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

Plants nutrient variability of oil palm and its correlation to fresh fruit bunch yield.

In recent times, among of the major problems in oil palm plantations is the lack of proper interpretation of yield maps for site-specific management. The ability to determine and diagnose leaf factors that influencing yield variability of oil palm will benefits in managing the plantation for better yield. A study on spatial variability of N, P, K, Mg and Ca in oil palm leaf was carried out at the Dusun Durian Estate of Golden Hope Plantations Berhad in Selangor, Malaysia. The aim of this study is to obtain accurate and timely information on the spatial distribution and status of N, P, K, Mg and Ca in leaf using semivariogram analysis and geographical information system (GIS), and its correlation to oil palm fresh fruit bunch (FFB) yield. The collection of leaf tissue data was conducted using systematic sampling. A GPS device (AgGPS Trimble) was used to precisely determine samples locations. Geostatistics software and classical statistics were used for data analysis. Correlation analysis was used to determine the strength of the relationship between nutrient content in leaf tissue and FFB yield. From kriged map, results indicate that about 32.2% of the area is low in yield, 51.6% is moderate and 16.2% is high in yield, respectively. Correlation analyses shown the total of N and available of P in the leaf have strong positive relationship (r2 = 0.84 and 0.83) with FFB yields. Thus, result implies that N and P in leaf tissue can be used to determine the FFB yields for oil palm production

Analysis of SPOT- 5 data for mapping turbidity level of River Klang, Peninsular Malaysia.

Water bodies in urban area are considered important ecological and sociological zones. Protection and management of urban water bodies such as lakes and rivers are a primary objective to related agencies such as Department of Environment Malaysia and Municipal Council, where sediment and other debris from uncontrolled sewage system are affected water quality and reduced the function of water bodies. The traditional measurement of water quality requires in situ sampling, which is relatively costly and time–consuming effort. Due to these impediments, it is not impractical to cover the whole water bodies. Therefore, it would be advantageous if we able to detect and monitor water quality level at large coverage of water bodies with minimal field measurement. The application of remote sensing in water quality control would provide resources managers’ with tools to monitor and maintain water bodies in a well-timed and cost-effective manner. The aims of this study were two folds: to map water turbidity and classify water turbidity level on SPOT 5 data based on Department of Environment classification index. A spectral reflectance of remote sensing was obtained SPOT 5 imagery for river surface analyses. By referring to the in-situ measurements of River Klang collected in September 13, 2005 at three permanent stations, which were Jambatan Pelabuhan Utara, Jambatan Bandar Kelang and Jambatan Cannaught Kelang, aid with reflectance data from SPOT 5 data imagery of August 16, 2005, a spectral indicators for the above mentioned water quality parameter were analysed. Turbidity concentration levels were quantified using band 3 [NIR] (0.79 - 0.89 μm), which showed a linear relationship with in situ measurement. From spectral reflectance analysis, the best single band to represent water turbidity differences was Band 3 Result from the remote sensing analysis generates a map of water turbidity level into three classes that were high (65 – 68 DN Value), moderate (58 – 63 DN Value) and low turbidity (51 – 57 DN Value). The causes of water turbidity were due to sediment concentration caused by human activities and high development area. However, the use of higher resolution remote sensing to assess the water turbidity precisely and timely is recommended in future research

Use of remote sensing and GIS in monitoring water quality.

The use of remote sensing and GIS in water monitoring and management has been long recognized. This paper however discusses the application of remote sensing and GIS specifically in monitoring water quality parameter such as suspended matter, phytoplankton, turbidity, and dissolved organic matter. In fact the capability of this technology offers great tools of how the water quality monitoring and managing can be operationalised in this country. Potential application and management is identified in promoting concept of sustainable water resource management. In conclusion remote sensing and GIS technologies coupled with computer modelling are useful tools in providing a solution for future water resources planning and management to government especially in formulating policy related to water quality

Planning of Access Road Using Satellite Technology and Best Path Modeling

Forest road construction for harvest operation are always been subjected to certain constrictions and limitations. Engineering practices on forest road alignment are hindered by costly environmental and operational assessment. GIS tools and related data such as remote sensing allows in allocating suitable access road by taking consideration of environmental and cost implication. The aim of this study is to present the method of integration of remote sensing data and GIS in allocating access road for forest harvesting using best path modeling. Therefore, the specific objectives of this study are to allocate the optimal forest roads network in forest operation, and to determine the density of forest road network. Allocating the best paths for forest road access for timber harvesting is a problem that can be solved by computer based approaches using spatial modeling. Spatial modeling is used to compute the indicative factors that suit road allocation. The model developed and designed using GIS to propose feasibility forest road allocation in the hill area. The method was designed to produce road layouts taking topographical features and forest environmental constraints into special consideration. In this study, four grid themes influencing the road construction were identified; elevation, slope, barrier of lake and distance to existing roads. The total of access road aligned and proposed in the respective area was 28,745.35m. Meanwhile the overall density calculated in selected compartments was about 9.93m/ha (0.80%). The densities of road paths presented here were achieved below as outlined by the forestry department. Thus, there is potential to reduce damage to the residual stand and to the ground area disturbance by the harvesting operation. The forest road alignment and information in this study provides an initial foundation on which GIS can be used for this kind of analysis in forest road planning. The result is not only associated with forest transportation, but at the same time is useful to identify a risk of road construction to the environment. This revealed that the minimum density of forest road construction can help mitigate the loss of ecological services of tropical forest subject to logging pressure and lead to greater financial benefit in future operations

Urban forestry planning using remote sensing/GIS technique

Urban forestry has become an important value, not only for the aesthetic but also their effectiveness in the environmental control and health. There is a potential to plan and develop urban forest landscape in Malaysian cities due to her richness in plant biodiversity. The advances in remote sensing technology and geographic information system (GIS) technique have provided an effective tool not just for monitoring the change of environment but also very useful for planning, managing and developing of urban forest landscaping. This study was undertaken to assess the capability of integrating remote sensing and GIS to provide information for urban forest potential sites surrounding Kuala Lumpur International Airport (KLIA) and its vicinity. Landsat TM imagery scene 126.58 (path/row) in the form of computer compatible tape (CCT) taken in May 1996 was digitally processed and analysed using a PC-based PCI EASIPACE software system version 6.2. Ancillary data such as topographical map, land use map and soil series map were used to support the satellite data.Integrating satellite data and GIS produced a map 'showing the potential site for urban forest landscaping at KLIA. Future studies should attempt to utilize airborne hyperspectral high-resolution data for more accurate mapping and landscape planning process

The Economic and Environmental Impact of a Suitable Forest Harvest Zone Allocation Using a GIS Analysis

Many countries are gradually adopting environmentally acceptable harvesting planning strategies. Various codes of practice such as FAO model code of forest harvesting have been developed for use at the international, regional and national levels to improve harvesting practices following concepts of low-impact harvesting. Since the last 20 years lowland forest in Peninsular Malaysia has declined gradually, and this has pushed harvesting operations to the hilly areas. The extent of damage to the forest environment, especially in hill forest has been alarming, mainly due to the complexity of its topography that lead to soil erosion. This study develops an integrated model of geoinformatics technology applied to forest harvest planning. The model determines the distribution and extent of allowable forest harvest zone from economic and environmental perspective using cartographical modelling and linear weighted combination approaches in a GIS. This study uses remote sensing data and geographic information system technology for data extraction, manipulation, analysis and evaluation of impacts of the difference perspective for forest harvest zone. The study revealed that by integrating remote sensing and GIS modelling, a suitable harvest zone for harvesting operations could be determined from the economic and environmental perspective, thus the impact to areal extent of a suitable forest harvest were analysed and determined

Soil disturbance from different mechanised harvesting in Hill Tropical Forest, Peninsular Malaysia.

The impacts of mechanised forest harvesting to soil physical properties are the major concern by forest managers, which have the potential to impact soil sustainability and forest productivity. Malaysia is practicing reduce impact logging (RIL) and applying code of forest harvest practice in forest harvesting and operations for sustainable forest resources management. In 2001, a machinery called Rimbaka Timber Harvester R2020-A was introduced for timber extraction for peat swamp forest and later on the machine was introduced to the hill tropical forest as an alternative to other machines. The study aimed to evaluate soil compaction (soil cone index, soil bulk density, soil moisture content and soil pore space) by Rimbaka Timber Harvester R2020-A and crawler tractor KOMATSU D60-A. A total of five samples were randomly taken using core sampler of 50 mm height and 50 mm diameter at the beneath a lug imprint for passes 1, 4 and 8. Altogether samples were 45. The locations of sample were to the right and left of each rut centre for both machines. Treatment effects were evaluated using analysis of variance (ANOVA). Result showed that compaction by Rimbaka machine was increased bulk density from 1.14 to 1.43 g/cc, cone index from 1.94 to 3.45 g/cm3 decreased total pore space by 43% and decreased soil moisture content by 19%. Meanwhile compaction by KOMATSU D60-A was increased bulk density from 1.2 to 1.43 g/cc, cone index from 1.24 to 1.94 g/cm3 decreased soil moisture content by 11% and total pore space by 6%, respectively. The value increased rapidly as more passes increase on the track surface. The higher soil disturbance by Rimbaka machine was due to physical design and specification of the machine. This study also observed that there was significant difference in the total passes of machinery used in harvesting operation. Although Rimbaka machine is showing more effected to soil compaction, the machine is a practical alternative to avoid skid trail and reduce road density in forest area