Journal articles: 'Remote sensing {Geographie}'

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Ehlers, M. "Fernerkundung und GIS bei Umweltmonitoring und Umweltmanagement." Geographica Helvetica 52, no. 1 (March 31, 1997): 5–10. http://dx.doi.org/10.5194/gh-52-5-1997.

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Abstract. Remote sensing image analysis Systems and geographie in formation Systems (GIS) show great promise for the Integra tion of a wide variety of spatial information as a support to en vironmental monitoring and managementtasks. Current and future remote sensing programs are based on a variety of sensors that will provide timely and repetitive multisensor earth Observation data on a global scale. GIS offer efficient tools for handling, manipulating, analyzing and presenting spatial data that are required for environmental ly sound deci sion making. To combine the power of both spatial techno logies, however, efficient synergistic processing techniques have to be developed to cope with large multisensor image datasets and to automatically extract information for environ mental GIS applications. These efforts have to be put in a broader perspective of an evolving discipline Geoinformatics as one component of a new and innovative interdisciplinary approach for academic education. One example of this approach is the new academic program Environmental Sciences at the University of Vechta.

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Ajar, Seno Budhi, Inna Prihartini, and Gentur Adi Tjahjono. "THE OBSTACLES FACTORS OF GEOGRAPHY INFORMATION SYSTEMS AND REMOTE SENSING PRACTICUM IN A HIGH SCHOOL LEVEL IN WONOGIRI DISTRICT." GeoEco 5, no. 2 (July 12, 2019): 151. http://dx.doi.org/10.20961/ge.v5i2.30198.

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Practicum Geographical information systems and remote sensing have become one of the basic competencies in the realm of skills in the geography learning process at the high school level The purpose of this study is to identify problems or obstacles faced by geography teachers in carrying out geographic information systems and remote sensing practicum activities in high schools in Wonogiri Regency this is a qualitative descriptive study with the use of random sampling. Data collection uses a questionnaire about the implementation of geographic information system practice and remote sensing to the teacher. This study uses descriptive statistical analysis techniques to analyze the factors that become obstacles in the application of geographic information system practice and remote sensing in high school. The result is the obstacles factor of geographic information system and remote sensing practicum in in high schools in Wonogiri is (1). Hardware devices that have not been installed software specifically for geography information systems and remote sensing The teacher has a low ability in the geography and remote sensing information system practicum skills and does not coordinate with the teacher or laboratory assistant for Information and Communication Technology (ICT) subjects (3) Insufficient time allocation for practicum and absence of geographic information system and remote sensing practice tests as evaluations

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Allaw, Kamel, Jocelyne Adjizian Gerard, Makram Zouheir Chehayeb, and Nada Badaro Saliba. "Population estimation using geographic information system and remote sensing for unorganized areas." Geoplanning: Journal of Geomatics and Planning 7, no. 2 (January 1, 2021): 75–86. http://dx.doi.org/10.14710/geoplanning.7.2.75-86.

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Population estimation using remotely sensed data has been largely discussed in the literature relative to human geography. However, the previously established models can be applied on organized areas (mainly urban areas) but they are not suitable for unorganized areas which already suffer from a lack of population data. So, the aim of this study is the establish a statistical model for population estimation based on remote sensing data and suitable for unorganized areas. To do so, the morphological characteristics have been studied and a bivariate analysis was carried out to determine factors having a strong relationship with population data as a first step. Second, factors with strongest correlations have been chosen to establish the required model. As a result, an equation has been generated which relates the population data to building volume, density of roads, number of nodes, actual urban areas, and urban trend.

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A, JOTHIBASU, and ANBAZHAGAN S. "Drought Hazard Assessment in Ponnaiyar River Basin, India Using Remote Sensing and Geographic Information System." INTERNATIONAL JOURNAL OF EARTH SCIENCES AND ENGINEERING 10, no. 02 (April 26, 2017): 247–56. http://dx.doi.org/10.21276/ijee.2017.10.0216.

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Lytvynenko, N. "THE APPLYING OF GIS INFORMATION TECHNOLOGIES IN THE SPHERE OF THE REMOTE SENSING OF THE EARTH TO SOLVE MILITARY PROBLEMS." Visnyk Taras Shevchenko National University of Kyiv. Military-Special Sciences, no. 2 (39) (2018): 18–22. http://dx.doi.org/10.17721/1728-2217.2018.39.18-22.

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The rapid development of geographic information systems and means of remote sensing, observed in recent decades, requires the mutual integration of these areas. This article focuses on the integration of geographic information systems and technologies in the field of remote sensing to solve military problems. Keywords: remote sensing, geographic information system.

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BAUMGARTNER, MICHAEL F., and GABRIELA M. APFL. "Remote sensing and geographic information systems." Hydrological Sciences Journal 41, no. 4 (August 1996): 593–607. http://dx.doi.org/10.1080/02626669609491527.

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Sun, Tong He, and Guo Qing Yan. "Land Classification Method and Analysis Based on Remote Sensing Technology." Advanced Materials Research 726-731 (August 2013): 4582–86. http://dx.doi.org/10.4028/www.scientific.net/amr.726-731.4582.

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In recent years, the research about land utilization changing already became one of the research about global changing's key topics, the land utilization classification, as its sub-topic, also attract men's high attention. Remote Sensing (RS) and the Geographic Information System (GIS) as the two big spatial technology tool to support modern geography, their union arouses people's universal interest and research. Because the remote sensing information has the advantage of covering wide area, timeliness and current situation, quick speed, short cycle and reliable accurate as well as time-saving, effort-saving, low status merit expense, it is widely used in the land resource and land utilization situation investigation at present, land utilization change monitor and so on. This paper discusses land utilization classification based on remote sensing technology. Taking the Xinjiang Kulja county bureau department area remote sensing images as the basic information, and using ERDAS IMAGINE, this paper discusses non-supervised classification and supervised classification methods. The results show that remote sensing technology applies to land utilization situation and land classification, which has reference value.

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Naue, Carine Rosa, Marilia W. Marques, Nelson Bernardi Lima, and Josiclêda Domiciano Galvíncio. "Sensoriamento remoto como ferramenta aos estudos de doenças de plantas agrícolas: uma revisão (Remote Sensing as a Toll for the Study of Plant Diseases on Agriculture: a Revision)." Revista Brasileira de Geografia Física 3, no. 3 (February 21, 2011): 190. http://dx.doi.org/10.26848/rbgf.v3i3.232675.

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Para que estudos epidemiológicos e medidas de controle de doenças de plantas fossem realizados foi necessário o desenvolvimento de métodos de quantificação de doenças. As doenças podem ser avaliadas por métodos diretos ou indiretos e dentre os métodos diretos encontram-se a estimativa dos parâmetros de incidência e severidade e as técnicas de sensoriamento remoto. Em estudos de doenças de plantas, o sensoriamento remoto, além de ser utilizado para quantificação, também poderá servir para a detecção de plantas infectadas. A detecção de doenças de plantas ou até mesmo sua quantificação, através do sensoriamento remoto, baseia-se na radiação refletida das folhagens. As diferenças de reflectância podem ser obtidas pelo sensoriamento remoto multispectral, que tem sido utilizado de forma eficiente para controlar a incidência de um número de patógenos de plantas e atualmente por medidas hiperespectrais. O objetivo deste artigo é apresentar uma revisão sobre o uso do sensoriamento remoto na detecção e análise de doenças de plantas. Os estudos apresentados aqui mostram que o sensoriamento remoto é uma ferramenta que pode ser utilizada para detectar plantas doentes de forma rápida e eficiente em pequenas e grandes áreas geográficas. Além disso, pode detectar plantas infectadas, dispensar a coleta e o processamento de amostras em laboratório permitindo levantamentos precisos e confiáveis, em curto espaço de tempo, independente do tamanho da área em questão. Além disso, pode proporcionar diversos estudos na área de fitopatologia e afins.Palavras-chave: Sensoriamento remoto, doenças de plantas, hiperespectral Remote Sensing as a Toll for the Study of Plant Diseases on Agriculture: a Revision ABSTRACT For epidemiological studies and measures to control plant diseases were carried out was necessary to develop methods of quantifying disease. The diseases can be assessed by direct or indirect methods and among the direct methods are estimating the incidence and severity parameters and remote sensing techniques. In studies of plant diseases, remote sensing is used to quantify, can also serve for detection of infected plants. The detection of plant diseases or even to quantify, through remote sensing, based on reflected radiation from foliage. The differences in reflectance can be obtained by multispectral remote sensing, which has been used effectively to control incidence a number of plant pathogens and recently, hyperspectral measurements. The aim of this paper is present a review on use of remote sensing in detection and analysis of plant diseases. The studies presented here show that remote sensing is a tool that can be used to detect diseased plants quickly and efficiently in large and small geographic areas. Moreover, it can detect infected plant, waive the collection and processing of lab samples allowing accurate and reliable surveys in a short space of time, regardless of size of the area. In addition, several studies can provide in the area of plant pathology and related areas. Key-words: remote sensing, diseased plants, hyperspectral.

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Han, X., and J. Wu. "DISASTER EMERGENCY RAPID ASSESSMENT BASED ON REMOTE SENSING AND BACKGROUND DATA." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3 (April 30, 2018): 481–83. http://dx.doi.org/10.5194/isprs-archives-xlii-3-481-2018.

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The period from starting to the stable conditions is an important stage of disaster development. In addition to collecting and reporting information on disaster situations, remote sensing images by satellites and drones and monitoring results from disaster-stricken areas should be obtained. Fusion of multi-source background data such as population, geography and topography, and remote sensing monitoring information can be used in geographic information system analysis to quickly and objectively assess the disaster information. According to the characteristics of different hazards, the models and methods driven by the rapid assessment of mission requirements are tested and screened. Based on remote sensing images, the features of exposures quickly determine disaster-affected areas and intensity levels, and extract key disaster information about affected hospitals and schools as well as cultivated land and crops, and make decisions after emergency response with visual assessment results.

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Mohommad, Shahid, and Shambhu Prasad Joshi. "ROLE OF REMOTE SENSING AND GEOGRAPHIC INFORMATION SYSTEM TO ANALYZE THE IMPACT OF CLIMATE CHANGE ON FOREST ECOSYSTEMS." International Journal of Research -GRANTHAALAYAH 3, no. 8 (August 31, 2015): 61–68. http://dx.doi.org/10.29121/granthaalayah.v3.i8.2015.2959.

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Climate change is an inevitable process impacting the forest ecosystem. Various impacts like treeline shift, forest fires, and Species distribution are due to the effect of climate change. Green House Gases concentration in the atmosphere is increasing day by day due to anthropogenic activities. The pace of climate change is very alarming which will have the substantial impact on the forest ecosystem. Role of remote sensing and geographic information system in observing the forest ecosystem was reviewed. Spatio-temporal analysis of change in forest structure can be proficiently done with the help of remote sensing and geographic information system. Climate Change Mitigation programmes like Reducing Emissions from Deforestation and Forest Degradation (REDD-plus) can be implemented with the help of remote sensing and geographic information system. Baseline data generation using remote sensing and geographic information system can be useful in designing the policies for forest management and monitoring.

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Voženílek, Vít. "Geoinformatic literacy: indispensability or nonsense?" Geografie 107, no. 4 (2002): 371–82. http://dx.doi.org/10.37040/geografie2002107040371.

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(Geo)information technologies have impacted most scientific fields. Geography takes part in this progress and educates new generation of decision makers which will be able to apply the latest scientific outcomes in many branches of science, society and landscape. This situation strongly requires geoinformatic literacy. The geoinformatic literacy consists of geographic, cartographic and informatic literacy. There are two main ways of applying geoinformatic literacy in geographic practice - awareness and using. A current multidisciplinarity in geographic applications requires awareness of fundamental knowledge of geoinformatics and their technologies. Geographers need either to understand GI-experts (involved in projects) or to process procedures of geoinformation technologies (GIS, GPS, remote sensing, geostatistics etc.).

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Ikhsan, Fahrudi Ahwan, Fahmi Arif Kurnianto, Bejo Apriyanto, and Elan Artono Nurdin. "GEOGRAPHY SKILLS DOMAIN TAXONOMY." Geosfera Indonesia 2, no. 1 (April 30, 2018): 54. http://dx.doi.org/10.19184/geosi.v2i1.7525.

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This study aims to explain the geography student skills domain. The focus of this research is the domain of geography skills possessed by students. The research method with the a qualitative approach. Subjects were students of Jember University geography education consisting of 2 men and 2 women with indicators of academic ability value of the national geography exam results. Data collection techniques by observation and interview. Data were analyzed using the processing unit, categorization and interpretation of data. The findings show that the skills of geography for prospective teachers of geography and geographers to be possessed composed as follows: 1st level thinking skills geography (space, phenomena, location and place, region, environment, coordinate, and humans), level 2 skills of analysis geography (scale, distribution, patterns of interaction, interrelation, connectivity, corologi, descriptions, and agglomeration), and level 3 skills of geographic applications (mapping/cartography, remote sensing, geographic information systems, surveying and mapping of the area, and Global Position systems (GPS). This level difference is used to distinguish the use of knowledge and application of the science of geography. Keywords: Students of geography education, geography Skills

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Li, Jing Zhong, Hui Yan, and Meng Meng Yang. "The Application of Agricultural Remote Sensing in Remote Sensing Teaching Practice." Advanced Materials Research 926-930 (May 2014): 4626–29. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.4626.

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This paper has analyzed the current application status of agricultural Remote Sensing and the situation of teaching practice of Remote Sensing in Geographic Information Systems (GIS) at length; and practically looked for their breakthrough point. On this basis, the paper constructs the frame structure of their combination preliminarily, making the teaching practice combine with the practical application, which allows for the finishing of the process of teaching practice as well as serving the society. This provides a new idea for the combination of production, studying and researching in GIS and broadens the combination mode of teaching and application. Simultaneously, it promotes the students practical ability of using remote sensing and GIS to process and analyze data in actual projects, inspires the students capability of initiative and creative thinking, and improves the students interests of Autonomous learning.

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Kholoshyn, Ihor V., Iryna M. Varfolomyeyeva, Olena V. Hanchuk, Olga V. Bondarenko, and Andrey V. Pikilnyak. "Pedagogical techniques of Earth remote sensing data application into modern school practice." Освітній вимір 53, no. 1 (December 19, 2019): 80–94. http://dx.doi.org/10.31812/educdim.v53i1.3834.

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The article dwells upon the Earth remote sensing data as one of the basic directions of Geo-Information Science, a unique source of information on processes and phenomena occurring in almost all spheres of the Earth geographic shell (atmosphere, hydrosphere, lithosphere, etc.). The authors argue that the use of aerospace images by means of the information and communication technologies involvement in the learning process allows not only to increase the information context value of learning, but also contributes to the formation of students’ cognitive interest in such disciplines as geography, biology, history, physics, computer science, etc. It has been grounded that remote sensing data form students’ spatial, temporal and qualitative concepts, sensory support for the perception, knowledge and explanation of the specifics of objects and phenomena of geographical reality, which, in its turn, provides an increase in the level of educational achievements. The techniques of aerospace images application into the modern school practice have been analyzed and illustrated in the examples: from using them as visual aids, to realization of practical and research orientation of training on the basis of remote sensing data. Particular attention is paid to the practical component of the Earth remote sensing implementation into the modern school practice with the help of information and communication technologies.

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Moore, A., and P. Whigham. "Special feature: geographic information science and remote sensing." Journal of Spatial Science 59, no. 2 (July 3, 2014): 235–36. http://dx.doi.org/10.1080/14498596.2014.922038.

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Bonnefon, R., P. Dhérété, and J. Desachy. "Geographic information system updating using remote sensing images." Pattern Recognition Letters 23, no. 9 (July 2002): 1073–83. http://dx.doi.org/10.1016/s0167-8655(02)00054-5.

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Chapman, D. P. "Geoinformation: Remote Sensing, Photogrammetry and Geographic Information Systems." Photogrammetric Record 18, no. 104 (December 2003): 330–31. http://dx.doi.org/10.1046/j.0031-868x.2003.024_02.x.

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Ablameyko, S., and B. Beregov. "Remote sensing image processing in geographic information systems." Computing & Control Engineering Journal 7, no. 5 (October 1, 1996): 235–39. http://dx.doi.org/10.1049/cce:19960508.

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Hay, Simon I. "Remote Sensing and Geographic Information Systems in Epidemiology." Emerging Infectious Diseases 8, no. 4 (April 2002): 448–49. http://dx.doi.org/10.3201/eid0804.010529.

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Farr, Tom G., Stephanie Granger, and Steve Kopp. "Integrating Remote Sensing Data Into Geographic Information Systems." Eos, Transactions American Geophysical Union 92, no. 18 (May 3, 2011): 154. http://dx.doi.org/10.1029/2011eo180007.

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Fu, N., L. Sun, H. Z. Yang, J. Ma, and B. Q. Liao. "RESEARCH ON MULTI-SOURCE SATELLITE IMAGE DATABASE MANAGEMENT SYSTEM." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLII-3/W10 (February 7, 2020): 565–68. http://dx.doi.org/10.5194/isprs-archives-xlii-3-w10-565-2020.

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Abstract. For the exploration and analysis of electricity, it is necessary to continuously acquire multi-star source, multi-temporal, multi-level remote sensing images for analysis and interpretation. Since the overall data has a variety of features, a data structure for multi-sensor data storage is proposed. On the basis of solving key technologies such as real-time image processing and analysis and remote sensing image normalization processing, the .xml file and remote sensing data geographic information file are used to realize effective organization between remote sensing data and remote sensing data. Based on GDAL design relational database, the formation of a relatively complete management system of data management, shared publishing and application services will maximize the potential value of remote sensing images in electricity remote sensing.

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Singh, Daljit. "Automatic Extraction of Glacial Outlines, Contours and Volume of Ice from Satellite Imageries (Use of Open Source GIS Software - QGIS)." International Journal of Emerging Research in Management and Technology 6, no. 9 (June 24, 2018): 138. http://dx.doi.org/10.23956/ijermt.v6i9.98.

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Remote Sensing and GIS are the two Geo-Spatial Technologies increasingly used in Geographic Research. The high cost of the software’s used to apply these technologies to geographical data did not allow expansion of its use in India except in the projects which are financed by some funding agencies. Moreover, its use for individual research by teachers and students in absence of license access to these technologies was highly restricted. Even if a license is purchased by the educational institution, its maintenance cost further inhibits is use. The present paper highlights how QGIS, open source GIS software can be used to extract glaciers from satellite imageries. By adopting UBUNTU, an open source operating system and QGIS, an open source GIS software any department of Geography can establish a GIS laboratory where not only teachers but students may learn its applications and start using it in a big way. This will enable geography teachers, researchers, and students to use remote sensing and geographical information system in understanding, analyzing and highlighting the importance of various indicators of development.

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Martinelli, Massimo, and Davide Moroni. "Volunteered Geographic Information for Enhanced Marine Environment Monitoring." Applied Sciences 8, no. 10 (September 27, 2018): 1743. http://dx.doi.org/10.3390/app8101743.

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The ability to detect and monitor oil spills at sea is becoming increasingly important due to the high demand of oil-based products. Remote sensing frameworks have been proven to give accurate results in case of major events; nonetheless, also medium and micro oil spills have their own importance, especially in protected areas that deserve special attention. In this paper, we propose a monitoring framework based on the collection of in situ observations and on their integration with remote sensing in order to fill out existing observational gaps. In particular, besides the data collected by special monitoring devices, in situ observations include volunteered geographical information as an additional source of valuable data. Oil spill sights, notified by volunteers through a specially-designed app, are integrated in the monitoring system and therein processed together with remote sensing data in order to proactively detect anomalous events and produce alerts. Field operational tests in two areas demonstrate the technical validity of the approach, while users’ reception testifies to its potential in raising people’s awareness on marine pollution.

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Zhang, Shi Liang, and Ting Cheng Chang. "A Study of Image Classification of Remote Sensing Based on Back-Propagation Neural Network with Extended Delta Bar Delta." Mathematical Problems in Engineering 2015 (2015): 1–10. http://dx.doi.org/10.1155/2015/178598.

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This paper proposes a model to extract feature information quickly and accurately identifying what cannot be achieved through traditional methods of remote sensing image classification. First, process the selected Landsat-8 remote sensing data, including radiometric calibration, geometric correction, optimal band combination, and image cropping. Add the processed remote sensing image to the normalized geographic auxiliary information, digital elevation model (DEM), and normalized difference vegetation index (NDVI), working together to build a neural network that consists of three levels based on the structure of back-propagation neural and extended delta bar delta (BPN-EDBD) algorithm, determining the parameters of the neural network to constitute a good classification model. Then determine classification and standards via field surveys and related geographic information; select training samples BPN-EDBD for algorithm learning and training and, if necessary, revise and improve its parameters using the BPN-EDBD classification algorithm to classify the remote sensing image after pretreatment and DEM data and NDVI as input parameters and output classification results, and run accuracy assessment. Finally, compare with traditional supervised classification algorithms, while adding different auxiliary geographic information to compare classification results to study the advantages and disadvantages of BPN-EDBD classification algorithm.

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Liu, J., H. T. Li, and H. Y. Gu. "A color balancing method for wide range Remote Sensing imagery based on Regionalization." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W4 (June 26, 2015): 103–8. http://dx.doi.org/10.5194/isprsarchives-xl-7-w4-103-2015.

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Quick mosaicking of wide range remote sensing imagery is an important foundation for land resource survey and dynamic monitoring of environment and nature disasters. It is also technically important for basis imagery of geographic information acquiring and geographic information product updating. This paper mainly focuses on one key technique of mosaicking, color balancing for wide range Remote Sensing imagery. Due to huge amount of data, large covering rage, great variety of climate and geographical condition, color balancing for wide range remote sensing imagery is a difficult problem. In this paper we use Ecogeographic regionalization to divide the large area into several regions based on terrains and climatic data, construct the algorithmic framework of a color balancing method according to the regionalization result, which conduct from region edge to center to fit wide range imagery mosaicking. The experimental results with wide range HJ-1 dataset show that our method can significantly improve the wide range of remote sensing imagery color balancing effects: making images well-proportioned mosaicking and better in keeping images' original information. In summary, this color balancing method based on regionalization could be a good solution for nationwide remote sensing image color balancing and mosaicking.

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Li, Junjie, Lingkui Meng, Beibei Yang, Chongxin Tao, Linyi Li, and Wen Zhang. "LabelRS: An Automated Toolbox to Make Deep Learning Samples from Remote Sensing Images." Remote Sensing 13, no. 11 (May 24, 2021): 2064. http://dx.doi.org/10.3390/rs13112064.

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Deep learning technology has achieved great success in the field of remote sensing processing. However, the lack of tools for making deep learning samples with remote sensing images is a problem, so researchers have to rely on a small amount of existing public data sets that may influence the learning effect. Therefore, we developed an add-in (LabelRS) based on ArcGIS to help researchers make their own deep learning samples in a simple way. In this work, we proposed a feature merging strategy that enables LabelRS to automatically adapt to both sparsely distributed and densely distributed scenarios. LabelRS solves the problem of size diversity of the targets in remote sensing images through sliding windows. We have designed and built in multiple band stretching, image resampling, and gray level transformation algorithms for LabelRS to deal with the high spectral remote sensing images. In addition, the attached geographic information helps to achieve seamless conversion between natural samples, and geographic samples. To evaluate the reliability of LabelRS, we used its three sub-tools to make semantic segmentation, object detection and image classification samples, respectively. The experimental results show that LabelRS can produce deep learning samples with remote sensing images automatically and efficiently.

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Chen, Yong Sheng, Zhi Jia Hong, Qun He, and Hong Bin Ma. "Road Extraction from High-Resolution Remote Sensing Images Based on Synthetical Characteristics." Applied Mechanics and Materials 333-335 (July 2013): 828–31. http://dx.doi.org/10.4028/www.scientific.net/amm.333-335.828.

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Road extraction is the recurring important application of high-resolution remote sensing images. In order to achieve the goal of road extraction, the various characteristics of geographic information of high-resolution remote sensing images as well as the application and models of road extraction are analyzed, then an effective way of extracting roads from high-resolution remote sensing images is found, and then the high-resolution remote sensing image road extraction algorithm based on texture characteristics assisted by other characteristic information is put forward. The specific process of road extraction in the algorithm is introduced, and the function of road extraction of urban high-resolution remote sensing image based on texture characteristics is also tested practically, the result shows that this method has a higher degree of accuracy in extracting roads from urban high-resolution remote sensing images.

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Gu, H. Y., H. T. Li, L. Yan, and X. J. Lu. "A Framework for Geographic Object-Based Image Analysis (GEOBIA) based on geographic ontology." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XL-7/W4 (June 26, 2015): 27–33. http://dx.doi.org/10.5194/isprsarchives-xl-7-w4-27-2015.

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GEOBIA (Geographic Object-Based Image Analysis) is not only a hot topic of current remote sensing and geographical research. It is believed to be a paradigm in remote sensing and GIScience. The lack of a systematic approach designed to conceptualize and formalize the class definitions makes GEOBIA a highly subjective and difficult method to reproduce. This paper aims to put forward a framework for GEOBIA based on geographic ontology theory, which could implement "Geographic entities - Image objects - Geographic objects" true reappearance. It consists of three steps, first, geographical entities are described by geographic ontology, second, semantic network model is built based on OWL(ontology web language), at last, geographical objects are classified with decision rule or other classifiers. A case study of farmland ontology was conducted for describing the framework. The strength of this framework is that it provides interpretation strategies and global framework for GEOBIA with the property of objective, overall, universal, universality, etc., which avoids inconsistencies caused by different experts’ experience and provides an objective model for mage analysis.

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Deshmukh, Priyanka, Pawade P. Y, and Rajashree Bothale. "Remote Sensing and Geographic Information System Based Route Planning." Civil Engineering and Urban Planning: An International Journal (CiVEJ) 5, no. 1 (March 30, 2018): 01–17. http://dx.doi.org/10.5121/civej.2018.5101.

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Lehmann, A., and J. B. Lachavanne. "Geographic information systems and remote sensing in aquatic botany." Aquatic Botany 58, no. 3-4 (October 1997): 195–207. http://dx.doi.org/10.1016/s0304-3770(97)00035-1.

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Kumar, Amit. "Rediscovering bamboo: remote sensing and geographic information systems perspective." Journal of Applied Remote Sensing 2, no. 1 (October 1, 2008): 022501. http://dx.doi.org/10.1117/1.3010736.

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Zhao, Xin, Hui Li, Ping Wang, and Linhai Jing. "An Image Registration Method for Multisource High-Resolution Remote Sensing Images for Earthquake Disaster Assessment." Sensors 20, no. 8 (April 17, 2020): 2286. http://dx.doi.org/10.3390/s20082286.

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For earthquake disaster assessment using remote sensing (RS), multisource image registration is an important step. However, severe earthquakes will increase the deformation between the remote sensing images acquired before and after the earthquakes on different platforms. Traditional image registration methods can hardly meet the requirements of accuracy and efficiency of image registration of post-earthquake RS images used for disaster assessment. Therefore, an improved image registration method was proposed for the registration of multisource high-resolution remote sensing images. The proposed method used the combination of the Shi_Tomasi corner detection algorithm and scale-invariant feature transform (SIFT) to detect tie points from image patches obtained by an image partition strategy considering geographic information constraints. Then, the random sample consensus (RANSAC) and greedy algorithms were employed to remove outliers and redundant matched tie points. Additionally, a pre-earthquake RS image database was constructed using pre-earthquake high-resolution RS images and used as the references for image registration. The performance of the proposed method was evaluated using three image pairs covering regions affected by severe earthquakes. It was shown that the proposed method provided higher accuracy, less running time, and more tie points with a more even distribution than the classic SIFT method and the SIFT method using the same image partitioning strategy.

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Ridwana, Riki, and Shafira Himayah. "UTILIZATION OF REMOTE SENSING TECHNOLOGY AND GEOGRAPHIC INFORMATION SYSTEMS FOR TOURISM DEVELOPMENT." International Journal of Applied Sciences in Tourism and Events 4, no. 2 (December 30, 2020): 158–69. http://dx.doi.org/10.31940/ijaste.v4i2.2042.

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The success of tourism in any country depends on the country's ability to develop, manage and market its tourism facilities and activities. Tourism development and management can be done in various ways. One of the most effective and efficient ways is to utilize remote sensing technology and geographic information systems (GIS). This article was created to archive and review some of the findings of the use of remote sensing technology and GIS for tourism management and development, using the literature review method. The use of remote sensing technology and GIS for tourism development and management has been widely used by various academics and researchers in various countries in the world including in Indonesia. This is acceptable because it is considered effective and efficient, the suitability of tourism development studies, for the study of tourism multimedia development, identification of the most desirable tourist areas, and for the evaluation of ecotourism areas.

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McDermid, Gregory J., Steven E. Franklin, and Ellsworth F. LeDrew. "Remote sensing for large-area habitat mapping." Progress in Physical Geography: Earth and Environment 29, no. 4 (December 2005): 449–74. http://dx.doi.org/10.1191/0309133305pp455ra.

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Remote sensing has long been identified as a technology capable of supporting the development of wildlife habitat maps over large areas. However, progress has been constrained by underdeveloped linkages between resource managers with extensive knowledge of ecology and remote sensing scientists with backgrounds in geography. This article attempts to traverse that gap by (i) clarifying the imprecise and commonly misunderstood concept of ‘habitat’, (ii) exploring the recent use of remote sensing in previous habitat-mapping exercises, (iii) reviewing the remote sensing toolset developed for extracting information from optical satellite imagery, and (iv) outlining a framework for linking ecological information needs with remote sensing techniques.

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Meissner, B. "Remote sensing cartography." GeoJournal 32, no. 1 (January 1994): 71–79. http://dx.doi.org/10.1007/bf00806359.

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ENCINA, C. C. C., M. R. MARQUES, M. A. DIODATO, J. S. MOTTA, R. F. GODOI, J. R. S. OLIVEIRA, R. M. GAMARRA, F. B. DALMAS, and A. C. PARANHOS. "Remoto Plant Structure Analysis of Cerrado Fragments by Remote Sensing." Anuário do Instituto de Geociências - UFRJ 41, no. 2 (August 20, 2018): 585–97. http://dx.doi.org/10.11137/2018_2_585_597.

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Silva, Francisco Jonh Lennon Tavares da, Dyego Freitas Rocha, and Cláudia Maria Sabóia de Aquino. "GEOGRAFIA, GEOTECNOLOGIAS E AS NOVAS TENDÊNCIAS DA GEOINFORMAÇÃO: indicação de estudos realizados na região Nordeste." InterEspaço: Revista de Geografia e Interdisciplinaridade 2, no. 6 (March 9, 2017): 176. http://dx.doi.org/10.18764/2446-6549/interespaco.v2n6p176-197.

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A difusão do Geoprocessamento, do Sensoriamento Remoto e dos Sistemas de Informação Geográfica, abriu novas possibilidades de aplicação aos estudos geográficos. Nesse contexto e considerando o método bibliográfico como procedimento de análise, o artigo objetivou: (i) refletir sobre o impacto da postura geotecnológica sobre a meta básica da ciência geográfica, qual seja, explicar a organização do espaço, mediante abordagens e técnicas exitosas; (ii) indicar algumas tecnologias de análise espacial utilizadas no Brasil, evidenciando as novas tendências no contexto da Geoinformação e (iii) discutir a aplicação das Geotecnologias, indicando estudos realizados na região Nordeste. A partir do levantamento preliminar de estudos regionais, infere-se que as Geotecnologias têm grande potencial de aplicação nos estudos de Geografia Física.Palavras-chave: Geoprocessamento; Sistemas de Informação Geográfica; Sensoriamento Remoto; Geoinformação.GEOGRAPHY, GEOTECHNOLOGIES AND THE NEW TRENDS IN GEOINFORMATION: indication of studies accomplished in the Northeast regionABSTRACTWith the spread of Geoprocessing, Remote Sensing and Geographic Information Systems, new applications possibilities was opened for to the geographical studies. In this context and considering the bibliographical method as an analytical procedure, the papper aimed: (i) reflect on the impact of geotechnologic stance on the basic goal of geographical science, that is, explain the organization of space, through successful approaches and techniques; (ii) indicate some spatial analysis technologies used in Brazil, highlighting the new trends in the context of Geoinformation and (iii) discuss the application possibilities of Geotechnologies, indicating studies in the Northeast region. From the preliminary survey of regional studies, it infers that the Geotechnologies have great potential of application in Physical Geography studies.Keywords: Geoprocessing; Geographic Information Systems; Remote Sensing; Geoinformation.GEOGRAFÍA, GEOTECNOLOGÍAS Y LAS NUEVAS TENDENCIAS EN GEOINFORMACIÓN: indicación de estudios realizados en la región NordesteRESUMENLa difusión del Geoprocesamiento, Sensoriamento Remoto y Sistemas de Información Geográficas abrieron nuevas posibilidades de aplicación a los estudios geográficos. En este contexto y teniendo en cuenta el método bibliográfico como procedimiento analítico, el artículo tiene como objetivo: (i) reflexionar sobre el impacto de la postura geotecnológica en el objetivo básico de la ciencia geográfica, que es explicar la organización del espacio, a través de enfoques y técnicas exitosas; (ii) indicar algunas tecnologías de análisis espacial utilizadas en Brasil, destacando las nuevas tendencias en el contexto de la Geoinformación y (iii) discutir las posibilidades de aplicación de Geotecnologias, indicando estudios realizados en la región Nordeste. A partir del levantamiento preliminar de estudios regionales, se pudo inferir que las Geotecnologias tienen un gran potencial para su aplicación en los estudios de Geografía Física.Palabras clave: Geoprocesamiento; Sistemas de Información Geográficas; Sensoriamento Remoto; Geoinformación.

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Mather, Paul M. "Teaching remote sensing." Journal of Geography in Higher Education 13, no. 2 (January 1989): 216–20. http://dx.doi.org/10.1080/03098268908709090.

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Lubis, Muhammad Zainuddin, Oktavianto Gustin, Wenang Anurogo, Husnul Kausarian, Kasih Anggraini, and Aditya Hanafi. "PENERAPAN TEKNOLOGI PENGIDERAAN JAUH DI BIDANG PESISIR DAN LAUTAN." OSEANA 42, no. 3 (October 30, 2017): 56–64. http://dx.doi.org/10.14203/oseana.2017.vol.42no.3.85.

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APPLICATIONS OF REMOTE SENSING TECHNOLOGY IN COASTAL AND OCEAN Many remote sensing applications are devoted to the coastal and ocean sector. Representative case studies are presented in the special issue “Advances in Remote Sensing of coastal and ocean”. Remote sensing techniques represent a powerful tool for landslide investigation: applications are traditionally sea surface temperature, marine habitat into three main classes, although this subdivision has some limitations and borders are sometimes fuzzy in coastal and ocean. Remote sensing combined with geographic information system (GIS) can be used as a technology tool to obtain information about the object quickly and accurately, including objects in coastal and ocean areas. Remote sensing data on coastal and marine areas specifically for the region in Indonesia have been widely practiced. The use of remote sensing data and GIS in coastal and marine areas can be used to determine sea surface temperature, determination of fish catchment area, and coastline morphological changes by adding other influential parameters. It can also be used to monitor a regional change by using multi-temporal recording data such as disaster monitoring, monitoring of land cover changes in coastal areas etc. Remote sensing data essentially can be used as an alternative technology in obtaining information at a cheaper cost when compared with the conventional way.

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Guo, Hong Tao, Zhi Guo Chang, and Shan Wei He. "Geostationary Meteorological Satellite Data Processing System." Advanced Materials Research 181-182 (January 2011): 257–60. http://dx.doi.org/10.4028/www.scientific.net/amr.181-182.257.

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In order to design a set of geostationary meteorological satellite data processing system，which have common data processing，practical remote sensing products and rich visual stylet，used VC++6.0 MFC and dynamic link library and the mature remote sensing products processing algorithms, to design it. Multi-satellite source geostationary meteorological satellite data are integrated, remote sensing products are generated, for example, cloud detection, cloud classification, cloud top height. The original cloud image, remote sensing and geographic information products are displayed vividly. The three-dimensional cloud image processing retrieval based on cloud detection product takes into account the visual effect, and also has a clear physical meaning, practicality is strong. The system makes geostationary meteorological satellite information play a more important role in the current weather forecast.

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Shaimerdenov, D., and A. Zakirova. "GENERAL STRUCTURE, TYPES AND FORMATS OF DIGITAL DATA OF REMOTE SENSING OF THE EARTH." BULLETIN Series of Physics & Mathematical Sciences 70, no. 2 (June 30, 2020): 295–300. http://dx.doi.org/10.51889/2020-2.1728-7901.47.

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Earth remote sensing technologies (ERS) are an indispensable tool for the study and continuous monitoring of our planet, helping to effectively use and manage its resources. The modern development of remote sensing technologies expands the scope of their application, covering all aspects of our lives. This article describes the main stages of the development of remote sensing technologies, provides an overview of methods for observing elements of the environment, and considers the General structure, types and formats of digital data for remote sensing of the Earth. The main characteristics of aerospace survey data are defined, methods of storing coordinate reference data and data storage formats are considered. The main methods for representing geographical data are given, and the important qualities of each type of remote sensing data representation are described. The analysis of integration types to represent geographic data and identified the principal benefits of an integrated data view ERS.

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Li, J., J. Sheng, Y. Chen, L. Ke, N. Yao, Z. Miao, X. Zeng, L. Hu, and Q. Wang. "A WEB-BASED LEARNING ENVIRONMENT OF REMOTE SENSING EXPERIMENTAL CLASS WITH PYTHON." ISPRS - International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences XLIII-B5-2020 (August 24, 2020): 57–61. http://dx.doi.org/10.5194/isprs-archives-xliii-b5-2020-57-2020.

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Abstract. Remote sensing course is a general disciplinary required course of human geography and urban-rural planning major. Its class hour is 48, including theoretical classes and experimental classes. Rapid technological developments is remote sensing area demand quick and steady changes in the education programme and its realization, especially in experimental classes. Experimental classes include: introduction to remote sensing software and basic operations, remote sensing data pre-processing (input, output, 2D and 3D terrain display, image cut, image mosaic, and projection transformation), remote sensing image enhancement, remote sensing image transformation, computer aided classification, image interpretation, and remote sensing image terrain analysis. There are two difficulties in the remote sensing experimental classes. First, it cost a lot of time to prepare the remote sensing software and the remote sensing images. Second, some students just want to use the remote sensing as a tool to investigate environment changing, some other students may want to study more remote sensing image processing technologies. A web-based learning environment of remote sensing is developed to facilitate the application of remote sensing experimental teaching. To make the learning more effective, there are eight modules including four optional modules. The Python programming language is chosen to implement the web-based remote sensing learning environment. The web-based learning environment is implemented in a local network server, including the remote sensing data processing algorithms and many satellite image data. Students can easily exercise the remote sensing experimental courses by connecting to the local network server. It is developed mainly for remote sensing experimental course, and also can be adopted by digital image processing or other courses. The feature of web-based learning may be very useful as the online education adopted because of Corona Virus Disease 2019. The results are encouraging and some recommendations will be extracted for the future.

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White, Kevin. "Remote sensing." Progress in Physical Geography: Earth and Environment 15, no. 1 (March 1991): 71–76. http://dx.doi.org/10.1177/030913339101500105.

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White, Kevin. "Remote sensing." Progress in Physical Geography: Earth and Environment 21, no. 2 (June 1997): 297–305. http://dx.doi.org/10.1177/030913339702100208.

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White, Kevin. "Remote sensing." Progress in Physical Geography: Earth and Environment 17, no. 3 (September 1993): 369–75. http://dx.doi.org/10.1177/030913339301700307.

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Donoghue, Daniel N. M. "Remote sensing." Progress in Physical Geography: Earth and Environment 23, no. 2 (June 1999): 271–81. http://dx.doi.org/10.1177/030913339902300207.

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White, Kevin. "Remote sensing." Progress in Physical Geography: Earth and Environment 19, no. 1 (March 1995): 138–46. http://dx.doi.org/10.1177/030913339501900108.

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White, Kevin. "Remote sensing." Progress in Physical Geography: Earth and Environment 20, no. 1 (March 1996): 89–96. http://dx.doi.org/10.1177/030913339602000106.

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White, K. "Remote sensing." Progress in Physical Geography 22, no. 1 (March 1, 1998): 95–102. http://dx.doi.org/10.1191/030913398669595653.

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Donoghue, D. N. M. "Remote sensing." Progress in Physical Geography 23, no. 2 (June 1, 1999): 271–81. http://dx.doi.org/10.1191/030913399675911653.

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Journal articles on the topic 'Remote sensing {Geographie}'

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