Mesoscale surface circulation and variability of Southern Indian Ocean derived by combining satellite altimetry and drifter observations

High resoultion Eulerian mean velocity field has been derived by combining the satellite tracked surface drifter data with satellite altimetry and ocean surface winds. The drifter data used in this study includes Argos and surface drifter data from Global Drifter Program. Maps of Sea Level Anomaly （MSLA） weekly files with a resolution of （1/3）° in both Latitude and Longitude for the period 1993-2012 have been used. The Ekman current is computed using ocean surface mean wind fields from scatterometers onboard ERS 1/2, Quikscat and ASCAT. The derived mean velocity field exhibits the broad flow of Antarctic Circumpolar Current with speeds up to 0.6 m/s. Anomalous field is quite significant in the western part between 20~ and 40~E and in the eastern part between 80~E and 100~E with velocity anomaly up to 0.3 m/s. The estimated mean flow pattern well agrees with the dynamic topography derived from in-situ observations. Also, the derived velocity field is consistent with the in-situ ADCP current measurements. Eddy kinetic energy illustrates an increasing trend during 1993-2008 and is in phase coherence with the Southern Annular Mode by three month lag. Periodic modulations are found in the eddy kinetic energy due the low frequency Antarctic Circumpolar Wave propagation.

Modelling the Violation of Restrictions Pertaining to Deforestation in a Given Land Right

This paper develops a model that could be used to visualize and predict the violation of restrictions in a given forest. The violation of restriction in this case is assumed to be the difference in areal extent between two forest cover scenes with time;termed “deforestation”. It analyses the relationship in forest cover changes overtime in Ganye Forest Reserve and Glide Cross Country Farm in Adamawa state, Nigeria. Cadastral maps of the forest reserve and farmland were used as the base maps, while the satellite images served as the spatio-temporal data. Landsat ETM+ images of 2003, 2008 and 2013 were used to identify, determine and estimate the violation of restrictions. The result shows that the violation of restrictions could be reliably determined for both the forest reserve and farmland and forecast made in order to predict future occurrence. It also revealed a continuous deforestation in the forest reserve, while in the farmland regeneration of forest stock was noticed. This information is very vital for forest management, planning and decision making in a viable land administration domain.

Recent snow cover variation in the Upper Indus Basin of Gilgit Baltistan, Hindukush Karakoram Himalaya

Mountainous basins like the Upper Indus Basin(UIB) of Gilgit Baltistan(GB) are dependent on seasonal snowmelt and glacier melt. Monitoring of the snow-covered area(SCA) is not only vital for the overall hydrology of the Indus basin but also important to the sustainable agriculture and hydropower system. The snow-covered area in the UIB of GB was investigated for changes over the last 18 years using the Moderate Resolution Imaging Spectroradiometer(MODIS) snow product. The study area was divided into five elevation zones ranging from 877-8564 meters above sea level(m ASL). In contrast to the global cryosphere related studies, SCA in the UIB is slightly increasing. Elevation based SCA analysis also indicated that SCA is slightly increasing in each elevation zone. However, a significant amount of snow is concentrated in areas above 5000 m ASL. Due to the strong correlation between SCA and precipitation, the precipitation data also follow a similar trend. Analysis of the climatic data suggests a statistically significant increase in total monthly precipitation and relative humidity, a slight decrease in mean monthly temperature and a significant upward tendency in monthly solar irradiance data. All these trends in combination with the increasing trend in global precipitation, winter westerly disturbances and orographic precipitation are the important factors behind the slightly increasing SCA in the study area. Our results though constrained by short observation period mainly contribute to the understanding of advancing snow cover and glaciers in Hindukush Karakoram.

Temporal Three-Dimensional Ontology for Geographical Information Science (GIS)—A Review

While the use of three-dimensional (3D) geographical information system (GIS) is becoming in rapid development and being used in various fields such as urban and regional planning, disaster management and planning, mobile navigation and etc., commercial and open source GIS software packages tend to offer 3D-GIS functionalities for their products. On the basis, GIS analysis functions are to provide information with respect to geographical location and by having 3D spatial data as an input, it will give advantages in providing horizontal position information. However, to analyze moving objects (temporal) in 3D seems not an easy task and not fully supported by current GIS platform packages. Previously in two-dimensional (2D) GIS practice, main issue addressed by researchers in managing temporal spatial objects is GIS packages were designed based on hardware and software constraints whereby it should be based on the temporal spatial objects ontology. Nowadays, the trend of managing temporal 3D data is via 3D spatial simulation or animation. This approach will not in assistance for GIS users in conducting spatial queries. Without having a suitable ontology and valid topological data structure for temporal 3D data, it will cause repetitive of temporal data (redundancy) and complications in executing spatial analysis in 3D environment. Therefore this paper focuses on the ontology for managing moving 3D spatial objects (i.e. air pollution, flood). The characteristics of moving objects were reviewed thoroughly by categorizing it based on its different appearances. Moreover, existing methods in managing temporal database were addressed and discussed for its practicalities. Another important aspect in managing temporal 3D objects is the implementation of topological data structures for 3D spatial objects were reviewed. In the last section of this paper it summarized the issues and further ideas towards implementing and managing temporal 3D spatial objects in GIS based on the Geoinformation Ontology (GeO).

A review of remote sensing applications for oil palm studies

Oil palm becomes an increasingly important source of vegetable oil for its production exceeds soybean,sunflower,and rapeseed.The growth of the oil palm industry causes degradation to the environment,especially when the expansion of plantations goes uncontrolled.Remote sensing is a useful tool to monitor the development of oil palm plantations.In order to promote the use of remote sensing in the oil palm industry to support their drive for sustainability,this paper provides an understanding toward the use of remote sensing and its applications to oil palm plantation monitoring.In addition,the existing knowledge gaps are identified and recommendations for further research are given.

Generalization of buildings within the framework of CityGML

For a better visual impression,3D information systems and architecture need detailed,photo-realistic visualization of 3D data-sets.However,easy accessibility with efficient rendering becomes difficult due to the detailed data associated with 3D objects.Therefore,different applications demand different levels of detail(LoD).Currently,City Geography Markup Language(CityGML),as the Open Geospatial Consortium standard,is being used to model and represent buildings in different LoDs(LoD0–LoD4),but it does not provide methods to generate different LoDs automatically.Thus,generalized(abstracted)3D scenes of buildings need to be generated to fulfill the demands of task-specific applications by reducing data volume.This paper discusses various ways to generalize building models,within the framework of CityGML,reducing the level of detail from higher LoD to lower.The LoD4 data is parsed and analyzed.Various heuristics are applied to simplify the ground plan and the results are then aggregated.The minimum length of an edge for simplification is restricted to the CityGML generalization specifications provided and is characterized by differing accuracies and minimal dimensions of objects for LoD1 and LoD2.This could maintain the accuracy of generalized objects and avoid the elimination or merging of important features.Second,the heights of the walls of the simplified ground plans are raised with the aim to construct simplified 3D building models.Algorithms for simplification and aggregation aiming to derive LoD2 and LoD1 are implemented and tested on a number of buildings of Putrajaya,Malaysia.The experiment results show that the minimum length of edges to be simplified is inversely proportional to the size of generalized models.

Mapping frequent spatio-temporal wind profile patterns using multi-dimensional sequential pattern mining

Holistic understanding of wind behaviour over space,time and height is essential for harvesting wind energy application.This study presents a novel approach for mapping frequent wind profile patterns using multidimensional sequential pattern mining(MDSPM).This study is illustrated with a time series of 24 years of European Centre for Medium-Range Weather Forecasts European Reanalysis-Interim gridded(0.125°×0.125°)wind data for the Netherlands every 6 h and at six height levels.The wind data were first transformed into two spatio-temporal sequence databases(for speed and direction,respectively).Then,the Linear time Closed Itemset Miner Sequence algorithm was used to extract the multidimensional sequential patterns,which were then visualized using a 3D wind rose,a circular histogram and a geographical map.These patterns were further analysed to determine their wind shear coefficients and turbulence intensities as well as their spatial overlap with current areas with wind turbines.Our analysis identified four frequent wind profile patterns.One of them highly suitable to harvest wind energy at a height of 128 m and 68.97%of the geographical area covered by this pattern already contains wind turbines.This study shows that the proposed approach is capable of efficiently extracting meaningful patterns from complex spatio-temporal datasets.