遥感与地球物理考古探测数据类型多样,然而各种探测数据因缺少综合管理和分析平台,使综合分析更加困难,从而限制了考古探测技术应用效果。在了解遥感与地球物理考古探测技术的基础上,本文对当前遥感地球物理考古探测数据管理系统进行逻辑和业务需求分析,构建基于ArcGIS Engine开发引擎和Visual Studio 2017平台的遥感与地球物理考古探测数据综合管理系统。系统通过分层次设计功能模块,实现考古探测数据的编辑、解释、分析以及数据之间的交互和管理。实际应用表明,对于遥感地球物理考古探测技术与地理信息技术相结合的思路和研究,能够提升遥感与地球物理考古探测数据的综合分析能力,促进考古探测技术的有效应用。 相似文献
This paper covers spatial and temporal variation in phytoplankton communities and physico-chemical water properties in the cage culture area of Sepanggar Bay, Sabah, Malaysia based on field measurement conducted during July 2005 to January 2006 to study the spatial and temporal variation in phytoplankton communities and physico-chemical water properties of the bay. Phytoplankton samples and water parameters data were collected from five different stations located inside the bay during Southwest, Interseasonal and Northeast monsoons. Forty phytoplankton genera, representatives of 23 families, were found in the study area with a mean abundance of 1.55 ± 1.19 × 106 cells L−1. Most of these genera belong to diatoms (82.17%), Dinoflagellates (17.55%) and cyanobacteria (0.29%). Three genera were found to be dominant (>10%) in phytoplankton abundance and these were Coscinodiscus spp. (36.38%), Chaetoceros spp (17.65%) and Bacteriastrum spp. (10.98%). The most dominant genus was Coscinodiscus spp. which showed high abundance during all monsoons and stations (except Station 3). Among the seven environmental parameters tested in this study, water temperature, pH and suspended sediment concentration were found to be significantly different between monsoons. On the other hand, no significant differences were found between stations for the studied physico-chemical parameters. A clear differences in phytoplankton densities were observed between monsoons and stations with higher mean abundances during interseasonal monsoon (2.40 ± 1.37 × 106 cells L−1) and at station five (2.05 ± 0.74 × 106 cells L−1), respectively. Conversely, the diversity indices, both Shannon–Wiener (H′) and Pielou (J′), showed no significant difference throughout stations and monsoons (except (H′) for monsoons). Analysis of similarity (ANOSIM) results demonstrated temporal differences in phytoplankton community structure with highly diverse phytoplankton assemblage. Through cluster analysis five groups of phytoplankton were attained (at 40% similarity level) though no marked separation of the taxonomic classes pointed towards the constant pattern of the phytoplankton assemblage in the studied area. 相似文献