Description

The provided map will show the overall distribution of the various Poultry Farms in Malaysia registered under DVS. Along with the location, additional informations regarding the total population from each farm was also collected.

Methodology

Information regarding each poultry farms under DVS were collected by means of ground truthing. The coordinate obtain was then cross referenced with known coordinate at Agensi Remote Sensing Malaysia to verify the accurancy of each points. The points were then plotted into REMap geodatabase.

Source

• Department of Veterinary Services (DVS)

Year of data collection

• 2005-2010

Coverage

• Peninsular Malaysia

  
  

Number of Poultry Farms

• Peninsular Malaysia: 194 Farms

Attributes

• Name of Farm


• Address


• Latitude


• Longitude


• Coordinate status


• Total Population of Poultry

Map showing the locations of Paddy Mill in Peninsular Malaysia.

Data Description

The provided map will show the overall distribution of the various Paddy Mill in Malaysia; whereby majority of the mills belongs to BERNAS. Along with the location, the average amount of paddy purchased, the average amount of rice produced per mill as well as the average amount of rice husk available are also included for the year 2006 to 2010

Methodology

Information regarding each paddy mills under BERNAS was collected and plotted using the estimated coordinated was then crossed referenced with known coordinate at Agensi Remote Sensing Malaysia to verify the accuracy of the each points. Along with the coordinates, additional information regarding each mills were also gathered; specifically the amount of paddy purchased, amount of husk produced and the amount of rice produced per mill.

Source

• Beras National Berhad(Bernas)

Year of data collection

• 2006-2010

Coverage

• Peninsular Malaysia

Number of Paddy Mills

• Peninsular Malaysia: Paddy Mills

Attributes

• Name


• Address


• State


• Latitude


• Longitude


• Coordinate Status


• Tel No


• Fax No


• Category


• Average Purchased (2006 -2010), MT


• Average Husk(2006 - 2010), Mt


• Average Rice(2006- 2010), MT

Map showing the potential wind energy for Peninsular Malaysia, Sabah and Sarawak

Data Description

The maps will provide a coarse information regarding the status of potential wind power in Malaysia. The data were extrapolated from the measured 2008 wind speed obtained from Jabatan Meteorologi Malaysia(JMM)

Methodology

Wind speed obtained from JMM was at the height of approximately 10 meters. Based on the measured data, the wind speed at the height of 50 meters and 100meters were then calculated. Following that, the map was then generated by interpolating as well as extrapolating the measured and calculated data for the whole of Malaysia. It should be noted however that the extrapolated data could be skewed towards location of known value as the continuous data generated was on the basis of mathematical calculation [model used for caldulation: inversed distance weighted(IDW)]. However, this dataset is only temporary as the measured data from the height of 60 meters are currently underway and is expected to be ready for view by end of the year(2012) .

Source

• Jabatan Meteorologi Malaysia (JMM)

Year of data collection

• 2008

Coverage

• Peninsular Malaysia, Sabah and Sarawak

Number of Wind Stations

• Peninsular Malaysia: 24 stations


• Sabah: 5 stations


• Sarawak: 5 stations

Attributes

• Latitude (Wind Station)


• Longitude (Wind Station)


• height of Anemometer Above Ground at Wind Station(m)


• Potential Wind Energy(Watt)



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Map showing the locations of potential mini hydro power for selected rivers in Malaysia.

Data Description

The hydro power potential are only calculated based on the sampling stations obtained from JPS. The rivers are then divided based on data availability; where rivers with available potential hydro power are highlighted in light blue.

Methodology

Datasets obtained from JPS include the Flow Rate as well as Precipitation data. From there, the data were screened to include rivers where the data were consistent for five years consecutively. To ensure the credibility and to ensure that the dataset were relevant, only data for year 2000 and above were used. Coupled with the flow rate of each river, the elevation of the upstream and downstream of each river were extracted from the Shuttle Radar Topography Mission (STRM) imagery obtained from NASA. The STRM was used primary due to the availability of the aforementioned data. The hydro power potential were then calculated based on the screened flow rate data and the extracted elevation data.

Source

• Jabatan Pengairan dan Saliran (JPS)


• SIRIM Berhad

Year of data collection

• Varies based on stations; from early 1980's to 2010. However, only stations with data from year 2000 onwards were considered.

Coverage

• Peninsular Malaysia, Sabah and Sarawak

Number of Rivers

• Peninsular Malaysia: 106 rivers


• Sabah: 22 rivers


• Sarawak: 11 rivers

Attributes

• Coordinate


• Max Power (3m Head)


• 5 years Average


• Standard Deviation


• Upstream Height


• Downstream Height


• Average Power (kW, 3m Head) (kW)


• Firm Power Uncertainty (kW)


• Annual Energy at Site (kWh)


• Total Annual Energy for River Segment(kWh)


• Availability of Sufficient Head (based on terrain data)


• Sub Total (MWh)

Map showing the distributions of potential renewable energy that can be generated from biomass waste/forest residues from :

• Upstream activities(Forestry)


• Downstream activities(Wood-based Industry)

Data Description

The calculated energy was based on the calorific values that are potentially beneficial for renewable energy generation from the capacity biomass waste(i.e. upstream & downstream)

Methodology

The energy maps are divided into two categories which are :

• Upstream: biomass waste and log residues from forest production processes, which includes natural forest, plantation forest & rubber plantation. Energy is calculated based on the productivity and waste generated within the reported year. Energy is represented in forest district-based (Daerah Hutan) on the map.

• Downstream : biomass waste from wood-based industry, including sawmills plywood mills, furniture mills, and other mills. CV/Energy is calculated from the reported capacity of the mills by using generalised conversion factor represented in the smallest sub-district unit(Mukim) on the map

Source

• Forest Research Institute Malaysia (FRIM)


• Department of Forestry Peninsular Malaysia,JPSM


• Department of Agriculture (DoA)


• Kementerian Perusahaan Perladangan dan Komoditi(KPPK)

Year of data collection

• Varies based on Annual Report & Statistical info acquired from respective agencies, ranging from 2007-2011

Coverage

• Peninsular Malaysia, Sabah and Sarawak

Attributes

• Coordinate


• Address


• Potential Energy from Rubber Plantation(GJ)


• Potential Energy from Forest Plantation(GJ)


• Potential Energy from Furniture Mills(GJ)


• Potential Energy from Sawmill(GJ)


• Potential Energy from Plywood / Veneer Mill (GJ)


• Potential Energy from Moulding Activities(GJ)


• Total Potential Energy from Downstream Activities(GJ)


• Total Potential Energy from Upstream Activities(GJ)

Potential Renewable Energy from Oil Palm Biomass in Malaysia (2009)

Data Description

Oil palm biomass availability in 2009 is assessed by locations of palm oil mills and oil palm plantations via GIS database. In the cases of the plantations, the emphasis is on biomass available after the productive oil palm life span of 25 years. Coordinates of all palm oil mills in Malaysia are collected via ground truthing by MOPB team in 2011. However, coordinates of oil palm plantations, thus the biomass availability data in the plantations is with the existing land use map available. The energy potential of various oil palm biomasses are calculated based on the individual fuel characteristics i.e. calorific value, and for the case of POME, BOD and COD concentration are used to calculate the biomethane potential.

Methodology

Data on material balances of standing oil palm biomass in the plantations and various other biomass from FFB processed are derived from MPOB database and or survey conducted, along with many other general information required to execute this exercise. The data on fuel characteristics of various oil palm biomass is derived from MPOB database via R&D conducted. The coordinates of oil palm mills in Malaysia are collected via ground truthing by MPOB team. The software used for the compilation of data on oil palm biomass availability and energy potential is ArcGIS 10. All data are standardized as spatial data with GIS database. The map is constructed based on assessment of data and computation of data on potential RE from oil palm biomass, GIS analysis, model building and seamless access to mapping data repository (database infrastructure).

Source

• Malaysian Palm Oil Board (MPOB)


• Malaysia Remote Sensing Agency (MRSA)

Year of data collection

• 2007 - 2010

Coverage

• Peninsular Malaysia, Sabah and Sarawak

Number of Palm Oil Mills

• Peninsular Malaysia: 244 Mills


• Sabah: 119 Mills


• Sarawak: 37 Mills

Attributes

• Name of palm oil mill


• Address of palm oil mill


• State


• Coordinate of palm oil mill


• Capacity of palm oil mill (Tonne/hr)


• Average POME generated per year (Tonne)


• Average COD of raw POME (mg/l)


• Amount of EFB generated per year (Tonne)


• Potential Energy Available (MJ)


• Potential Power Available (MW/h)

Map showing the locations of potential locations for harvesting tidal energy in Malaysia.

Data Description

The tidal energy is calculated from the data which is obtained from National Hydrography Centre. The tidal data is retrieved from 60 stations around Malaysia. Based on the data, the characteristic of tidal can be recognized whether diurnal or semi-diurnal. If the tidal type is diurnal, the low tide and high tide will occur once in 24 hours but for semi-diurnal, the low tide and high tide will occur twice in 24 hours. In Peninsular Malaysia the charteristics of tidal is mainly semi-diurnal and mixed tide dominant semi-diurnal. However, for East Malaysia the characteristic is mainly mixed with dominant diurnal.

Methodology

The data which is received from National Hydrography Centre consists of daily water level for every month. From the generated data, the energy density of each location is calculated. Average energy density for every month is determined from the daily data. The monthly average is used as the input for mapping process. However, the energy density is identified as energy per area where a specific size or capacity of tidal dam is required to obtain the total energy density for a particular location.

Source

• Pusat Hidrografi Nasional


• SIRIM Berhad

Year of data collection

• Forecast 2011; data for low tide and high is almost the same for every year and not much significance changed happened. The fore coast data also is projected from the previous actual data which is collected from the tidal stations.

Coverage

• Peninsular Malaysia, Sabah and Sarawak

Number of Tidal Stations

• Peninsular Malaysia: 29 tidal stations


• Sabah: 9 tidal stations


• Sarawak: 20 tidal stations

Attributes

• Potential Tidal Power (MW/km2)

Map showing the monthly average daily global solar radiation and yearly average daily global solar radiation for Malaysia.

Data Description

The global solar radiation data was mapped based on estimates of daily average solar radiation data. The datasets comprises of monthly average daily global solar radiation for each month and a yearly daily global solar radiation of Malaysia.

Methodology

In estimating the monthly average daily global solar radiation and yearly average daily global solar radiation, satellite images from MTSAT-1R satellite and hourly solar radiation data for several station obtained from Malaysian Meteorological Department was used. The hourly cloud cover data from satellite images were measured and compared with the actual readings of hourly solar radiation data obtained from ground measuring station by using empirical method. The results were then used to model and estimate solar intensity for other places where solar instruments were not available. Finally maps that shows the monthly average global solar radiation for Malaysia was developed by using GIS application.

Source

• Malaysian Meteorological Department


• Universiti Kebangsaan Malaysia

Year of data collection

• 2006

Coverage

• Peninsular Malaysia, Sabah and Sarawak

Attributes

• Diffuse Solar Irradiation (WHr/m2)


• Global Solar Irradiation (WHr/m2)

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