Effect of tracked and rubber-tyred logging machines on soil physical properties of the Berkelah Forest Reserve, Malaysia

Wheel and track traffic of heavy forest machinery is causing increased concern about forest soil compaction. Compared to agriculture, forest mechanization is potentially more damaging to site productivity because forestry machines tend to be heavier and operations are performed throughout the year regardless of weather conditions. Field experiments of vehicular compaction tests were initiated in dry and wet months (June and November, respectively) on a clay loam soil at the Berkelah Forest Reserve in central Pahang, Malaysia. Two unloaded tree harvesting (TH) machine types (crawler tractor and rubber-tyred loader), two soil moisture contents (14 and 21 % of oven dry weight) and vehicular trips (0,1, 2, 4, 8,16, 32 and 50 passes) were assessed on soil conditions from 0 to 15cmdepth. Rates of soil degradation are very different for the two machines. Changes in soil dry bulk density (DBD), total pore space (TPS), aeration porosity (AP), available water-holding capacity (AWC), saturated hydraulic conductivity (SHC) and resistance to penetration (RP) of the rubber-tyred tractor did not exceed those caused by a track-type crawler tractor despite a two-fold difference in mean ground contact pressure. The changes in soilDBD and TPS caused by both machines increased with increasing soil moisture content. However, AP, AWC, SHC and RP decreased with increasing soil moisture content. Most soil physical properties studied reached a maximum or minimum after the first two passes and remained constant thereafter with the tyred machine. SHC appears to be the most sensitive parameter for machine differences. Effects of heavy machinery operation on surface soil compaction should be recognized in forest mechanization

A Forest Science Effective Research Supervision in the Faculty Of Forestry, Universiti Putra Malaysia

At least historically, undergraduate research supervision has predominantly been seen as part of the basic research function of academic staff. In many fields of study, success in research requires not only sophisticated experimental and analytical skills, but good mentoring and managerial skills as well. This paper presents an observational case study and perception based on the author’s true experiences exploring the most effective supervision of undergraduate students in the Faculty of Forestry, Universiti Putra Malaysia (UPM). Due to the need of a highly calibre first class honours undergraduates for the future pool of postgraduates and top notch academia in the Faculty and in UPM, the aim of this paper is therefore to provide a good practice guideline for supervision of undergraduates final year project reports/theses to ensure consistency of approach for staff and students across the faculty and university. Key topics covered include building an effective undergraduate final year project/theses supervisory relationship, negotiating expectations, providing good communication and feedback and providing motivation and guidance to them. Personal interviews of undergraduates' perceptions of their supervision as they undertake their final year research projects were presented. Students reported that only a select few of their supervisors were supportive and sympathetic to their needs. Only a few of the Faculty supervisors adopted the role of resource person, directing undergraduates to references and contacts, discussing ideas and work undertaken. Only a few students had considerable freedom in the conduct of their final year project work. They were not able to choose their own research topic and supervisor but most determined the pace at which they worked. Some appeared to cope well with the autonomous role of a junior researcher while some commented on difficulties. Though the majority of students were given considerable freedom in their research the results of the observation indicated some differences amongst supervisors

Estimation of rate of recovery of disturbed soils from ground-based logging in Peninsular Malaysia

A field study was conducted to determine the rate of natural recovery of compacted soils in a logged-over hill forest area in Sg. Tekam, Pahang, Peninsular Malaysia. Based upon regression analysis, the estimated average times required for natural recovery of bulk density, total porosity, saturated hydraulic conductivity and resistance to penetration on skid trail, bush landing and secondary forest road to conditions found in the undisturbed soil are respectively listed in consecutive order as follows: (i) 22, 17and 14 years; (ii) 24, 17 and 15 years; (iii) 52, 37 and 28 years; and (iv) 19, 14 and 12 years. The study showed that ground-based logging is most damaging to the skid trails, as the natural rate of recovery of such disturbed soils is exceedingly slow compared to bush landing and secondary forest road. Future research should focus on improved logging machine and systems that will lessen the damage on skid trails

Advanced Processing of UPM-APSB’s AISA Airborne Hyperspectral Images for Individual Timber Species Identification and Mapping

UPM-APSB’s AISA airborne hyperspectral imaging offers the possibility of identifying and characterizing commercial and non-commercial individual timber species in the Malaysian tropical high mountain forests on the basis of the unique reflectance patterns that result from the interaction of solar energy with the molecular structure of the tree crowns. In this paper, a seminal view on recent advances in techniques for hyperspectral data processing was provided. It examines the performance of image processing techniques specifically developed for hyperspectral data in the context of individual timber species inventory mapping applications. The area chosen, located in Berangkat Forest Reserve, Kelantan near the locality of Kompleks Perkayuan Kelantan sawmill, had relatively virgin dense forest stand density at the time of imagery acquisition (dry month). The main focus is on the development of approaches able to naturally integrate the spatial and spectral information available from the hyperspectral data. Special attention is paid to techniques that circumvent the curse of dimensionality introduced by high-dimensional data spaces. Image processing was carried out in two steps, namely data conversion from radiance units to reflectance using a radiative transfer method and application of the mapping algorithm, specifically designed for identifying superficial materials based on similarities between image pixels and spectra from a spectral library of timber species. Experimental results, focused in this work on a specific case-study of individual timber species data analysis, demonstrate the success of the considered techniques. The results show that UPM-APSB’s AISA airborne hyperspectral imaging can identify 22 individual species in Block 53, Berangkat F.R and separated damar from non-damar group of species. Kelat constituted the highest count of species (1,402) mapped followed by Kedondong (1,185 trees), Medang (1,116 trees) and others out of the total 13,861 trees. It is therefore a valuable tool for mapping and quantification of individual tree in tropical dense virgin forested regions. This paper represents a first step towards the development of a quantitative and comparative assessment of advances in UPM-APSB’s AISA airborne hyperspectral data processing techniques

Sustainable management of a matured oil palm plantation in UPM campus, Malaysia using airbone remote sensing

Accurate and reliable near-real time information is needed for a sustainable oil palm plantation management, especially on plant quality and health. Airborne remote sensing provides the effective recent agricultural crop information for the oil palm plantation industry planning, management and sustainable development. A study on the characteristic of a matured oil palm plantation in UPM campus was conducted using airborne hyperspectral remote sensing technique. Airborne hyperspectral remote sensing can be used as an effective tool in monitoring the characteristic of oil palm plantation in order to predict and manage the oil palm production. The general objective of this study is to assess the capability and usefulness of UPM-APSB’s AISA airborne hyperspectral sensor to determine the characteristic of a matured oil palm plantation for its sustainable development while the specific objective is to identify, classify and produce the thematic map of matured oil palm plantation in the study site. The age of the oil palm plantation used in this study is 27 years old. Sobel filtering was used to enhance the image. Spectral Angle Mapper (SAM) analysis was then used to classify the characteristic of the plantation within the study area. A thematic map of 27 years old matured oil palm plantation was produced and the characteristic of the oil palm plantation in the study site was identified as 173 healthy, 7 dead, 9 stressed oil palm trees and open areas in the plantation with a mapping accuracy of 93.33%. This has shown that UPM-APSB’s AISA airborne hyperspectral sensor is capable of mapping a matured oil palm plantation with such characteristics for its sustainable management and future development

Land use and cover mapping with airbone hyperspectral imager in Setiu, Malaysia.

In recent years, land use and land cover plays a pivotal role in global environmental change. Under these circumstances,the need of a new dimension for detecting land use and cover is getting more imperative for conservation and effective management of land use and cover types. Importantly, the use of information technology to support decision making in detecting land use and cover is essential and recent. One of the technologies used is Airborne Remote Sensing. The objective of this study is to identify, quantify, classify and map land use and land cover mapping in Setiu, Terengganu using UPM-APSB’s AISA airborne hyperspectral remote sensing. Detection of land use and cover was performed using airborne hyperspectral imaging data taken on 20 April 2006 with the support of existing land use and cover maps. The size of the study area is 100 ha. The image was displayed in ENVI 4.0 Software using bands 202217 (RGB) combination. The data were then enhanced and classified for different land use and cover classes. From the data analysis, the image can be classified into eight classes. The classes are 2-3 years old oil palm plantation, 4-5 years old oil palm plantation, young (3-4 years old) rubber plantation, matured (15-17 years old) rubber plantation, vegetation crops, open area, road and river. The land use and land cover classes area distribution of the plots under study in Setiu, Terengganu were 4.18 ha, 8.58 ha, 6.26 ha, 70.43 ha, 2.98 ha, 2.31 ha, 2.78 ha, and 2.48 ha. Overall, the classification accuracy of interpretation of the airborne imagery for land use and cover in Setiu, Terengganu is 89.51 and kappa coefficient is 0.86. This study shows that, airborne hyperspectral remote sensing technique is capable in identifying, quantifying, classifying and mapping land use and cover in Setiu, Terengganu, hence a good decision support tool in land use and cover planning and management

In search of best impact factor and citation indexed journals towards achieving the goals of universities

This paper provides an introduction to the concept and importance of journal impact factor (JIF), citation indexes. The paper takes the form of a short history of JIF, the importance of journal performance indicators, about calculating and determining JIF and the significance of using Citation Indexes. Elements of the factors affecting impact factor namely scientometrics and journalology were also highlighted. A guide to locating the best impact factor journals in various research fields was demonstrated. Despite that JIF is still a dilemma for some fields of research, academic members are still subjected to the Key Performance Index (KPI) criteria compliance for further promotion and excellence service awards on top of the need to generate high impact research publications

Construction of New Forest Roads in Malaysia Using a GIS-Based Decision Support System

This paper describes how a Geographical Information System (GIS)-based Decision Support System (DSS) was applied in selecting the most compatible block or compartment to construct a new forest road for a sustainable timber harvesting purposes. The study area was located in Gunong Stong Permanent Forest Reserve, Kelantan, Malaysia between latitude 5o00’ N and 5o25’ N and longitude 101o20’ E and 102o05’ E. Four criteria have been considered in this paper which is timber volume (m3), slope (degree), ground condition and distance from the primary and secondary forest road that previously exists (m). ArcView and ArcMap softwares were used to evaluate all the criteria using remote sensing and field data. Results indicated that the best block that fulfill all the criteria chosen for the new forest road construction is Block Nos. 9 and 11

Ayer Hitam Forest (AHFR) from space using satellite remote sensing

There is a high demand to map and monitor the land use and assess their condition for ecological and economic reasons. Information on existing land and cover and their spatial distribution is a pre-requisite for any planning, development and management programme. In this study, Landsat TM data of 1998 were acquired over the AHFR and it's vicinity which covers an area more than 1, 300 ha. The objective of this paper is to map AHFR and assess the land cover of AHFR in 1998 as well as its surrounding area using remote sensing technology. Digital data processing and analysis were carried out using PCI/EASI PACE software, version 6.2 available in Faculty of Forestry, UPM. A false Colour Composite (FCC) of Landsat TM band 4-5-3 (R-G-B) was used in supervised classification using Maximum Likelihood Classifier (MLC). From a visual interpretation, several features of AHFR could be identified such as federal road, forest road, cleared land, built-up area, oil palm, water bodies and rubber plantation etc. Meanwhile, digital classification showed that seven land use types surrounding AHFR such as forest, secondary forest/shrubs, oil palm, rubber, built-up area, cleared land and water bodies could a easily be mapped out. The mean overall classification accuracy obtained is 86.08 percent with an average accuracy o] 85.64 percent. Satellite map of AHFR is found to be useful for the macro planning and management purposes especially on the Environmental Impact Assessment (EIA) if further development on the area is to be politicized

Estimating Acacia mangium Plantation's Standing Timber Volume Using an Airborne Hyperspectral Imaging System

Individual tree mapping in the forest is usually done by several techniques such as the sequential target and point origin mapping. Generally, the estimation of standing timber volume operation is considered a difficult task as ground survey is expensive. Most of this task is being done on the ground and takes a lot of time to be accomplished. However, the use of airborne remote sensing such as the UPM-APSB's Airborne Imaging Spectrometers for Applications (AISA) that plays its part in Global Positioning System (GPS) could change the way on how tree mapping and standing timber volume estimation are done. The general objective of this study is to map the individual wild A. mangium trees and estimate their standing timber volume using the airborne hyperspectral imaging technique. The specific objectives were to assess the capability of UPM-APSB's AISA airborne hyperspectral data in mapping A. mangium plantation and estimate its standing timber volume by delineating the individual trees crown areas. The hyperspectral image of A. mangium plantation in Lebuh Silikon, UPM in ENVI (.img) format taken on February 2004 was enhanced using the ENVI software. The age of the A. mangium stand was about 30 years old. Results indicated the presence of 29 canopies of A. mangium trees over a 0.8 ha plot. A single crown or canopy represented a single tree. A set of simple linear regression model for predicting volume from the crown area was developed using the 29 samples of tree crown. The value for r2 was 0.801 for this fit of the model, which showed 80.1% erratum data could be evaded. The equation developed in this study was V = 0.1045 + 0.0111(CA) where it provided a mean for predicting volume from the crown size measurement using the airborne sensor. The total standing timber volume mapped and quantified by the UPM-APSB's for the study site of 0.8 ha A. mangium plantation was about 20.73 m3 with a mapping accuracy of 80.45%. In practice, users of airborne hyperspectral data can now predict the timber volume by measuring tree crown size using ENVI software and apply the appropriate equation developed from linear regression as the indirect method of timber volume estimation. Further work in this area is to estimate the above ground biomass, carbon sequestration and biodiversity of planted A. mangium plantations in Malaysia