MODIS data based semi-real time media GIS contents to support natural disaster mitigation

Natural disaster mitigation is a collective effort of; forecast, assessment, and encouraging the public participation in disaster mitigation. This study focused on the rarely addressed aspect, 'the value of public awareness' in natural disaster mitigation. The methodology used satellite data and Geographic Information Systems (GIS) to produce semi-real-time 'Media GIS' contents. When deliver the content to the media with maximizing four related factors; speed, attractiveness, richness, and accuracy, Media GIS contents will help to increase the public awareness on the respective disaster. The methodology to produce Media GIS contents is based on; basic fundamentals of GIS, freely available satellite images, and information extracted from Google Earth. Hence, contents carry inherent characters of GIS and significantly different from conventional graphics in media. Also the graphical variables like, size, value, texture, hue, orientation, and shape, were optimized to match with target content users (age group, social group) and medium (print, TV, WEB, mobile), while minimizing the cost. With the news brakes of the disaster, MODIS (250m) satellite data can be extracted in GeoTIFF and KLM (Keyhole Markup Language) formats. The KML file can be overlayed on Google Earth, to extract more spatial information of the area of interest. Photoshop or any similar graphic software can be used to create the product while keeping the geometric character of the content. The final output (in TIFF/JPEG and KLM file) is the GIS media content for TV, WEB, mobile contents, and for print media, which support to increase the public awareness of the disaster. Two cases studies; disastrous flood occurred in Bangkok in 2011 and the severe drought recorded in eastern Sri Lanka in 2014, are presented in the study

Assisting mitigation of bushfire threat in regional Australia through MODIS imagery based media GIS

Bushfires have been part of the Australian environment since before human settlement of the continent. Some Australian flora and fauna has evolved to coexist with bushfires, and in the case of eucalypt forest, fire forms an integral part of its regeneration cycle. Today, bushfires have become the dominant phenomenon in Australian natural hazards. According to the Australian bureau of meteorology, the whole southern half of Australia is at fire risk in summer and autumn months. Australian bureau of Criminology published a bushfire damage recorded from 1967 to 1999, and estimated the cost as about $2.5 billion excluding forestry losses. The public attention to bushfire disasters reached to a new peak, after the disastrous Black Saturday bushfire in Victoria. The Black Saturday bushfires in 2009 killed 173 injured 500 more and cause over$2.5 billion in damages. Annually, fire authorities respond to an average 54,000 bushfires in Australia where up to 50% of these fires are deliberately lit or start in suspicious circumstances. This grave situation of bushfire damage encourages researches to explore various bushfire mitigation scenarios. The present study focuses on educating the rural communities by awakening their participation in fire mitigation efforts using semi-real time fire information. In Australia, fire prevention related agencies work extensively to make available various data sources for public and schools. However, the flow of information to rural communities is not smooth due to various technical and social reasons, though their participation is vital. 'I could see the real value of us educating the locals,' said Glenn O’Rourke, Deputy Captain and Community Safety Officer at the Wollombi Rural Fire Brigade. This study discusses an approach to educate rural communities through Media GIS contents based on daily MODIS imagery. These bushfire contents can be uploaded daily to local newspapers, TV, and to mobile subscribers to establish a participatory user cohort. Google functions such as placemarks will be used in KML environment to deliver media GIS contents as spot/image information. Collected Participatory GIS inputs will be used to enrich the GIS database to further enhancements of the communication process on bushfire developments

Assessing land use of lower Mekong basin using multi-temporal MODIS imagery

Among rice producing regions of the world, Lower Mekong Basin (LMB) can be ranked as the most important region due to the huge population it feeds. About 60 million people are engaged in agriculture and freshwater fishing activates in LMB where produce enough food for over 300 million people annually. Food consumption in LMB is also increasing and studies have found it to be doubled by 2050. This socio-economic background has attracted many researchers to work on various aspects of the LMB. To collaborate with these research interests, the present study is designed to assess the land use conditions of the massive LMB, using multitemporal MODIS imagery. The authors have previously produced the land cover map of LMB in 2005 (edited in 2008) using MODIS data at 250m spatial resolution. The present land use assessment will be used the old map and a new map produced in 2014 using the same land cover classification. The investigation on land use conditions is based on the trends on land cover changes, with a focus on food production aspects of the basin, in order to supply a GIS database for food production assessment studies. Annual devastating floods in south and frequent droughts in central regions are also counted in the assessment. The expected results of the study will be GIS data layers of the basin in raster format comprising old and new land cover data, natural disaster hotspots, together with an assessment of the land use

Improving Tropical Forest Mapping using Combination of Optical and Microwave Data of ALOS

[ABSTRACT]Optical remote sensing usually has not enough multi-temporal high resolution images to describe phenology of objects for forest mapping in local scale. This paper presents a possibility to improve accuracy of tropical forest mapping by combination of optical and microwave images. Study area is located in the southern part of Vietnam. The first, ALOS/AVNIR-2 images were used to create the forest map, then ALOS/PALSAR single-polarized and dual-polarized images were used to improve the accuracy of the classification result by a combination model. ALOS/PRISM images were also used to make Pan-sharpen images for collecting training data and validation data. Discrimination of Planted Forest and Natural Forest is one of the most important purposes of this study. The overall accuracy of ALOS/AVNIR-2 classification result is 77.0%, while after combining with ALOS/PALSAR, it is increased up to 88.2%. The accuracy is higher than 90% for main forest classes

A hybrid pansharpening approach and multiscale object-based image analysis for mapping diseased pine and oak trees

We developed a multiscale object-based classification method for detecting diseased trees (Japanese Oak Wilt and Japanese Pine Wilt) in high-resolution multispectral satellite imagery. The proposed method involved (1) a hybrid intensity-huesaturation smoothing filter-based intensity modulation (IHS-SFIM) pansharpening approach to obtain more spatially and spectrally accurate image segments; (2) synthetically oversampling the training data of the 'Diseased tree' class using the Synthetic Minority Over-sampling Technique (SMOTE); and (3) using a multiscale object-based image classification approach. Using the proposed method, we were able to map diseased trees in the study area with a user's accuracy of 96.6% and a producer's accuracy of 92.5%. For comparison, the diseased trees were mapped at a user's accuracy of 84.0% and a producer's accuracy of 70.1% when IHS pansharpening was used alone and a single-scale classification approach was implemented without oversampling the 'Diseased tree' class

A Combined Approach of Remote Sensing, GIS, and Social Media to Create and Disseminate Bushfire Warning Contents to Rural Australia

Bushfires are an integral part of the forest regeneration cycle in Australia. However, from the perspective of a natural disaster, the impact of bushfires on human settlements and the environment is massive. In Australia, bushfires are the most disastrous natural hazards. According to the records of the Parliament of Australia, the recent catastrophic bushfires in NSW and Victoria burnt out over 10 million hectares of land, a figure more significant than any previous bushfire damage on record. After the deadly 2009 Black Saturday bushfires, which killed 173 people in Victoria, public attention to bushfires reached a new peak. Due to the disastrous consequences of bushfires, scientists have explored various methods to mitigate or even avoid bushfire damage, including the use of bushfire alerts. The present study adds satellite imagery and GIS-based semi-real-time bushfire contents to various bushfire warnings issued by government authorities. The new product will disseminate graphical bushfire contents to rural Australians through social media, using Google Maps. This low-cost Media GIS content can be delivered through highly popular smartphone networks in Australia through social media (Facebook and Twitter). We expect its success to encourage people to participate in disaster mitigation efforts as contributors in a participatory GIS network. This paper presents a case study to demonstrate the production process and the quality of media GIS content and further discusses the potential of using social media through the mobile network of Australia while paying attention to mobile blackspots. Media GIS content has the potential to link with the public information systems of local fire management services, disseminate contents through a mobile app, and develop into a fully automated media GIS content system to expand the service beyond bushfires

Optimization of Urban Highway Bypass Horizontal Alignment: A Methodological Overview of Intelligent Spatial MCDA Approach Using Fuzzy AHP and GIS

Selection of urban bypass highway alternatives involves the consideration of competing and conflicting criteria and factors, which require multicriteria decision analysis. Analytic hierarchy process (AHP) is one of the most commonly used multicriteria decision making (MCDM) methods that can integrate personal preferences in performing spatial analyses on the physical and nonphysical parameters. In this paper, the traditional AHP is modified to fuzzy AHP for the determination of the optimal bypass route for Eldoret town in Kenya. The fuzzy AHP is proposed in order to take care of the vagueness type uncertainty encountered in alternative bypass location determination. In the implementation, both engineering and environmental factors comprising of physical and socioeconomic objectives were considered at different levels of decision hierarchy. The results showed that the physical objectives (elevation, slope, soils, geology, and drainage networks) and socioeconomic objectives (land-use and road networks) contributed the same weight of 0.5 towards the bypass location prioritization process. At the subcriteria evaluation level, land-use and existing road networks contributed the highest significance of 47.3% amongst the seven decision factors. Integrated with GIS-based least cost path (LCP) analysis, the fuzzy AHP results produced the most desirable and optimal route alignment, as compared to the AHP only prioritization approach

An analysis of forest biomass changes using geospatial tools and ground survey data: a case study in Yok Don national park, Central Highlands of Vietnam

Vietnam conducts a national forest survey every five years using optical satellite imagery as Landsat, SPOT satellites and ground survey data. However, estimation of change in biomass due to change in forest types has not been of research interest despite of its importance in the face of climate change and applicability for REDD implementation. In this study, we used SPOT HRV satellite data of 2004, 2011 and ground survey data for analysis of changes in biomass of forest cover in Yok Don National Park, Central Highlands of Vietnam. This method has been effectively employed for mapping of land cover with overall classification accuracy of 84.30% to 86.63%. The results demonstrated that between 2004 and 2011, the biomass of Evergreen broad leaved rich forest decreased by 2.95 Megatons, biomass of the Evergreen broad leaved medium forest decreased by 0.09 Mega tons and biomass of the Dry open dipterocarps medium forest decreased 2.20 Mega tons. In that period, biomass of the Evergreen broad-leavedpoor forest increased by 0.02 Mega tons and biomass of the Dry open dipterocarps-poor forest increased by 0.91 Mega tons.References Bao Huy, 2008: Methodology for research on CO2 sequestration in natural forests to join the program of reducing emission from deforestation and degradation-REDD. Journal of Agriculture and Rural Development, MARD, 2008, pp. 1-10. Bhishma, P. et al., 2010: Forest carbon stock measurement-Guidelines for measuring carbon stocks in community-managed forest. Asia Network for Sustainable Agriculture and Bioresource (ANSAB), 79 pp. Brown, S., 1997. Estimating biomass and biomass change of tropical forests: a Primer. FAO Forestry paper–134.ISBN 92-5-103955-0. Brown, S., 2002: Measuring carbon in forests: current status and future challenges. Environmental Pollution, 116(3): 363-372.. Canh N. X. et al., 2009: Conservation planning and Sustainable Development of Yok Don National Park in 2010-2020,150pp. Chaiyo, U., Garivait,  S.,  Wanthongchai,  K., 2011: Carbon storage in Above-Ground Biomass of Tropical Deciduous Forest in Ratchaburi Province, Thailand. World Academy of Science, Engineering and Technology, pp. 636-641.. Chave, J., Andalo, C., Brown, S., Cairns, M.A. et al., 2005:  Tree  allometry  and  improved  estimation  of  carbon  stocks  and  balance  in  tropical  forests. Oecologia Vol. 145, No. 1, pp. 87-99. Guide to the Kyoto Protocol to United Nations framework convention on climate change, 1998. Howarth, Wickware, 1981: Spatial analysis of land cover and land use in evaluating land degradation in Northwestern Al-Mafraq city, Jordan, pp. 55-62. IPCC, 2003: Good Practice Guidance for Land Use, Land-Use Change and Forestry. IPCC National Greenhouse Gas Inventories Programme Technical Support Unit.  Printed in Japan.ISBN 4-88788-003-0.2003, 590pp. IPCC, 2006: Guidelines for National Greenhouse Gas Inventories. Volume 4: Agriculture, Forestry and Other Land Use. Chapter 4. Forest land, 83 pp. Losi, C.J. et al., 2003: Analysis of alternative methods for estimating carbon stock in young tropical plantations. Forest Ecology and Management, 184(1-3): 355-368. Lu, D. S., 2006: The potential and challenge of remote sensing-based biomass estimation. International Journal of Remote Sensing. Vol. 27, No. 7,: 1297-1328. Luong, N.V., 2011: Essay to use remote sensing images to estimate biomass as a basis for calculating the amount of CO2 sequestration by vegetation cover in in Yok Don National Park, Highlands of Viet Nam.Scientific Conference "Research, development and application of space technology-2011".ISBN: 987-604-913-032-8. Hanoi. 9pp. Ministry of Agriculture and Rural Development (MARD).Circular 34/TT-BNN issued by (MARD) of Vietnamese government, 2009: Quy định tiêu chí xác định và phân loại rừng (in Vietnamese), translated by Luong N.V-Regulation on criteria for identifying and classifying forest (in English), 5, 3. Phat, N.K. et al., 2004 : Appropriate measures for conservation of terrestrial carbon stocks- Analysis of trends of forest management in Southeast Asia. Forest Ecology and Management, 191(1-3): 283-299. Thin, N. N. et al., 2007: The vegetation of Yok Don National Park, a special ecosystem in Central Highlands of Vietnam, 2007,6, 4-5. Trung, T. V.The tropical forest ecosystem in Vietnam.Science and Technics Publishing House, Hanoi. Chapter IV, 1998, 291pp. Trung, T.V.The vegetation cover in Vietnam. Science and Technics Publishing House, Hanoi. Chapter IV, V, 1978: 276 pp. UNESCO Paris, 1973. International classification and mapping of vegetation. Published by the United Nations Educational, Scientific and Cultural Organization. ISBN 92-3-001046-4 LC No.  72-96442, 1973, 102pp. UN-REDD in Vietnam programme, 2012: Guidelines on Destructive Measurement for Forest Biomass Estimation for technical staff use. (Version for discussion). UN-REDD Vietnam Programme, 2012: Tree allometric equation development for estimation of forest above-ground biomass in Viet Nam. Part A - Introduction and Background of the Study Viet Nam.

Quantifying biomass fluctuations in Mitchell grassland, Queensland, using multi-temporal MODIS data

Abstract: The Mitchell grassland in northern Australia covers more than 335,300 sq km of land. The sustainability of this unique ecosystem is the key to efficient use of grassland in related economic activities. In this regard, satellite images provide the most effective data source to monitor, especially when consider its huge coverage and homogeneous land cover. The amount of greenery of the grassland is directly related to fluctuations of the rainfall which has greater variations from year to year. The present study links greenness changes of Mitchell grass with rainfall fluctuations within rainy months. We utilized temporal MODIS images to study greenness changes in a selected area in eastern region of the Mitchell grassland. After evaluating the use of Normalized Difference Vegetation Index (NDVI) and Enhanced Vegetation Index (EVI) in grassland and cropland studies, NDVI was used to extract greenness of the grassland. The mapping task was supported by field investigations already completed in the area and very high resolution image potions available in Google Image. Results clearly indicated a significant change in greenness, when the rainfall amount is changing within rainy months. The finding can be developed into a methodology that gives recommendations for the use of grassland, according to the productivity of the rainy season. Future research directions will include NDVI calculations for different dry months, and collecting field photo evidence under different rainfall conditions, to build a solid relationship between rainfall and sustainable use of the grassland

Phenological assessment of Darling River claypan lakes using satellite imagery

Earth observation satellites with higher spatial resolution capability provide four or more image bands at less than 10m resolution and ideally suitable for conducting numerous land cover classifications, especially for small areas. This study uses AVENIR 2, SPOT, and DigitalGlobe images on multitemporal basis to examine the health of clay pan lakes associate with spontaneous wetlands in the Murray-Darling River Basin, Australia. These unique lakes along the river add an essential lifeline to numerous flora and fauna in harsh central Australian climate. A research conducted in 1996 estimated that there are 18,500 wetlands located within the basin. In another recent study, 98 waterbird species were recorded in these wetlands. The same study recorded that bird species like ibis and egrets have very high sensitivity for water level changes. However, extreme fluctuations in water levels are negatively affecting the health of these lakes and wetlands. Due to the ever increasing human activities such as irrigation, recreation, and changing land use of the river system and highly fluctuating river water regime and water quality, the spatial status of small linear shape lakes can be used as a phenological indicator to assess the river health. After a long drought spell, Darling River catchment received a huge amount of rainfall in last two years, causing dynamic environmental changes along the river. These changes can be affected to mapping aspects too, due to the expansion of wetlands associate with lakes. The study founded that high resolution satellite images can be counted as a good candidate to monitor small land cover features in these wetlands. Mapping detail land cover of selected lakes under number of extreme weather conditions like prolong drought and heavy rain will help to understand and evaluate spatial conditions of claypan lakes and the surrounding environment