图切割为20幅1×1度的地理配准PNG图像，该过程已将相邻哨兵2号影像的alpha混合效果固化。再通过GDAL（通过QGIS调用）将PNG图像合并为单幅大型GeoTiff影像，并移除alpha通道。调整影像亮度，使影像中最暗的像素值为1，将像素值0保留用于无数据掩膜，并通过多边形边界裁剪掉外围的羽化区域。最后通过内部瓦片化与添加影像概视图对影像进行性能优化。上述步骤的完整明细可在“浏览并下载所有数据文件”链接对应的README.md文件中查看。合并后的最终影像存储于`exportTS_AIMS_Torres Strait-Sentinel-2_Composite.tif`路径下。 **源数据集** 1. 完整大堡礁（Great Barrier Reef, GBR）岛屿与礁体特征边界，含托雷斯海峡版本1b（NESP TWQ 3.13，AIMS，大堡礁海洋公园管理局[GBRMPA]），来源链接：https://eatlas.org.au/data/uuid/d2396b2c-68d4-4f4b-aab0-52f7bc4a81f5 2. 澳大利亚地质科学局（2014b）：《1973年海洋与淹没土地法——2014年澳大利亚海事边界 地理数据库[数据集]》，堪培拉，澳大利亚：作者。许可协议：https://creativecommons.org/licenses/by/4.0/。数据获取时间：2017年7月12日，DOI：https://dx.doi.org/10.4225/25/5539DFE87D895，底图路径：Basemap/AU_GA_AMB_2014a/Exclusive_Economic_Zone_AMB2014a_Limit.shp。原始数据取自澳大利亚地质科学局（2014a），在ArcMap中加载地理数据库，导出Exclusive_Economic_Zone_AMB2014a_Limit图层为Shapefile格式。由于该文件体积较小，未对数据进行裁剪。 3. 澳大利亚地质科学局（2014a）：《条约——2014年澳大利亚海事边界（AMB）[数据集]》，堪培拉，澳大利亚：作者。许可协议：https://creativecommons.org/licenses/by/4.0/。数据获取时间：2017年7月12日，DOI：http://dx.doi.org/10.4225/25/5539E01878302，底图路径：Basemap/AU_GA_Treaties-AMB_2014a/Papua_New_Guinea_TSPZ_AMB2014a_Limit.shp。原始数据取自澳大利亚地质科学局（2014b），在ArcMap中加载地理数据库，导出Papua_New_Guinea_TSPZ_AMB2014a_Limit图层为Shapefile格式。由于该文件体积较小，未对数据进行裁剪。 4. AIMS珊瑚海特征数据集（2022，草稿版）：本数据集为草稿版本，仅对阿什莫尔礁与布特礁区域进行了校验，数据集中的属性尚未清理。请注意该文件尚未定稿，仅适用于阿什莫尔礁周边的地图制作，其他用途请使用该数据集的更新版本。文件路径： - CS_AIMS_Coral-Sea-Features/CS_Names/Names.shp - CS_AIMS_Coral-Sea-Features/CS_Platform_adj/CS_Platform.shp - CS_AIMS_Coral-Sea-Features/CS_Reef_Boundaries_adj/CS_Reef_Boundaries.shp - CS_AIMS_Coral-Sea-Features/CS_Depth/CS_AIMS_Coral-Sea-Features_Img_S2_R1_Depth5m_Coral-Sea.shp - CS_AIMS_Coral-Sea-Features/CS_Depth/CS_AIMS_Coral-Sea-Features_Img_S2_R1_Depth10m_Coral-Sea.shp 5. 2011年9月20日默里岛15厘米分辨率SISP航空影像，昆士兰州空间影像服务项目，昆士兰州资源部：该高分辨率影像用于制作默里岛（Mer）地图。 6. World_AIMS_Marine-satellite-imagery：本数据集使用的基础影像合成基于Lawrey, E., Hammerton, M. (2024)的早期版本：《海洋卫星影像测试集（AIMS）[数据集]》，eAtlas平台，DOI：https://doi.org/10.26274/zq26-a956。本数据集研发时的代码快照已保存于本数据集下载包的01-data/World_AIMS_Marine-satellite-imagery文件夹中。 **数据存储位置** 本数据集存储于eAtlas持久化数据仓库中，路径为：datacustodian2020-2029-AIMSTS_AIMS_Torres-Strait-Sentinel-2-regional-maps。在eAtlas服务器上的存储路径为：eAtlas GeoServerdata2020-2029-AIMS。 **更新日志** - 2025-05-12：Eric Lawrey 新增Torres-Strait-Region-Map-Masig-Ugar-Erub-45k-A0与Torres-Strait-Eastern-Region-Map-Landscape-A0两幅地图。该系列地图对卫星影像进行了亮度增强，便于地图上文字的识别，同时添加了用于地图数字化地理配准的标记点。 - 2025-02-04：Eric Lawrey 修正了World_AIMS_Marine-satellite-imagery数据集的引用，明确了本数据集使用的数据源。在记录中添加了ORCID与ROR标识符。 - 2023-11-22：Eric Lawrey 新增默里岛特写地图及相关数据： - 01-data/TS_DNRM_Mer-aerial-imagery/ - preview/Torres-Strait-Mer-Map-Landscape-A0.jpeg - exports/Torres-Strait-Mer-Map-Landscape-A0.pdf 更新02-Torres-Strait-regional-maps.qgz工程文件，添加新地图的布局。 - 2023-03-02：Eric Lawrey 制作了无alpha混合的卫星影像合并版本，使其可在ArcGIS Pro中使用，现已转换为单幅大型GeoTiff格式影像。添加了World_AIMS_Marine-satellite-imagery的Google Earth Engine源代码，以提升数据集的可复现性与溯源性，同时计算了最终合成影像使用的影像日期分布。搭建了影像的Web地图服务（WMS），并在元数据中添加了链接。在记录中添加了对旧版托雷斯海峡晴朗天空、清澈水体Landsat合成影像的交叉引用。