Multi-Decadal Changes in Mangrove Extent, Age and Species in the Red River Estuaries of Viet Nam

[1]  E. Vermote,et al.  Operational Atmospheric Correction of Landsat TM Data , 1999 .

[2]  Paul M. Mather,et al.  An assessment of the effectiveness of decision tree methods for land cover classification , 2003 .

[3]  Russell G. Congalton,et al.  A review of assessing the accuracy of classifications of remotely sensed data , 1991 .

[4]  R. Pontius,et al.  Death to Kappa: birth of quantity disagreement and allocation disagreement for accuracy assessment , 2011 .

[5]  Stuart R. Phinn,et al.  Hyperspectral Data for Mangrove Species Mapping: A Comparison of Pixel-Based and Object-Based Approach , 2011, Remote. Sens..

[6]  Peter M. Atkinson,et al.  Spatiotemporal Variation in Mangrove Chlorophyll Concentration Using Landsat 8 , 2015, Remote. Sens..

[7]  H. Abdi,et al.  Principal component analysis , 2010 .

[8]  Bradley C. Rundquist,et al.  Using the Hazus-MH flood model to evaluate community relocation as a flood mitigation response to terminal lake flooding: The case of Minnewaukan, North Dakota, USA , 2012 .

[9]  Hyung-Sup Jung,et al.  Please Scroll down for Article International Journal of Image and Data Fusion Radar Image and Data Fusion for Natural Hazards Characterisation Radar Image and Data Fusion for Natural Hazards Characterisation , 2022 .

[10]  Toshiro Sugimura,et al.  Analysis of landuse change in periphery of Tokyo during last twenty years using the same seasonal landsat data , 1998 .

[11]  Hartono,et al.  Mangrove biomass carbon stock mapping of the Karimunjawa Islands using multispectral remote sensing , 2016 .

[12]  W. Verhoef,et al.  Remote sensing of solar-induced chlorophyll fluorescence (SIF) in vegetation: 50 years of progress. , 2019, Remote sensing of environment.

[13]  Natascha Oppelt,et al.  Remote Sensing in Mapping Mangrove Ecosystems - An Object-Based Approach , 2013, Remote. Sens..

[14]  N. Quang,et al.  Synthetic aperture radar and optical remote sensing image fusion for flood monitoring in the Vietnam lower Mekong basin: a prototype application for the Vietnam Open Data Cube , 2019, European Journal of Remote Sensing.

[15]  Naoto Yokoya,et al.  Estimating Mangrove Above-Ground Biomass Using Extreme Gradient Boosting Decision Trees Algorithm with Fused Sentinel-2 and ALOS-2 PALSAR-2 Data in Can Gio Biosphere Reserve, Vietnam , 2020, Remote. Sens..

[16]  Pi-Fuei Hsieh,et al.  Effect of spatial resolution on classification errors of pure and mixed pixels in remote sensing , 2001, IEEE Trans. Geosci. Remote. Sens..

[17]  A. Held,et al.  High resolution mapping of tropical mangrove ecosystems using hyperspectral and radar remote sensing , 2003 .

[18]  Mahmod Reza Sahebi,et al.  Forest structure parameter extraction using SPOT-7 satellite data by object- and pixel-based classification methods , 2019, Environmental Monitoring and Assessment.

[19]  Chih-Jen Lin,et al.  Probability Estimates for Multi-class Classification by Pairwise Coupling , 2003, J. Mach. Learn. Res..

[20]  A. Skidmore,et al.  Tropical mangrove species discrimination using hyperspectral data: A laboratory study , 2005 .

[21]  Christine Pohl,et al.  Multisensor image fusion in remote sensing: concepts, methods and applications , 1998 .

[22]  Anil K. Jain,et al.  Multisource classification of remotely sensed data: fusion of Landsat TM and SAR images , 1994, IEEE Trans. Geosci. Remote. Sens..

[23]  Timothy A. Warner,et al.  Implementation of machine-learning classification in remote sensing: an applied review , 2018 .

[24]  K. Viergever,et al.  Mapping of mangrove forest land cover change along the Kenya coastline using Landsat imagery , 2013 .

[25]  Alfred Stein,et al.  Spatiotemporal Image Fusion in Remote Sensing , 2019, Remote. Sens..

[26]  Catherine Ticehurst,et al.  Mapping the multi-decadal mangrove dynamics of the Australian coastline , 2020, Remote Sensing of Environment.

[27]  Praveen K. Thakur,et al.  Detecting, mapping and analysing of flood water propagation using synthetic aperture radar (SAR) satellite data and GIS: A case study from the Kendrapara District of Orissa State of India , 2017, The Egyptian Journal of Remote Sensing and Space Science.

[28]  F. Blasco,et al.  Assessment from space of mangroves evolution in the Mekong Delta, in relation to extensive shrimp farming , 2004 .

[29]  Steffen Gebhardt,et al.  Remote Sensing of Mangrove Ecosystems: A Review , 2011, Remote. Sens..

[30]  Hui Lin,et al.  GF-5 Hyperspectral Data for Species Mapping of Mangrove in Mai Po, Hong Kong , 2020, Remote. Sens..

[31]  F. Blasco,et al.  A remote sensing based methodology for mangrove studies in Madagascar , 1998 .

[32]  S. Robeson,et al.  Mapping spatial distribution and biomass of coastal wetland vegetation in Indonesian Papua by combining active and passive remotely sensed data , 2016 .

[33]  Pablo J. Zarco-Tejada,et al.  Assessing the effects of forest health on sun-induced chlorophyll fluorescence using the FluorFLIGHT 3-D radiative transfer model to account for forest structure , 2017 .

[34]  Leo Breiman,et al.  Random Forests , 2001, Machine Learning.

[35]  Karen E. Joyce,et al.  Quantifying mangrove chlorophyll from high spatial resolution imagery , 2015 .

[36]  N. Loneragan,et al.  Assessing techniques for estimating the extent of mangroves: Topographic maps, aerial photographs and Landsat TM images , 2001 .

[37]  Hankui K. Zhang,et al.  Meta-discoveries from a synthesis of satellite-based land-cover mapping research , 2014 .

[38]  A. C. Ellis,et al.  Remote sensing techniques for mangrove mapping , 1998 .

[39]  D. Amarsaikhan,et al.  Data fusion and multisource image classification , 2004 .

[40]  Chandra P. Giri,et al.  Mapping the Philippines’ Mangrove Forests Using Landsat Imagery , 2011, Sensors.

[41]  Sandeep Thakur,et al.  A review of the application of multispectral remote sensing in the study of mangrove ecosystems with special emphasis on image processing techniques , 2019, Spatial Information Research.

[42]  Dengsheng Lu,et al.  Assessment of atmospheric correction methods for Landsat TM data applicable to Amazon basin LBA research , 2002 .

[43]  F. Blasco,et al.  RECENT ADVANCES IN MANGROVE STUDIES USING REMOTE SENSING DATA , 1998 .

[44]  W. Adger Social Vulnerability to Climate Change and Extremes in Coastal Vietnam , 1999 .

[45]  M. Marconcini,et al.  Normalized Difference Flood Index for rapid flood mapping: Taking advantage of EO big data , 2018 .

[46]  Martin Kappas,et al.  Comparison of Multiple Linear Regression, Cubist Regression, and Random Forest Algorithms to Estimate Daily Air Surface Temperature from Dynamic Combinations of MODIS LST Data , 2017, Remote. Sens..

[47]  C. Proisy,et al.  Predicting and mapping mangrove biomass from canopy grain analysis using Fourier-based textural ordination of IKONOS images , 2007 .

[48]  Le Wang,et al.  A review of remote sensing for mangrove forests: 1956–2018 , 2019, Remote Sensing of Environment.

[49]  R. Vidhya,et al.  Improved Classification of Mangroves Health Status Using Hyperspectral Remote Sensing Data , 2014 .

[50]  V. Klemas,et al.  Mangrove mapping in Ecuador: The impact of shrimp pond construction , 1986 .

[51]  P. Gong,et al.  Comparison of IKONOS and QuickBird images for mapping mangrove species on the Caribbean coast of Panama , 2004 .

[52]  C. Hackney,et al.  Hydrological/Hydraulic Modeling-Based Thresholding of Multi SAR Remote Sensing Data for Flood Monitoring in Regions of the Vietnamese Lower Mekong River Basin , 2019, Water.

[53]  W. Adger,et al.  Natural resource management in mitigating climate impacts: the example of mangrove restoration in Vietnam , 1998 .

[54]  Peter F. Fisher,et al.  Spatial analysis of remote sensing image classification accuracy , 2012 .

[55]  Hava T. Siegelmann,et al.  Support Vector Clustering , 2002, J. Mach. Learn. Res..

[56]  AbdiHervé,et al.  Principal Component Analysis , 2010, Essentials of Pattern Recognition.

[57]  C. Duarte,et al.  The determination of the age and growth of SE Asian mangrove seedlings from internodal counts , 1999 .

[58]  Shing Yip Lee,et al.  Seeing the forest as well as the trees: An expert opinion approach to identifying holistic condition indicators for mangrove ecosystems , 2019, Estuarine, Coastal and Shelf Science.

[59]  Anuar Ahmad,et al.  A new approach for surface water change detection: Integration of pixel level image fusion and image classification techniques , 2015, Int. J. Appl. Earth Obs. Geoinformation.

[60]  Manfred Ehlers,et al.  Multisensor image fusion techniques in remote sensing , 1991 .