Land cover change on Mt. Pinatubo,the Philippines,monitored using ASTER VNIR

Ashfall and pyroclastic flows from the large eruption of June 1991 destroyed much of the vegetation on the flanks of Mt. Pinatubo. Subsequent vegetation recovery has helped stabilize slopes and reduce debris flow hazard. In this project, visible and near-infrared (VNIR) satellite imagery from the advanced spaceborne thermal emission and reflection radiometer (ASTER) captured at a similar time of year in 2001, 2004 and 2008 were used to quantify vegetation recovery within 22 upland watersheds on the mountain, 10–16 years after the eruption took place. Differences in the normalized difference vegetation index (NDVI) derived from these images were used to measure the areal extent of losses and gains in ground cover and derive average net rates of change in ground cover. The success of this approach was dependent on post-processing ASTER imagery to correct for the effects of variation in satellite-sun geometry and vegetation reflectance and to calibrate and adjust the derived NDVI images for the influence of different atmospheric conditions at the time of image capture. All watersheds showed a variable pattern of losses and gains in vegetation and ground cover. Losses were related to shifting cultivation practices and gully and channel migration, and these amounted to 1–12% of watershed areas. Gains were related to revegetation of pyroclastic flows, recent channel terraces, abandoned gardens and areas of burnt vegetation, and these amounted to 3–45% of watershed areas. Consistent overall net gains in ground cover were observed in all watersheds, with the average NDVI increasing by up to 0.074 over each consecutive 3-year period. The rates of change in NDVI were used to derive a vegetation recovery curve from bare ground. The result showed that it will take approximately 50 years for hillslopes to regain a dense vegetative cover in this climate. This supports published findings which indicate rapid recovery of vegetation in tropical environments following such large volcanic eruptions. Results additionally showed that the trajectory of change and the speed of recovery were influenced by terrain type, geology, watershed morphology and the activity of erosion and depositional processes. Prior to 2001, revegetation had been fastest on mountain slopes that helped protect vegetation from the effects of eruption. Gains in ground cover are now greatest in areas that were most impacted by the eruption.     

Eruptive history of Dubbi volcano,northeast Afar (Eritrea), revealed by optical and SAR image interpretation

A study of the remote Dubbi volcano, located in the northeastern part of the Afar triangle, Eritrea, was carried out using JERS-1 Synthetic Aperture Radar (SAR) and Landsat Thematic Mapper (TM) imagery. It investigated the last known eruption of Dubbi volcano in 1861, the only volcano in Afar for which historical reports indicate a major explosive eruption. Various image processing techniques were tested and compared in order to map different volcanic units, including effusive and explosive products. Principal component analysis and optical-SAR fusion were found to be useful to determine the extent of the 1861 pumice deposits surrounding the volcano. SAR imagery revealed old lava flows buried below tephra deposits, emphasizing the ground penetrating property of the L-band (HH polarization). The interpretation obtained from satellite imagery was cross-checked with sparse historical testimonies and available ground-truth data. Two scenarios are proposed for the 1861 eruptive sequences in order to estimate the volumes of lava flows erupted and the timing of explosive and effusive activity. Identified as a bimodal basaltic-trachytic eruption, with a minimum volume of 1.2 km³ of hawaiite lava and a minimum area of 70 km² of trachytic pumice, it represents the largest known historic eruption in the Afar triangle. This paper raises the issue of the potential volcanic hazards posed by Dubbi, which concern both the local population and the maritime traffic using the strategic route of the Red Sea.     

The 2006 pyroclastic deposits of Merapi Volcano, Java, Indonesia: High-spatial resolution IKONOS images and complementary ground based observations

On 16 June 2006 an overpass of IKONOS coincided with the emplacement of an active block-and-ash flow fed by a lava dome collapse at Merapi Volcano (Java, Indonesia). It was the first moving pyroclastic flow recorded on a satellite image. The very high-spatial resolution of the image indicated the extent and impact of pyroclastic material that was deposited during and prior to the day of image acquisition. A number of features associated with the hazardous block-and-ash flows emplaced in narrow, deep gorges were mapped, interpreted and analysed. The high-spatial-resolution IKONOS imagery worked extremely well for identifying pyroclastic deposits.The block-and-ash flow and surge deposits recognized in the IKONOS images include: (1) several channel-confined flow lobes and tongues in the box-shaped gorge; (2) thin ash-cloud surge deposit and knocked-down trees in constricted areas on both slopes of the gorge; (3) fan-like overbank deposits on the Gendol-Tlogo interfluves from which flows were re-routed in the Tlogo minor valley; (4) massive overbank flow lobes on the right bank of the Gendol River, which destroyed the village of Kaliadem 0.5 km from the main channel. A small part of this flow was re-channelled into the Opak tributary valley.The high-resolution IKONOS images also helped us to identify geomorphic obstacles that enabled flows to ramp up and spill out from the sinuous channel, as flow avulsion. Flow avulsions are dangerous as the redirect flows to unexpected areas away from the main channel. Valley fills from previous deposits, channel bends, and anthropogenic barriers in the channel (locally known as Sabo dams) influence the down valley passage of the flows. Sabo dams, originally built to ameliorate the effect of high sediment load streams, caused block-and-ash flows to avulse of the containing channel, and devastate populated areas.     

Remote monitoring of Indonesian volcanoes using satellite data from the Internet

The Internet now harbours vast amounts of cheap and potentially useful remote sensing data. Advanced Very High Resolution Radiometer (AVHRR) data are being increasingly used for volcano surveillance, and the provision of AVHRR Global Area Coverage (GAC) imagery at no cost over the Internet offers the possibility of cheap volcano monitoring on a global scale. Herein we use an extensive, 690-scene AVHRR GAC dataset to observe volcanic activity in the Indonesian island arc between January 1996 and November 1997. Indonesia contains over 70 active volcanoes, with styles of activity during the observation period including active lava domes, lava flows, pyroclastic flows and hot crater lakes, many in close proximity to major centres of population. The detection potential of these and other phenomena in GAC data is assessed. Thermal anomalies were identified at ～18 volcanoes during the observation period, including lava flows at Anak Krakatau, persistent open-vent activity at Semeru and a previously unreported eruption at Sangeang Api volcano. Using these results, a classification scheme for night-time Indonesian GAC data is presented. Routine use of freely available high temporal resolution data such as AVHRR GAC could help elucidate cyclic activity at active volcanoes, which would contribute significantly to hazard mitigation in affected areas. Browse images of higher resolution data (e.g. SPOT) from the daily updated archives of the Centre for Remote Imaging, Sensing and Processing (CRISP) in Singapore also show potential as an aid to volcano monitoring in the region.     

厦门岛内涝灾害风险评价制图

城市内涝灾害风险评价图件是城市内涝灾害防灾减灾基础技术资料。利用城市管 网等基础地理数据,经过汇水区划分和管网概化以及参数率定建立厦门岛内涝模型,模拟出不 同重现期降雨量下厦门岛地表积水深度并作为内涝灾害风险评价中的危险性评价因子,以河网 影响度、敏感点密度、植被覆盖度作为孕灾环境的敏感性因子,人口密度、人均 GDP 作为承灾 体的易损性评价因子,建立厦门岛的内涝灾害风险评估模型,计算得到不同重现期下厦门岛内 涝灾害风险等级评价图。结果表明,随着重现期的增加高风险指数的区域逐渐增加,主要呈现 由沿海向岛内扩展的趋势,部分区域由于下垫面的构成如山体水系等影响表现出稳定的低风险 特征。     

Pyroclastic flows modelling using cellular automata

Cellular automata (CA) and derived computational paradigms represent an alternative approach to differential equations to model and simulating complex fluid dynamical systems, whose evolution depends on the local interactions of their constituent parts. A new notion of CA was developed according to an empirical method for modelling macroscopic phenomena; its application to PYR, a CA model for simulating pyroclastic flows, generated PYR2, which permitted an improvement of the model and a more efficient implementation. PYR2 was utilised for the 1991 eruption of Mt. Pinatubo in the Philippines islands and for the 1996 eruption of the Soufriere Hills in the Montserrat Island. Results of the simulations are satisfactory if the comparison between real and simulated event is performed, considering the area involved by the event and the variations of thickness of the deposit, as generated by collapsing volcanic columns.     

Watershed-Based Segmentation and Region Merging

In recent years, the watershed line has emerged as the primary tool of mathematical morphology for image segmentation. Several very efficient algorithms have been devised for the determination of watersheds. Nevertheless, the application of watershed algorithms to an image is often disappointing: the image is oversegmented into a large number of tiny, shallow watersheds, where one wanted to obtain only a few deep ones. This paper presents a novel approach to watershed merging. Mainly, it addresses the following question: given an image, what is the closest image that has a simpler watershed structure? The basic idea is to replicate the process of watershed merging that takes place when rain falls over a real landscape: smaller watersheds progressively fill until an overflow occurs. The water then flows to a nearby, larger or deeper watershed, in which the overflown watersheds are merged. The methods presented in this paper apply the minimum extensive modifications possible to a given image to obtain a new one that has many fewer watersheds but is still “close” to the original. Their usefulness is demonstrated for several biomedical applications.     

Assessing the activity of a large landslide in southern Italy by ground-monitoring and SAR interferometric techniques

Landslides are recognized as one of the most damaging natural hazards in Italy. Campania region represents a complex geological setting, where mass movements of different types are widespread, and urban expansion can be increasingly seen by the presence of buildings and infrastructure in landslide-prone areas. In such a context, monitoring of unstable slopes represents a key activity in the process of landslide risk prevention and mitigation, in order to correctly establish a cause–effect correlation and to predict the possible reactivation phases that may result in high costs for the human society. This article focuses on the application of different methods of landslide analysis and monitoring, including those developed more recently and based on data acquired by satellites and processed by synthetic aperture radar (SAR) interferometric techniques. The study area is a small town, Calitri, known worldwide for the large landslide reactivated by the 23 November 1980 earthquake that destroyed a large sector of the historical centre. The site has been investigated by two ground-monitoring campaigns, the analysis of which allowed identification of the evolution of landslide activity over time. Furthermore, differential SAR interferometry (DInSAR), based upon two different approaches, allowed us to produce point-wise and wide area deformation maps after processing data sets of Earth Resource Satellite 1/2 (ERS-1/2) images, respectively acquired in 1992–2001 and 1992–1995. The results obtained from this analysis highlighted the potentiality of remote-sensing tools in landslide hazard assessment and led to development of a research project based on the installation of corner reflectors along unstable slopes and aimed at creating a field–Earth observation monitoring system.     

ASTER- and field-based observations at Bezymianny Volcano: Focus on the 11 May 2007 pyroclastic flow deposit

Bezymianny (Kamchatka Peninsula, Russia) is an active stratovolcano, characterized by a summit lava dome and overlapping pyroclastic flow (PF) deposits to the southeast. Three explosive eruptions (24 December 2006, 11 May 2007, and 14 October 2007) generated PFs that were dominated by juvenile material and were emplaced primarily due to column collapse. Following this, a gravitational lava flow front collapse event generated block and ash flow on 5 November 2007. Moderate spatial resolution data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) instrument were collected between October 2006 and December 2007 to assist in post-eruption monitoring and interpretation of the volcanological processes that produced the PF deposits. Using multitemporal ASTER thermal infrared (TIR) data, three periods of increased activity were observed that coincided with each eruption and subsequent activity. During a field campaign in August 2007, the May 2007 PF deposit was investigated in detail. Eight ASTER TIR pixels (90 m spatial resolution) were selected from the 30 June 2007 ASTER TIR image, seven of which were accessible in the field. Forward-Looking Infrared (FLIR) image and thermocouple data over these areas were collected to observe thermal heterogeneities with distance along the PF deposit. Although synchronous ASTER data were not possible at the time of fieldwork due to cloud cover, a field survey of blocks versus ash in each pixel was carried out to investigate thermal and textural variation with distance from the vent and to provide preliminary field results. Based on the field-derived temperature data and surface block percentages, the May 2007 PF deposit was more block-rich in the medial portion of the flow surface, but more ash-dominated at the PF terminus region, which promoted more rapid cooling. We present multitemporal ASTER data spanning a 14 month period and highlight ground-based observations acquired within the same period of eruptive and dome-growth activity. These data collectively provide thermal radiative and emissivity information on an actively changing explosive volcanic system and specifically documents changes over recently-emplaced and cooling PF deposits.     

Watershed Forest Management Information System (WFMIS)

Maintenance of a sustainable clean water supply is critical for our future. However, watershed degradation is a common phenomenon around the world that leads to poor water quality. In order to protect water resources, the Watershed Forest Management Information System (WFMIS), was developed as an extension of ArcGIS^® and is described in this paper. There are three submodels to address nonpoint source pollution mitigation, road system management, and silvicultural operations, respectively. The Watershed Management Priority Indices (WMPI) is a zoning approach to prioritize critical areas for conservation and restoration management. It meets the critical need to spatially differentiate land cover and site characteristics within a watershed to quantify their relative influence on overall water quality. The Forest Road Evaluation System (FRES) is a module to evaluate road networks in order to develop preventive management strategies. The Harvest Schedule Review System (HSRS) is a module to analyze and evaluate multi-year and multi-unit forest harvesting to assist in the reduction of impact on water yield and associated changes in water quality. The WFMIS utilizes commonly available spatial data and has user friendly interfaces to assist foresters and planners to manage watersheds in an environmentally healthy way. Application examples of each submodel are presented.     

A spatial–temporal analysis of impacts from human development on the Shih-men Reservoir watershed,Taiwan

Human activity such as the development of slope land around watersheds has dramatically affected the ecological environment in Taiwan. This situation has been aggravated by heavy precipitation from typhoons in the summertime. The results include serious soil erosion and mass movement in the Shih-men Reservoir watershed. In order to identify the most fragile areas and seek the triggering factors of landslide changes that can cause turbid currents in the Shih-men Reservoir watershed, this study integrates different types of satellite imagery and geographic information system data to determine changes in land cover and vegetation cover since the early 1970s. Results from spatial regression models indicate road and land uses are the main factors that lead to slope failure along roads and contribute to a large number of landslides in environmental hotspots like the Baishih River sub-watershed. Soil erosion estimates indicate a positive relationship between the increases in landslide and soil loss areas and the road system development. Therefore, human development has a significant negative influence both on sensitive mountainous watersheds and on critical environmental hotspots.     

Remote sensing data types and techniques for lahar path detection: A case study at Mt Ruapehu, New Zealand

Mt Ruapehu is New Zealand's most active onshore volcano. In 2007, the volcano produced a large lahar following a break-out from the summit Crater Lake. Here, satellite and airborne remote sensing and image processing is used to extract the path of the lahar using ASTER and SPOT5 visible and near infra-red imagery, ALOS-PALSAR L-band synthetic aperture RADAR data, and airborne LiDAR. The results obtained from each of these datasets were compared to the lahar deposit manually digitized from aerial photography. SPOT5 imagery produced the most accurate map of the lahar deposit (77% correct), even though these data were acquired a year after the event. This is attributed to the spatial resolution of the data. The ALOS-PALSAR coherence mapping calculated from images acquired 2 months before and nine months after the lahar was not as accurate as that obtained using the optical imagery (43% correct), but this was still considered an important tool for acquiring data during cloudy periods. LiDAR topographic data, collected to constrain geomorphic changes caused by the lahar, was the least accurate in terms of mapping the lahar path (28% correct). No single technique was deemed to be the most accurate under all circumstances, and a combination of data types would produce the best results. By combining the satellite and LiDAR data, it was possible to accurately classify 92% of the lahar path.     

智能叫应系统在数字孪生凤凰河小流域“四预”中的应用

传统山洪预警发布手段存在叫不醒、无回应、效率低等问题，“叫应-反馈”机制落实不到位，不能完全实现闭环管理。为解决此类问题，安徽省基于已建省级山洪灾害监测预警平台，以大别山腹地山洪频发、易发的凤凰河小流域为试点，进一步完善小流域山洪灾害“四预”能力建设，将智能语音技术应用在小流域“四预”的临灾预警发布场景中。开发基于语音识别、语音合成、自然语言处理等人工智能技术的山洪预警智能叫应系统，具有多场景话术训练、自动群呼预警信息、实时转写叫应内容、预警发布可视化动态监控、叫应结果统计分析等实用功能。系统实现小流域山洪灾害预警发布全过程留痕，切实落实临灾预警叫应机制，解决水利用户在山洪灾害预警信息发布方面的难题，确保预警信息及时叫应到基层责任人。     

A window-based inquiry system for design discharge based on geomorphic runoff modeling

When hydraulic design decisions are made in a watershed, engineers rely on estimation of the design discharge. Historically, they have applied empirical methods to do this, but empirical methods can only describe the hydrologic characteristics of the watersheds from which they were derived. Although more advanced methods now exist, engineers find them challenging to use because of the abundant data needed and intensive data analyses. In this study, we make the more advanced hydrological analysis methods simpler to use by linking them with DEM terrain analyses in a GIS platform. The system provides hydrologic and geomorphic information needed to create a design discharge at any location in a watershed. Since the system allows users to test several locations of subwatershed outlets, it is convenient for them to examine different aspects for engineering alternatives.     

Remote sensing and geologic mapping of glaciovolcanic deposits in the region surrounding Askja (Dyngjufjöll) volcano,Iceland

The surface geology of the Northern Volcanic Zone in Iceland is dominated by volcanic ridges, central volcanoes, shield volcanoes, and tuyas. The largest features are typically ice-confined (glaciovolcanic) in origin, and are overlain by voluminous Holocene (subaerial) lavas and glacial outwash deposits. The literature has focused heavily on prominent or very young features, neglecting small and older volcanic features. The purpose of this study is to demonstrate the application of remote-sensing mapping techniques to the glaciovolcanic environment in order to identify dominant lithologies and determine locations for textural, stratigraphic, and age studies. The deposits targeted in this study occur on and around Askja volcano, in central Iceland, including Pleistocene glaciovolcanic tuffs and subaerial pumice from the 1875 rhyolitic eruption of Askja. Data from the Advanced Spaceborne Thermal Emission and Reflection Radiometer (ASTER) were used in conjunction with previously published geologic and remote-sensing data sets and recent field work on glaciovolcanic deposits of Askja for validation. Remotely acquired data sets include aerial photographs and one ASTER scene obtained in August 2010. Visible and near-infrared (VNIR) and thermal infrared (TIR) classifications and linear deconvolution of the TIR emissivity data were performed using end-members derived from regions of interest and laboratory spectra. End-members were selected from samples of representative lithologic units within the field area, including glaciovolcanic deposits (pillow lavas, tuffs, etc.), historical deposits (1875 pumice, 1920s basaltic lavas), and Holocene basaltic lavas from Askja. The results demonstrate the potential for remote sensing-based ground cover mapping of areas of glaciovolcanic deposits relevant to palaeo-ice reconstructions in areas such as Iceland, Antarctica, and British Columbia. Remote sensing-based mapping will benefit glaciovolcanic studies, by determining the lithologic variability of these relatively inaccessible massifs and serving as an important springboard for the identification of future field sites in remote areas.     

A new framework for modeling decentralized low impact developments using Soil and Water Assessment Tool

Assessing the performance of LID practices at a catchment scale is important in managing urban watersheds. Few modeling tools exist that are capable of explicitly representing the hydrological mechanisms of LIDs while considering the diverse land uses of urban watersheds. In this paper, we propose computational modules that simulate the hydrological processes of LIDs including green roof, rain garden, cistern, and porous pavement. The applicability of the modules was evaluated using plot scale experimental monitoring data. The effectiveness of LIDs was investigated in a highly urbanized watershed located in Austin, TX. Results indicate that the performance of LIDs is sensitive to LID configurations, application areas, and storm event characteristics, suggesting the need for studies on spatial optimization of LIDs and critical storm events to maximize the utility of LIDs. The LID modules offer a comprehensive modeling framework that explicitly simulates the water quantity processes of the LIDs considering landscape heterogeneity.     

Preliminary analyses of SIR-B radar data for recent Hawaii lava flows

The Shuttle Imaging Radar (SIR-B) experiment acquired two L-band (23 cm wavelength) radar images (at about 28° and 48° incidence angles) over the Kilauea Volcano area of southeastern Hawaii. Geologic analysis of these data indicates that, although as lava flows and pyroclastic deposits can be discriminated, pahoehoe lava flows are not readily distinguished from surrounding low return materials. Preliminary analysis of data extracted from isolated flows indicates that flow type (i.e., as or pahoehoe) and relative age can be determined from their basic statistics and illumination angle.     

Validation and comparison of different techniques for the derivation of digital elevation models and volcanic monitoring (Vulcano Island,Italy)

High accurate digital elevation models (DEM) acquired periodically over a volcanic area can be used for monitoring crustal deformations. Airborne stereoscopic photography is a powerful tool for the derivation of high resolution DEM, especially when combined with Global Positioning System (GPS). We analyse data acquired on Vulcano Island (Italy) to assess the performance of two photogrammetry methods for DEM generation. The first method is based on automatic digital processing of scanned airborne stereo images from a film camera (Wild RC20). In the second method digital stereo data from the multi-spectral High Resolution Stereo Camera-Airborne (HRSC-A) are used. Accuracy assessment through comparison with kinematic GPS height profiles shows that both DEMs have accuracy on the order of few decimetres. Direct comparison of the two DEMs on the La Fossa volcanic cone provides a standard deviation of the residuals of 78 cm. Residuals greater than two metres between the two DEMs acquired at one year interval are locally evidenced in unstable areas with uneven morphology. The application of photogrammetric DEMs is also discussed within a SAR interferometry study carried out on Vulcano Island to evaluate the potentialities of such techniques for ground deformation monitoring. Although accuracy better than 1 m or 2 m is not required for satellite SAR interferometry, we show how the precise photogrammetric DEMs could still significantly improve SAR interferograms of Vulcano Island.     

Forecasting smog-related health hazard based on social media and physical sensor

Smog disasters are becoming more and more frequent and may cause severe consequences on the environment and public health, especially in urban areas. Social media as a real-time urban data source has become an increasingly effective channel to observe people׳s reactions on smog-related health hazard. It can be used to capture possible smog-related public health disasters in its early stage. We then propose a predictive analytic approach that utilizes both social media and physical sensor data to forecast the next day smog-related health hazard. First, we model smog-related health hazards and smog severity through mining raw microblogging text and network information diffusion data. Second, we developed an artificial neural network (ANN)-based model to forecast smog-related health hazard with the current health hazard and smog severity observations. We evaluate the performance of the approach with other alternative machine learning methods. To the best of our knowledge, we are the first to integrate social media and physical sensor data for smog-related health hazard forecasting. The empirical findings can help researchers to better understand the non-linear relationships between the current smog observations and the next day health hazard. In addition, this forecasting approach can provide decision support for smog-related health hazard management through functions like early warning.