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Predicting upslope expansion of sub-alpine forest in the Makalu Barun National Park, Eastern Nepal, with a hybrid cartographic model

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Journal of Forestry Research 2018年第1期29卷 129-137页

作者： Parveen Kumar Chhetri Department of Geography Texas A&M UniversityCollege Station

The natural upper boundary of a forest（forest line） in mountain environments is an indicator of climate conditions. An increase in global average temperatures has resulted in an upward advance of the forest line. This advance may result in fragmentation of the alpine ecosystem and a loss of biodiversity. Therefore, it is important to identify potential areas where current forests can advance under scenarios of future climate change. I used expert knowledge and cartographic modeling to create a hybrid cartographic model considering five topographic variables to predict areas where forest line can expand in the future.The prediction accuracy of the model is around 82%. The model is able to predict areas above the current forest line that are suitable or unsuitable for future forest advance.Further inclusion of high-resolution satellite imagery and digital elevation models, as well as field-based information into the model can help to improve the model accuracy.

关键词： Climate change Forest line Forest line advance Hybrid cartographic model Makalu Barun National Park

Morphological and Microstructural Evidences of Paleo-Seisminc Occurrences in an Earthquake Prone Zone of Tripura, India

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Journal of Earth Science 2014年第2期25卷 289-298页

作者： Sudip Dey Sushmita Paul Prasamita Sarkar Department of Geography and Disaster Management Tripura University

Morphology and structure of a faulted zone not only express the present status but also preserve the evidences of early seismo-tectonic occurrences. The present paper aims to assess the morphological as well as subsurface evidences of early seismo-tectonic occurrences in an earth- quake prone zone of Baromura Hill, Tripura. Tectonically this is a part of Tripura-Mizoram fold belt and fall within Zone V of BIS seismic map. In the present research the tectonic lineaments of Baromura Hill was identified by using satellite data. For that purpose, Landsat TM shortwave in- frared, midwave infrared and near infrared was selected for preparing suitable band combination. A classified thermal infrared was used for final operation. From the remote sensing operation five clear tectonic lineaments were found. During the field work rock samples were collected for labora- tory testing. Thin sections of the rocks show that complex stress pattern was developed during the geological past which caused strong seismo-tectonic occurrences. From the study it can be assessed that though the nature of the paleo-seismic occurrences were almost same but the level of impact varied through spatial and temporal scales due different physical properties and arrangements. It is also clear from the study that the geological evolution of this place is more complex as it seems to be. Tectonic and geomorphic processes worked together through the Tertiary and Quaternary periods and played equally important role for landform evolution.

关键词： morphology tectonic lineament microstructure grain scale deformation Baromura Hill geomorphic process.

Use of Sentinel-1 imagery for flood management in a reservoir-regulated river basin

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Frontiers of Earth Science 2018年第3期12卷 506-520页

作者： T. PERROU A. GAR/OUD I. PARCHARIDIS Department of Geography Harokopio University of Athens Athens Greece European Space Agency/ESRIN Frascati Rome Italy Department of Geography University Paris Diderot Paris France

Flood hazard monitoring and mapping is of great importance because it represents a significant contribution to risk management. The present study investigated the flood event that occurred downstream from the transboundary Strymon River basin, more specifically at Serres basin-a reservoir-regulated basin, in the beginning of 2015. The focus of this study was to better understand the spatio-temporal dynamic of the flood and the causes that initiated the hazard. Within the Serres basin, the Strymon transboundary river outflows to Lake Kerkini, which regulates water flow downstream for irrigation purposes and flood protection. For this research, a dataset of Sentinel-1 SAR GRD images was collected and processed covering the period of October 2014-October 2015 to investigate the water level changes in Lake Kerkini. Based on SAR images, binary water/non-water products and multitemporal RGB amplitude images were generated and interpreted. Sentinel-1 products have proved to be an effective tool on flood hazard dynamic extension mapping and estimation of water extent bodies retained by small reservoirs. In agreement with hydro-meteorological data and the high-resolution DEM, it was conceived that the flood event occurred due to the water volume flowing from upstream in the reservoir and the large amount of water draining from the tributaries into nearby sub-basins. Moreover, inefficient water management of the overwhelming water flow through the dam could further strengthen the flood event. The proposed approach, which is entirely based on open access remotely sensed data and processing tools, could be implemented in the same area for past flood events to produce archive retrospective data, as well as in other similar reservoir-regulated river basins in terms of water management and flood risk management.

关键词： flood mapping Sentinel-1 SAR binary images multitemporal image river basin

Deep learning for real-time social media text classification for situation awareness-using Hurricanes Sandy,Harvey,and Irma as case studies

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International Journal of Digital Earth 2019年第11期12卷 1230-1247页

作者： Manzhu Yu Qunying Huang Han Qin Chris Scheele Chaowei Yang Department of Geography and Geoinformation Science George Mason UniveristyFairfaxVAUSA Department of Geography University of Wisconsin-MadisonMadisonWIUSA Ankura WashingtonDCUSA

Social media platforms have been contributing to disaster management during the past several years.Text mining solutions using traditional machine learning techniques have been developed to categorize the messages into different themes,such as caution and advice,to better understand the meaning and leverage useful information from the social media text content.However,these methods are mostly event specific and difficult to generalize for cross-event classifications.In other words,traditional classification models trained by historic datasets are not capable of categorizing social media messages from a future event.This research examines the capability of a convolutional neural network(CNN)model in cross-event Twitter topic classification based on three geo-tagged twitter datasets collected during Hurricanes Sandy,Harvey,and Irma.The performance of the CNN model is compared to two traditional machine learning methods:support vector machine(SVM)and logistic regression(LR).Experiment results showed that CNN models achieved a consistently better accuracy for both single event and crossevent evaluation scenarios whereas SVM and LR models had lower accuracy compared to their own single event accuracy results.This indicated that the CNN model has the capability of pre-training Twitter data from past events to classify for an upcoming event for situational awareness.

关键词： Text mining deep learning hurricanes Twitter convolutional neural network situational awareness

Evaluation of MODIS-Landsat and AVHRR-Landsat NDVI data fusion using a single pair base reference image:a case study in a tropical upstream catchment on Java,Indonesia

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International Journal of Digital Earth 2022年第1期15卷 164-197页

作者： Andry Rustanto Martijn J.Booij department of Water Engineering and Management Faculty of Engineering TechnologyUniversity of TwenteEnschedethe Netherlands Department of Geography Universitas IndonesiaDepokIndonesia

Image blending is one of the alternative methods to fill temporal gaps in the monitoring of historical vegetation properties using continuous NDVI derived from Landsat 5 TM/7 ETM+and 8 OLI images.Frequent cloud occurrence in the tropical upstream catchment limits the use of image blending methods that allow to employment of a single pair base reference.This study aims to evaluate two image blending methods with nine input data configurations to select the most applicable one.Scatter plots and statistical indices such as ME,RMSE,model efficiency and structure similarity showed FSDAF outperforms STARFM in generating both synthetic Landsat 8 OLI NDVI and Landsat 5 TM/7 ETM+NDVI when employing unsupervised and supervised classification images,respectively,where both were applied along with MODIS NDVI 250 m v.005.When generating synthetic Landsat 5 TM/7 ETM+NDVI using AVHRR NDVI,both algorithms performed similarly.However,when considering the temporal over spatial variance ratio between base reference and predictor images,both algorithms performed almost similar when the value close to minimum.This study shows that selection of image blending algorithm with use single pair base reference image should consider input data configuration and temporal over spatial variance ratio.

关键词： Image blending Landsat NDVI MODIS NDVI AVHRR NDVI tropical upstream catchment

Spatial expansion effects on urban ecosystem services supply-demand mismatching in Guanzhong Plain Urban Agglomeration of China

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Journal of Geographical Sciences 2022年第5期32卷 806-828页

作者： PENG Lixian ZHANG Liwei LI Xupu WANG Zhuangzhuang WANG Hao JIAO Lei Department of Geography School of Geography and TourismShaanxi Normal UniversityXi’an710119China State Key Laboratory of Urban and Regional Ecology Research Center for Eco-Environmental SciencesCASBeijing100085China

Global urbanization has led to drastic land use change,interfering the ecosystem services(ES)supply-demand balance,in turn threatening the well-being of humans.However,existing studies mainly stranded at the historical and current analysis,and the effects of urban spatial expansion on the relationship between ES supply and demand in the future are less clear,in particular at an urban agglomeration scale.This study was constructed with a framework of assessing the effects of urban spatial expansion on ES supply-demand mismatching under different future scenarios in the Guanzhong Plain Urban Agglomeration(GPUA)by using the Future Land Use Simulation(FLUS)model and expert-based Land-Use and Land-Cover Change(LUCC)matrix.The results showed that:(1)Urban expansion is significant in the natural development(ND)scenario,mainly manifesting the great transfer of dry land to construction land.(2)The gap between total ES supply and demand is narrowed from 2000 to 2030 and the mismatch between ES supply and demand is mainly reflected in the spatial distribution pattern in the GPUA.The ES budgets were in high surplus in Northern Qinling Mountains and northeast mountain areas,while they were in severe deficit in urban center areas.The budgets deficit under the ND scenario in 2030 is the most severe.(3)The gradient differences of ES budgets of the GPUA between urban centers and suburbs increase from 2000 to 2030 under two scenarios.The deficit region expands largest under ND scenario.The findings revealed that ES declining and supply-demand mismatching were triggered by the drastic land-use change driven by rapid urban expansion.The expansion has brought about an increasing material demand and growing industries,threatening the sustainability of ecosystems.Scenarios setting could contribute to coordinating the relationship between future urban development and ecological protection,and the policy strategies proposed in the study could inform ecological management and urban planning in the regions facing the similar urbanization s

关键词： urban spatial expansion ES supply and demand FLUS expert-based LUCC matrix Guanzhong Plain Urban Agglomeration

Geospatial characteristics of fire occurrences in southern hemispheric Africa and Madagascar during 2001-2020

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Journal of Forestry Research 2023年第2期34卷 553-563页

作者： Chuyan Wan Shouraseni Sen Roy department of Earth and Planetary Sciences Northwestern UniversityEvanstonILUSA Department of Geography and Sustainable Development University of MiamiCoral GablesFLUSA

For this study of long-term spatial patterns and trends of active fires in southern hemispheric Africa and on Madagascar from 2001 to 2020,active fire data from the MODIS FIRMS global fire data products were analyzed.The annual center of fire concentration tended to migrate toward the preserved rainforests and nature conservation areas in the Congo Basin and the mountain forests on the northeastern coast of Madagascar.Fire frequency varied seasonally at both study areas.We used geo statistical analysis techniques,such as measures of dispersion and emerging hot spot analysis,to reveal long-term trends in spatial patterns of fire events.In southern hemispheric Africa,the observed active fires tended to drift northward toward the Zambia-DRC border in the Congo basin.This northward migration progressed toward humid rainforests,which were better suited to sustaining repeated fire events.On Madagascar,the observed active fires tended to migrate toward the east coast in protected mountain forests.The spatial patterns of long-term trends showed a concentration of fires in the tropical regions of southern hemispheric Africa.Moreover,smaller clusters of new hot spots were located over eastern South Africa,overlapping with undifferentiated woodlands.On Madagascar,both hot and cold spots were identified and were separated by the highland region in the center of the island.Most of the eastern island was characterized by cold spots that received less precipitation than did the rest of the island.The presence of increasing hots spots in the densely vegetated areas highlights the urgent need for fire prevention and management in this region.

关键词： Emerging hot spots analysis FIRMS Forest fi res Madagascar MODIS Southern hemispheric Africa Wildfi res

A Systematic Study of Disaster Risk in Brunei Darussalam and Options for Vulnerability-Based Disaster Risk Reduction

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International Journal of Disaster Risk Science 2017年第2期8卷 208-223页

作者： Anthony Banyouko Ndah John Onu Odihi Environmental Studies Program Department of Geography and DevelopmentFaculty of Arts and Social ScienceUniversiti Brunei Darussalam Faculty of Social Sciences Department of GeographyUniversity of Maiduguri

This systematic study of disaster risk and disaster management efforts in Brunei Darussalam uncovers the reasons why floods and landslides in particular continue to inflict significant social,economic,and psychological toll.Vulnerability to the impacts of hydro-meteorological hazards continue to rise despite international awareness and improved disaster governance and information,and regardless of the vast financial and material resources spent on structural and nonstructural measures for disaster relief and community awareness.Our premise is that,a poor diagnosis of the disaster risk issue is at the root of the disaster risk dilemma in Brunei Darussalam.We conducted our vulnerability-centered disaster risk assessment based largely on the Pressure and Release(PAR) Model proposed by Wisner et al.Our research results reveal that:(1)Hazard-risk in Brunei is high due to the impact of global climate change,the country's local geography,and Brunei's relative location in the Asia–Pacific Region.Limited reporting of localized disasters to international databases however fuels the misperception of low disaster risk in Brunei;(2) High community vulnerability and disaster risk is due to limited knowledge,awareness,and motivation among the general population,which prevents effective mitigation and adaptation to low magnitude but recurrent hazardous events;and(3) Partial incorporation of disasterrisk reduction into governance structures and development plans contributes to heightened disaster risks.Integrated frameworks are proposed that can minimize social vulnerability,reduce disaster risk,and enhance community resilience and adaptive capacity as part of a strengthened governance mechanism.Coupled with improvements in preparedness,response,recovery,and reconstruction promoted by the National Disaster Management Centre(NDMC),vulnerability and disaster risk can be minimized,and a more inclusive and sustainable growth can be generated.

关键词： Brunei Darussalam Community vulnerability Disaster risk reduction Pressure and Release Model(PAR)

Comparisons of two global built area land cover datasets in methods to disaggregate human population in eleven countries from the global South

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International Journal of Digital Earth 2020年第1期13卷 78-100页

作者： Forrest R.Stevens Andrea E.Gaughan Jeremiah JNieves Adam King Alessandro Sorichetta Catherine Linard Andrew JTatem Department of Geography and Geosciences University of LouisvilleLouisvilleKYUSA WorldPop Department of Geography and EnvironmentUniversity of SouthamptonSouthamptonUK Spatial Epidemiology Lab(SpELL) UniversitéLibre de BruxellesBrusselsBelgium Department of Geography Universitéde NamurNamurBelgium Flowminder Foundation StockholmSweden

Mapping built land cover at unprecedented detail has been facilitated by increasing availability of global high-resolution imagery and image processing methods.These advances in urban feature extraction and built-area detection can refine the mapping of human population densities,especially in lower income countries where rapid urbanization and changing population is accompanied by frequently out-of-date or inaccurate census data.However,in these contexts it is unclear how best to use built-area data to disaggregate areal,count-based census data.Here we tested two methods using remotely sensed,built-area land cover data to disaggregate population data.These included simple,areal weighting and more complex statistical models with other ancillary information.Outcomes were assessed across eleven countries,representing different world regions varying in population densities,types of built infrastructure,and environmental characteristics.We found that for seven of 11 countries a Random Forest-based,machine learning approach outperforms simple,binary dasymetric disaggregation into remotely-sensed built areas.For these more complex models there was little evidence to support using any single built land cover input over the rest,and in most cases using more than one built-area data product resulted in higher predictive capacity.We discuss these results and implications for future population modeling approaches.

关键词： Land cover built areas remote sensing settlement mapping population modeling