Exploring changes of land use and mangrove distribution in the economic area of Sidoarjo District, East Java using multi-temporal Landsat images
Tài liệu tham khảo
Kanniah, 2015, Satellite images for monitoring mangrove cover changes in a fast growing economic region in Southern Peninsular Malaysia, Remote Sens, 7, 14361, 10.3390/rs71114360
Son, 2015, Mangrove mapping and change detection in Ca Mau Peninsula, Vietnam, using landsat data and object-based image analysis, IEEE J Sel Top Appl Earth Obs Remote Sens, 8, 503, 10.1109/JSTARS.2014.2360691
Furukawa, 1997, Currents and sediment transport in mangrove forests, Estuar Coast Shelf Sci, 44, 301, 10.1006/ecss.1996.0120
Giri, 2011, Status and distribution of mangrove forests of the world using earth observation satellite data, Glob Ecol Biogeogr, 20, 154, 10.1111/j.1466-8238.2010.00584.x
Septayana, 2014, The decline in housing supply after the emergency of lapindo mudflow disaster in the Peri Urban Areas of Surabaya, Procedia Soc Behav Sci, 135, 50, 10.1016/j.sbspro.2014.07.324
Primavera, 2005, Mangroves, fishponds, and the quest for sustainability, Science, 5745, 57, 10.1126/science.1115179
Lin, 2015, Effects of atmospheric correction and pansharpening on LULC classification accuracy using worldview-2 imagery, Inform Process Agr, 2, 25
Lin, 2015, A novel reflectance-based model for evaluating chlorophyll concentration of fresh and water-stressed leaves, Biogeosciences, 12, 49, 10.5194/bg-12-49-2015
Lin, 2015, Deriving the spatiotemporal NPP Pattern in terrestrial ecosystems of mongolia using MODIS imagery, Photogramm Eng Remote Sens, 81, 587, 10.14358/PERS.81.7.587
Lopresti, 2015, Relationship between MODIS-NDVI data and wheat yield: a case study in Northern Buenos Aires province, Argentina Inform Process Agr, 2, 73
Popescu, 2011, Satellite lidar vs. small footprint airborne lidar: comparing the accuracy of aboveground biomass estimates and forest structure metrics at footprint level, Remote Sens Environ, 115, 2786, 10.1016/j.rse.2011.01.026
Lin, 2013, Comparison of carbon sequestration potential in agricultural and afforestation farming systems, Sci Agr, 70, 93, 10.1590/S0103-90162013000200006
Lin, 2016, An IPCC-compliant technique for forest carbon stock assessment using airborne LiDAR-derived tree metrics and competition index, Remote Sens, 8, 528, 10.3390/rs8060528
Singh, 2017, Detection of plant leaf diseases using image segmentation and soft computing techniques, Inform Process Agr, 4, 41
Lin, 2011, A multi-level morphological active contour algorithm for delineating tree crowns in mountainous forest, Photogramm Eng Remote Sens, 77, 241, 10.14358/PERS.77.3.241
Lo, 2013, Growth-competition-based stem diameter and volume modeling for tree-level forest inventory using airborne LiDAR Data, IEEE Trans Geosci Remote Sens, 51, 2216, 10.1109/TGRS.2012.2211023
Lin, 2015, Classification of tree species in overstorey canopy of subtropical forest using quickbird images, PLoS One, 10, e0125554, 10.1371/journal.pone.0125554
Lin C, Lo KL, Huang PL. A classification method of unmanned-aerial-systems-derived point cloud for generating a canopy height model of farm forest. In: Proc. IGARSS’16. Proceedings of Geoscience and Remote Sensing Symposium (IGARSS), 2016 IEEE International. Beijing, China, vol. 1; 2016. p. 740–743. doi: 10.1109/IGARSS.2016.7729186.
Lin, 2016, Identifying forest ecosystem regions for agricultural use and conservation, Sci Agr, 73, 62, 10.1590/0103-9016-2014-0440
Chen, 2013, PPI-SVM-Iterative FLDA approach to unsupervised multispectral image classification, IEEE J Sel Top Appl Earth Obs Remote Sens, 6, 1834, 10.1109/JSTARS.2012.2225097
Lin C, Trianingsih D. Evaluation of the Reliability of Classifiers for the Mapping of Mangrove Forest using Landsat TM Images. In: Proc. ICETCE’12. Proceedings of the Second International conference on Electric Technology and Civil Engineering (ICETCE), 2012 Three Gorges, China, vol. 5; 2012. p. 3163–3166. doi: 10.1109/ICETCE.2012.291.
Huang, 2002, An assessment of support vector machines for land cover classification, Int J Remote Sens, 23, 725, 10.1080/01431160110040323
Koetz, 2008, Multi-source land cover classification for forest fire management based on imaging spectrometry and LiDAR data, For Ecol Manage, 256, 263, 10.1016/j.foreco.2008.04.025
Petropoulos, 2011, Burnt area delineation from a uni-temporal perspective based on Landsat TM imagery classification using support vector machines, Int J Appl Earth Obs Geoinf, 13, 70, 10.1016/j.jag.2010.06.008
Central Bureau of Statistics. Sidoarjo Regency in Figures 2015 (Sidoarjo Dalam Angka 2015). Statistics of Sidoarjo 2015; 29–35 and 252–257.
Rochmania, 2015, Society reception on the marine ecotourism in minneapolitan region of Sidoarjo District, Asian J Hum Soc Stud, 3, 433
Jensen, 2004
Matthew MW, Adler-Golden SM, Berk A, Felde G, Anderson GP, Gorodetzky D, Paswaters S, Shippert M. Atmospheric Correction of Spectral Imagery: Evaluation of the FLAASH Algorithm with AVIRIS Data. In: Proc. Proceedings SPIE 2003; vol. 5093, p. 474–482.
Hatfield, 2008, Application of spectral remote sensing of agronomic decisions, Agron J, 100, S117, 10.2134/agronj2006.0370c
Ricotta, 1999, Mapping and monitoring net primary productivity with AVHRR NDVI time series, ISPRS J Photogramm Remote Sens, 54, 325, 10.1016/S0924-2716(99)00028-3
Gench, 2013, Determination of water stress with spectral reflectance on sweet corn (Zea mays L.) using classification tree (CT) analysis, Zemdirbyste-Agri, 100, 81, 10.13080/z-a.2013.100.011
Jiang, 2006, Analysis of NDVI and scaled difference vegetation index retrievals of vegetation fraction, Remote Sens Environ, 101, 367, 10.1016/j.rse.2006.01.003
Lillesand, 2011, 520
Cristiano, 2010, Uncertainties in fPAR estimation of grass canopies under different stress situations and differences in architecture, Int J Remote Sens, 31, 4095, 10.1080/01431160903229192
DeJonge, 2016, Assessing corn water stress using spectral reflectance, Int J Remote Sens, 37, 2294, 10.1080/01431161.2016.1171929
Abdalla, 2015, Using MODIS- derived NDVI and SAVI to distinguish between different rangeland sites according to soil types in semi-arid areas of Sudan (North Kordofan State), Int J Life Sci Eng, 1, 150
Zheng, 2016, Discrimination of settlement and industrial area using landscape metrics in rural region, Remote Sens, 8, 845, 10.3390/rs8100845
Congalton, 1991, A review of assessing the accuracy of classifications of remotely sensed data, Remote Sens Environ, 37, 35, 10.1016/0034-4257(91)90048-B
Hegazy, 2015, Monitoring urban growth and land use change detection with GIS and remote sensing techniques in Daqahlia Governorate Egypt, Int J Sust Built Environ, 4, 117, 10.1016/j.ijsbe.2015.02.005
Butt, 2015, Land use change mapping and analysis using remote sensing and GIS: a case study of simly Watershed, Islamabad, Pakistan, Egypt J Remote Sens Space Sci (EJRS), 18, 251
Huang, 2009, Evaluation of morphological texture features for mangrove forest mapping and species discrimination using multispectral IKONOS imagery, IEEE Trans Geosci Remote Sens, 6, 393, 10.1109/LGRS.2009.2014398
Heumann, 2011, An object-based classification of mangroves using a hybrid decision tree support vector machine approach, Remote Sens, 3, 2440, 10.3390/rs3112440
Paneque-Galvez, 2013, Enhanced land use/cover classification of heterogeneous tropical landscapes using support vector machines and textural homogeneity, Int J Appl Earth Obs Geoinf, 23, 372, 10.1016/j.jag.2012.10.007
Doxani G, Siachalou S, Tsakiri-Strati M. An Object-oriented Approach to Urban Land Cover Change Detection. http://www.isprs.org/proceedings/XXXVII/congress/7_pdf/10_ThS-18/22.pdf. 2008.
Thomlinson, 1999, Coordinating methodologies for scaling land cover classifications from site-specific to global: steps toward validating global map products, Remote Sens Environ, 70, 25, 10.1016/S0034-4257(99)00055-3
Istadi, 2009, Modeling study of growth and potential Geohazard for LUSI Mud Volcano: East Java, Indonesia, Mar Pet Geol, 26, 1724, 10.1016/j.marpetgeo.2009.03.006
Bidayani E, Soemarno, Harahap N, Rudianto. Blue Economy Approach-Based Mangrove Resources Conservation for Coastal Community’s Prosperity in Sidoarjo Regency, East Java, Indonesia. Int. J. Ecosyst. 2016; 6(1), 1–9.
Jennerjahn, 2013, Environmental impact of Mud Volcano inputs on the anthropogenically altered Porong River and Madura Strait Coastal Waters, Java, Indonesia, Estuar Coast Shelf Sci, 130, 152, 10.1016/j.ecss.2013.04.007
Sidik, 2016, Effect of High Sedimentation Rates on Surface Sediment Dynamics and Mangrove Growth in the Porong River, Indonesia, Mar Pollut Bull, 107, 355, 10.1016/j.marpolbul.2016.02.048
Alongi, 2009, 2
Morrisey, 2010, The ecology and management of temperate mangroves, Oceanogr Mar Biol Annu, 48, 43
Lin, 2016, A decompositional stand structure analysis for exploring stand dynamics of multiple attributes of a mixed-species forest, For Ecol Manag, 378, 111, 10.1016/j.foreco.2016.07.022