Seasonal Water Change Assessment at Mahanadi River, India using Multi-temporal Data in Google Earth Engine |
Jena, Ratiranjan
(The Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), University of Technology Sydney)
Pradhan, Biswajeet (The Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), University of Technology Sydney) Jung, Hyung-Sup (Department of Geoinformatics, University of Seoul) Rai, Abhishek Kumar (Centre for Oceans, Rivers, Atmosphere and Land Sciences (CORAL), Indian Institute of Technology Kharagpur) Rizeei, Hossein Mojaddadi (The Centre for Advanced Modelling and Geospatial Information Systems (CAMGIS), University of Technology Sydney) |
1 | Alley, W.M., T.E. Reilly, and O.L. Franke, 1999. Sustainability of Groundwater Resources, U. S. Geological Survey (U.S.GS), Denver, CO, USA. |
2 | Al-shalabi, M., L. Billa, B. Pradhan, S. Mansor, and A.A. Al-Sharif, 2013. Modelling urban growth evolution and land-use changes using GIS based cellular automata and SLEUTH models: the case of Sana'a metropolitan city, Yemen, Environmental Earth Sciences, 70(1): 425-437. DOI |
3 | Azeez, O.S., B. Pradhan, R. Jena, H.S. Jung, and A.A. Ahmed, 2019. Traffic Emission Modelling Using LiDAR Derived Parameters and Integrated Geospatial Model, Korean Journal of Remote Sensing, 35(1): 137-149. DOI |
4 | Bagan, H. and Y. Yamagata, 2012. Landsat analysis of urban growth: How Tokyo became the world's largest megacity during the last 40 years, Remote Sensing of Environment, 127: 210-222. DOI |
5 | Brisco, B., A. Schmitt, K. Murnaghan, S. Kaya, and A. Roth, 2013. SAR polarimetric change detection for flooded vegetation, International Journal of Digital Earth, 6(2): 103-114. DOI |
6 | Government of India central ground water board, Ministry of Water Resources & Ganga Rejuvenation, South Eastern Region Bhubaneswar, 2017. Ground water year book 2016-2017, http://cgwb.gov.in/Regions/GW-year-Books/GWYB-%202016-17/Orissa.pdf, Accessed on Feb. 15, 2019. |
7 | Demir, B., F. Bovolo, and L. Bruzzone, 2013. Updating land-cover maps by classification of image time series: A novel change-detection-driven transfer learning approach, IEEE Transactions on Geoscience and Remote Sensing, 51(1): 300-312. DOI |
8 | Dronova, I., P. Gong, and L. Wang, 2011. Object-based analysis and change detection of major wetland cover types and their classification uncertainty during the low water period at Poyang Lake, China, Remote Sensing of Environment, 115(12): 3220-3236. DOI |
9 | Ghasemi, K., B. Pradhan, and R. Jena, 2018. Spatial Identification of Key Alteration Minerals Using ASTER and Landsat 8 Data in a Heavily Vegetated Tropical Area, Journal of the Indian Society of Remote Sensing, 46(7): 1061-1073. DOI |
10 | Google Earth Engine, 2012. https://earthengine.google.com, Accessed on Feb. 5, 2017. |
11 | Gorelick, N., M. Hancher, M. Dixon, S. Ilyushchenko, D. Thau, and R. Moore, 2017. Google Earth Engine: Planetary-scale geospatial analysis for everyone, Remote Sensing of Environment, 202: 18-27. DOI |
12 | Hong, H., S.A. Naghibi, H.R. Pourghasemi, and B. Pradhan, 2016. GIS-based landslide spatial modelling in Ganzhou City, China, Arabian Journal of Geosciences, 9(2): 112. DOI |
13 | Pradhan, B., A.A.A. Moneir, and R. Jena, 2018. Sand dune risk assessment in Sabha region, Libya using Landsat 8, MODIS, and Google Earth Engine images, Geomatics, Natural Hazards and Risk, 9(1): 1280-1305. DOI |
14 | Jena, R., B. Pradhan, G. Beydoun, H. Sofyan, and M. Affan, 2019. Integrated model for earthquake risk assessment using neural network and analytic hierarchy process: Aceh province, Indonesia, Geoscience Frontiers, https://doi.org/10.1016/j.gsf.2019.07.006. |
15 | Kaliraj, S., S. Muthu Meenakshi, and V.K. Malar, 2012. Application of remote sensing in detection of forest cover changes using geo-statistical change detection matrices- A case study of devanampattu reserve forest, tamilnadu, India, Nature Environment and Pollution Technology, 11(2): 261-269. |
16 | Lu, S., B. Wu, N. Yan, and H. Wang, 2011. Water body mapping method with HJ-1A/B satellite imagery, International Journal of Applied Earth Observation, 13(3): 428-434. DOI |
17 | Markogianni, V., E. Dimitriou, and D.P. Kalivas, 2013. Land-use and vegetation change detection in plastira artificial lake catchment (Greece) by using remote sensing and GIS techniques, International Journal of Remote Sensing, 34(4): 1265-1281. DOI |
18 | Panda, U.C., S.K. Sundaray, P. Rath, B.B. Nayak, and D. Bhatta, 2006. Application of factor and cluster analysis for characterization of river and estuarine water systems-a case study: Mahanadi River (India), Journal of Hydrology, 331(3-4): 434-445. DOI |
19 | Pradhan, B., U. Hagemann, M.S. Tehrany, and N. Prechtel, 2014. An easy to use ArcMap based texture analysis program for extraction of flooded areas from TerraSAR-X satellite image, Computers & Geosciences, 63: 34-43. DOI |
20 | Raja, R.A., V. Anand, A.S. Kumar, S. Maithani, and V.A. Kumar, 2013. Wavelet based post classification change detection technique for urban growth monitoring, Journal of the Indian Society of Remote Sensing, 41(1): 35-43. DOI |
21 | South Asia Network on Dams, Rivers and People, 2017. State of India's River for India Rivers week, https://sandrp.in/2017/05/20/odisha-riversprofile, Accessed on Feb. 5, 2016. |
22 | Ridd, M.K. and J. Liu, 1998. A comparison of four algorithms for change detection in an urban environment, Remote Sensing of Environment, 63(2): 95-100. DOI |
23 | Rokni, K., A. Ahmad, A. Selamat, and S. Hazini, 2014. Water Feature Extraction and Change Detection Using Multitemporal Landsat Imagery, Remote Sensing, 6(5): 4173-4189. DOI |
24 | Salmon, B.P., W. Kleynhans, F. van Den Bergh, J.C. Olivier, T.L. Grobler, and K.J. Wessels, 2013. Land cover change detection using the internal covariance matrix of the extended Kalman filter over multiple spectral bands, IEEE Journal of Selected Topics Applied Earth Observations Remote Sensing, 6(3): 1079-1085. DOI |
25 | Sundaray, S.K., B.B. Nayak, S. Lin, and D. Bhatta, 2011. Geochemical speciation and risk assessment of heavy metals in the river estuarine sediments-a case study: Mahanadi basin, India, Journal of Hazardous Materials, 186(2-3): 1837-1846. DOI |
26 | Tang, Z., W. Ou, Y. Dai, and Y. Xin, 2013. Extraction of water body based on Landsat TM5 imagery - A case study in the Yangtze river, Proc. of 2012 International Conference on Computer and Computing Technologies in Agriculture, Zhangjiajie, China, Oct. 19-21, vol. 393, pp. 416-420. |
27 | Upadhyay, S., 1988. Physico-chemical characteristics of the Mahanadi estuarine ecosystem, east coast of India, http://nopr.niscair.res.in/handle/123456789/38450. |
28 | Xu, Y.B., X.J. Lai, and C.G. Zhou, 2010. Water surface change detection and analysis of bottomland submersion-emersion of wetlands in Poyang Lake reserve using ENVISAT ASAR data, China Environmental Science, 30: 57-63. |
29 | Volpi, M., G.P. Petropoulos, and M. Kanevski, 2013. Flooding extent cartography with Landsat TM imagery and regularized Kernel Fisher's discriminant analysis, Computers & Geosciences, 57: 24-31. DOI |