Fuyuan Liang

Holocene stalagmite δ18O records in the East Asian monsoon region and their correlation with those in the Indian monsoon region

We compare well-dated Holocene stalagmite δ18O records from the East Asian Summer Monsoon (EASM) region and from the Indian Summer Monsoon (ISM) region. We found that the pattern of latitudinal change of speleothem δ18O values from the Indian monsoon region to the East Asian monsoon region is almost identical to that of modern precipitation. This suggests that the modern moisture transport route from the Indian Ocean to the East Asian monsoon region has existed since at least the early Holocene. The δ18O records from both regions exhibit a remarkably similar trend of variation in that the values are more negative during the early Holocene, rapidly become heavy from the mid-Holocene, and are heaviest during the late Holocene. The stalagmite δ18O changes in the East Asian monsoon region are statistically well correlated with those in the Indian monsoon region, both over the entire Holocene and in detail over the last 2000 years. However, in contrast to the obvious consistency of the δ18O values in all of the speleothem records, both instrumental and historical climate records indicate significant spatial variations in rainfall over eastern China. The early-Holocene strong EASM pattern referred from speleothem δ18O in the East Asian monsoon region is quite different to that of other paleoclimatic records such as Holocene paleosol development in the Chinese Loess Plateau, eolian activity in the northern Chinese sandlands, and lake sediments in EASM-dominated region in China, in which the strongest EASM was documented during the mid-Holocene. These findings suggest that the speleothem δ18O record from the East Asian monsoon region may not record EASM variability, but rather that it is controlled by variations in the isotopic composition of precipitation, which is determined mainly by rainfall variability in the ISM region.

A k-d tree-based algorithm to parallelize Kriging interpolation of big spatial data

Parallel computing provides a promising solution to accelerate complicated spatial data processing, which has recently become increasingly computationally intense. Partitioning a big dataset into workload-balanced child data groups remains a challenge, particularly for unevenly distributed spatial data. This study proposed an algorithm based on the k-d tree method to tackle this challenge. The algorithm constructed trees based on the distribution variance of spatial data. The number of final sub-trees, unlike the conventional k-d tree method, is not always a power of two. Furthermore, the number of nodes on the left and right sub-trees is always no more than one to ensure a balanced workload. Experiments show that our algorithm is able to partition big datasets efficiently and evenly into equally sized child data groups. Speed-up ratios show that parallel interpolation can save up to 70% of the execution time of the consequential interpolation. A high efficiency of parallel computing was achieved when the datasets were divided into an optimal number of child data groups.

A representation framework for studying spatiotemporal changes and interactions of dynamic geographic phenomena

This research presented a framework to track and query spatiotemporal changes and interactions of dynamic geographic phenomena. The framework organized information of dynamic phenomena as a hierarchy of static structures, processes, and scenarios. Static structures of a dynamic phenomenon at its different evolution stages were described by its corepoint, footprint border, and composite border, which were extracted from time series remote sensing images. Time series static structures of a phenomenon were then grouped into processes to show its changes over space and time. Scenarios were used to describe a collection of interacting processes in space. We expanded the identity-based change (IBC) model by adding more primitives and operations to represent semantics of these changes and interactions. A geographic information system (GIS) database was built by integrating the expanded IBC model with our spatiotemporal framework. As demonstrated by a case study of ocean eddies in the South China Sea (SCS), query results of the behaviors and relationships of ocean eddies from the GIS database help us better understand their development and evolution, demonstrating the usefulness of this spatiotemporal framework. Spatial and semantic queries about a specific eddy from the database can further efficiently present its lifetime dynamic changes and all other eddies that interacted with it.

Integration of case-based reasoning and object-based image classification to classify SPOT images: a case study of aquaculture land use mapping in coastal areas of Guangdong province, China

We present a method to integrate case-based reasoning (CBR) with object-oriented image classification to classify SPOT images. Images were first segmented into discrete objects at multiple scales. CBR was then used to classify these objects by comparing their geometric shapes, spectral characteristics, and textural measurements with those of the past objects prepared from archived SPOT images and land use data. Once enough past objects were accumulated, this method was able to successfully classify image objects with promising results as demonstrated by a case study of aquaculture land use mapping in coastal areas of Guangdong province, China.

Stalagmite multi-proxy evidence of wet and dry intervals in northeastern Namibia: Linkage to latitudinal shifts of the Inter-Tropical Convergence Zone and changing solar activity from AD 1400 to 1950

Multiple proxies using variation in δ18O, δ13C, mineralogy, and petrography in a newly generated high-resolution record of Stalagmite DP1 from Dante Cave indicate a linkage between changes in hydroclimate in northeastern Namibia and changes in solar activity and changes in global temperatures. The record suggests that during solar minima and globally cooler conditions (ca. 1660–1710 and ca. 1790–1830), wetter periods (reflecting longer summer seasons) in northeastern Namibia were linked to advances of the Inter-Tropical Convergence Zone (ITCZ) and the Inter-Ocean Convergence Zone (IOCZ) southwestward. A slight southward push of the Angola–Benguela Front (ABF) during such intervals could also be expected, bringing more rainfall inland. On the other hand, drier and warmer periods in northeastern Namibia, inferred from the increasing δ18O trend in Stalagmite DP1 after AD 1715, coincide with globally warmer conditions, and thus a northeastward migration of the ITCZ, specifically with more warming of the Northern Hemisphere (NH). This finding agrees with reducing precipitation observed in the summer rainfall zone of southern Africa since ca. 1900. Therefore, predictions of warming in high-latitude regions of the NH in the next century should suggest that the presently semi-arid climate of northern Namibia may become even drier.

Automatic Identification of Oceanic Multieddy Structures From Satellite Altimeter Datasets

Very few of current eddy detection algorithms are capable of identifying multieddy structures resulted from interactions among eddies. In this study, we improve our previous hybrid detection (HD) algorithm by incorporating a new criterion to better identify multieddy structures from satellite altimeter data. The criterion defines an aspect ratio to determine if eddies have vortex overlaps and, as such, result in a composite structure of multiple eddies (a.k.a. multieddy structures). Compared with two previous studies on observed eddy-eddy interactions in eddy mergers from altimeter data, the improved HD algorithm not only successfully captures multieddy structures but also shows how eddies interact and evolve, including merging, splitting, and partial vorticity exchange. Tests of the improved HD algorithm on a series of sea-level anomaly maps in the South China Sea (SCS) from 1993 to 2012 show that single eddies, in contrast to eddies with composite structures, appear more concentrated in northwest of the Luzon and southeast of Vietnam. Tracking dual-eddy structures reveals several processes of eddy interactions in the SCS. The study demonstrates the potential value of the new HD algorithm in helping scientists to investigate characteristics of eddy-eddy interactions from satellite observations.

Mesoscale oceanic eddies in the South China Sea from 1992 to 2012: evolution processes and statistical analysis

Automated identification and tracking of mesoscale ocean eddies has recently become one research hotspot in physical oceanography. Several methods have been developed and applied to survey the general kinetic and geometric characteristics of the ocean eddies in the South China Sea (SCS). However, very few studies attempt to examine eddies’ internal evolution processes. In this study, we reported a hybrid method to trace eddies’ propagation in the SCS based on their internal structures, which are characterized by eddy centers, footprint borders, and composite borders. Eddy identification and tracking results were represented by a GIS-based spatiotemporal model. Information on instant states, dynamic evolution processes, and events of disappearance, reappearance, split, and mergence is stored in a GIS database. Results were validated by comparing against the ten Dongsha Cyclonic Eddies (DCEs) and the three long-lived anticyclonic eddies (ACEs) in the northern SCS, which were reported in previous literature. Our study confirmed the development of these eddies. Furthermore, we found more DCE-like and ACE-like eddies in these areas from 2005 to 2012 in our database. Spatial distribution analysis of disappearing, reappearing, splitting, and merging activities shows that eddies in the SCS tend to cluster to the northwest of Luzon Island, southwest of Luzon Strait, and around the marginal sea of Vietnam. Kuroshio intrusions and the complex sea floor topography in these areas are the possible factors that lead to these spatial clusters.

A quantitative morphometric comparison of cockpit and doline karst landforms

This study presented a quantitative comparison of cockpit and doline karst by examining the numbers and characteristics of typical types of landform entities that are developed in Guilin (Guangxi, China), La Alianza (PR, USA), Avalton (KY, USA), and Oolitic (IN, USA). Five types of landform entities were defined: isolated hill (IH), clustered hills (CHs), isolated sinkhole (IS), clustered sinkholes (CSs), and clustered hills with sinkholes (CHSs). An algorithm was developed to automatically identify these types of landform entities by examining the contour lines on topographic maps of two cockpit karst areas (Guilin and La Alianza) and two doline karst areas (Oolitic and Avalton). Within each specific study area, the CHSs is the least developed type yet with a larger size and higher relief. The IH and IS entities are smaller in size, lower in relief, and outnumber their clustered counterparts. The total numbers of these types of entities are quite different in cockpit and doline karst areas. Doline karst is characterized by more negative (IS and CSs) than positive (IH and IHs) landforms and vice versa for cockpit karst. For example, the Guilin study area has 1192 positive landform entities in total, which occupy 9.81% of the total study area. It has only 622 negative landform entities occupying only 3.91% of the total study area. By contrast, the doline karst in Oolitic has 130 negative while only 10 positive landform entities. The positive and negative landforms in Oolitic occupy 12.68% and 2.61% of the total study area, respectively. Furthermore, average relief and slope of the landform entities are much higher and steeper in the cockpit karst than the doline karst areas. For instance, the average slope of CHs in Alvaton is 3.90 degrees while it is 19.78 degrees in La Alianza. The average relief of CSs is 4.07 m and 34.29 m in Oolitic and Guilin respectively. Such a difference within a specific area or between the cockpit and doline karst may reveal different controls on the development of karst landscape.

A Gaussian-surface-based approach to identifying oceanic multi-eddy structures from satellite altimeter datasets

This study presents a Gaussian-surface-based approach to identifying multi-eddy structures from the sea level anomaly (SLA) maps. The SLA signals of an eddy are modeled by a two-dimensional anisotropic Gaussian surface. An identification criterion is introduced to determine whether to retain or split a multi-eddy structure. Detection result of a three-eddy structure from the SLA in the South China Sea (SCS) demonstrates the effectiveness of the identification approach. Comparison with a merger event previously reported about a multi-eddy structure in northern SCS reveals the advantage of this approach over simple splitting strategy, which may lose the eddy-eddy interaction details conveyed by real multi-eddy structures.

Floor Area Ratio extraction based on Airborne Laser Scanning data over urban areas

Floor Area Ratio (FAR) is an important indicator in urban planning and other urban applications, therefore, it is of great significance to acquire FAR of the functional areas in the city. Traditional method to acquire FAR is slow and of low efficiency. FAR calculation by remote sensing methods can overcome these shortcomings above, so many scholars in recent years concerns about it. But methods through aerial photography or satellite optical images are of low accuracy and much manual intervention is needed. Airborne Laser Scanning remote sensing is a new three-dimensional information acquisition means in the urban areas. This paper presents a new method to calculate FAR using Airborne Laser Scanning Data. Experiment shows that this method can get a high rate of accuracy without a lot of human intervention.