Ultraviolet radiation is at shorter wavelengths than the visible spectrum (400 to 700 nm) and is divided into three components: UV-A (315 to 400 nm), UV-B (280 to 315 nm), and UV-C (less than 280 nm). Global increases in UV-B fluxes from decreasing stratospheric ozone amounts caused by anthropogenic chlorine releasing gases (mostly chlorofluorocarbons) have been a matter of public concern for the past 20 years. This surface UV irradiance data retrieved from Ozone Monitoring Instrument (OMI) from AURA spacecraft with the filename OMUVB. OMUVB contains surface UV irradiance data along with supplementary information generated using the OMI global mode measurements. In this mode each file contains the sunlit portion of a single orbit from pole-to-pole, with an approximately 2600 km wide swath composed of 60 ground pixels. The OMI measurements are used to estimate the ultraviolet (UV) radiation reaching the Earth’s surface. The product contains spectral irradiances at 305.1, 310.1, 324.1, and 380.1 nm corresponding to both the overpass time and the local solar noon. Using the correspondence latitude and longitude of Peninsular Malaysia, we can develop the pattern of distribution of UV irradiance interpolations using Sigma Plot and Adobe Photoshop.
Chlorophyll-a concentrations (mg/l) in surface waters of Songsong Islands were mapped using an optically derived remote sensing model. Landsat TM imagery dated 8 October 2008 was used in the classification process and in situ measurements made on 19 May 2012 during spring tidal condition (HW: 2.6 m, LW: 0.9 m) served as ground truthing data. The temporal difference between data used will be useful to review the robustness of the model. Three classes of chlorophyll-a concentrations were mapped: Class 1: 10 mg/l. Considering the dynamic nature of coastal and marine waters particularly the shallow region, and the temporal difference between the Landsat TM imagery used in classification and the field data, results of chlorophyll-a mapping using the developed remote sensing model was high at 83.3%, with producer’s accuracy of 50%–100% and user’s accuracy of 80%–100%. Kappa coefficient of agreement, Kˆ , calculated was 57.1%.
Carbon monoxide (CO) is a ubiquitous, an indoor and outdoor air pollutant. It is not a significant greenhouse gas as it absorbs little infrared radiation from the Earth. It is produced by the incomplete combustion of fossil fuels, and biomass burning. The CO data are obtained from Atmospheric Infrared Sounder (AIRS) onboard NASA’s Aqua satellite. The AIRS provides information for several greenhouse gases, CO2, CH4, CO, and O3 as a one goal of the AIRS instrument (included on the EOS Aqua satellite launched, May 4, 2002) as well as to improve weather prediction of the water and energy cycle. The results of the analysis of the retrieved CO total column amount (CO_total_column_A) as well as effective of the CO volume mixing ratio (CO_VMR_eff_A), Level-3 monthly (AIR*3STM) 1º*1º spatial resolution, ascending are used to study the CO distribution over the East and West Malaysia for the year 2003. The CO maps over the study area were generated by using Kriging Interpolation technique and analyzed by using Photoshop CS. Variations in the biomass burning and the CO emissions where noted, while the highest CO occurred at late dry season in the region which has experienced extensive biomass burning and greater draw down of CO occurred in the pristine continental environment (East Malaysia). In all cases, the CO concentration at West Malaysia is higher than East Malaysia. The southeastern Sarawak (lat. 3.5˚ - long. 115.5˚) is less polluted regions and less the CO in most of times in the year. Examining satellite measurements revealed that the enhanced CO emission correlates with occasions of less rainfall during the dry season.
The problem of difficulty in obtaining cloud-free scene at the equatorial region from satellite platforms can be
overcome by using airborne imagery as an attempt for introducing an economical method of remote sensing
data; which only requires a digital camera to provide near time data. Forty three digital images were captured
using a high resolution digital camera model pentax optio A40 (12 megapixels)at a selected location in the same day in Penang Island from a low-altitude flying autopilot aircraft (CropCam) to generate land use/land cover (LULC) map of the test area. The CropCam was flown at an average altitude of 320 meters over the ground while capturing images which were taken during two flying missions for the duration of approximately 15 and 20 minutes respectively. The CropCam was equipped with a digital camera as a sensor to capture the GPS points based digital images according to the present time to ensure the mosaic of the digital images. Forty one images were used in providing a mosaic image of a bigger coverage of area (full panorama). Training samples were collected simultaneously when the CropCam captured the images by using hand held GPS. Supervised classification techniques, such as the maximum likelihood, minimum-to-distance, and parallelepiped were applied to the panoramic image to generate LULC map for the study area. It was found that the maximum likelihood classifier produce superior results and achieved a high degree of accuracy. The results indicated that the CropCam equipped with a high resolution digital camera can be useful and suitable tool for the tropical region, and this technique could reduce the cost and time of acquiring images for LULC mapping.
Digital elevation model (DEM) generation from stereo images is an effective and economical method in topography mapping. This paper used the stereo pair methodology to generate the digital elevation model (DEM) from PRISM (Panchromatic Remote-Sensing Instrument Satellite) sensor which is onboard of ALOS (Advanced Land Observing Satellite). The pair of forward-backward is used as stereoscopic imagery in this study. Ten ground control points (GCPs) are collected with residual error 0.49 pixels to generate an absolute DEM. This generated DEM with 2.5 m spatial resolution is then matched with the 90 m spatial resolution of
SRTM (Space Shuttle Radar Topography Mission) DEM to compare the result. Although SRTM-DEM has a much coarser resolution, the positional accuracy of the matching is found. The difference of the height from the mean sea level (MSL) between the SRTM-DEM and the PRISM-DEM is analyzed and the correlation between the two DEMs is R²=0.8083. The accuracy of the DEM generated is given by the RMSE value of 0.8991 meter.
Microwave Remote sensing data have been widely used in land cover and land use classification. The objective of this research paper is to investigate the feasibility of the multi-polarized ALOS-PALSAR data for land cover mapping. This paper presents the methodology and preliminary result including data acquisitions, data processing and data analysis. Standard supervised classification techniques such as the maximum likelihood, minimum distance-to-mean, and parallelepiped were applied to the ALOS-PALSAR images in the land cover mapping analysis. The PALSAR data training areas were chosen based on the information obtained from
optical satellite imagery. The best supervise classifier was selected based on the highest overall accuracy and
kappa coefficient. This study indicated that the land cover of Butterworth, Malaysia can be mapped accurately
using ALOS PALSAR data.