Understanding the Value of Green Event: A Case Study of Event’s Company

This paper attempts to bring forward the idea of organizing a green event. A case study was conducted at AOS Convention and Events Sdn. Bhd. which is one of event’s company in Kuala Lumpur. Based on active participative observation and semi-structure interview it found that AOS Convention and Events Sdn. Bhd. is very committed to practice green during an event. It also found that the event’s attendees who attended the event were very satisfied with the organizing of event by the event’s organizer. Future researcher is suggested to explore more on the value of organizing a green event. Keywords: Green event; Salue; Sustainable event eISSN: 2398-4287© 2021. The Authors. Published for AMER ABRA cE-Bs by e-International Publishing House, Ltd., UK. This is an open access article under the CC BY-NC-ND license (http://creativecommons.org/licenses/by-nc-nd/4.0/). Peer–review under responsibility of AMER (Association of Malaysian Environment-Behaviour Researchers), ABRA (Association of Behavioural Researchers on Asians/Africans/Arabians) and cE-Bs (Centre for Environment-Behaviour Studies), Faculty of Architecture, Planning & Surveying, Universiti Teknologi MARA, Malaysia. DOI: https://doi.org/10.21834/ebpj.v6iSI4.292

Forest disturbance and regeneration: a mosaic of discrete gap dynamics and open matrix regimes?

Question: Recent research in boreal forest suggests that an ‘open matrix’ model may be more appropriate than the traditional model of spatially discrete gap dynamics for describing forest disturbance and regeneration, but what is the evidence from temperate broad-leaved deciduous forests concerning the prevalence of these alternative models? Location: Semi-natural temperate broad-leaved deciduous forest in southern England. Methods: Multi-temporal LiDAR data were used to monitor the changes in tree canopy height and canopy gaps over a 10-yr period for a 130-ha area of forest. Gap dynamics were characterized by quantifying gap creation, expansion, contraction and closure. By identifying the types and rates of canopy height transitions, areas of gap contraction and closure were attributed to the processes of lateral crown growth or vertical regeneration. Results: Across the study site there was a zonation in canopy and gap properties and their dynamics. Many areas of the forest had the characteristics of open wood-pasture dominated by large, complex gaps being maintained under a regime of chronic disturbance. In these areas, several characteristics of the gap dynamics indicated that regeneration was restricted and this may be attributable to spatially-focused overgrazing by large herbivores. In contrast, other areas were characterized by high, closed canopy forest with small, discrete gaps where gap creation and infill were balanced. Conclusions: At the landscape-scale broad-leaved deciduous forests contain a spatial mosaic of zones, which conform to different models of disturbance and regeneration dynamics; discrete gap dynamics and open matrix regimes are juxtaposed. It is now important to elucidate the abiotic factors and biotic interactions that determine the spatio-temporal distribution of the different regimes and to examine whether such a ‘regime mosaic’ model is applicable in other forest types

Geospatial Technology in Sustainable Cities and Communities: Introduction to the Special Issue

This special issue aims to demonstrate how we could leverage geospatial technology for sustainable cities and communities. Contributions on a wide range of geospatial technologies (e.g., GIS, remote sensing, spatial statistics, photogrammetry, and geomatics) as well as issues addressing better cities and communities for a sustainable future are encouraged. This issue contains selected papers from the 7th International Conference on Geomatics and Geospatial Technology (GGT) 2021, which took place in Kuala Lumpur, Malaysia, on 24th March 2021. The five articles selected for this special issue demonstrate how geospatial technology can be used to create more sustainable cities and communities. The diverse applications of geospatial technology were demonstrated in each manuscript, sending a clear message that geospatial technology goes beyond visualization and incorporates intelligence and analysis to provide you with geospatial solutions

Fusion of airborne LiDAR with multispectral SPOT 5 image for enhancement of feature extraction using Dempster–Shafer theory

This paper presents an application of data-driven Dempster-Shafer theory (DST) of evidence to fuse multisensor data for land-cover feature extraction. Over the years, researchers have focused on DST for a variety of applications. However, less attention has been given to generate and interpret probability, certainty, and conflict maps. Moreover, quantitative assessment of DST performance is often overlooked. In this paper, for implementation of DST, two main types of data were used: multisensor data such as Light Detection and Ranging (LiDAR) and multispectral satellite imagery [Satellite Pour l'Observation de la Terre 5 (SPOT 5)]. The objectives are to classify land-cover types from fused multisensor data using DST, to quantitatively assess the accuracy of the classification, and to examine the potential of slope data derived from LiDAR for feature detection. First, we derived the normalized difference vegetation index (NDVI) from SPOT 5 image and the normalized digital surface model (DSM) (nDSM) from LiDAR by subtracting the digital terrain model from the DSM. The two products were fused using the DST algorithm, and the accuracy of the classification was assessed. Second, we generated a surface slope from LiDAR and fused it with NDVI. Subsequently, the classification accuracy was assessed using an IKONOS image of the study area as ground truth data. From the two processing stages, the NDVI/nDSM fusion had an overall accuracy of 88.7%, while the NDVI/slope fusion had 75.3%. The result indicates that NDVI/nDSM integration performed better than NDVI/slope. Although the overall accuracy of the former is better than the latter (NDVI/slope), the contribution of individual class reveals that building extraction from fused slope and NDVI performed poorly. This study proves that DST is a time- and cost-effective method for accurate land-cover feature identification and extraction without the need for a prior knowledge of the scene. Furthermore, the ability to generate ot- er products like certainty, conflict, and maximum probability maps for better visual understanding of the decision process makes it more reliable for applications such as urban planning, forest management, 3-D feature extraction, and map updating

Mapping for Indoor Walking Environment from Point Clouds by Using Mobile Mapping Systems

Walkability is one of the issues to be addressed in the planning of smart urban cities. Although, there is a substantial amount of studies on outdoor walking pedestrian, limited study has been done to address indoor walkability. Recently, most of the pedestrians are likely to use indoor route than outdoor route to protect themselves from sun and rain as most of the indoor routes are located on the buildings such as shopping mall and rail transit station. Therefore, it important to collect all the relevant information in the indoor building to addressed the walkability issues. The GeoSLAM ZEB REVO scanner is used for its convenience to access narrow space, busy area and complex building structure. This scanner is portable and easy to handle by the operator as it can be attached on the cart or carry it with backpack. The scanner captures the building geometry and facilities and present it in the form of point cloud. Then necessary information can be extracted from the point cloud using point cloud segmentation method. The end user such as town planner can benefit from the final product to design future building with pedestrian-friendly tool to encourage more people to walk. Therefore, it brings impact to the society by providing the healthy lifestyle in addition to reducing the use of private vehicle on the road

Coupling of remote sensing data and environmental-related parameters for dengue transmission risk assessment in Subang Jaya, Malaysia.

In Malaysia, the endemic level of dengue fever (DF) has already changed morbidity indicators, and the magnitude of these incidences in the last few years has surpassed the incidences of all other diseases of compulsory notification. The reasons for the dramatic emergence of DF are complex and not well understood. There are many factors that contribute to the epidemiological conditions that favour viral transmission by the main mosquito vector. This study, therefore, is filling this gap by analysing the impact of dengue incidence at a local (Subang Jaya) scale using environmental factors. Meteorological data and land-use pattern were consolidated using geographic information system (GIS) and its components as an analytical tool. We have shown that weather variables (relative humidity, temperature and precipitation) have significant correlation with DF incidence with seasonal variation. Besides land-use pattern, DF incidence shows the higher distribution in the residential area, followed by commercial and industrial area. This is due to the higher population density in residential area as well as favourable places for the breeding of dengue-carrying Aedes mosquitos created by humans in the residential area, especially one-storey houses. The analysis on the trends of DF incidence towards various housing types indicate that most of the victims’ houses fall into interconnection houses and mixed houses types compared to the independent houses area. The outcome driven from this analysis suggested that each character of the environmental factors has their own risk towards dengue incidence. In line with that, it is possible to develop a dynamic model of DF transmission using the knowledge produced by this comprehensive time series data and the results provided by the different analyses

Functional relation of land surface albedo with climatological variables: a review on remote sensing techniques and recent research developments

Surface albedo has been documented as one of the Essential Climate Variables (ECV) of the Global Climate Observing System (GCOS) that governs the Earth's Radiation Budget. The availability of surface albedo data is necessary for a comprehensive environmental modelling study. Thus, both temporal and spatial scale issues need to be rectified. This study reports about the availability of surface albedo data through in-situ and remote sensing satellite observations. In this paper, we reviewed the existing models for surface albedo derivation and various initiatives taken by related environmental agencies in order to understand the issues of climate with respect to surface albedo. This investigation evaluated the major activities on albedo-related research specifically for the retrieval methods used to derive the albedo values. Two main existing albedo measurement methods are derived through in-situ measurement and remotely sensed observations. In-situ measurement supported with number of instruments and techniques such aspyrheliometers, pyranometers and Baseline Surface Radiation Network (BSRN) and remotely sensed observations using angularly integrated Bi-directional Reflectance Distribution Function (BRDF) by both geostationary and polar orbit satellites. The investigation results reveals that the temporal and spatial scaling is the major issues when the albedo values are needed for microclimatic study, i.e. high-resolution time-series analyses and at heterogeneity and impervious surface. Thus, an improved technique of albedo retrieval at better spatial and temporal scale is required to fulfil the need for such kind of studies. Amongst many others, there are two downscaling methods that have been identified to be used in resolving the spatial scaling biased issues: Smoothing Filter-based Intensity Modulation (SFIM) and Pixel Block Intensity Modulation (PBIM). The temporal issues can be resolved using the multiple regression techniques of land surface temperature, selected air quality parameters, aerosol and daily skylight

Integration of GIS-Based Model with Epidemiological data as a Tool for Dengue Surveillance

This study aims to fully integrated and validated spatial temporal statistical model using epidemiological data as a predictive model for surveillance and control of DF cases. Kernel-density estimation (KDE) method was carried out by using spatial union analysis in order to predict and visualize the DF hotspot area by monthly basis in the Subang Jaya area. The generated maps were then verified using Receiver operating characteristics (ROC) was performed to validate the DF hotspot simulation model. Spatial analysis showed that the dengue epidemics in Subang Jaya were spatially dependent. This analysis demonstrated spatial clustering of dengue activity which can facilitate prediction of the magnitude, timing and location of future dengue epidemic. The model developed highlights the adaptation capabilities of the approach where the accuracy assessment result showed accuracy about 60% agreements between the hotspot map and the actual DF location data. It can thus be suggested that any future population increase will be associated with increased DF risk in areas which already accommodate this disease environmentally, climatically and socioeconomically. Future risk could be modelled using the same methods. This would help decision maker in choosing which areas should be under intensive treatment to counter mosquito breeding and reduce prevalence of DF

Effective Building Surveying Using Laser Scanning for Heritage Building Documentation

In conservation works, a thorough pathology survey is required to identify building defects. Early detection of defects can prevent the increase in cost during conservation works. Conventionally, common defects that occur in heritage buildings can be observed and recorded during a walk-by inspection; however, the process is often time consuming. Furthermore, all recorded defects require a precise but conventional data collection to identify, test, and observe the level of defects. This study aims to compare the effectiveness of manual walk-in building condition assessment with the point cloud data analysis that utilises the Light Detection and Ranging (LiDAR) technology. A building condition assessment was conducted involving the Ipoh Town Hall and Post Office, Galeri Kraftangan Seremban, and Bangunan Dato’ Jaafar in Johor Bahru using both conventional walk-in survey and the laser scanning process. This study concludes that combining digital tools with the traditional methods promotes a more accurate and effective assessment for heritage building assessment, which is crucial for ensuring the sustainability of historic structures. Additionally, 3D point cloud data allows the exploration of building deterioration from a wider perspective