Reclassifying forest type to a new forest class based on vegetation and lithology characteristics using geographic information system at southern Johore, Malaysia

Recently forest resources management with regard to precision forestry concept has been highlighted by forest managers, in order to fulfill the demand on quality and reliable information about forest area. According to the Malaysian National Forestry Act 1984, forest is classified into several types by general classification which is based on vegetation types broadly into dipterocarp forest, peat swamp forest and mangrove forest. In applying precision forestry approach, details classification and information are required to render more accurate about managed forest. Therefore, this study was carried out to reclassify forest type to a new forest class based on vegetation and lithology characteristic using GIS technique. Ten new classes were successfully generated and mapped by fusing layer of forest vegetation types and lithology layer in Southern Johore, namely Dipterocarp-Igneous, Dipterocarp-Sediment, Dipterocarp-Alluvial, Peat-Igneous, Peat-Sediment, Peat-Alluvial, Mangrove-Igneous, Mangrove-Sediment, Mangrove-Alluvial and Limestone forest. In this study, Syzygium spp. (19.83 %) was found in abundance in two new forest classes; Dipterocarp-Igneous and Dipterocarp-Sediment forest in Hulu Sedili Permanent Forest Reserve (PFR). Beside that, Elateriospermum tapos (9.92 %) and family of Lauraceae (7.22 %) were found to be the most dominant species in the Dipterocarp-Sediment forest, while Macaranga spp. (11.21 %) and Elateriospermum tapos (11.02 %) found dominant in Dipterocarp-Igneous forest. From the sample plot, Dipterocarpaceae family constituted only 3.09 % whereas the non-Dipterocarpaceae family was 96.91 %. Hence, this study indicated that there is variation in species dominancy at different lithology of the same forest vegetation site

Antioxidative properties and proximate analysis of spent coffee ground (SCG) extracted using ultrasonic-methanol assisted technique as a potential functional food ingredient

Spent coffee ground (SCG) produced in tons by restaurants and cafeterias and domestic consumers is a potentially good source of natural antioxidants because it contains substantial amounts of bioactive compounds. The purpose of this study was to identify the physicochemical and antioxidant properties of three different types of spent coffee ground (SCG), namely Robusta, Arabica and Liberica extracted using ultra-sonicmethanol assisted technique. DPPH, FTC, TBA, total phenolic content (TPC) and total flavonoid content (TFC) were used to measure the antioxidant properties. Robusta SCG exhibited the highest DPPH inhibition 41.63±0.04%), FTC (60.42±0.03%) and TBA analysis (73.09±0.08%). The total phenolic compounds in the samples varied widely ranging from 18.94±0.06 to 26.23±0.86 mg GAE/g sample, with Robusta SCG showing the highest value among the three, while Arabica SCG depicted the highest amount total flavonoid content (47.62±0.05 to 56.20±0.08). A strong correlation between antioxidant activity and total phenolic content were observed in this study. Compared to Arabica and Liberica SCGs expended, Robusta SCG demonstrated a stronger beneficial effect against lipid peroxidation. This study reveals that SCGs can be regarded as a new useful source of natural antioxidant with a view to increasing the use of antioxidant synthetics by using the ingredient of agro-industrial residues in food production especially ingredients for functional food

Field assessments of above ground biomass (AGB) of mangrove stand in Merbok, Malaysia

Mangroves are considered as unique and important ecosystems that occupy an intertidal zone of protected shorelines. The halophytic plants present in mangroves provide support not only for social economic needs but also for ecological roles which include carbon sinks. Above ground biomass (AGB) of mangroves was estimated in mangrove stands in Merbok, Kedah. Field data collection was conducted from January 2013 to May 2013. A total of 25 sites measuring 100 m x 100 m were surveyed in the study area. Within randomly selected plots, diameter at breast height (DBH), tree height and crown width were measured. Mangrove trees were identified at the species level. Published allometric functions were used to compute the AGB of mangroves. Rhizophoraapiculata was found to be the most abundant species followed by Bruguieraparviflora, Bruguieragymnorrhiza and Avicennia marina. An overall mean for AGB in study area was estimated to be 176 Mg/ha. From the analysis of variance (ANOVA), it was found that there is a significant different in the means of all mangrove variables measured between four mangrove species (p <0.0001). Positive relationships were found between DBH, height and crown width and AGB with r values of 0.88, 0.43 and 0.81 respectively. The subsequent analysis will involve a study of relationships between mangrove stand attributes with spectral radiance recorded from remote sensing

Aquatic insects assemblage in Penang Botanic Garden

This study investigated the diversity of aquatic insects as well as the chemical parameters of Sungai Air Terjun that runs in Penang Botanic Garden. Aquatic insects and chemical parameters of river were studied from April 2013 until January 2014. A total of twenty specimens were collected monthly using D and rectangular net following kick-net sampling technique. A total of 2966 individuals from 48 families of seven orders of aquatic insects were collected. The most abundant aquatic insects were recorded in July 2013 with 566 individuals from 44 genera, while the least abundant was in May 2013 with 156 individuals from 31 genera. The Diptera (996 individuals), Trichoptera (689 individuals) and Ephemeroptera (327 individuals) were very rich and diverse in this river during all the sampling months. This study provides a current situation of aquatic insect’s community and river condition of Sungai Air Terjun, Penang Botanic Garden

Evaluating supervised and unsupervised techniques for land cover mapping using remote sensing data

Several methods exist for remote sensing image classification. They include supervised and unsupervised approaches. Accuracy assessment of a remote sensing output is a most important step in classification of remotely sensed data. Without accuracy assessment the quality of map or output produced would be of lesser value to the end user. However, supervised and unsupervised techniques show different levels of accuracy after accuracy assessment was conducted. This paper describes a study that was carried out to perform supervised and unsupervised techniques on remote sensing data for land cover classification and to evaluate the accuracy result of both classification techniques. The study used SPOT 5 satellite image taken on January 2007 for 270 / 343 (path / row) as a primary data and topographical map and land cover maps as supporting data. The land cover classes for the study area were classified into 5 themes namely vegetation, urban area, water body, grassland and barren land. Ground verification was carried out to verify and assess the accuracy of classification. A total of 72 sample points were collected using Systematic Random Sampling. The sample point represented 25% of the total study area. The results showed that the overall accuracy for the supervised classification was 90.28% where Kappa statistics was 0.86, while the unsupervised classification result was 80.56% accurate with 0.73 Kappa statistics. In conclusion, this study found that the supervised classification technique appears more accurate than the unsupervised classification

Developing priorities and ranking for suitable forest road allocation using Analytical Hierarchy Process (AHP) in Peninsular Malaysia

In hilly forest area, aligning forest roads is the key towards an effective and sustainable forest management. Constraints in forest road planning are mainly due to environmental factors and topographical conditions. Selecting the criteria for planning forest road and setting the priorities, ranking them for environmental sustainability and reduce cost in road construction is important. Different criteria are required at different forest area since the quantifiable relationship between cause and effect to meet the goal are not comprehensively prioritized. In order to solve the problem, the relative importance factor from multi criteria basis, namely Analytic Hierarchy Process (AHP) was applied. Therefore, the objective of this study was to develop priorities and rank a selected criterion for planning forest road in hilly area using AHP approach. Four criteria had been identified to meet the goal of suitable forest road allocation namely slope, river crossing, elevation and existing forest road. The suitable criteria selected were sorted with weight in ranking order to minimize the impact of timber harvesting. Our results showed that the priorities and ranking were as follows; slope (w = 0.558), followed by river crossing (w = 0.303), elevation (w = 0.095) and lastly existing forest road (w = 0.044), respectively. Therefore, the relative preference factor developed in this study can be used by the Forestry Department for formulating suitable forest road allocation in hilly area simultaneously to be integrated with geographic information system technology

Remote Sensing For Mapping Ramsar Heritage Site At Sungai Pulai Mangrove Forest Reserve, Johore, Malaysia

The Sungai Pulai Mangrove Forest Reserve (SPMFR) is the largest riverine mangrove system in Johore State. In 2003 about 9,126 ha of the Sungai Pulai mangrove was designated as a RAMSAR site. RAMSAR sites are wetland areas that are deemed to have international importance and are included in the List of Wetlands of International Importance. The SPMFR playa significant role for socio-economic to the adjacent 38 villages. The villagers depends on the estuary as its mudflats, an ideal feeding, spawning and fattening ground, support a significant proportion of fish species. Other mangrove uses include wood cutting, charcoal production, aquaculture activities and eco-tourism. The current development of Iskandar Development Region (IDR) and construction of a new port at the river estuary may represent a direct impact on the mangrove ecosystem, causing shorelines erosion and water pollution from associated reclamation and dredging works. However the conservation management of the site is managed in line with Integrated Management'Plan for the sustainable use of mangroves in Iohor state. Satellite remote sensing'is a useful source of information as it provides timely and complete coverage for vegetation mapping especially in mangroves where the access is difficult. This study was carried out to identify and map land cover types using SPOT 4 image in the Sungai Pulai-RAMSAR site and its surrounding areas. Unsupervised classification technique has produce eight classes of land cover type over the study site. Ground verification was carried out to verify and assess the accuracy of classification. The results showed that approximately 90% of the area was classified correctly. Vegetation density was classified into five levels namely very high, high, medium, low and very low based on crown density scale. The study concludes that SPOT 4 was capable to discriminate mangrove area clearly from other land covers type, meanwhile vegetation indices model can be used as a tool for mapping vegetation density level in the SPMFR and its surrounding area. Results clearly showed usefulness of remote sensing for monitoring, management and development of mangrove forest for sustainable management and preserve the SPMFR as a RAMSAR site in Peninsular Malaysia

Bees algorithm for Forest transportation planning optimization in Malaysia

Algorithm is widely used in various areas due to its ability to solve classes of problems. Due to multiple objectives to be met and varied algorithm application in this digital era, addressing the problem-solving optimization in a more efficient and effective way has become more reasonable. Forest transportation planning is one of the most expensive activities in timber harvesting and can be optimized through algorithm application. Forest transportation planning is a vital component of timber harvesting activities. Inappropriate planning may raise the overall costs of harvesting activities. This paper aims to give an overview of several algorithm application in optimizing the forest transportation planning problem and give an insightful information regarding the relationships between algorithm and the integration of transportation system characteristics and variables. Examples of algorithm that are finding their way to the forest transportation planning problem include Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Ant Colony Optimization (ACO) algorithm, Simulated Annealing (SA) algorithm and Tabu Search (TS) algorithm. Although no literature was found regarding forest transportation planning problem optimization with regards to Bees Algorithm (BA), rules set for several transportation problem evidenced from literature search seems to be applicable to forestry. Generally, in this paper, the BA has been given focus for forest transportation planning problem optimization as a potential algorithm to overcome the challenges of environmental degradation and efficiency of timber extraction used, as well as its accuracy and less processing time for problem-solving

The DPSIR framework for causes analysis of mangrove deforestation in Johor, Malaysia

Globally, the coastal areas are changing due to increasing threats from different sources. Mangroves are most vulnerable and reducing its size during last few couple of decades. Some of the factors such as land use changes are acting directly while some factors are acting indirectly like socioeconomic factors. The mangroves ecosystem in Johor is changing for the purposes of developments such as agriculture, aquaculture, urbanization etc., which are triggered by different socioeconomic factors like population growth, population density, income etc. This change affects the local mangrove dependent communities both subsistence and commercially by reducing the ecosystem services both production and services functions of the mangroves. In this work the environmental assessment was studied by using the Driver-Pressure-State-Impact-Response (DPSIR) framework to identify, analyze and evaluate complex environmental problems. This complex situation is responded by the society or government through different initiatives (activities or planning) to reduce the negative impacts or to encourage the positive impacts. However this paper only focused on the anthropogenic factors of mangrove changes and the impact of deforestation for understanding the phenomena. The information of this study can be used by ecologists, environmentalists, social scientists, planners and decision makers

Mangrove carbon stock assessment by optical satellite imagery

Matang Mangrove Forest Reserve or known as Matang Mangroves is the largest single mangroves in Peninsular Malaysia. Covering an area of about 41,000 ha, majority of this area is forest reserve. Mangroves have long been known as extremely productive ecosystem that cycle carbon (C) rapidly, but studies related to carbon in this ecosystem are limited. This study was carried out to assess the carbon stock and quantify their changes following deforestation, wood extraction and forest degradation. Landsat-TM and SPOT-5 satellite images for 1991 and 2011 respectively were utilised to identify mangroves. Vegetation index generated from the images was used as a variable to indicate carbon stock and it was correlated to forest inventory information through regression. The study showed that carbon stocks of Matang Mangroves ranged from 1.03 to 263.65 t C ha-1 and 1.01 to 259.68 t C ha-1 for the years 1991 and 2011 respectively. Total carbon stock in Matang Mangroves was estimated at about 3.04 mil t C in year 1991 and 2.15 mil t C in 2011. The study suggested that the traditional use of vegetation index from optical imagery systems is still relevant and viable in vegetative studies