1 INVESTIGATIONS ON THE ACCURACY ASPECTS IN THE LAND USE/LAND COVER MAPPING USING REMOTE SENSING SATELLITE IMAGERY By M.C.PALIWAL Department of Civil Engineering NATIONAL INSTITUTE OF TECHNICAL TEACHERS TRAINING & RESEARCH, BHOPAL (M.P.), INDIA
2 INTRODUCTION: Different methods of land use/land cover Conventional methods Modern methods- RS,GIS,GPS Classification of satellite image Accuracy aspects
3 Need for land use maps: Now a days due to rapid growth in urbanization and industrialization, there is increasing pressure on land, water and environment. Urban sprawl may be found everywhere in major cities. There are many problems related with conversion of agricultural land in to urban use. Every city is expanding in all directions resulting in large-scale changes in urban land use.
4 Land cover and Land use : Land cover is that which covers the surface of the earth and land use describes how the land cover is modified. Land cover includes: water, grassland, forest, bare soil etc. Land use includes agricultural land, recreation area, built up land, etc.
5 The function of Land use maps: To make property maps and to do settlement. To conduct topographic survey for infrastructure development. To keep database records related to property. To evaluate the property value. To divide the property in case of disputes. To work with Board of Revenue, Public works departments, Utility companies etc.
6 Conventional Methods: Chains to measure distances Old mechanical Theodolites Vernier Theodolites Paper maps etc.
7 Disadvantages of using Conventional Method: Chains data can be taken only in perpendicular direction, while actually land/fields is of Zig Zag shape. Chain data is always inaccurate. The land cost of today demands a more accurate method. The maps generated by manual methods can not be reproduced at user required scale. If scale has to be changed then whole map has to be redrawn. Attribute data for a field can not be attached on a paper map. (i.e.the name of the owner, the area, the cost etc. has no relation with the map.) Decision making process using old paper maps becomes very cumbersome and some time it leads to wrong decision.
8 Modern methods: Making a map using Coordinates rather than by Angles and distances. Area computation can be done using Total Stations as well as GPS then and there itself. Using Total Stations and Mapping Software the maps can be created automatically. Map at any scale can be created because of availability of data in electronic format. A full-fledged GIS can be generated so that just be click of a key all the attributes corresponding to a land piece can be obtained.
9 Developments in the Surveying Techniques and advantages of new mapping Techniques: Conventional Survey Methods are very tedious and time consuming. Large Number of measurements are required to prepare a map. Automated Survey Techniques are simpler and easy to record survey measurements. 9
10 AUTOMATED SURVEYING TECHNOLOGY Automatic and Laser level Total Stations Global Positioning Systems (GPS) Photogrammetric Survey Remote Sensing Methods (RS) 10
11 Ground based technique limitations and advantages of satellite based techniques. In Conventional Survey all the field values are to be noted down in the field book and plotting is done manually in the office. In GPS based surveys, the GPS Receiver records the Satellite signal. GPS receiver can be attached to computer and automatically plots the maps.. 11
12 Conventional Survey GPS Survey GPS Survey 12
13 REMOTE SENSING [RS] A-Energy Sources B-Radiation & Atmosphere C-Interaction with target D-Recording of Energy by the sensor E-Transmission, Recording and Processing F-Interpretation and Analysis G-Application Introduction Cont
14 GIS AND ITS COMPONENTS Component
15 IRS-1D LISS-III DATA (23.5 M RESOLUTION) AIR STRIP UPPER LAKE BHEL MANTRALAYA BHOPAL AS SEEN ON 25 th NOV
16 IRS-1D PAN & LISS III MERGED DATA (5.8 M RESOLUTION) BHOPAL AS SEEN ON 14th NOV
17 Accuracy aspects in land use/land cover maps: Land cover maps derived from remotely sensed data inevitably contain error of various types and degrees. It is therefore very important that the nature of these errors be determined, to gauge their appropriateness for specific uses. Identifying and correcting the sources of errors may increase the quality of map information. Classification accuracy assessment is necessary for comparing the performance of various classification techniques. 17
18 Today, the error matrix has become the standard medium for reporting the accuracy of maps derived from remotely sensed data (Congalton and Green, 1993). More recent research into classification accuracy assessment has focused on factors influencing the accuracy of spatial data, such as sampling scheme and sample size, classification scheme, and spatial autocorrelation ( Congalton and Green, 1993). Other important considerations in classification accuracy assessment include ground verification techniques, and evaluation of all sources of error in the spatial data set. 18
19 Accuracy aspects : Assessing the accuracy of maps generated from remotely sensed data requires evaluating both positional accuracy and thematic accuracy. While these two accuracies can be assessed separately, they are very much interrelated and failure to consider both of them is a serious mistake.
20 Positional Accuracy: Positional accuracy, a measure of how closely the imagery fits the ground, is the most common measure of map accuracy. In other words, positional accuracy is the accuracy of the location of a point in the imagery with reference to its physical location on the ground.
21 Thematic Accuracy: Thematic accuracy refers to the accuracy of a mapped land cover category at a particular time compared to what was actually on the ground at that time. Clearly, to perform a meaningful assessment of accuracy, land cover classifications must be assessed using data that are believed to be correct.
22 Accuracy aspects : A classification is not complete until its accuracy is assessed. A classification error matrix is prepared based on training data. Error matrix compares the ground truth and the corresponding results of an automated classification. Overall accuracy and individual accuracy is calculated. 22
23 Need of reliable calibration and ground truthing in the map extraction. KAPPA is a technique developed by Cohen (1960) and has been utilized for land cover and land use accuracy assessment derived from remotely sensed data (Congalton et al., 1983; Rosenfield and Fitzpatrick-Lins, 1986; Gong and Howarth, 1990). The result of performing a KAPPA analysis is the KHAT statistic (an estimate of KAPPA) which is another measure of accuracy or agreement. 23
24 Trend in map extraction from imagery using classification and feature extraction. In order to obtain unbiased ground reference information to compare with the remote sensing classification map and fill the error matrix values, we need to determine the most appropriate (i.e., minimum) sample size acceptable for a valid statistical testing of accuracy of the land cover map. In addition, an appropriate sampling scheme must be used to locate the sample points. 24
25 METHODOLOGY: Select various feasible land use categories in and around Bhopal city. Classify images by using ERDAS software and selecting different supervised methods as well as unsupervised methods. Verify classification accuracy by ground truthing with the help of GPS as well as Google images. Digitize each class boundary on Google image as well as different classified images and superimpose then in ERDAS to verify accuracy. 25
26 Study area and Data Resources: Bhopal City & adjoining area Some data of LISS-4 were purchased from NRSA Hyderabad for the date of field work done. 26
28 After acquiring the satellite images of the study areas, classification of LISS 4 Image of Bhopal was applied to the four methods of classification. These are: Unsupervised classification in which the applied algorithm is Iterative Self-Organizing Data Analysis Technique (ISODATA) Three different supervised methods which include Maximum likelihood, Mahalanobis Distance, and Minimum Distance.
29 After classified thematic maps were developed, accuracy was tested by different methods of accuracy assessment, and the post- classification process was the last process in classification. The software packages used for classification was ERDAS IMAGINE 11.
30 Class No. Name of class 1 Water bodies 2 Agricultural fields 3 Clouds/error 4 Urban buildings 5 Barren land 6 Forest
36 Image Classifi ication Ground Reference Row Total Colum n Total Maximum Likelihood Method:.Overall Accuracy= (104/130) x100=80% Calculate Producer s Accuracy for each class and User s Accuracy for each class.
37 Class 1=(12/15)x100=80.00% Class 2=(18/24)x100=75.00% Class 3=(12/18)x100=66.67% Class 4=(16/20)x100=80.00% Class 5=(16/21)x100=76.19% Class 6=(30/32)x100=93.75%
38 Class 1=(12/14)x100=85.71% Class 2=(18/22)x100=81.81% Class 3=(12/16)x100=75.00% Class 4=(16/21)x100=76.19% Class 5=(16/21)x100=76.19% Class 6=(30/36)x100=83.33%
39 Image Classifi ication Ground Reference Ro w Tot al Colum n Total Mahalanobis Distance Method:..Overall Accuracy= (107/140) x100=74.28%
40 Image Classifi ication Ground Reference Ro w Tot al Colum n Total Minimum Distance Method:.Overall Accuracy= (87/130) x100=67%
41 Error matrices produced to evaluate the classification methods show that the best overall classification accuracy method was the maximum likelihood with an average accuracy of about 80%. The second best overall classification accuracy method was mahalanobis distance; with an average accuracy of 74% and the worst overall classification accuracy method was minimum distance with an average accuracy of 67%.
42 References: 1.Jay Gao (2008):DETECTION OF CHANGES IN LAND DEGRADATION IN NORTHEAST CHINA FROM LANDSAT TM AND ASTER DATA, The International Archives of the Photogrammetry, Remote Sensing and Spatial Information Sciences. Vol. XXXVII. Part B7. Beijing-pp Prakasam.C.(2010):Land use and land cover change detection through remote sensing approach: A case study of Kodaikanal taluk, Tamil nadu, INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 1, No 2, 2010, 42
43 Contd. Yichun Xie et.al.(2008),remote sensing imagery in vegetation mapping: a review, Journal of Plant Ecology VOLUME 1, NUMBER 1, PAGES 9 23 MARCH 2008 Y.Babykalpana, K.ThanushKodi (2011):CLASSIFICATION OF LAND USE LAND COVER CHANGE DETECTION USING REMOTELY SENSED DATA,International Journal on Computer Science and Engineering (IJCSE) pp S. Balaselvakumar et.al. (2003),Remote Sensing Techniques for Land Use Mapping of Arjuna Basin, Tamil Nadu, Map Asia
44 Claudio Conese and Fabio MaseUi (1992), Use of Error Matrices to Improve Area Estimates with Maximum Likelihood Classification Procedures, REMOTE SENSING AND ENVIRONMENT 40: (1992) Ramachandra, T.V. and Uttam Kumar(2004): Geographic Resources Decision Support System for land use, land cover dynamics analysis, Proceedings of the FOSS/GRASS Users Conference - Bangkok, Thailand, September 2004 Marcus E. Engdahl and Juha M. Hyyppä(2003): Land- Cover Classification Using Multitemporal ERS-1/2 InSAR Data, IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING, VOL. 41, NO. 7, JULY
45 contd. M. A. Ibrahim et.al.(2004):approaches to Improve Accuracy of Neural Network Classification of Images Dominated by Mixed Pixels, IEEE,(2004), pp Nancy Thomas, et. al.(2003): A Comparison of Urban Mapping Methods Using High-Resolution Digital Imagery, Photogrammetric Engineering & Remote Sensing Vol. 69, No. 9, September 2003, pp
REMOTE SENSING AND GIS IN LAND USE PLANNING Sathees kumar P 1, Nisha Radhakrishnan 2 1 1 Ph.D Research Scholar, Department of Civil Engineering, National Institute of Technology, Tiruchirappalli- 620015,
INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 2, No 1, 2011 Copyright 2010 All rights reserved Integrated Publishing services Research article ISSN 0976 4380 Spatio-Temporal changes of Land
7 LAND USE AND LAND COVER 7.1 INTRODUCTION The knowledge of land use and land cover is important for many planning and management activities as it is considered as an essential element for modeling and
Landuse and Landcover change analysis in Selaiyur village, Tambaram taluk, Chennai K. Ilayaraja Department of Civil Engineering BIST, Bharath University Selaiyur, Chennai 73 ABSTRACT The synoptic picture
Cloud Publications International Journal of Advanced Remote Sensing and GIS 2013, Volume 2, Issue 1, pp. 374-378, Article ID Tech-181 ISSN 2320-0243 Case Study Open Access Remote Sensing and GIS Application
International Journal of Scientific & Engineering Research, Volume 3, Issue 11, November-2012 1 ABSTRACT Land use land cover change detection of Ghatkesar mandal,rangareddy district using Remote sensing
7 LAND USE AND LAND COVER 7.1 INTRODUCTION The knowledge of land use and land cover is important for many planning and management activities as it is considered an essential element for modeling and understanding
LAND USE MAPPING AND MONITORING IN THE NETHERLANDS (LGN5) Hazeu, Gerard W. Wageningen University and Research Centre - Alterra, Centre for Geo-Information, The Netherlands; email@example.com ABSTRACT
79 International Journal of Scientific & Engineering Research, Volume 4, Issue 12, December-2013 Approach to Assessment tor RS Image Classification Techniques Pravada S. Bharatkar1 and Rahila Patel1 ABSTRACT
Geospatial Information for Urban Sprawl Planning and Policies Implementation in Developing Country s NCR Region: A Study of NOIDA City, India Dr. Madan Mohan Assistant Professor & Principal Investigator,
International Journal of Scientific and Research Publications, Volume 3, Issue 5, May 2013 1 Accuracy Assessment of Land Use & Land Cover Classification (LU/LC) Case study of Shomadi area- Renk County-Upper
DETECTION AND ANALYSIS OF LAND-USE/LAND-COVER CHANGES IN NAY PYI TAW, MYANMAR USING SATELLITE REMOTE SENSING IMAGES Kay Khaing Oo 1, Eiji Nawata 1, Kiyoshi Torii 2 and Ke-Sheng Cheng 3 1 Division of Environmental
Proceedings of the 8th International Symposium on Spatial Accuracy Assessment in Natural Resources and Environmental Sciences Shanghai, P. R. China, June 25-27, 2008, pp. 183-188 A Method to Improve the
Overview of Remote Sensing in Natural Resources Mapping What is remote sensing? Why remote sensing? Examples of remote sensing in natural resources mapping Class goals What is Remote Sensing A remote sensing
Spatiotemporal Analysis of Noida, Greater Noida and Surrounding Areas (India) Using Remote Sensing and GIS Approaches Gopal Krishna* Indian Agricultural Research Institute, New Delhi, India ABSTRACT Spatiotemporal
Research on Topographic Map Updating Ivana Javorovic Remote Sensing Laboratory Ilica 242, 10000 Zagreb, Croatia Miljenko Lapaine University of Zagreb, Faculty of Geodesy Kaciceva 26, 10000 Zagreb, Croatia
P-318 Summary Application of Remote Sensing and GIS in Seismic Surveys in KG Basin M.Murali, K.Ramakrishna, U.K.Saha, G.Sarvesam ONGC Chennai Remote Sensing provides digital images of the Earth at specific
INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 4, No 1, 2013 Copyright 2010 All rights reserved Integrated Publishing services Research article ISSN 0976 4380 Spatio-temporal analysis of land
Progress and Land-Use Characteristics of Urban Sprawl in Busan Metropolitan City using Remote sensing and GIS Homyung Park, Taekyung Baek, Yongeun Shin, Hungkwan Kim ABSTRACT Satellite image is very usefully
Title Land cover/land use mapping and cha Mongolian plateau using remote sens Author(s) Bagan, Hasi; Yamagata, Yoshiki International Symposium on "The Imp Citation Region Specific Systems". 6 Nove Japan.
Hydrograph simulation for a rural watershed using SCS curve number and Geographic Information System Dr. S.SURIYA Assistant professor Department of Civil Engineering B. S. Abdur Rahman University Chennai
INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 6, No 2, 2015 Copyright by the authors - Licensee IPA- Under Creative Commons license 3.0 Research article ISSN 0976 4380 An Analysis of Land use
INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 4, No 4, 2014 Copyright 2010 All rights reserved Integrated Publishing services Research article ISSN 0976 4380 Land use/land cover change detection:
Indian Journal of Science and Technology, Vol 7(11), 1832 1841, November 2014 ISSN (Print) : 0974-6846 ISSN (Online) : 0974-5645 Spatio-Temporal Analysis of Land Cover/Land Use Changes Using Geoinformatics
RADAR BACKSCATTER AND COHERENCE INFORMATION SUPPORTING HIGH QUALITY URBAN MAPPING Peter Fischer (1), Zbigniew Perski ( 2), Stefan Wannemacher (1) (1)University of Applied Sciences Trier, Informatics Department,
Temporal Analysis of Land use Pattern Changes of Noida, NCR Using Geospatial Tools Noyingbeni Kikon & Prafull Singh Amity Institute of Geo-informatics and Remote Sensing Amity University, Sector-125, Noida,
INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 4, No 2, 2013 Copyright 2010 All rights reserved Integrated Publishing services Research article ISSN 0976 4380 Evaluation of landuse / landcover
Development of an urban classification method using a built-up index JIN A LEE, SUNG SOON LEE, KWANG HOON CHI Dep.Geoinformatic Engineering, University of Science & Technology Dep. Geoscience Information,
SATELLITE REMOTE SENSING of NATURAL RESOURCES David L. Verbyla LEWIS PUBLISHERS Boca Raton New York London Tokyo Contents CHAPTER 1. SATELLITE IMAGES 1 Raster Image Data 2 Remote Sensing Detectors 2 Analog
International Journal of Scientific and Research Publications, Volume 6, Issue 1, January 2016 197 Landuse/Landcover Change Detection in Umshing- Mawkynroh of East Khasi Hills District, Meghalaya Using
Polish J. of Environ. Stud. Vol. 19, No. 5 (2010), 881-886 Review Using the Geographical Information System and Remote Sensing Techniques for Soil Erosion Assessment Nuket Benzer* Landscape Architecture
Journal of Innovative Research in Engineering and Sciences 2(4), June, 2011. ISSN : 2141-8225. http://www.grpjournal.org. Printed in Nigeria. All rights researved. Global Research Publishing, 2011. Analysis
LAND USE AND LAND COVER CHANGE DETECTION AND URBAN SPRAWL ANALYSIS OF VIJAYAWADA CITY USING MULTITEMPORAL LANDSAT DATA *K. SUNDARAKUMAR 1, M. HARIKA 2, SK. ASPIYA BEGUM 2, S. YAMINI 2, K. BALAKRISHNA 2
Research Paper Land Use Changing Scenario at Kerniganj Thana of Dhaka District Using Remote Sensing and GIS Farzana Raihan 1 * and Nowrine Kaiser 1 1 Assistant Professor, Department of Forestry and Environment
INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 2, No 3, 2012 Copyright 2010 All rights reserved Integrated Publishing services Research article ISSN 0976 4380 Evaluation of Object-Oriented and
1. Abstract The use of SPOT and CIR aerial photography for urban planning P. Lohmann, G. Altrogge Institute for Photogrammetry and Engineering Surveys University of Hannover, Nienburger Strasse 1 o 3000
Mapping and Predicting Urban Sprawl Using Remote Sensing and Geographic Information System Techniques: A Case Study of Eti-Osa Local Government Area, Lagos, Nigeria Ajoke Onojeghuo & Alex Onojeghuo (Nigeria)
The 1 st Regional Conference of Eng. Sci. NUCEJ Spatial ISSUE vol.11,no.3, 2008 pp 357-365 Remote Sensing and GIS Techniques for Monitoring Industrial Wastes for Baghdad City Mohammad Ali Al-Hashimi University
Advances in Remote Sensing, 2013, 2, 276-281 http://dx.doi.org/10.4236/ars.2013.23030 Published Online September 2013 (http://www.scirp.org/journal/ars) Monitoring and Change Detection along the Eastern
THE CONTRIBUTION OF GIS AND REMOTE SENSING IN URBAN LAND USE NEGOTIATION IN DEVELOPING COUNTRIES Faith KARANJA*and Peter LOHMANN** University of Hannover Institute of Photogrammetry and Engineering Surveys(IPI)
Development of a Web Based Land Information System (LIS) using Integrated Remote Sensing and GIS Technology for Guwahati City, India Biswajit Sarma, Buragohain, S.*, Dhanunjaya Reddy, Y.*, Venkata Rao,
GLOBAL/CONTINENTAL LAND COVER MAPPING AND MONITORING Ryutaro Tateishi, Cheng Gang Wen, and Jong-Geol Park Center for Environmental Remote Sensing (CEReS), Chiba University 1-33 Yayoi-cho Inage-ku Chiba
Proceedings of the 13 th International Conference on Environmental Science and Technology Athens, Greece, 5-7 September 2013 MODELLING OF URBAN LAND USE AND ASSESSMENT OF FUTURE URBAN EXPANSION: APPLICATION
Regional Centre for Mapping of Resources for Development (RCMRD), Nairobi, Kenya Introduction GIS (: 10 days) Intake Dates: 9 th Jan, 6 th Feb, 6 th Mar, 3 rd April, 8 th May, 5 th June, 3 rd July, 2017
IMPROVING REMOTE SENSING-DERIVED LAND USE/LAND COVER CLASSIFICATION WITH THE AID OF SPATIAL INFORMATION Yingchun Zhou1, Sunil Narumalani1, Dennis E. Jelinski2 Department of Geography, University of Nebraska,
Global Journal of Environmental Science and Technology: ISSN-2360-7955, Vol. 3(1): pp 088-094, November, 2014. Copyright 2014 Spring Journals Full Length Research Paper Land use land cover change detection:
IJIRST International Journal for Innovative Research in Science & Technology Volume 2 Issue 10 March 2016 ISSN (online): 2349-6010 GIS Based Site Suitability Analysis for Establishing a Solar Power Park
Joint International Mechanical, Electronic and Information Technology Conference (JIMET 2015) Extracting Land Cover Change Information by using Raster Image and Vector Data Synergy Processing Methods Tao
Defining microclimates on Long Island using interannual surface temperature records from satellite imagery Deanne Rogers*, Katherine Schwarting, and Gilbert Hanson Dept. of Geosciences, Stony Brook University,
AUTOMATED CHANGE DETECTION FOR THEMATIC DATA USING OBJECT-BASED ANALYSIS OF REMOTE SENSING IMAGERY M. Reinhold a, *, P. Selsam a a Dept. of Geoinformatics, Hydrology and Modelling, Friedrich Schiller University,
Land Restoration /Reclamation Monitoring of Opencast Coal Mines of WCL Based On Satellite Data for the Year 2009 CMPDI A Miniratna Company Land Restoration /Reclamation Monitoring of Opencast Coal Mines
FLOOD ANALYSIS USING SATELLITE DATA AND GEOMORPHOLOGICAL SURVEY MAP SHOWING CLASSIFICATION OF FLOOD-INUNDATED AREAS Yasuharu YAMADA* *Japan International Research Center for Agricultural Sciences (JIRCAS),
IOP Conference Series: Earth and Environmental Science OPEN ACCESS Land use and land cover change detection at Mirzapur Union of Gazipur District of Bangladesh using remote sensing and GIS technology To
170 IAPRS, Vol. 32, Part 4 "GIS-Between Visions and Applications", Stuttgart, 1998 IMPROVEMENT OF THE AUTOMATIC MOMS02-P DTM RECONSTRUCTION Dieter Fritsch 1), Michael Kiefner 1), Dirk Stallmann 1), Michael
OBJECT-BASED CLASSIFICATION USING HIGH RESOLUTION SATELLITE DATA AS A TOOL FOR MANAGING TRADITIONAL JAPANESE RURAL LANDSCAPES K. Takahashi a, *, N. Kamagata a, K. Hara b a Graduate School of Informatics,
An Investigation of Reliability on Remote Sensing and GIS Data as an Aid to Urban Development Plan: A Case Study on Bhopal Abstract This study investigates the four criterias - namely scale of GIS map,
European Water 60: 67-71, 2017. 2017 E.W. Publications Indexing vulnerability of an embankment reach against breaching: A remote sensing and hydrodynamic based study B. Talukdar *, A. Baid and R. Das Civil
http:// STUDIES ON LAND USE/LAND COVER AND CHANGE DETECTION OF G.MADUGULA TRIBAL MANDAL OF VISAKHAPATNAM DISTRICT, ANDHRA PRADESH, INDIA USING REMOTE SENSING AND GIS TECHNIQUES. 1 Ch.Vasudeva Rao, 2 K.Harikrishna,
CHANGE DETECTION FROM LANDSAT-5 TM SATELLITE DATA Ummi Kalsom Mohd Hashim 1, Asmala Ahmad 1, Burhanuddin Mohd. Aboobaider 1, Hamzah Sakidin 2, Subatira B. 3 and Mohd Saari Mohamad Isa 4 1 Faculty of Information
International Journal of Geosciences, 2017, 8, 611-622 http://www.scirp.org/journal/ijg ISSN Online: 2156-8367 ISSN Print: 2156-8359 Accuracy Assessment of Land Use/Land Cover Classification Using Remote
Division of Spatial Information Science Graduate School Life and Environment Sciences University of Tsukuba Fundamentals of Remote Sensing Prof. Dr. Yuji Murayama Surantha Dassanayake 10/6/2010 1 Fundamentals
Object Based and Pixel Based Classification using Rapideye Satellite Imagery of Eti-Osa, Lagos, Nigeria Abstract E. O. Makinde a, A. T. Salami b, J. B. Olaleye a, O. C. Okewusi a a Department of Surveying
URBAN WATERSHED RUNOFF MODELING USING GEOSPATIAL TECHNIQUES DST Sponsored Research Project (NRDMS Division) By Prof. M. GOPAL NAIK Professor & Chairman, Board of Studies Email: firstname.lastname@example.org Department
Combination of Microwave and Optical Remote Sensing in Land Cover Mapping Key words: microwave and optical remote sensing; land cover; mapping. SUMMARY Land cover map mapping of various types use conventional
Yabancı Dil III (YDL285) Introduction to Geomatics Yrd. Doç. Dr. Saygın ABDİKAN 2017-2018 Öğretim Yılı Güz Dönemi 1 géomatique Geo (Earth) + informatics Geodesy + Geoinformatics Geomatics: The mathematics
Concurrent Self-Organizing Maps for Pattern Classification Victor-Emil NEAGOE and Armand-Dragos ROPOT Depart. of Applied Electronics and Information Eng., POLITEHNICA University of Bucharest, Bucharest,
LAND USE AND LAND COVER CHANGES AND URBAN SPRAWL IN RIYADH, SAUDI ARABIA: AN ANALYSIS USING MULTI-TEMPORAL LANDSAT DATA AND SHANNON'S ENTROPY INDEX M. T. Rahman a a King Fahd University of Petroleum and
INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 7, No 1, 2016 Copyright by the authors - Licensee IPA- Under Creative Commons license 3.0 Research article ISSN 0976 4380 Urban land use change
GIS AND REMOTE SENSING FOR WATER RESOURCE MANAGEMENT G. GHIANNI, G. ADDEO, P. TANO CO.T.IR. Extension and experimental station for irrigation technique - Vasto (Ch) Italy. E-mail : email@example.com, firstname.lastname@example.org,
njournal of Telecommunicatio s System & Management Journal of Telecommunications System & Management Kota et al., J Telecommun Syst Manage 2017, 6:1 DOI: 10.4172/2167-0919.1000148 Research Article OMICS
ADVANCED GIS SOLUTIONS TekMindz are developing innovative solutions that integrate geographic information with niche business applications. TEK INDZ TM GIS Services Overview At the leading edge of geospatial
DEVELOPMENT OF GPS PHOTOS DATABASE FOR LAND USE AND LAND COVER APPLICATIONS An Ngoc VAN and Wataru TAKEUCHI Institute of Industrial Science University of Tokyo 4-6-1 Komaba, Meguro-ku, Tokyo 153-8505 Japan
INT. J. REMOTE SENSING, 2003, VOL. 24, NO. 3, 583 594 Use of normalized difference built-up index in automatically mapping urban areas from TM imagery Y. ZHA College of Geographical Sciences, Nanjing Normal
DATA SOURCES AND INPUT IN GIS By Prof. A. Balasubramanian Centre for Advanced Studies in Earth Science, University of Mysore, Mysore 1 1. GIS stands for 'Geographic Information System'. It is a computer-based
INTERNATIONAL JOURNAL OF GEOMATICS AND GEOSCIENCES Volume 3, No 3, 2013 Copyright by the authors - Licensee IPA- Under Creative Commons license 3.0 Research article ISSN 0976 4380 Role of Remote Sensing
6. Image Classification 6.1 Concept of Classification Objectives of Classification Advantages of Multi-Spectral data for Classification Variation of Multi-Spectra Data Segmentation in Feature Domain Supervised
Customization of freeware GIS software for management of natural resources data for developmental planning - A case study Arati Paul, V. M. Chowdary, D. Chakraborty, D. Dutta, J. R. Sharma Abstract GIS
Global Journal of Human Social Science Vol. 10 Issue 1 (Ver 1.0), April 2010 Page 19 Analysis of Urban Surface Biophysical Descriptors and Land Surface Temperature Variations in Jimeta City, Nigeria Ambrose
13th World Conference on Earthquake Engineering Vancouver, B.C., Canada August 1-6, 2004 Paper No. 678 AUTOMATED BUILDING DETECTION FROM HIGH-RESOLUTION SATELLITE IMAGE FOR UPDATING GIS BUILDING INVENTORY
SUPPLEMENTARY Brief Communication INFORMATION DOI: 10.1038/s41559-017-0317-1 In the format provided by the authors and unedited. Reassessing the conservation status of the giant panda using remote sensing
Land Use Land Cover Change Projection for use in Municipal Water Resource Planning in the Saugahatchee Watershed by Rajesh Ramchandra Sawant A thesis submitted to the Graduate Faculty of Auburn University
IJCSIT International Journal of Computer Science and Information Technology, Vol. 4, No. 2, December 2011, pp. 55-59 Artificial Neural Network: A Tool for Classification of Land Use and Land Covers Using
CONCEPTUAL DEVELOPMENT OF AN ASSISTANT FOR CHANGE DETECTION AND ANALYSIS BASED ON REMOTELY SENSED SCENES J. Schiewe University of Osnabrück, Institute for Geoinformatics and Remote Sensing, Seminarstr.
Regional Centre for Mapping of Resources for Development (RCMRD), Nairobi, Kenya Introduction to GIS (2 weeks: 10 days) Intakes: 8 th January, 6 th February, 5th March, 3 rd. April 9 th, May 7 th, June
CENSUS MAPPING WITH GIS IN NAMIBIA BY Mrs. Ottilie Mwazi Central Bureau of Statistics E-mail: email@example.com Tel: + 264 61 283 4060 October 2007 Content of Presentation HISTORICAL BACKGROUND OF CENSUS