Taravudh Tipdecho

Analyzing the spatio-temporal relationship between dengue vector larval density and land-use using factor analysis and spatial ring mapping

BackgroundDengue, a mosquito-borne febrile viral disease, is found in tropical and sub-tropical regions and is now extending its range to temperate regions. The spread of the dengue viruses mainly depends on vector population (Aedes aegypti and Aedes albopictus), which is influenced by changing climatic conditions and various land-use/land-cover types. Spatial display of the relationship between dengue vector density and land-cover types is required to describe a near-future viral outbreak scenario. This study is aimed at exploring how land-cover types are linked to the behavior of dengue-transmitting mosquitoes.MethodsSurveys were conducted in 92 villages of Phitsanulok Province Thailand. The sampling was conducted on three separate occasions in the months of March, May and July. Dengue indices, i.e. container index (C.I.), house index (H.I.) and Breteau index (B.I.) were used to map habitats conducible to dengue vector growth. Spatial epidemiological analysis using Bivariate Pearson’s correlation was conducted to evaluate the level of interdependence between larval density and land-use types. Factor analysis using principal component analysis (PCA) with varimax rotation was performed to ascertain the variance among land-use types. Furthermore, spatial ring method was used as to visualize spatially referenced, multivariate and temporal data in single information graphic.ResultsResults of dengue indices showed that the settlements around gasoline stations/workshops, in the vicinity of marsh/swamp and rice paddy appeared to be favorable habitat for dengue vector propagation at highly significant and positive correlation (p = 0.001) in the month of May. Settlements around the institutional areas were highly significant and positively correlated (p = 0.01) with H.I. in the month of March. Moreover, dengue indices in the month of March showed a significant and positive correlation (p <= 0.05) with deciduous forest. The H.I. of people living around horticulture land were significantly and positively correlated (p = 0.05) during the month of May, and perennial vegetation showed a highly significant and positive correlation (p = 0.001) in the month of March with C.I. and significant and positive correlation (p <= 0.05) with B.I., respectively.ConclusionsThe study concluded that gasoline stations/workshops, rice paddy, marsh/swamp and deciduous forests played highly significant role in dengue vector growth. Thus, the spatio-temporal relationships of dengue vector larval density and land-use types may help to predict favorable dengue habitat, and thereby enables public healthcare managers to take precautionary measures to prevent impending dengue outbreak.

Reducing hillslope size in digital elevation models at various scales and the effects on slope gradient estimation

Several models simulate watershed areas by delineating hillslopes. Hillslope size depends on the length of stream tributaries, which are affected by the drainage area threshold (DAT). There is no universal approach to identify the appropriate DAT. Therefore, a method to derive the DAT and a series of steps to delineate a watershed into smaller sizes were proposed in this study, and the impact of hillslope size on slope gradient estimation was investigated. The DAT obtained in this study was smaller than that obtained using other methods, resulting in a shorter length of the tributaries. Dividing these tributaries into equal short segments and using them to delineate the study area reduced the size of the hillslope. The results revealed that the shorter the length of the tributaries, the smaller the hillslope size. The accuracy of gradient estimation increased when the size of the hillslope was reduced.

Estimation of the Effect of Soil Texture on Nitrate-Nitrogen Content in Groundwater Using Optical Remote Sensing

The use of chemical fertilizers in Thailand increased exponentially by more than 100-fold from 1961 to 2004. Intensification of agricultural production causes several potential risks to water supplies, especially nitrate-nitrogen (NO3−-N) pollution. Nitrate is considered a potential pollutant because its excess application can move into streams by runoff and into groundwater by leaching. The nitrate concentration in groundwater increases more than 3-fold times after fertilization and it contaminates groundwater as a result of the application of excess fertilizers for a long time. Soil texture refers to the relative proportion of particles of various sizes in a given soil and it affects the water permeability or percolation rate of a soil. Coarser soils have less retention than finer soils, which in the case of NO3−-N allows it to leach into groundwater faster, so there is positive relationship between the percentage of sands and NO3−-N concentration in groundwater wells. This study aimed to estimate the effect of soil texture on NO3−-N content in groundwater. Optical reflectance data obtained by remote sensing was used in this study. Our hypothesis was that the quantity of nitrogen leached into groundwater through loam was higher than through clay. Nakhon Pathom province, Thailand, was selected as a study area where the terrain is mostly represented by a flat topography. It was found that classified LANDSAT images delineated paddy fields as covering 29.4% of the study area, while sugarcane covered 10.4%, and 60.2% was represented by “others”. The reason for this classified landuse was to determine additional factors, such as vegetation, which might directly affect the quantity of NO3−-N in soil. Ideally, bare soil would be used as a test site, but in fact, no such places were available in Thailand. This led to an indirect method to estimate NO3−-N on various soil textures. Through experimentation, it was found that NO3−-N measured through the loam in sugarcane (I = 0.0054, p < 0.05) was lower than clay represented by paddies (I = 0.0305, p < 0.05). This had a significant negative impact on the assumption. According to the research and local statistical data, farmers have always applied an excess quantity of fertilizer on paddy fields. This is the main reason for the higher quantity of NO3−-N found in clay than loam in this study. This case might be an exceptional study in terms of quantity of fertilizers applied to agricultural fields.

Temporal climate trend of Ping Basin of Thailand and implications for Mekong Region

The Ping Basin is the major basin in Northern Thailand with drainage area of 35,000 km 2 . Climate trend of Ping Basin for current period (1961-2010) and projected trend (2011-2059) are discussed for maximum and minimum temperature and precipitation. Current trend was analyzed from actual representative three stations data and averaging at basin level. Measures of the variability analysis included temporal variability, trend, anomaly, coefficient of variation (C.V) and index. The basin showed high temporal climate variability throughout the study period (1961-2059). The current period showed significant positive trend of minimum temperature and negative trend of maximum temperature while no significant trend in precipitation with high variability, fluctuation and inconsistency. Minimum temperature of Ping increased at a faster rate than that of Thailand. In the first two decades (1961-80), maximum temperature increased by 1.5 ° C and decreased by1 ° C in the later decades (1981-2010) while minimum temperature dropped by 2.3 ° C in the period of 1961-80 and increased by 1.53°C in the years 1981-2010 as compared to the long term 50 years normal temperature of 1961-2010. Intercomparison of 5 GCMs at 50 km spatial scale in projecting future trends indicated that all the five models show similar prediction of future mean temperature while ECHAM5 had the most robust prediction power of rainfall. Projected trend (2011-2059) from ECHAM4 PRECIS RCM debiased, calibrated and validated at finer 20 km spatial scale shows precipitation will increase as compared to current intensity and minimum temperature will significantly increase at a higher rate (R 2=0.76 at the rate of 0.042°C\annum) than maximum temperature (R2=0.5 at the rate of 0.038 ° C\annum). Our findings are consistent with projections for Mekong Basin.

Effect of sea level rise in the validation of geopotential/geoid models in Metro Manila, Philippines

Abstract The release of new global geopotential models (GGMs) has raised the question of whether these GGMs could now supplant the development of regional/local geoid models. For geodetic surveying purposes the importance of a geoid model fitted to the local condition will greatly help in the resolution of many vertical datum issues especially for an archipelagic country such as the Philippines. Since the geoid as a vertical reference surface is used to convert ellipsoidal heights acquired through GNSS survey to orthometric heights, it is vital that this should at least match the heights derived through geodetic levelling within the allowed accuracy. However, the issue of mean sea level (MSL) as vertical reference for geodetic levelling has introduced another issue of concern especially when it is exhibiting accelerated sea level rise (ASLR). The results of the validation and comparison of recent GGMs showed that EGM 2008 and the 2012 released EIGEN-6C2 both classified as combined type model have RMS around 14 and 13 cm respectively in the study area. These results were achieved when ASLR was considered in the validation. The local geoid model (LGM) developed using least squares modification of Stokes formula with additive corrections (LSMSA) approach has RMS around 11 cm using an integration cap of 3° from the limit of study area. The LGM validated the level of the combined type GGMs in reference to the local vertical datum in Manila Bay. Based on the result of this study, the ASLR contributed much to the departure of the latest MSL from the geoid.

Transformation Based Polynomial Model: In Case of Generating Orthophoto

Abstract A new approach for generating orthophoto based on polynomial models is proposed. Polynomial plays a key role in proposed transformation from 3D to 2D; meanwhile the Efficiency Index measures the accuracy of the results of orthophoto. Airborne laser and aerial photograph were two data sources for researching. Both manual and automatic functions were employed to assist and improve modes of gathering and increasing control points. Height constraint was considered in order to increase the accuracy of generating orthophoto. It was block processing as recursive applied for smaller area, when the accuracy of whole area or prior area was not accepted. Finally orthophoto with its accepted accuracy was produced. It can be summarized that polynomials could assist to generate orthophoto with acceptable accuracy (R2>0.990) of output, which could further be increased with greater control points by recursive block processing.

Rain Fed Rice Agriculture under Climate Variability in Southeast Asia: The Case of Thailand

This study was undertaken to analyze historical climate variability and quantify its impacts on rice production in the Ping River Basin, Northern Thailand. Catchment based climate gradient trend showed Upper Ping received the highest rainfall followed by Lower Ping and Middle Ping, respectively. Temperature and evaporation increased with decreasing altitude. The Ping climate exhibited high spatiotemporal variability. Temperature had an increasing trend but no significant trend in rainfall during the period of 1961-2010. Multiple regression models significantly explained 54% (P<0.01) rice yield, 43% (P<0.01) total production, and 47% (P=0.01) rice area temporal variation by climatic factors variability in Ping Basin, respectively. A critical impact assessment of climate variability on rice production showed that highest yield gap of 48%, planted area loss as high as of 55% and yield loss of 32% were observed. These losses in planted area and productivity are of paramount importance from food security perspective opting appropriate adaptation strategy at basin level. Planting of rice could be done Mid May to end of May in Upper and Middle Ping catchments while end of May to first week of June in Lower Ping without waiting until Mid-June and early July. Our findings indicate that there is a need to modify rice crop calendar that would ensure farmers to obtain better yield. This proposed adjustment of crop calendar will encourage farmers to plant early in May and harvest in September to avoid risk of flooding in October as an adaptation strategy in the face of prevailing climate variability.

Influence of surface height variance on distribution of ground control points

Abstract The process of geometric correction of a satellite image requires a network of ground control points (GCPs), the density of which depends on the accuracy required. In this study, an approach to determine the distribution of the GCPs was developed based on dividing the surface terrain into zones of low- and high-height variances. Comparative statistics were investigated to summarize the optimum number and distribution of the GCPs. For a uniform arrangement of 10 GCPs, the accuracy using root mean square error was 7.19 m. This accuracy was improved to 6.13 m following the inclusion of just two additional GCPs in the zone of high-surface height variance. Thus, the transformation using the polynomial model and a set of GCPs, for which the surface variance in height was considered, resulted in greater accuracy than using the conventional uniformly distributed method. In addition, the time required for the trial-and-error selection of the locations of the GCPs was reduced. Our results suggest that a method that considers the variance in height of the surface terrain could be applied to various types of images such as satellite or aerial photography.

Coastal and marine ecological changes and fish cage culture development in Phu Quoc, Vietnam (2001 to 2011)

This study employed image enhancement for LANDSAT TM and ALOS imagery to monitor the changing status of coastal resources from 2001 to 2011, object-based classification of high-resolution THEOS imagery to extract fish cage culture sites and interpolation methods to determine marine environmental quality in 2011 in the northern part of Phu Quoc Island. There were five classes in the study site: natural forest, Melaleuca forest, agriculture, peat and built-up areas. Agricultural land and Melaleuca forest changing into built-up areas constituted approximately 51.13% of the total area changing. The benthic seagrass habitat increased dramatically from 2001 to the end of 2010. Besides, marine culture has been concerned to cage culture which is one of the sources directly affecting aquatic life and water quality in coastal environment. Cage culture locations were detected using high-resolution imagery as THEOS data for image fusion and Object-based Image Analysis methods. Water quality criteria including nitrogen, phosphorus and chlorophyll-a concentrations were determined by interpolation method, and the spatial distribution of these parameters showed a concentration in the study area in the range from 0.17 to 0.49 mg/L, 0.012 to 0.073 mg/L and 0.26 to 1.046 μg/L, respectively.

Modelling electrical conductivity of soil from backscattering coefficient of microwave remotely sensed data using artificial neural network

Soil salinity is one of the main agricultural problems which expand to larger areas. Soil scientists categorize salinity level by electrical conductivity (EC) measurement. However, field measurements of EC require extensive time, cost and experiences. Remote sensing is one suitable option to investigate and collect spatial data in larger areas. Many researches estimated soil moisture through microwave, but there are fewer studies which mentioned about direct relationship between EC and backscattering coefficient (BC). Thus, this study aims to propose the estimation of EC directly from BC of microwave. The relationship between EC obtained from field survey and BC from microwave is non-linear, artificial neural network (ANN) is one technique proposed in this study to figure out EC and BC relationship. ANN uses multilayer of interconnected processing resulting in EC value with high accuracy which is acceptable. For this reason, ANN model can be successfully utilized as an effective tool for EC estimation from microwave.