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At least 19 records

Characteristics and Composition of Atmospheric Aerosols in Phimai, Central Thailand During BASE-ASIA

Popular summary: Atmospheric aerosols play an important role in the Earth's climate system, and can also have adverse effects on air quality and human health. The environmental impacts of aerosols, on the other hand, are highly regional, since their temporal/spatial distribution is inhomogeneous and highly depends on the regional emission sources. To better understand the effects of aerosols, intensive field experiments are necessary to characterize the chemical and physical properties on a region-by-region basis. From late February to early May in 2006, NASA/GSFC's SMARTLabs facility was deployed at a rural site in central Thailand, Southeast Asia, to conduct a field experiment dubbed BASE-ASIA (Biomass-burning Aerosols in South East-Asia: Smoke Impact Assessment). The group was joined by scientists from the University of Hawaii and other regional institutes. Comprehensive measurements were made during the experiment, including aerosol chemical composition, optical and microphysical properties, as well as surface energetics and local . meteorology. This study analyzes part of the data from the BASE-ASIA experiment. It was found that, even for the relatively remote rural site, the aerosol loading was still substantial. Besides agricultural burning in the area, industrial pollution near the Bangkok metropolitan area, about 200 km southeast of the site, and even long-range transport from China, also contribute to the area's aerosol loading. The results indicate that aerosol pollution has developed into a regional problem for northern Indochina, and may become more severe as the region's population and economy continue to grow. Abstract: Comprehensive measurements of atmospheric aerosols were made in Phimai, central Thailand (15.l83 N, 102.565 E, elevation: 206 m) during the BASE-ASIA field experiment from late February to early May in 2006. The observed aerosol loading was sizable for this rural site (mean aerosol scattering: 108 +/- 64 Mm(exp -1); absorption: 15 +/- 8 Mm(exp -1); PM(sub 10) concentration: 33 +/- 17 miro-g/ cubic m and dominated by submicron particles. Major aerosol compounds included carbonaceous (OC: 9.5 +/- 3.6miro-g/ cubic m; EC: 2.0 2.3 miro-g/ cubic m and secondary species (SO4(2-): 6.4 +/- 3.7 miro-g/ cubic m, NH4(+): 2.2 +/- 1.3 miro-g/ cubic m). While the site was seldom under the direct influence of large forest fires to its north, agricultural fires were ubiquitous during the experiment, as suggested by the substantial concentration of K+ (0.56 +/- 0.33 micro-g/ cubic m). Besides biomass burning, aerosols in Phimai during the experiment were also strongly influenced by industrial and vehicular emissions from the Bangkok metropolitan region and long-range transport from southern China. High humidity played an important role in determining the aerosol composition and properties in the region. Sulfate was primarily formed via aqueous phase reactions, and hygroscopic growth could enhance the aerosol light scattering by up to 60%, at the typical morning RH level of 85%. The aerosol single scattering albedo demonstrated distinct diurnal variation, ranging from 0.86 +/- 0.04 in the evening to 0.92 +/- 0.02 in the morning. This experiment marks the first time such comprehensive characterization of aerosols was made for rural central Thailand. Our results indicate that aerosol pollution has developed into a regional problem for northern Indochina, and may become more severe as the region's population and economy continue to grow.

Li, Can↗

Thailand national programme of the Earth Resources Technology Satellite

The author has identified the following significant results. ERTS-1 data has been used to delineate floating rice regions with a clear distinction between irrigated and nonirrigated areas and recognition of orchard and horitcultural crops. Alluvial fans marking the ancient river outlets in the northwestern portion of the Central Plain of Thailand and the shape and size of the flood plains in the central region have been identified and outlined. A new forestry map was constructed using band 5 and band 7 imagery combined with ground observations. A geologic map of Thailand has been constructed from ERTS imagery.

Cheosakul, P.↗

Thailand National Programme of the Earth Resources Technology Satellite

The author has identified the following significant results. Forest inventory of Thailand was completed in January 1975, using LANDSAT-1 imagery and ground truth survey. Results showed the existing forest covers only 37% of the land area. The last country-wide survey using aerial survey photographs at 1:60,000 scale conducted in 1961 gave the figure of 58%. ERTS-1 imagery showed that Thailand's mangrove forest covers an area of approximately 3130 sq k. The previous aerial survey showed 3681 sq k of mangroves.

Sabhasri, S.↗

Thailand national programme of the earth resources technology satellite

The author has identified the following significant results. Accomplishments include the identification of a series of active alluvial fans along the margins of the Central Plain, the compilation of crop resources maps of central and eastern Thailand, and evaluation of the Purdue/LARS printout using unsupervised mode of an area near Bangkok. Results from LANDSAT 1 imagery and ground truth survey showed that Thailand existing forest in 1973 covered an area of approximately 37% of total land area. The last countrywide survey using aerial photographs at 1:60,000 scale conducted in 1961 gave the figure of 58%. Experience has shown many advantages of LANDSAT imagery over the conventional aerial photography in locating faults and fractures in the preparation of tectonic maps. Several rock types can also be identified from LANDSAT imagery.

Sabhasri, S.↗

Surveillance and Control of Malaria Transmission in Thailand using Remotely Sensed Meteorological and Environmental Parameters

These slides address the use of remote sensing in a public health application. Specifically, this discussion focuses on the of remote sensing to detect larval habitats to predict current and future endemicity and identify key factors that sustain or promote transmission of malaria in a targeted geographic area (Thailand). In the Malaria Modeling and Surveillance Project, which is part of the NASA Applied Sciences Public Health Applications Program, we have been developing techniques to enhance public health's decision capability for malaria risk assessments and controls. The main objectives are: 1) identification of the potential breeding sites for major vector species; 2) implementation of a risk algorithm to predict the occurrence of malaria and its transmission intensity; 3) implementation of a dynamic transmission model to identify the key factors that sustain or intensify malaria transmission. The potential benefits are: 1) increased warning time for public health organizations to respond to malaria outbreaks; 2) optimized utilization of pesticide and chemoprophylaxis; 3) reduced likelihood of pesticide and drug resistance; and 4) reduced damage to environment. !> Environmental parameters important to malaria transmission include temperature, relative humidity, precipitation, and vegetation conditions. The NASA Earth science data sets that have been used for malaria surveillance and risk assessment include AVHRR Pathfinder, TRMM, MODIS, NSIPP, and SIESIP. Textural-contextual classifications are used to identify small larval habitats. Neural network methods are used to model malaria cases as a function of the remotely sensed parameters. Hindcastings based on these environmental parameters have shown good agreement to epidemiological records. Discrete event simulations are used for modeling the detailed interactions among the vector life cycle, sporogonic cycle and human infection cycle, under the explicit influences of selected extrinsic and intrinsic factors. The output of the model includes the individual infection status and the quantities normally observed in field studies, such as mosquito biting rates, sporozoite infection rates, gametocyte prevalence and incidence. Results are in good agreement with mosquito vector and human malaria data acquired by Coleman et al. over 4.5 years in Kong Mong Tha, a remote village in western Thailand. Application of our models is not restricted to the Greater Mekong Subregion. Our models have been applied to malaria in Indonesia, Korea, and other regions in the world with similar success.

Kiang, Richard K.↗

Integrating High-Resolution Taskable Imagery into a Sensorweb for Automatic Space-Based Monitoring of Flooding in Thailand

Several space-based assets (Terra, Aqua, Earth Observing One) have been integrated into a sensorweb to monitor flooding in Thailand. In this approach, the Moderate Imaging Spectrometer (MODIS) data from Terra and Aqua is used to perform broad-scale monitoring to track flooding at the regional level (250m/pixel) and EO-1 is autonomously tasked in response to alerts to acquire higher resolution (30m/pixel) Advanced Land Imager (ALI) data. This data is then automatically processed to derive products such as surface water extent and volumetric water estimates. These products are then automatically pushed to organizations in Thailand for use in damage estimation, relief efforts, and damage mitigation. More recently, this sensorweb structure has been used to request imagery, access imagery, and process high-resolution (several m to 30m), targetable asset imagery from commercial assets including Worldview-2, Ikonos, Radarsat-2, Landsat-7, and Geo-Eye-1. We describe the overall sensorweb framework as well as new workflows and products made possible via these extensions.

sensorweb operations↗

Space-Based Sensorweb Monitoring of Wildfires in Thailand

We describe efforts to apply sensorweb technologies to the monitoring of forest fires in Thailand. In this approach, satellite data and ground reports are assimilated to assess the current state of the forest system in terms of forest fire risk, active fires, and likely progression of fires and smoke plumes. This current and projected assessment can then be used to actively direct sensors and assets to best acquire further information. This process operates continually with new data updating models of fire activity leading to further sensing and updating of models. As the fire activity is tracked, products such as active fire maps, burn scar severity maps, and alerts are automatically delivered to relevant parties.We describe the current state of the Thailand Fire Sensorweb which utilizes the MODIS-based FIRMS system to track active fires and trigger Earth Observing One / Advanced Land Imager to acquire imagery and produce active fire maps, burn scar severity maps, and alerts. We describe ongoing work to integrate additional sensor sources and generate additional products.

sensorweb↗

The Analysis of Using Satellite Soil Moisture Observations for Flood Detection, Evaluating Over the Thailand’s Great Flood of 2011

A flood monitoring and warning system provides critical information that can protect property and save lives. A basin-scale flood monitoring system requires an effective observation platform that offers extensive ground coverage of flood conditions, low latency, and high spatiotemporal resolution. While satellite imagery offers substantial spatial flood extent in detail due to its high spatial resolution, the coarse temporal resolution and cloud obstruction limit its near real-time application. Daily soil moisture data derived from satellite sensors at a scale of a few km can be used to monitor extreme wet surface conditions arising in flood occurrences. This study analyses the flood detection capabilities of several sources of soil moisture information, including the Soil Moisture and Ocean Salinity mission (SMOS), the Advanced Microwave Scanning Radiometer on EOS (AMSR-E), the Advanced SCATterometer (ASCAT) on MetOp, the Global Land Data Assimilation System (GLDAS), and the WaterGAP Global Hydrology Model (WGHM). In addition to soil moisture, the analysis includes measurements of surface reflectance from the Moderate Resolution Imaging Spectroradiometer (MODIS), precipitation measurements from the Tropical Rainfall Measuring Mission (TRMM), and terrestrial water storage estimates from the Gravity Recovery And Climate Experiment (GRACE) as proxies for flood inundations. The analysis was conducted over the Chao Phraya River Basin (CPB) in Thailand, where the Great Flood of 2011 led to one of the most significant economic losses in the country's history. Satellite-derived soil moisture exhibits a stronger correlation with the flood inundations than the precipitation, model-derived soil moisture, and terrestrial water storage data. SMOS soil moisture observation agrees best with the MODIS-derived flood extent/occurrence, both in terms of spatial distribution and timing, and providing approximated flood lead-time of one week or longer. A neural network constructed from SMOS and MODIS data is used to predict flood intensity/occurrence (given soil moisture input) with a predicted time window from eight days to thirty-two days. The short-term prediction (e.g., eight days) achieves the highest accuracy with an averaged recovery rate of approximately 60% (correlation coefficient). This study's results suggest a potential application of satellite soil moisture data in assisting flood monitoring and warning systems.

Satellite soil moisture↗

The Thailand programme of Earth Resources Technology Satellite

The author has identified the following significant results. Multispectral scanner image quality is considered excellent. It is immediately apparent that details of the coastline, water courses, and many other features readily apparent in the imagery will permit important updating and correction of available maps of Thailand.

Cheosakul, P.↗

Thailand national programme of the Earth Resources Technology Satellite

The author has identified the following significant results. Intensive interpretation of ERTS-1 scenes covering agricultural regions near Bangkok, backed up by ground surveys and low altitude reconnaissance flights, has established that the major agricultural crops of Thailand can be positively differentiated, and in most cases identified, after some experience has been gained, by examination of ERTS-1 imagery. A country-wide survey of remaining forest cover will be completed during 1974. MSS band 5 and band 7 and white positive transparencies were found to be the most desirable medium for identification of geological structure. The Royal Irrigation Department conducted a pilot study to examine the possibility of determining water reservoir capacity from surface area measurements derived from ERTS-1 images.

Cheosakul, P.↗

Agricultural utilization of ERTS-1 data in Thailand

Recent advances made in three disciplinary areas that are of major importance to Thailand are briefly discussed. These areas are; (1) agriculture, (2) forestry, and (3) land use. Preliminary investigations of the ERTS-1 data have been so successful that the Thai Government has decided to develop a remote sensing data handling and research center.

Cheosakul, P.↗

Agent-Based Simulations of Malaria Transmissions with Applications to a Study Site in Thailand

The dynamics of malaria transmission are driven by environmental, biotic and socioeconomic factors. Because of the geographic dependency of these factors and the complex interactions among them, it is difficult to generalize the key factors that perpetuate or intensify malaria transmission. Methods: Discrete event simulations were used for modeling the detailed interactions among the vector life cycle, sporogonic cycle and human infection cycle, under the explicit influences of selected extrinsic and intrinsic factors. Meteorological and environmental parameters may be derived from satellite data. The output of the model includes the individual infection status and the quantities normally observed in field studies, such as mosquito biting rates, sporozoite infection rates, gametocyte prevalence and incidence. Results were compared with mosquito vector and human malaria data acquired over 4.5 years (June 1999 - January 2004) in Kong Mong Tha, a remote village in Kanchanaburi Province, western Thailand. Results: Three years of transmissions of vivax and falciparum malaria were simulated for a hypothetical hamlet with approximately 1/7 of the study site population. The model generated results for a number of scenarios, including applications of larvicide and insecticide, asymptomatic cases receiving or not receiving treatment, blocking malaria transmission in mosquito vectors, and increasing the density of farm (host) animals in the hamlet. Transmission characteristics and trends in the simulated results are comparable to actual data collected at the study site.

Kiang, Richard K.↗

Modeling Malaria Transmission in Thailand and Indonesia

Malaria Modeling and Surveillance is a project in the NASA Applied Sciences Public Health Applications Program. The main objectives of this project are: 1) identification of the potential breeding sites for major vector species: 2) implementation of a malaria transmission model to identify they key factors that sustain or intensify malaria transmission; and 3) implementation of a risk algorithm to predict the occurrence of malaria and its transmission intensity. Remote sensing and GIs are the essential elements of this project. The NASA Earth science data sets used in this project include AVHRR Pathfinder, TRMM, MODIS, NSIPP and SIESIP. Textural-contextual classifications are used to identify small larval habitats. Neural network methods are used to model malaria cases as a function of precipitation, temperatures, humidity and vegetation. Hindcastings based on these environmental parameters have shown good agreement to epidemiological records. Examples for spatio-temporal modeling of malaria transmissions in Southeast Asia are given. Discrete event simulations were used for modeling the detailed interactions among the vector life cycle, sporogonic cycle and human infection cycle, under the explicit influences of selected extrinsic and intrinsic factors. The output of the model includes the individual infection status and the quantities normally observed in field studies, such as mosquito biting rates, sporozoite infection rates, gametocyte prevalence and incidence. Results are in good agreement with mosquito vector and human malaria data acquired by Coleman et al. over 4.5 years in Kong Mong Tha, a remote village in western Thailand. Application of our models is not restricted to Southeast Asia. The model and techniques are equally applicable to other regions of the world, when appropriate epidemiological and vector ecological parameters are used as input.

Kiang, Richard↗

Malaria Modeling and Surveillance in Thailand and Indonesia

This viewgraph presentation reviews the modeling of malaria transmission in Thailand and Indonesia to assist in the understanding and reducing the incidence of the deadly disease. Satellite observations are being integrated into this work, and this is described herein.

Kiang, Richard↗

Using Multiple Space Assests with In-Situ Measurements to Track Flooding in Thailand

Increasing numbers of space assets can enable coordinated measurements of flooding phenomena to enhance tracking of extreme events. We describe the use of space and ground measurements to target further measurements as part of a flood monitoring system in Thailand. We utilize rapidly delivered MODIS data to detect major areas of flooding and the target the Earth Observing One Advanced Land Imager sensor to acquire higher spatial resolution data. Automatic surface water extent mapping products delivered to interested parties. We are also working to extend our network to include in-situ sensing networks and additional space assets.

flooding↗