Use of Remote Sensing Techniques for Robust Digital Change Detection of Land: A Review

[1]  A. Huete,et al.  Overview of the radiometric and biophysical performance of the MODIS vegetation indices , 2002 .

[2]  Graciela Metternicht Change detection assessment using fuzzy sets and remotely sensed data: an application of topographic map revision , 1999 .

[3]  Pramod K. Varshney,et al.  Robustness of Change Detection Algorithms in the Presence of Registration Errors , 2007 .

[4]  Pierre Goovaerts,et al.  Propagating error in land-cover-change analyses: impact of temporal dependence under increased thematic complexity , 2010, Int. J. Geogr. Inf. Sci..

[5]  Qihao Weng Thermal infrared remote sensing for urban climate and environmental studies: Methods, applications, and trends , 2009 .

[6]  C. C. Petit,et al.  Integration of multi-source remote sensing data for land cover change detection , 2001, Int. J. Geogr. Inf. Sci..

[7]  Volker Walter,et al.  Object-based classification of remote sensing data for change detection , 2004 .

[8]  S. Sader,et al.  Comparison of change-detection techniques for monitoring tropical forest clearing and vegetation regrowth in a time series , 2001 .

[9]  Limin Yang,et al.  Urban Land-Cover Change Detection through Sub-Pixel Imperviousness Mapping Using Remotely Sensed Data , 2003 .

[10]  C. Woodcock,et al.  Classification and Change Detection Using Landsat TM Data: When and How to Correct Atmospheric Effects? , 2001 .

[11]  W. Cohen,et al.  Comparison of Tasseled Cap-based Landsat data structures for use in forest disturbance detection , 2005 .

[12]  Pol Coppin,et al.  Change Detection in Forest Ecosystems with Remote Sensing Digital Imagery , 1996 .

[13]  Pablo J. Zarco-Tejada,et al.  Detection of water stress in an olive orchard with thermal remote sensing imagery , 2006 .

[14]  Gonzalo Pajares,et al.  Support vector machines for shade identification in urban areas , 2004 .

[15]  Rattan Lal,et al.  Integrative geospatial approaches for the comprehensive monitoring and assessment of land management sustainability: Rationale, Potentials, and Characteristics , 2011 .

[16]  Ayad Mohammed Fadhil,et al.  Drought mapping using Geoinformation technology for some sites in the Iraqi Kurdistan region , 2011, Int. J. Digit. Earth.

[17]  Heng-Da Cheng,et al.  Effective image retrieval using dominant color descriptor and fuzzy support vector machine , 2009, Pattern Recognit..

[18]  D. Dutta,et al.  Predicting agricultural drought in eastern Rajasthan of India using NDVI and standardized precipitation index , 2013 .

[19]  L. Stringer,et al.  Integrated land degradation monitoring and assessment: Horizontal knowledge management at the national and international levels , 2011 .

[20]  Gerald Forkuor,et al.  Dynamics of land-use and land-cover change in Freetown, Sierra Leone and its effects on urban and peri-urban agriculture – a remote sensing approach , 2011 .

[21]  Hassiba Nemmour,et al.  Support Vector Machines for Automatic Multi-class Change Detection in Algerian Capital Using Landsat TM Imagery , 2010 .

[22]  Ranga B. Myneni,et al.  Remote sensing of vegetation and land-cover change in Arctic Tundra Ecosystems , 2004 .

[23]  A. Karnieli,et al.  Comparison of methods for land-use classification incorporating remote sensing and GIS inputs , 2011 .

[24]  Jixian Zhang Multi-source remote sensing data fusion: status and trends , 2010 .

[25]  D. Lu,et al.  Urban surface biophysical descriptors and land surface temperature variations , 2006 .

[26]  M. S. Moran,et al.  Estimating crop water deficit using the relation between surface-air temperature and spectral vegetation index , 1994 .

[27]  Cagatay Tanriverdi,et al.  Improved Agricultural Management Using Remote Sensing to Estimate Water Stress Indices , 2010 .

[28]  Suha Berberoglu,et al.  Assessing different remote sensing techniques to detect land use/cover changes in the eastern Mediterranean , 2009, Int. J. Appl. Earth Obs. Geoinformation.

[29]  Tao Zhang,et al.  Determination of ocean primary productivity using support vector machines , 2008 .

[30]  Dengsheng Lu,et al.  Detection of impervious surface change with multitemporal Landsat images in an urban-rural frontier. , 2011, ISPRS journal of photogrammetry and remote sensing : official publication of the International Society for Photogrammetry and Remote Sensing.

[31]  Chengquan Huang,et al.  The 250 m global land cover change product from the Moderate Resolution Imaging Spectroradiometer of NASA's Earth Observing System , 2000 .

[32]  D. Lu,et al.  Change detection techniques , 2004 .

[33]  José Cristóbal Riquelme Santos,et al.  Automatic environmental quality assessment for mixed-land zones using lidar and intelligent techniques , 2011, Expert Syst. Appl..

[34]  Yeqiao Wang,et al.  Remote sensing change detection tools for natural resource managers: Understanding concepts and tradeoffs in the design of landscape monitoring projects , 2009 .

[35]  S. Running,et al.  Estimation of regional surface resistance to evapotranspiration from NDVI and thermal-IR AVHRR data , 1989 .

[36]  Yun Zhang,et al.  Detection of urban housing development by fusing multisensor satellite data and performing spatial feature post-classification , 2001 .

[37]  Siamak Khorram,et al.  The effects of image misregistration on the accuracy of remotely sensed change detection , 1998, IEEE Trans. Geosci. Remote. Sens..

[38]  Claudia Notarnicola,et al.  Identification of orchards and vineyards with different texture-based measurements by using an object-oriented classification approach , 2011, Int. J. Geogr. Inf. Sci..

[39]  Nita Bhagia,et al.  Monitoring Cropping Pattern Changes Using Multi‐temporal WiFS Data , 2002 .

[40]  C. Woodcock,et al.  An assessment of several linear change detection techniques for mapping forest mortality using multitemporal landsat TM data , 1996 .

[41]  P. O. Adeniyi,et al.  An enhanced classification approach to change detection in semi-arid environments , 1988 .

[42]  L.D. Yarbrough,et al.  Using at-sensor radiance and reflectance tasseled cap transforms applied to change detection for the ASTER sensor , 2005, International Workshop on the Analysis of Multi-Temporal Remote Sensing Images, 2005..

[43]  Jungho Im,et al.  ISPRS Journal of Photogrammetry and Remote Sensing , 2022 .

[44]  W. Cohen,et al.  An efficient and accurate method for mapping forest clearcuts in the Pacific Northwest using Landsat imagery , 1998 .

[45]  S. Gopal,et al.  Remote sensing of forest change using artificial neural networks , 1996, IEEE Trans. Geosci. Remote. Sens..

[46]  Thomas J. Schmugge,et al.  Remote estimation of soil moisture availability and fractional vegetation cover for agricultural fields , 1990 .

[47]  L. Boschetti,et al.  Combining ASTER multispectral imagery analysis and support vector machines for rapid and cost-effective post-fire assessment: a case study from the Greek wildland fires of 2007 , 2010 .

[48]  T. Carlson An Overview of the “Triangle Method” for Estimating Surface Evapotranspiration and Soil Moisture from Satellite Imagery , 2007, Sensors (Basel, Switzerland).

[49]  K. Seto,et al.  Comparing ARTMAP Neural Network with the Maximum-Likelihood Classifier for Detecting Urban Change , 2003 .

[50]  Lorenzo Bruzzone,et al.  Automatic analysis of the difference image for unsupervised change detection , 2000, IEEE Trans. Geosci. Remote. Sens..

[51]  P. Gong,et al.  Urban built-up land change detection with road density and spectral information from multi-temporal Landsat TM data , 2002 .

[53]  Juan C. Jiménez-Muñoz,et al.  Temporal analysis of normalized difference vegetation index (NDVI) and land surface temperature (LST) parameters to detect changes in the Iberian land cover between 1981 and 2001 , 2011 .

[54]  Jianjun Wu,et al.  Comparison of remotely sensed and meteorological data-derived drought indices in mid-eastern China , 2012 .

[55]  Ashish Ghosh,et al.  Fuzzy clustering algorithms for unsupervised change detection in remote sensing images , 2011, Inf. Sci..

[56]  M. Turker,et al.  Detecting Land Use Changes at the Urban Fringe from Remotely Sensed Images in Ankara, Turkey , 2002 .

[57]  Sayan Mukherjee,et al.  Choosing Multiple Parameters for Support Vector Machines , 2002, Machine Learning.

[58]  Xiaoling Chen,et al.  Remote sensing and GIS application in the detection of environmental degradation indicators , 2011, Geo spatial Inf. Sci..

[59]  J. Rogan,et al.  Remote sensing technology for mapping and monitoring land-cover and land-use change , 2004 .

[60]  J. Cihlar,et al.  Radiometric normalization of multitemporal high-resolution satellite images with quality control for land cover change detection , 2002 .

[61]  Marvin E. Bauer,et al.  Processing of multitemporal Landsat TM imagery to optimize extraction of forest cover change features , 1994, IEEE Trans. Geosci. Remote. Sens..

[62]  Martin Brown,et al.  Linear spectral mixture models and support vector machines for remote sensing , 2000, IEEE Trans. Geosci. Remote. Sens..

[63]  Vijay Bhagat,et al.  Use of Landsat ETM+ data for delineation of water bodies in hilly zones , 2011 .

[64]  Philip N. Slater,et al.  Calibration of Space-Multispectral Imaging Sensors , 1999 .

[65]  Deren Li Remotely sensed images and GIS data fusion for automatic change detection , 2010 .

[66]  Badrinath Roysam,et al.  Image change detection algorithms: a systematic survey , 2005, IEEE Transactions on Image Processing.

[67]  Geoffrey J. Hay,et al.  Object-based change detection , 2012 .

[68]  D. Al-Khudhairy,et al.  Structural Damage Assessments from Ikonos Data Using Change Detection, Object-Oriented Segmentation, and Classification Techniques , 2005 .

[69]  Stephen V. Stehman,et al.  Impact of sample size allocation when using stratified random sampling to estimate accuracy and area of land-cover change , 2012 .

[70]  Douglas J. King,et al.  Automated tree crown detection and delineation in high-resolution digital camera imagery of coniferous forest regeneration , 2002 .

[71]  Yun Zhang,et al.  A critical review of image registration methods , 2010 .

[72]  Peng Gong,et al.  Detection of Recently Constructed Multi‐storey Buildings Using SPOT Panchromatic and Landsat TM/ETM+ Data , 2005 .

[73]  Hui Lin,et al.  Remote sensing change detection based on canonical correlation analysis and contextual bayes decision , 2007 .

[74]  T. Carlson,et al.  An assessment of satellite remotely-sensed land cover parameters in quantitatively describing the climatic effect of urbanization , 1998 .

[75]  Hanspeter Liniger,et al.  Cross‐scale monitoring and assessment of land degradation and sustainable land management: A methodological framework for knowledge management , 2011 .

[76]  S. Goetz Multi-sensor analysis of NDVI, surface temperature and biophysical variables at a mixed grassland site , 1997 .

[77]  Manfred Ehlers,et al.  Multi-sensor image fusion for pansharpening in remote sensing , 2010 .

[78]  Dengsheng Lu,et al.  Integration of Landsat TM and SPOT HRG Images for Vegetation Change Detection in the Brazilian Amazon. , 2008, Photogrammetric engineering and remote sensing.

[79]  Christopher Justice,et al.  The impact of misregistration on change detection , 1992, IEEE Trans. Geosci. Remote. Sens..

[80]  D. Roberts,et al.  A comparison of methods for monitoring multitemporal vegetation change using Thematic Mapper imagery , 2002 .

[81]  Pol Coppin,et al.  Review ArticleDigital change detection methods in ecosystem monitoring: a review , 2004 .

[82]  Gabriele Moser,et al.  Generalized minimum-error thresholding for unsupervised change detection from SAR amplitude imagery , 2006, IEEE Trans. Geosci. Remote. Sens..

[83]  A. Sepehry,et al.  FLOOD INDUCED LAND COVER CHANGE DETECTION USING MULTITEMPORAL ETM+ IMAGERY , 2006 .

[84]  Thomas Blaschke,et al.  Object based image analysis for remote sensing , 2010 .

[85]  R. Congalton,et al.  A Quantitative Comparison of Change-Detection Algorithms for Monitoring Eelgrass from Remotely Sensed Data , 1998 .

[86]  M. Schaepman,et al.  Global assessment of land degradation and improvement: 1. Identification by remote sensing , 2008 .

[87]  Chris Clifton Change Detection in Overhead Imagery Using Neural Networks , 2004, Applied Intelligence.

[88]  Eric F. Lambin,et al.  Change Detection at Multiple Temporal Scales: Seasonal and Annual Variations in Landscape Variables , 1996 .

[89]  G. M. Foody,et al.  Relating the land-cover composition of mixed pixels to artificial neural network classification outpout , 1996 .

[90]  Yohei Sato,et al.  Assessment of hydrosaline land degradation by using a simple approach of remote sensing indicators , 2005 .

[91]  Sunil Narumalani,et al.  A Comparative Evaluation of ISODATA and Spectral Angle Mapping for the Detection of Saltcedar Using Airborne Hyperspectral Imagery , 2006 .

[92]  Christopher Munyati,et al.  Use of Principal Component Analysis (PCA) of Remote Sensing Images in Wetland Change Detection on the Kafue Flats, Zambia , 2004 .