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Uncertainty analysis of hydrological modeling in a tropicalarea using different algorithms

Frontiers of Earth Science 2018年第4期12卷 661-671页

作者： Ammar RAFIEI EMAM Martin KAPPAS Steven FASSNACHT Nguyen Hoang Khanh LINH department of Cartography GIS and Remote SensingUniversity of Goettingen37077GoettingenGermany Colorado State University Fort CollinsCO 80523-1476USA Faculty of Land Resources and Agricultural Environment (FLRAE) Flue University of Agriculture and Forestry (F1UAF)Hue UniversityHue City 0084Vietnam

Hydrological modeling outputs are subject to uncertainty resulting from different sources of errors (e.g., error in input data, model structure, and model parameters), making quantification of uncertainty in hydrological modeling imperative and meant to improve reliability of modeling results. The uncertainty analysis must solve difficulties in calibration of hydrological models, which further increase in areas with data scarcity. The purpose of this study is to apply four uncertainty analysis algorithms to a semi-distributed hydrological model, quantifying different source of uncertainties (especially parameter uncertainty) and evaluate their performance. In this study, the Soil and Water Assessment Tools (SWAT) eco-hydrological model was implemented for the watershed in the center of Vietnam. The sensitivity of parameters was analyzed, and the model was calibrated. The uncertainty analysis for the hydrological model was conducted based on four algorithms: Generalized Likelihood Uncertainty Estimation (GLUE), Sequential Uncertainty Fitting (SUFI), Parameter Solution method (ParaSol) and Particle Swarm Optimization (PSO). The performance of the algorithms was compared using P-factor and Rfactor, coefficient of determination (R2), the Nash Sutcliffe coefficient of efficiency (NSE) and Percent Bias (PBIAS). The results showed the high performance of SUFI and PSO with P-factor>0.83, R-factor 0.91, NSE>0.89, and 0.18<0.32. Hence, we would suggest to use SUFI-2 initially to set the parameter ranges, and further use PSO for final analysis. Indeed, the uncertainty analysis must be accounted when the outcomes of the model use for policy or management decisions.

关键词： SWAT-CUP GLUE SUFI2 ParaSol PSO Vietnam

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Evaluating the Impact of Different Vegetation Types on NEE: A Case Study of Banni Grasslands, India

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Journal of Environmental Protection 2021年第7期12卷 490-507页

作者： Usha Joshi G. Sandhya Kiran RS-gis and Ecophysiology Lab. Department of Botany Faculty of Science The Maharaja Sayajirao University of Baroda Vadodara India

Estimation of NEE of Grasslands ecosystems becomes mandatory as these grasslands with their wide spread (almost 40% of land of the earth) and high plant diversity play a major role in global carbon balances and NEE at both local and global scale. The present study has been focused on understanding the role of different plant species responsible for variation in NEE of the Banni Grasslands of India. These grasslands form a belt of arid grassland having low growing forbs, graminoids and scattered tree cover. Due to its wide spread and inaccessibility of Banni, this study utilized spatial approach for evaluating carbon emissions and NEE. Landsat data was utilized for vegetation type classification and SMAP data for extraction of NEE values proved their potential for categorising vegetation type and generating NEE values precisely. Three major plant types were identified from the study area viz., Grasslands, Land with Acacia and Land with Prosopis. Grasses were dominant covering 77% and the rest of the area was occupied by the other two classes, i.e. Acacia and Prosopis. The NEE values were higher for the grasses when compared to the other two plant species proving to be the active sinks when compared to other plants. The differential contribution of NEE by species has been depicted in the present work.

关键词： Normalized Difference Vegetation Index (NDVI) Fractional Vegetation Coverage (FVC) CO2 Flux Prosopis Grasses Acacia

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Morphometric Behavior of Shahzad Watershed, Lalitpur District, Uttar Pradesh, India: A Geospatial Approach

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Journal of Geographic Information System 2022年第3期14卷 193-220页

作者： Tanzeel Khatoon Akram Javed Interdisciplinary department of Remote Sensing and gis Applications Aligarh Muslim University Aligarh India department of Geology Aligarh Muslim University Aligarh India

Morphometric parameters are an important aspect for understanding the hydrological and morphological behaviour of the watershed. The present study is carried out in the region of the Bundelkhand region (India) which is socio-economically backward and has a history of frequent drought hence studying the watershed characteristics with reference to morphometric analysis becomes important. The remote sensing and gis technique has been utilized to mathematically quantify the parameters of the Shahzad watershed. The watershed is mainly fed by the Shahzad River (a tributary of Jamini River) flowing from south to north direction contributing the area of 1100 km2. The various morphometric aspect viz., linear, aerial, relief and morpho-tectonic parameters indicate that the watershed is elongated in shape and is slightly uplifted from the right side in the southern part. Moreover, the watershed experiences low dissection and low run-off discharge there by indicating less erosion in the area. The other factors like drainage density, drainage frequency, infiltration number and length of over land flow indicate that the watershed has high permeability and infiltration capacity. Through this study, it can be concluded that remote sensing and gis can be fruitfully utilized in analysing the morphometric behaviour of the region. This helps the researcher, planner and stakeholders to establish the relationship between watershed characteristics, thereby resulting in watershed management and sustainable resource management.

关键词： Shahzad Watershed Morphometric Analysis Watershed Characteristics Remote Sensing gis

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Using gis for Time Series Analysis of the Dead Sea from Remotely Sensing Data

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Open Journal of Civil Engineering 2014年第4期4卷 386-396页

作者： Maher A. El-Hallaq Mohammed O. Habboub Surveying and Geodesy Civil Engineering Department The Islamic University of Gaza Gaza Palestine gis IT Department The University College of Applied Science Gaza Palestine

Developed tools of Remote Sensing and Geographic Information System are rapidly spread in recent years in order to manage natural resources and to monitor environmental changes. This research aims to study the spatial behavior of the Dead Sea through time. To achieve this aim, time series analysis has been performed to track this behavior. For this purpose, fifteen satellite imageries are collected from 1972 to 2013 in addition to 2011-ASTGTM-DEM. Then, the satellite imageries are radiometrically and atmospherically corrected. Geographic Information system and Remote Sensing techniques are used for the spatio-temporal analysis in order to detect changes in the Dead Sea area, shape, water level, and volume. The study shows that the Dead Sea shrinks by 2.9 km2/year while the water level decreases by 0.65 m/year. Consequently, the volume changes by –0.42 km3/year. The study has also concluded that the direction of this shrinkage is from the north, northwest and from the south direction of the northern part due to the nature of the bathymetric slopes. In contrast, no shrinkage is detected from the east direction due to the same reason since the bathymetric slope is so sharp. The use of the Dead Sea water for industrial purposes by both Israel and Jordan is one of the essential factors that affect the area of the Dead Sea. The intensive human water consumption from the Jordan and Yarmouk Rivers for other usages is another main reason of this shrinkage in the area as well.

关键词： Dead Sea Time Series Analysis Remote Sensing gis

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Machine Learning and Deep Learning for Smart Urban Transportation Systems with GPS， gis， and Advanced Analytics: A Comprehensive Analysis

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Journal of Harbin Institute of Technology(New series) 2024年

作者： E. Kalaivanan S.Brindha department of Computer Science and Applications， St.Peters Institute of Higher Education And Research

As urbanization continues to accelerate， the challenges associated with managing transportation in metropolitan areas become increasingly complex. The surge in population density contributes to traffic congestion， impacting travel experiences and posing safety risks. Smart urban transportation management emerges as a strategic solution， conceptualized here as a multidimensional big data problem. The success of this strategy hinges on the effective collection of information from diverse， extensive， and heterogeneous data sources， necessitating the implementation of full-stack Information and Communication Technology (ICT) solutions. The main idea of the work is to investigate the current technologies of ITS and enhance the safety of urban transportation systems. Machine learning models， trained on historical data， can predict traffic congestion， allowing for the implementation of preventive measures. Deep learning architectures， with their ability to handle complex data representations， further refine traffic predictions， contributing to more accurate and dynamic transportation management. The background of this research underscores the challenges posed by traffic congestion in metropolitan areas and emphasizes the need for advanced technological solutions. By integrating GPS and gis technologies with machine learning algorithms， this work aims to pay attention to the development of intelligent transportation systems that not only address current challenges but also pave the way for future advancements in urban transportation management.

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Principle of small target detection for hyperspectral imagery

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Science China Earth Sciences 2007年第8期50卷 1225-1231页

作者： GENG XiuRui1,2,3 & ZHAO YongChao2,3,4 1 Research Center for Remote Sensing and gis, department of Geography, Beijing Normal University, Beijing 100875, China 2 State Key Laboratory of Remote Sensing Science, Chinese Academy of Sciences, Beijing 100101, China 3 Institute of Erectronics, Chinese Academy of Sciences, Beijing 100080, China 4 Center for for Assessment and Monitoring of Forest and Environmental Resources and Division of Ecosystem Sciences University of California Berkeley, CA 94720-3114, USA Research Center for Remote Sensing and gis Department of Geography Beijing Normal University Beijing China State Key Laboratory of Remote Sensing Science Chinese Academy of Sciences Beijing China Institute of Erectronics Chinese Academy of Sciences Beijing China Center for for Assessment and Monitoring of Forest and Environmental Resources and Division of Ecosystem Sciences University of California Berkeley USA

This paper generalizes the progress of algorithms in small target detection for hyperspectral imaging, and finds that whitening the image is the key point of many methods in small target detection. An al-gorithm is presented to detect desired targets by converting large targets into small ones based on the weighted sample autocorrelation matrix.

关键词： hyperspectral whiten target detection

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Geospatial and Statistical Analysis of Land Surface Temperature and Land Surface Characteristics of Jaipur and Ahmedabad Cities of India

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Journal of Geoscience and Environment Protection 2024年第8期12卷 1-19页

作者： Rupesh Kumar Gupta department of Continuing Education and Extension Faculty of Social Science University of Delhi Delhi India

Land surface temperature (LST) is a phenomenon that significantly affects the environment, the cities’ liveability, and the citizens’ well-being. This Study aims to perform a comparative study of the microclimate and Surface Urban Heat Island (SUHI) phenomenon of two metropolitan cities of India, i.e. Jaipur and Ahmedabad, using MODIS Satellite data, whereas Landsat Data was used to analyse the Land Surface Characteristics by an index-based approach. The Study’s findings reveal that Ahmedabad has 35.53 per cent of the total area classified as having a low potential, and 13.55 per cent is designated as a high potential LST zone. Meanwhile, in Jaipur, 30.45 per cent of the city’s total area is identified as a low potential LST zone and 12.69 per cent as a high potential LST zone. This Study highlights the importance of mitigating the UHI phenomenon in urban centres for the overall well-being of city dwellers. It will help policymakers and stakeholders comprehend plans and take initiatives to minimise the effects of the UHI phenomenon on rapidly growing cities. .

关键词： LST UHI Index-Based Approach Built-Up Remote Sensing gis

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The Role of Certificates and Labels for Cocoa in the Face of Climate Change: A Scientific Review

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American Journal of Climate Change 2024年第2期13卷 281-313页

作者： Charles Hans Opoku department of Agricultural Economics and Rural Development Georg-August-Universitt Gttingen Gttingen Germany

Climate change threatens cocoa quality, raising concerns regarding sustainable premium cocoa production. Evaluating the effectiveness of certification standards is imperative to address this concern effectively. A multi-stage method was employed for a systematic review of 39 peer-reviewed articles to highlight the impacts of climate change on the biophysical environment of cocoa and its implications for adapting Geographical Indications (gis). Additionally, a comprehensive review was conducted on climate-relevant standards of certificates in Ecuador, Indonesia, and Ghana. The findings of this study provide practical insights into possible difficulties that cocoa-producing countries may encounter in maintaining the distinctive flavours and quality trademarks of cocoa in the face of changing climate. Moreover, the findings emphasize the need for producer countries to prioritize viable adaptation and product differentiation strategies that meet sustainable marketing standards to protect gis or place-based intellectual property. Furthermore, the findings indicate certificates require effective multi-level climate change management and environmental-social-governance principles that promote scientifically proven mitigation strategies, such as increasing soil organic carbon, zero deforestation, and reducing emissions while striving to leverage local adaptation policies to reduce location-specific vulnerability. Finally, certificates can accelerate the expansion, intensification, and redistribution of sustainable production for gains that outweigh the inconveniences caused by climate change.

关键词： Adaptation Biophysical Environment Climate Change Cocoa Certificates Environmental Social Governance Mitigation Geographical Indications

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Mapping of Flood Risk Zones Using Multi-Criteria Approach and Radar a Case Study of Ala and Akure-Ofosu Communities, Ondo State, Nigeria

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International Journal of Geosciences 2024年第8期15卷 605-631页

作者： Olamiposi Caleb Fagunloye department of Remote Sensing and Geoscience Information Systems Federal University of Technology Akure Nigeria

Floods are among the worst natural catastrophes, devastating homes, businesses, public buildings, farms, and crops. Studies show that it’s not the flood itself that’s deadly but people’s vulnerability. This study investigates the Ala and Akure-Ofosu flood-prone zones;identifies elements that cause flooding in the study area;classifies each criterion by its effect;develops a flood risk map;estimates flood damage using Sentinel-1A SAR data;compares AHP results. Literature study and gis-computer database georeferenced fieldwork data. Photos from the 2020 Sentinel 2A satellite have been organized. Built-up area, cropland, rock, the body of water, and forest Land use and cover, slope, rainfall, soil, Euclidean River Distance, and flow accumulation were mapped. These variables were integrated into a Multi-Criteria Analysis (MCA) using gis tools, resulting in the creation of a flood risk map that categorizes the region into five risk zones: 5% of the area is identified as high-risk, 21% as low-risk, and 74% as moderate-risk. Copernicus SAR data from before and after the flood were processed on Google Earth Engine to map flood extent and ensured that the MCA map accurately reflected flood-prone areas. Periodic review, real-time flood susceptibility monitoring, early warning, and quick damage assessment are suggested to avoid flood danger and other environmental problems.

关键词： Remote Sensing Flooding gis Akure Flood Risk Damage Assessment

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Study on NDVI-T_s space by combining LAI and evapotranspiration

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Science China Earth Sciences 2006年第7期49卷 747-754页

作者： HAN Lijuan1,2,3, WANG Pengxin4, YANG Hua1,2,3, LIU Shaomin1,2,3 & WANG Jindi1,2,3 1. Research Center for Remote Sensing and gis, School of Geography, Beijing Normal University, Beijing 100875, China 2. State Key Laboratory of Remote Sensing Science, Beijing 100875, China 3. Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities, Beijing 100875, China 4. department of Information Management, College of Information and Electronic Engineering, China Agricultural University, Beijing 100083, China Research Center for Remote Sensing and gis School of Geography Beijing Normal University Beijing China State Key Laboratory of Remote Sensing Science Beijing China Beijing Key Laboratory for Remote Sensing of Environment and Digital Cities Beijing China department of Information Management College of Information and Electronic Engineering China Agricultural University Beijing China

This paper focuses on interpreting the different spatial relationships between NDVI and Ts, a triangular or a trapezoid, and on analyzing transformation conditions, the physical and ecological meanings of the vegetation index-surface temperature space as well. Further, we use the Tempera-ture-Vegetation Dryness Index (TVDI) to explain the existent meaning of a triangular space after NDVI reaches its saturated state by employing the relationships between NDVI, LAI and evapotranspiration. The specific relations between NDVI and Ts are useful for describing, validating and updating land surface models.

关键词： NDVI, land surface temperature, evapotranspiration, leave area index.

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