Darwin Harbour Habitat Mapping Program: Backscatter entropy

This resource contains a GLCM (Grey-Level Co-occurrence Matices) entropy grid of the backscatter data for the greater Darwin Harbour region as part of a baseline seabed mapping program of Darwin Harbour and Bynoe Harbour. This project was funded through offset funds provided by an INPEX-led Ichthys LNG Project to the Northern Territory Government’s Department of Environment and Natural Resources (NTG-DENR) with co-investment from Geoscience Australia (GA) and the Australian Institute of Marine Science (AIMS). The intent of this program is to improve knowledge of the marine environments in the Darwin and Bynoe Harbour regions by collating and collecting baseline data that enable the creation of thematic habitat maps and information to underpin marine resource management decisions. The GLCM (Grey-Level Co-occurrence Matices) entropy grid of the backscatter data was derived from a compilation of multiple surveys undertaken by GA, AIMS and NTG-DENR between 2011 and 2017, including GA0333 (Siwabessy et al., 2015), GA0341 (Siwabessy et al., 2015), GA0351/SOL6187 (Siwabessy et al., 2016), GA4452/SOL6432 (Siwabessy et al., 2017), GA0356 (Radke et al., 2017), and GA0358 and GA0359 (Radke et al., 2018), adding to those from a previous survey GA0333 collected by GA, AIMS and NTG-DENR. Entropy measures the disorder or complexity of an image. The entropy is large when the image is texturally complex.

本数据集包含大达尔文港区域后向散射数据的灰度共生矩阵（Grey-Level Co-occurrence Matices, GLCM）熵栅格，该成果是达尔文港与拜诺港海底底质基线测绘项目的组成部分。本项目由INPEX牵头的伊契斯液化天然气（Ichthys LNG）项目拨付补偿资金资助至北领地政府环境与自然资源部（NTG-DENR），并由澳大利亚地球科学局（Geoscience Australia, GA）与澳大利亚海洋科学研究所（Australian Institute of Marine Science, AIMS）共同参与投资。本项目的核心目标是通过整理与采集基线数据，深化对达尔文港及拜诺港海域海洋环境的认知，此类基线数据可用于生成专题生境地图与相关信息，为海洋资源管理决策提供坚实支撑。本次研究中的后向散射数据灰度共生矩阵熵栅格，源自2011年至2017年间GA、AIMS与NTG-DENR开展的多份勘测数据汇编，涵盖GA0333（Siwabessy等，2015）、GA0341（Siwabessy等，2015）、GA0351/SOL6187（Siwabessy等，2016）、GA4452/SOL6432（Siwabessy等，2017）、GA0356（Radke等，2017）以及GA0358与GA0359（Radke等，2018），同时纳入了此前由GA、AIMS与NTG-DENR完成的GA0333勘测数据。熵用于衡量图像的无序程度与复杂度，当图像纹理复杂度较高时，熵值也会更大。