Pub Date : 2020-11-18DOI: 10.5194/isprs-archives-xliv-3-w1-2020-13-2020
V. Barrile, G. Bilotta, A. Fotia, E. Bernardo
Fires continue to devour hundreds of thousands of hectares of forest even in 2020, generating gigantic damage to the ecosystem, if we think that we are in the midst of a climate crisis caused precisely by CO2 emissions into the atmosphere by man, due to burning of fossil fuels. The action to safeguard the territory and the fight against its progressive environmental degradation focus a great attention towards forest fires, also considering the enormous environmental damage that these have caused to important and very large areas of the globe. The aim of the contribution that we here propose is the design and implementation of a software tool that performs predictive functions of triggering possible forest fires, thanks to the integration and manipulation of data from different sources and processed by predictive mathematical models, to support decisions; the comparison of techniques for the processing of high-resolution remote sensing data from optical satellites for the best automatic discrimination of the areas covered by fire plays a fundamental role in the analysis. This allows managing the burnt areas also considering subsequent fire risks, and the integration of the techniques developed in a GIS in order to obtain an accurate perimeter and a fire risk map prevision.
{"title":"INTEGRATED GIS SYSTEM FOR POST-FIRE HAZARD ASSESSMENTS WITH REMOTE SENSING","authors":"V. Barrile, G. Bilotta, A. Fotia, E. Bernardo","doi":"10.5194/isprs-archives-xliv-3-w1-2020-13-2020","DOIUrl":"https://doi.org/10.5194/isprs-archives-xliv-3-w1-2020-13-2020","url":null,"abstract":"Fires continue to devour hundreds of thousands of hectares of forest even in 2020, generating gigantic damage to the ecosystem, if we think that we are in the midst of a climate crisis caused precisely by CO2 emissions into the atmosphere by man, due to burning of fossil fuels. The action to safeguard the territory and the fight against its progressive environmental degradation focus a great attention towards forest fires, also considering the enormous environmental damage that these have caused to important and very large areas of the globe. The aim of the contribution that we here propose is the design and implementation of a software tool that performs predictive functions of triggering possible forest fires, thanks to the integration and manipulation of data from different sources and processed by predictive mathematical models, to support decisions; the comparison of techniques for the processing of high-resolution remote sensing data from optical satellites for the best automatic discrimination of the areas covered by fire plays a fundamental role in the analysis. This allows managing the burnt areas also considering subsequent fire risks, and the integration of the techniques developed in a GIS in order to obtain an accurate perimeter and a fire risk map prevision.","PeriodicalId":14757,"journal":{"name":"ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"11 1","pages":"13-20"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"89290022","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-18DOI: 10.5194/isprs-archives-xliv-3-w1-2020-65-2020
O. Isioye, E. A. Akomolafe, U. H. Ikwueze
This study explores the capabilities of Sentinel-2 over Landsat-8 Operational Land Imager (OLI) imageries for vegetation monitoring in the vegetated region of Minjibir LGA in Kano State. Accurate vegetation mapping is essential for monitoring crop and sustainable agricultural practice. Vegetation indices, comprising the Normalized Difference Vegetation Index (NDVI), Green Chlorophyll Index (GCI), Leaf Area Index (LAI) and Moisture Stress Index (MSI) were determined for each year. The findings showed an increase in Sentinel 2A value of the vegetation indices with respect to Landsat 8 throughout the time of the study (2015-2019). The best average performance over the supervised classification was obtained using Sentinel-2A bands, which are dependent on the training sample and resolution. While the spectral consistency of the data was inferred by cross-calibration analysis using regression analysis. The spatial consistency was assessed by descriptive statistical analysis of examined variables. Regarding the spatial consistency, the mean and standard deviation values of all variables were steady for all seasons excluding for the mean value of the LAI and MSI. Based on this finding, it is recommended that Sentinel-2A data could be used as a complementary data source with Landsat 8 OLI in vegetation assessment. * Corresponding author
{"title":"ACCURACY ANALYSIS OF SENTINEL 2A AND LANDSAT 8 OLI+ SATELLITE DATASETS OVER KANO STATE (NIGERIA) USING VEGETATION SPECTRAL INDICES","authors":"O. Isioye, E. A. Akomolafe, U. H. Ikwueze","doi":"10.5194/isprs-archives-xliv-3-w1-2020-65-2020","DOIUrl":"https://doi.org/10.5194/isprs-archives-xliv-3-w1-2020-65-2020","url":null,"abstract":"This study explores the capabilities of Sentinel-2 over Landsat-8 Operational Land Imager (OLI) imageries for vegetation monitoring in the vegetated region of Minjibir LGA in Kano State. Accurate vegetation mapping is essential for monitoring crop and sustainable agricultural practice. Vegetation indices, comprising the Normalized Difference Vegetation Index (NDVI), Green Chlorophyll Index (GCI), Leaf Area Index (LAI) and Moisture Stress Index (MSI) were determined for each year. The findings showed an increase in Sentinel 2A value of the vegetation indices with respect to Landsat 8 throughout the time of the study (2015-2019). The best average performance over the supervised classification was obtained using Sentinel-2A bands, which are dependent on the training sample and resolution. While the spectral consistency of the data was inferred by cross-calibration analysis using regression analysis. The spatial consistency was assessed by descriptive statistical analysis of examined variables. Regarding the spatial consistency, the mean and standard deviation values of all variables were steady for all seasons excluding for the mean value of the LAI and MSI. Based on this finding, it is recommended that Sentinel-2A data could be used as a complementary data source with Landsat 8 OLI in vegetation assessment. * Corresponding author","PeriodicalId":14757,"journal":{"name":"ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"39 1","pages":"65-72"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83580053","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-18DOI: 10.5194/isprs-archives-xliv-3-w1-2020-73-2020
J. Jia, S. Zlatanova, K. Zhang
With the growth of urban population and the increasing urban density, urban green space has become a kind of precious and limited resources. It not only has a positive impact on the health of urban residents with high work-life pressure but also offers opportunities as part of blue-green solutions for sustainable urban water management. Therefore, to effectively utilise the limited green spaces, experts are exploring a way of organising the green space layout to balance human needs and other urban developing requirements (e.g., in this case, urban stormwater management) within the certain common area. With this target, translating the space accessibility to human and other urban developments on green space into space parameter is a critical step to organize space model for the multi-functional green space. Although there are plenty of existing spatial parameters developed for evaluating human accessibility (such as travel distance, land-use, spatial connectivity etc.), there isn’t a way to organize them to satisfy the diverse evaluation needs from different research purposes. Besides, most of them are suitable for analyzing space on a city scale or at least a precinct scale in a 2D model. To the accurate design on a micro-scale, it is still a big challenge. The reason is some parameters for city analysis don’t work on a micro-scale, and some parameters should be reorganised in the evaluation algorithm or should include more micro-scale factors. Thus, this paper, based on the characteristics of human behaviour, redefines the complex conceptaccessibility and develop measurable parameters with feasible factors on micro-scale. Overall, this paper presents: (1) a new definition of walking accessibility of green space; (2) evaluation criteria (3) parameters (depth and Integration) reflecting connectivity criteria (4) Parameters (travel time and speed, slope, direction changes) relating travel distance criteria with updated evaluation algorithm and factors. This paper aims at useful spatial parameters and evaluation measures that are applicable to integrate human needs within multi-functional green space design, especially green stormwater management design.
{"title":"EXPLORING SPATIAL PARAMETERS TO EVALUATE HUMAN WALKING ACCESSIBILITY OF URBAN GREEN SPACE","authors":"J. Jia, S. Zlatanova, K. Zhang","doi":"10.5194/isprs-archives-xliv-3-w1-2020-73-2020","DOIUrl":"https://doi.org/10.5194/isprs-archives-xliv-3-w1-2020-73-2020","url":null,"abstract":"With the growth of urban population and the increasing urban density, urban green space has become a kind of precious and limited resources. It not only has a positive impact on the health of urban residents with high work-life pressure but also offers opportunities as part of blue-green solutions for sustainable urban water management. Therefore, to effectively utilise the limited green spaces, experts are exploring a way of organising the green space layout to balance human needs and other urban developing requirements (e.g., in this case, urban stormwater management) within the certain common area. With this target, translating the space accessibility to human and other urban developments on green space into space parameter is a critical step to organize space model for the multi-functional green space. Although there are plenty of existing spatial parameters developed for evaluating human accessibility (such as travel distance, land-use, spatial connectivity etc.), there isn’t a way to organize them to satisfy the diverse evaluation needs from different research purposes. Besides, most of them are suitable for analyzing space on a city scale or at least a precinct scale in a 2D model. To the accurate design on a micro-scale, it is still a big challenge. The reason is some parameters for city analysis don’t work on a micro-scale, and some parameters should be reorganised in the evaluation algorithm or should include more micro-scale factors. Thus, this paper, based on the characteristics of human behaviour, redefines the complex conceptaccessibility and develop measurable parameters with feasible factors on micro-scale. Overall, this paper presents: (1) a new definition of walking accessibility of green space; (2) evaluation criteria (3) parameters (depth and Integration) reflecting connectivity criteria (4) Parameters (travel time and speed, slope, direction changes) relating travel distance criteria with updated evaluation algorithm and factors. This paper aims at useful spatial parameters and evaluation measures that are applicable to integrate human needs within multi-functional green space design, especially green stormwater management design.","PeriodicalId":14757,"journal":{"name":"ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"12 1","pages":"73-80"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74875075","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-18DOI: 10.5194/isprs-archives-xliv-3-w1-2020-139-2020
C. Sun, S. Choy, Z. Chua, I. Aitkenhead, Y. Kuleshov
Australia frequently experiences extended periods of severe droughts which have a significant negative impact on populations and economy. To improve preparedness for drought, decision-support tools which provide comprehensive information about current dry conditions are essential. In this paper, we present a conceptual design for a Drought Risk Analyser (DRA) web-based information App for drought risk mapping developed using geographic information system (GIS). The developed DRA is based on combining Drought Hazard/Vulnerability/Exposure Indices (DHI, DVI and DEI respectively) into a final Drought Risk Index (DRI) for total of 542 Local Government Areas (LGA) in Australia. Drought indicators selected to compute drought hazard the Standardised Precipitation Index (SPI), the Vegetation Health Index (VHI) and Soil Moisture were obtained through the World Meteorological Organization (WMO) Space-based Weather and Climate Extremes Monitoring (SWCEM) international initiative. Australian Bureau of Statistics (ABS) census data were used to develop the drought-related population vulnerability index – DVI. Australian national Digital Elevation Model and catchment scale land use data were used to calculate the DEI. Implemented functionality of the designed DRA is illustrated using a case study for the 2019 drought in Australia. The DRA App will be beneficial for Australian farmers and rural communities to assist with decision making, as well as for LGA planners to gain insights on current state of drought risk at both local and national levels. The developed methodology of using space-based observations for assessing drought hazard could be applied for developing similar web-based information tools in drought-prone areas of other countries.
{"title":"GEOGRAPHIC INFORMATION SYSTEM FOR DROUGHT RISK MAPPING IN AUSTRALIA – DROUGHT RISK ANALYSER WEB APP","authors":"C. Sun, S. Choy, Z. Chua, I. Aitkenhead, Y. Kuleshov","doi":"10.5194/isprs-archives-xliv-3-w1-2020-139-2020","DOIUrl":"https://doi.org/10.5194/isprs-archives-xliv-3-w1-2020-139-2020","url":null,"abstract":"Australia frequently experiences extended periods of severe droughts which have a significant negative impact on populations and economy. To improve preparedness for drought, decision-support tools which provide comprehensive information about current dry conditions are essential. In this paper, we present a conceptual design for a Drought Risk Analyser (DRA) web-based information App for drought risk mapping developed using geographic information system (GIS). The developed DRA is based on combining Drought Hazard/Vulnerability/Exposure Indices (DHI, DVI and DEI respectively) into a final Drought Risk Index (DRI) for total of 542 Local Government Areas (LGA) in Australia. Drought indicators selected to compute drought hazard the Standardised Precipitation Index (SPI), the Vegetation Health Index (VHI) and Soil Moisture were obtained through the World Meteorological Organization (WMO) Space-based Weather and Climate Extremes Monitoring (SWCEM) international initiative. Australian Bureau of Statistics (ABS) census data were used to develop the drought-related population vulnerability index – DVI. Australian national Digital Elevation Model and catchment scale land use data were used to calculate the DEI. Implemented functionality of the designed DRA is illustrated using a case study for the 2019 drought in Australia. The DRA App will be beneficial for Australian farmers and rural communities to assist with decision making, as well as for LGA planners to gain insights on current state of drought risk at both local and national levels. The developed methodology of using space-based observations for assessing drought hazard could be applied for developing similar web-based information tools in drought-prone areas of other countries.","PeriodicalId":14757,"journal":{"name":"ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"48 1","pages":"139-144"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"79116376","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-18DOI: 10.5194/isprs-archives-xliv-3-w1-2020-125-2020
M. Rotilio, B. Tudini
Nowadays, it is well known that digitization has tenaciously become part of the construction industry. The document is aimed at being an analysis of the state of the art, focusing on the digitization application in post-disaster reconstruction. The new technologies have influenced all the actors involved to adapt to a new designing way, but this methodology brings with itself advantages and disadvantages. This paper will try to identify, clarify and review them. In fact, it will try to explain to what extent the logic related to the design and construction of the post-disaster area may be guided by a single common thread, that consists in the Building Information Modelling (BIM) methodology use. Through this methodology it is possible to reduce time and improve costs, thanks to the possibility to optimize the design and construction processes and to carry out virtual inspections and analysis based on the information from the construction phases. In addition, the various BIM tools, that allow interoperability, guarantee a semi-automatic review of the project's compliance with regulations and interference between the different design levels (structural, architectural, plant engineering and energy). In this way, there is the chance to improve the accuracy and reliability of the validation process. The entire process is also based on a multidisciplinary approach involving all branches of engineering. * Corresponding author
{"title":"THE ROLE OF DIGITIZATION IN POST-DISASTER RECONSTRUCTION","authors":"M. Rotilio, B. Tudini","doi":"10.5194/isprs-archives-xliv-3-w1-2020-125-2020","DOIUrl":"https://doi.org/10.5194/isprs-archives-xliv-3-w1-2020-125-2020","url":null,"abstract":"Nowadays, it is well known that digitization has tenaciously become part of the construction industry. The document is aimed at being an analysis of the state of the art, focusing on the digitization application in post-disaster reconstruction. The new technologies have influenced all the actors involved to adapt to a new designing way, but this methodology brings with itself advantages and disadvantages. This paper will try to identify, clarify and review them. In fact, it will try to explain to what extent the logic related to the design and construction of the post-disaster area may be guided by a single common thread, that consists in the Building Information Modelling (BIM) methodology use. Through this methodology it is possible to reduce time and improve costs, thanks to the possibility to optimize the design and construction processes and to carry out virtual inspections and analysis based on the information from the construction phases. In addition, the various BIM tools, that allow interoperability, guarantee a semi-automatic review of the project's compliance with regulations and interference between the different design levels (structural, architectural, plant engineering and energy). In this way, there is the chance to improve the accuracy and reliability of the validation process. The entire process is also based on a multidisciplinary approach involving all branches of engineering. * Corresponding author","PeriodicalId":14757,"journal":{"name":"ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"146 1","pages":"125-130"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"77469506","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-18DOI: 10.5194/isprs-archives-xliv-3-w1-2020-87-2020
I. Kuznetsov, E. Panidi, V. Korovka, V. Galkin, D. Voronov
In 2019-2020, we conducted a set of case studies devoted to the investigation and design of a methodology for GIS-based support of medical administration and planning on a city scale when accounting and controlling infectious disease. The studies were conducted for the administrative territory of St. Petersburg city (Russia), and were based upon the medical statistics data collected and accounted by St. Petersburg medical administration. The statistics included data on tuberculosis, human immunodeficiency virus and hepatitis infection. All the medical data used in the study are impersonalized. GIS-based MDMS prototype was developed upon the QGIS software. Moving forward in the previously formed study direction, now we are working on MDMS interface redesigning to facilitate its usability. Current activities are focussed on incorporation of the Web interface into previously developed MDMS prototype. The paper discusses development of the Web GIS interface prototype, and poses feature research and development aims. First feedback collected from medicals makes it possible to pose a Web-GIS-based MDMS as more flexible and easy to use, in comparison to the desktop-GIS-based. * Corresponding author
{"title":"WEB-BASED REPRESENTATION AND MANAGEMENT OF INFECTIOUS DISEASE DATA ON A CITY SCALE, CASE STUDY OF ST. PETERSBURG, RUSSIA","authors":"I. Kuznetsov, E. Panidi, V. Korovka, V. Galkin, D. Voronov","doi":"10.5194/isprs-archives-xliv-3-w1-2020-87-2020","DOIUrl":"https://doi.org/10.5194/isprs-archives-xliv-3-w1-2020-87-2020","url":null,"abstract":"In 2019-2020, we conducted a set of case studies devoted to the investigation and design of a methodology for GIS-based support of medical administration and planning on a city scale when accounting and controlling infectious disease. The studies were conducted for the administrative territory of St. Petersburg city (Russia), and were based upon the medical statistics data collected and accounted by St. Petersburg medical administration. The statistics included data on tuberculosis, human immunodeficiency virus and hepatitis infection. All the medical data used in the study are impersonalized. GIS-based MDMS prototype was developed upon the QGIS software. Moving forward in the previously formed study direction, now we are working on MDMS interface redesigning to facilitate its usability. Current activities are focussed on incorporation of the Web interface into previously developed MDMS prototype. The paper discusses development of the Web GIS interface prototype, and poses feature research and development aims. First feedback collected from medicals makes it possible to pose a Web-GIS-based MDMS as more flexible and easy to use, in comparison to the desktop-GIS-based. * Corresponding author","PeriodicalId":14757,"journal":{"name":"ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"11 1","pages":"87-91"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"85333542","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-18DOI: 10.5194/isprs-archives-xliv-3-w1-2020-151-2020
V. Yordanov, M. Brovelli, D. Carrion, L. Barazzetti, L. J. A. Francisco, H. R. Comia, M. I. Caravela
Mozambique is highly vulnerable to clime change induced hazards. The extreme weather impacts are directly related to the temperature and precipitation variations leading to more frequent and devastating events as floods, droughts and cyclones. Even though Mozambique has committed to international policies and has adopted mitigation measures, still it is lacking of sufficient capacity on various levels to lower the country’s vulnerability level. A consortium of eight partner countries, along with Mozambique, commenced a Climate Change Induced Disaster Management in Africa (CIDMA) project which aims at building education capacity through implementing geospatial information technology for improved disaster management in Mozambique. The core of the project is in developing three 10 ECTS courses that will implement state-of-the-art techniques and methodologies for dealing with climate change induced hazards. The courses are intended from one hand to university students and staff, but on the other to local authorities, organisations and companies occupied with disaster management, and local communities. As one of course, “Public Participatory GIS and Spatial Data Infrastructure in Disaster Management” is designed to prepare students to be able to produce thematic maps through GIS and crowdsourced data, as well as various EO data. With the presented course it is expected for the students to gain valuable theoretical and practical knowledge of GIS, VGI and SDI for exploiting, managing and processing geospatial data for risk mitigation and hazard mapping. Moreover, they will be skilled in using free and open-source GIS software, desktop and mobile mapping techniques, and free web-based dissemination and processing services. In addition, it is expected for the students to develop critical judgement for analysing data with the correct tools in case of climate induced disasters. This paper describes the design, structure and topics of the “Public Participatory GIS and Spatial Data Infrastructure in Disaster Management”.
{"title":"CAPACITY BUILDING FOR DISASTER MANAGEMENT IN MOZAMBIQUE THROUGH TEACHING PUBLIC PARTICIPATORY GIS AND SPATIAL DATA INFRASTRUCTURE","authors":"V. Yordanov, M. Brovelli, D. Carrion, L. Barazzetti, L. J. A. Francisco, H. R. Comia, M. I. Caravela","doi":"10.5194/isprs-archives-xliv-3-w1-2020-151-2020","DOIUrl":"https://doi.org/10.5194/isprs-archives-xliv-3-w1-2020-151-2020","url":null,"abstract":"Mozambique is highly vulnerable to clime change induced hazards. The extreme weather impacts are directly related to the temperature and precipitation variations leading to more frequent and devastating events as floods, droughts and cyclones. Even though Mozambique has committed to international policies and has adopted mitigation measures, still it is lacking of sufficient capacity on various levels to lower the country’s vulnerability level. A consortium of eight partner countries, along with Mozambique, commenced a Climate Change Induced Disaster Management in Africa (CIDMA) project which aims at building education capacity through implementing geospatial information technology for improved disaster management in Mozambique. The core of the project is in developing three 10 ECTS courses that will implement state-of-the-art techniques and methodologies for dealing with climate change induced hazards. The courses are intended from one hand to university students and staff, but on the other to local authorities, organisations and companies occupied with disaster management, and local communities. As one of course, “Public Participatory GIS and Spatial Data Infrastructure in Disaster Management” is designed to prepare students to be able to produce thematic maps through GIS and crowdsourced data, as well as various EO data. With the presented course it is expected for the students to gain valuable theoretical and practical knowledge of GIS, VGI and SDI for exploiting, managing and processing geospatial data for risk mitigation and hazard mapping. Moreover, they will be skilled in using free and open-source GIS software, desktop and mobile mapping techniques, and free web-based dissemination and processing services. In addition, it is expected for the students to develop critical judgement for analysing data with the correct tools in case of climate induced disasters. This paper describes the design, structure and topics of the “Public Participatory GIS and Spatial Data Infrastructure in Disaster Management”.","PeriodicalId":14757,"journal":{"name":"ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"39 1","pages":"151-158"},"PeriodicalIF":0.0,"publicationDate":"2020-11-18","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"83240611","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-17DOI: 10.5194/isprs-archives-xliv-m-2-2020-87-2020
S. Sen, N. Turel
Abstract. Classified Point Cloud data are increasingly the form of geospatial data that are used in engineering applications, smart digital twins and geospatial data infrastructure around the globe. Characterized by high positional accuracy such dense 3D datasets are often rated very highly for accuracy and reliability. However such data pose important challenges in semantic segmentation, especially in the context of Machine Learning(ML) techniques and the training data employed to provide classification codes to every point in massive point cloud datasets. These challenges are particularly significant since ML based processing of data is almost unavoidable due to the massive nature of the data that. We review different sources of uncertainty introduced by ML based classification and segmentation and outline concepts of uncertainty that is inherent in such automatically processed data. We also provide a theoretical framework for quantification of such uncertainty and argue that the standards of accuracy of such data should account for errors and omissions during auto segmentation and classification in addition to positional accuracy measures. Interestingly, the ability to quantify accuracies of ML based automation for processing such data is limited by the volume and velocity of such data.
{"title":"QUANTIFYING UNCERTAINTY IN CLASSIFIED POINT CLOUD DATA FOR GEOSPATIAL APPLICATIONS","authors":"S. Sen, N. Turel","doi":"10.5194/isprs-archives-xliv-m-2-2020-87-2020","DOIUrl":"https://doi.org/10.5194/isprs-archives-xliv-m-2-2020-87-2020","url":null,"abstract":"Abstract. Classified Point Cloud data are increasingly the form of geospatial data that are used in engineering applications, smart digital twins and geospatial data infrastructure around the globe. Characterized by high positional accuracy such dense 3D datasets are often rated very highly for accuracy and reliability. However such data pose important challenges in semantic segmentation, especially in the context of Machine Learning(ML) techniques and the training data employed to provide classification codes to every point in massive point cloud datasets. These challenges are particularly significant since ML based processing of data is almost unavoidable due to the massive nature of the data that. We review different sources of uncertainty introduced by ML based classification and segmentation and outline concepts of uncertainty that is inherent in such automatically processed data. We also provide a theoretical framework for quantification of such uncertainty and argue that the standards of accuracy of such data should account for errors and omissions during auto segmentation and classification in addition to positional accuracy measures. Interestingly, the ability to quantify accuracies of ML based automation for processing such data is limited by the volume and velocity of such data.","PeriodicalId":14757,"journal":{"name":"ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"86 1","pages":"87-93"},"PeriodicalIF":0.0,"publicationDate":"2020-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"74827640","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-17DOI: 10.5194/isprs-archives-xliv-m-2-2020-111-2020
C. Witharana, M. A. R. Bhuiyan, A. Liljedahl
Abstract. Permafrost thaw has been observed at several locations across the Arctic tundra in recent decades; however, the pan-Arctic extent and spatiotemporal dynamics of thaw remains poorly explained. Thaw-induced differential ground subsidence and dramatic microtopographic transitions, such as transformation of low-centered ice-wedge polygons (IWPs) into high-centered IWPs can be characterized using very high spatial resolution (VHSR) commercial satellite imagery. Arctic researchers demand for an accurate estimate of the distribution of IWPs and their status across the tundra domain. The entire Arctic has been imaged in 0.5 m resolution by commercial satellite sensors; however, mapping efforts are yet limited to small scales and confined to manual or semi-automated methods. Knowledge discovery through artificial intelligence (AI), big imagery, and high performance computing (HPC) resources is just starting to be realized in Arctic science. Large-scale deployment of VHSR imagery resources requires sophisticated computational approaches to automated image interpretation coupled with efficient use of HPC resources. We are in the process of developing an automated Mapping Application for Permafrost Land Environment (MAPLE) by combining big imagery, AI, and HPC resources. The MAPLE uses deep learning (DL) convolutional neural nets (CNNs) algorithms on HPCs to automatically map IWPs from VHSR commercial satellite imagery across large geographic domains. We trained and tasked a DLCNN semantic object instance segmentation algorithm to automatically classify IWPs from VHSR satellite imagery. Overall, our findings demonstrate the robust performances of IWP mapping algorithm in diverse tundra landscapes and lay a firm foundation for its operational-level application in repeated documentation of circumpolar permafrost disturbances.
{"title":"BIG IMAGERY AND HIGH PERFORMANCE COMPUTING AS RESOURCES TO UNDERSTAND CHANGING ARCTIC POLYGONAL TUNDRA","authors":"C. Witharana, M. A. R. Bhuiyan, A. Liljedahl","doi":"10.5194/isprs-archives-xliv-m-2-2020-111-2020","DOIUrl":"https://doi.org/10.5194/isprs-archives-xliv-m-2-2020-111-2020","url":null,"abstract":"Abstract. Permafrost thaw has been observed at several locations across the Arctic tundra in recent decades; however, the pan-Arctic extent and spatiotemporal dynamics of thaw remains poorly explained. Thaw-induced differential ground subsidence and dramatic microtopographic transitions, such as transformation of low-centered ice-wedge polygons (IWPs) into high-centered IWPs can be characterized using very high spatial resolution (VHSR) commercial satellite imagery. Arctic researchers demand for an accurate estimate of the distribution of IWPs and their status across the tundra domain. The entire Arctic has been imaged in 0.5 m resolution by commercial satellite sensors; however, mapping efforts are yet limited to small scales and confined to manual or semi-automated methods. Knowledge discovery through artificial intelligence (AI), big imagery, and high performance computing (HPC) resources is just starting to be realized in Arctic science. Large-scale deployment of VHSR imagery resources requires sophisticated computational approaches to automated image interpretation coupled with efficient use of HPC resources. We are in the process of developing an automated Mapping Application for Permafrost Land Environment (MAPLE) by combining big imagery, AI, and HPC resources. The MAPLE uses deep learning (DL) convolutional neural nets (CNNs) algorithms on HPCs to automatically map IWPs from VHSR commercial satellite imagery across large geographic domains. We trained and tasked a DLCNN semantic object instance segmentation algorithm to automatically classify IWPs from VHSR satellite imagery. Overall, our findings demonstrate the robust performances of IWP mapping algorithm in diverse tundra landscapes and lay a firm foundation for its operational-level application in repeated documentation of circumpolar permafrost disturbances.","PeriodicalId":14757,"journal":{"name":"ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"44 1","pages":"111-116"},"PeriodicalIF":0.0,"publicationDate":"2020-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"80942618","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
Pub Date : 2020-11-17DOI: 10.5194/isprs-archives-xliv-m-2-2020-105-2020
S. Weidler, R. Sivanpillai
Abstract. Every autumn, leaves of deciduous trees change from green to other colors and eventually drop to the ground. The rate of color change is influenced by a several factors including the amount of sunlight and temperature. As part of an inquiry-based learning activity, University of Wyoming students have been recording leaf color change (% change) and its drop date (%) in Aspen trees (Populus tremuloides) growing in Laramie (WY) using NEON’s (National Ecology Observation Network) Phenology data form. In this study, the data recorded from 2015 through 2018 were analyzed to identify trends in the rate of color change in dry and normal years. Trees that were in an area with a high amount of shade were observed to change leaf color and drop their leaves faster than those in areas that received more sun. This pattern was consistent even in years that experienced winter-like conditions in September. Findings from this multi-year study indicate that future environmental modeling projects must factor in the amount of sunlight received by aspen trees in the growing season into account.
{"title":"SUNBATHED ASPEN GROW TO SHOW HOW SUNLIGHT INFLUENCES ASPEN LEAF CHANGES IN THE AUTUMN SEASON","authors":"S. Weidler, R. Sivanpillai","doi":"10.5194/isprs-archives-xliv-m-2-2020-105-2020","DOIUrl":"https://doi.org/10.5194/isprs-archives-xliv-m-2-2020-105-2020","url":null,"abstract":"Abstract. Every autumn, leaves of deciduous trees change from green to other colors and eventually drop to the ground. The rate of color change is influenced by a several factors including the amount of sunlight and temperature. As part of an inquiry-based learning activity, University of Wyoming students have been recording leaf color change (% change) and its drop date (%) in Aspen trees (Populus tremuloides) growing in Laramie (WY) using NEON’s (National Ecology Observation Network) Phenology data form. In this study, the data recorded from 2015 through 2018 were analyzed to identify trends in the rate of color change in dry and normal years. Trees that were in an area with a high amount of shade were observed to change leaf color and drop their leaves faster than those in areas that received more sun. This pattern was consistent even in years that experienced winter-like conditions in September. Findings from this multi-year study indicate that future environmental modeling projects must factor in the amount of sunlight received by aspen trees in the growing season into account.","PeriodicalId":14757,"journal":{"name":"ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences","volume":"1 1","pages":"105-110"},"PeriodicalIF":0.0,"publicationDate":"2020-11-17","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"88495584","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}
京公网安备 11010802042870号
京ICP备2023020795号-1
扫码关注我们
求助内容：
应助结果提醒方式：