Remote Sensing Time Series Revealing Land Surface Dynamics: Status Quo and the Pathway Ahead
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[1] Damien Sulla-Menashe,et al. MODIS Collection 5 global land cover: Algorithm refinements and characterization of new datasets , 2010 .
[2] de Beurs,et al. A statistical framework for the analysis of long image time series , 2005 .
[3] Zhiqiang Yang,et al. Detecting trends in forest disturbance and recovery using yearly Landsat time series: 1. LandTrendr — Temporal segmentation algorithms , 2010 .
[4] N. Oppelt,et al. Tree cover and forest cover dynamics in the Mekong Basin from 2001 to 2011 , 2015 .
[5] Joanne C. White,et al. Generation of dense time series synthetic Landsat data through data blending with MODIS using a spatial and temporal adaptive reflectance fusion model. , 2009 .
[6] Richard M. Goldstein,et al. Rapid subsidence over oil fields measured by SAR interferometry , 1998 .
[7] J. Peñuelas,et al. European phenological response to climate change matches the warming pattern , 2006 .
[8] P. Hostert,et al. Mining dense Landsat time series for separating cropland and pasture in a heterogeneous Brazilian savanna landscape , 2015 .
[9] R. Marchand,et al. Constraining cloud lifetime effects of aerosols using A‐Train satellite observations , 2012 .
[10] Alan H. Strahler,et al. Global land cover mapping from MODIS: algorithms and early results , 2002 .
[11] J. Masek,et al. Long-term time series of the Earth's land-surface observations from space , 2012 .
[12] Joanne C. White,et al. An integrated Landsat time series protocol for change detection and generation of annual gap-free surface reflectance composites , 2015 .
[13] W. Wagner,et al. A Method for Estimating Soil Moisture from ERS Scatterometer and Soil Data , 1999 .
[14] C. Kuenzer,et al. Land-surface temperature dynamics in the Upper Mekong Basin derived from MODIS time series , 2014, Remote Sensing the Mekong.
[15] Y. Ban. Synergy of multitemporal ERS-1 SAR and Landsat TM data for classification of agricultural crops , 2003 .
[16] W. Wagner,et al. Suitability of SAR imagery for automatic flood mapping in the Lower Mekong Basin , 2014, Remote Sensing the Mekong.
[17] P. Defourny,et al. Monitoring forest changes in Borneo on a yearly basis by an object-based change detection algorithm using SPOT-VEGETATION time series , 2012 .
[18] D. Roberts,et al. A comparison of methods for monitoring multitemporal vegetation change using Thematic Mapper imagery , 2002 .
[19] M. Bauer,et al. Land cover classification and change analysis of the Twin Cities (Minnesota) Metropolitan Area by multitemporal Landsat remote sensing , 2005 .
[20] Jiunn-Der Duh,et al. Rates of urbanisation and the resiliency of air and water quality. , 2008, The Science of the total environment.
[21] W. Keeton,et al. Forest cover change and illegal logging in the Ukrainian Carpathians in the transition period from 1988 to 2007 , 2009 .
[22] Michele Manunta,et al. Long-term ERS/ENVISAT deformation time-series generation at full spatial resolution via the extended SBAS technique , 2012 .
[23] Claudia Kuenzer,et al. Analysis of coal fire dynamics in the Wuda syncline impacted by fire-fighting activities based on in-situ observations and Landsat-8 remote sensing data , 2015 .
[24] Huadong Guo,et al. Earth observation satellite sensors for biodiversity monitoring: potentials and bottlenecks , 2014 .
[25] Christopher Conrad,et al. Snow-cover variability in central Asia between 2000 and 2011 derived from improved MODIS daily snow-cover products , 2013 .
[26] Yi Y. Liu,et al. Evaluating global trends (1988–2010) in harmonized multi‐satellite surface soil moisture , 2012 .
[27] H. Zebker,et al. Sensing the ups and downs of Las Vegas: InSAR reveals structural control of land subsidence and aquifer-system deformation , 1999 .
[28] Yang Zhong,et al. Urbanization, land use, and water quality in Shanghai. 1947-1996. , 2003, Environment international.
[29] Nicholas C. Coops,et al. Detecting forest damage after a low-severity fire using remote sensing at multiple scales , 2015, Int. J. Appl. Earth Obs. Geoinformation.
[30] Maurizio Santoro,et al. Multitemporal repeat pass SAR interferometry of boreal forests , 2005, IEEE Trans. Geosci. Remote. Sens..
[31] Ranga B. Myneni,et al. Monitoring spring canopy phenology of a deciduous broadleaf forest using MODIS , 2006 .
[32] Deming Zhao,et al. Evaluation of the ERS Scatterometer-Derived Soil Water Index to Monitor Water Availability and Precipitation Distribution at Three Different Scales in China , 2008 .
[33] Christiane Schmullius,et al. Large-scale mapping of boreal forest in Siberia , 2003 .
[34] Christina Eisfelder,et al. Net primary productivity in Kazakhstan, its spatio-temporal patterns and relation to meteorological variables , 2014 .
[35] Christiane Schmullius,et al. Large area forest stem volume mapping in the boreal zone using synergy of ERS-1/2 tandem coherence and MODIS vegetation continuous fields , 2011 .
[36] Xinwu Li,et al. A Novel Land Cover Classification Map Based on a MODIS Time-Series in Xinjiang, China , 2014, Remote. Sens..
[37] Claudia Kuenzer,et al. European Snow Cover Characteristics between 2000 and 2011 Derived from Improved MODIS Daily Snow Cover Products , 2012, Remote. Sens..
[38] Rosa Lasaponara,et al. Satellite time-series analysis , 2012 .
[39] M. Pandit,et al. Threats from India's Himalaya Dams , 2013, Science.
[40] E. Lambin,et al. Dynamics of Land-Use and Land-Cover Change in Tropical Regions , 2003 .
[41] Runqiu Huang,et al. GIS modelling of earthquake damage zones using satellite remote sensing and DEM data , 2012 .
[42] Andreas Mueller,et al. Partial unmixing as a tool for single surface class detection and time series analysis , 2008 .
[43] M. D. Schwartz. Phenology: An Integrative Environmental Science , 2003, Tasks for Vegetation Science.
[44] Xinwu Li,et al. Flood Mapping and Flood Dynamics of the Mekong Delta: ENVISAT-ASAR-WSM Based Time Series Analyses , 2013, Remote. Sens..
[45] Klaus Scipal,et al. Azimuthal anisotropy of scatterometer measurements over land , 2006, IEEE Transactions on Geoscience and Remote Sensing.
[46] Annett Bartsch,et al. Detection of open water dynamics with ENVISAT ASAR in support of land surface modelling at high latitudes , 2012 .
[47] Urs Wegmüller,et al. Forest growing stock volume of the northern hemisphere: Spatially explicit estimates for 2010 derived from Envisat ASAR , 2015 .
[48] Wolfgang Wagner,et al. Seven Years of Advanced Synthetic Aperture Radar (ASAR) Global Monitoring (GM) of Surface Soil Moisture over Africa , 2014, Remote. Sens..
[49] Mathew R. Schwaller,et al. On the blending of the Landsat and MODIS surface reflectance: predicting daily Landsat surface reflectance , 2006, IEEE Transactions on Geoscience and Remote Sensing.
[50] Maurizio Santoro,et al. Stem volume retrieval in boreal forests from ERS-1/2 interferometry , 2002 .
[51] I. Overeem,et al. Land subsidence at aquaculture facilities in the Yellow River delta, China , 2013 .
[52] Lorenzo Bruzzone,et al. A partially unsupervised cascade classifier for the analysis of multitemporal remote-sensing images , 2002, Pattern Recognit. Lett..
[53] Carlos Torres-Verdín,et al. Efficient Numerical Simulation of Axisymmetric Electromagnetic Induction Measurements Using a High-Order Generalized Extended Born Approximation , 2006, IEEE Transactions on Geoscience and Remote Sensing.
[54] Damien Sulla-Menashe,et al. Detecting forest disturbance in the Pacific Northwest from MODIS time series using temporal segmentation , 2014 .
[55] Christopher Conrad,et al. Identifying Changing Snow Cover Characteristics in Central Asia between 1986 and 2014 from Remote Sensing Data , 2014, Remote. Sens..
[56] Stephen V. Stehman,et al. International Journal of Applied Earth Observation and Geoinformation: Time-Series Analysis of Multi-Resolution Optical Imagery for Quantifying Forest Cover Loss in Sumatra and Kalimantan, Indonesia , 2011 .
[57] Wolfgang Wagner,et al. How do Spatial Scale, Noise, and Reference Data affect Empirical Estimates of Error in ASAR-Derived 1 km Resolution Soil Moisture? , 2014, IEEE Journal of Selected Topics in Applied Earth Observations and Remote Sensing.
[58] Martha C. Anderson,et al. Free Access to Landsat Imagery , 2008, Science.
[59] Xiaolin Zhu,et al. An enhanced spatial and temporal adaptive reflectance fusion model for complex heterogeneous regions , 2010 .
[60] Geoffrey M. Henebry,et al. Land surface phenology and temperature variation in the International Geosphere–Biosphere Program high‐latitude transects , 2005 .
[61] Urs Wegmüller,et al. Retrieval of growing stock volume in boreal forest using hyper-temporal series of Envisat ASAR ScanSAR backscatter measurements , 2011 .
[62] William B. Rossow,et al. Update of Radiance Calibrations for ISCCP , 1997 .
[63] Mark D. Schwartz,et al. Assessing satellite‐derived start‐of‐season measures in the conterminous USA , 2002 .
[64] Yoshio Yamaguchi,et al. Monitoring freeze/thaw cycles using ENVISAT ASAR Global Mode , 2011 .
[65] Stefan Dech,et al. Characterisation of land surface phenology and land cover based on moderate resolution satellite data in cloud prone areas — A novel product for the Mekong Basin , 2013 .
[66] L. Rebelo,et al. Remote sensing and GIS for wetland inventory, mapping and change analysis. , 2009, Journal of environmental management.
[67] J. Eitzinger,et al. The ASCAT Soil Moisture Product: A Review of its Specifications, Validation Results, and Emerging Applications , 2013 .
[68] Wolfgang Wagner,et al. Evaluation of Soil Moisture Retrieval from the ERS and Metop Scatterometers in the Lower Mekong Basin , 2013, Remote. Sens..
[69] Per Jönsson,et al. TIMESAT - a program for analyzing time-series of satellite sensor data , 2004, Comput. Geosci..
[70] Jan Haas,et al. Urban growth and environmental impacts in Jing-Jin-Ji, the Yangtze, River Delta and the Pearl River Delta , 2014, Int. J. Appl. Earth Obs. Geoinformation.
[71] Stefan Dech,et al. Quantitative comparison of the operational NOAA-AVHRR LST product of DLR and the MODIS LST product V005 , 2012 .
[72] Stefan Dech,et al. Results of the Global WaterPack: a novel product to assess inland water body dynamics on a daily basis , 2015 .
[73] Rob J Hyndman,et al. Detecting trend and seasonal changes in satellite image time series , 2010 .
[74] Michael A. Wulder,et al. Opening the archive: How free data has enabled the science and monitoring promise of Landsat , 2012 .
[75] Klaus Scipal,et al. El Niño southern oscillation influences represented in ERS scatterometer-derived soil moisture data. , 2009 .
[76] Feng Gao,et al. Temporally smoothed and gap‐filled MODIS land products for carbon modelling: application of the fPAR product , 2009 .
[77] M. Schaepman,et al. Intercomparison, interpretation, and assessment of spring phenology in North America estimated from remote sensing for 1982–2006 , 2009 .
[78] Matthias Drusch,et al. Sentinel-2: ESA's Optical High-Resolution Mission for GMES Operational Services , 2012 .
[79] Thuy Le Toan,et al. Rice crop mapping and monitoring using ERS-1 data based on experiment and modeling results , 1997, IEEE Trans. Geosci. Remote. Sens..
[80] T. Esch,et al. Monitoring urbanization in mega cities from space , 2012 .
[81] R. Fensholt,et al. Evaluation of earth observation based long term vegetation trends - Intercomparing NDVI time series trend analysis consistency of Sahel from AVHRR GIMMS, Terra MODIS and SPOT VGT data , 2009 .