@article{khorram_nelson_wiele_cakir_2017, title={Processing and Applications of Remotely Sensed Data}, ISBN={["978-3-319-23385-7"]}, DOI={10.1007/978-3-319-23386-4_92}, journal={HANDBOOK OF SATELLITE APPLICATIONS,2ND EDITION}, author={Khorram, Siamak and Nelson, Stacy A. C. and Wiele, Cynthia F. and Cakir, Halil}, year={2017}, pages={1017–1046} }
 @article{krish_heinrich_snyder_cakir_khorram_2010, title={Global registration of overlapping images using accumulative image features}, volume={31}, ISSN={0167-8655}, url={http://dx.doi.org/10.1016/j.patrec.2009.09.016}, DOI={10.1016/j.patrec.2009.09.016}, abstractNote={This paper introduces a new feature-based image registration technique which registers images by finding rotation- and scale-invariant features and matching them using a novel feature matching algorithm based on an evidence accumulation process reminiscent of the generalized Hough transform. Once feature correspondence has been established, the transformation parameters are then estimated using non-linear least squares (NLLS) and the standard RANSAC (random sample consensus) algorithm. The technique is evaluated under similarity transforms – translation, rotation and scale (zoom) and also under illumination changes.}, number={2}, journal={Pattern Recognition Letters}, publisher={Elsevier BV}, author={Krish, Karthik and Heinrich, Stuart and Snyder, Wesley E. and Cakir, Halil and Khorram, Siamak}, year={2010}, month={Jan}, pages={112–118} }
 @article{hester_nelson_cakir_khorram_cheshire_2010, title={High-resolution land cover change detection based on fuzzy uncertainty analysis and change reasoning}, volume={31}, ISSN={0143-1161 1366-5901}, url={http://dx.doi.org/10.1080/01431160902893493}, DOI={10.1080/01431160902893493}, abstractNote={Land cover change detection is an important research and application area for analysts of remote sensing data. The primary objective of the research described here was to develop a change detection method capable of accommodating spatial and classification uncertainty in generating an accurate map of land cover change using high resolution satellite imagery. As a secondary objective, this method was designed to facilitate the mapping of particular types and locations of change based on specific study goals. Urban land cover change pertinent to surface water quality in Raleigh, North Carolina, was assessed using land cover classifications derived from pan-sharpened, 0.61 m QuickBird images from 2002 and 2005. Post-classification map errors were evaluated using a fuzzy logic approach. First, a ‘change index’ representing a quantitative gradient along which land cover change is characterized by both certainty and relevance, was created. The result was a continuous representation of change, a product type that retains more information and flexibility than discrete maps of change. Finally, fuzzy logic and change reasoning results were integrated into a binary change/no change map that quantified the most certain, likely, and relevant change regions within the study area. A ‘from-to’ change map was developed from this binary map inserting the type of change identified in the raw post-classification map. A from-to change map had an overall accuracy of 78.9% (κ = 0.747) and effectively mapped land cover changes posing a threat to water quality, including increases in impervious surface. This work presents an efficient fuzzy framework for transforming map uncertainty into accurate and practical change analysis.}, number={2}, journal={International Journal of Remote Sensing}, publisher={Informa UK Limited}, author={Hester, D. B. and Nelson, S. A. C. and Cakir, H. I. and Khorram, S. and Cheshire, H.}, year={2010}, month={Jan}, pages={455–475} }
 @article{hester_cakir_nelson_khorram_2008, title={Per-pixel classification of high spatial resolution satellite imagery for urban land-cover mapping}, volume={74}, ISSN={["2374-8079"]}, DOI={10.14358/PERS.74.4.463}, abstractNote={Commercial high spatial resolution satellite data now provide a synoptic and consistent source of digital imagery with detail comparable to that of aerial photography. In the work described here, per-pixel classification, image fusion, and GIS-based map refinement techniques were tailored to pan-sharpened 0.61 m QuickBird imagery to develop a six-category urban land-cover map with 89.3 percent overall accuracy ( �� 0.87). The study area was a rapidly developing 71.5 km 2 part of suburban Raleigh, North Carolina, U.S.A., within the Neuse River basin. “Edge pixels” were a source of classification error as was spectral overlap between bare soil and impervious surfaces and among vegetated cover types. Shadows were not a significant source of classification error. These findings demonstrate that conventional spectral-based classification methods can be used to generate highly accurate maps of urban landscapes using high spatial resolution imagery.}, number={4}, journal={PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING}, author={Hester, David Barry and Cakir, Halil I. and Nelson, Stacy A. C. and Khorram, Siamak}, year={2008}, month={Apr}, pages={463–471} }
 @article{cakir_khorram_2008, title={Pixel level fusion of panchromatic and multispectral images based on correspondence analysis}, volume={74}, ISSN={["2374-8079"]}, DOI={10.14358/PERS.74.2.183}, abstractNote={A pixel level data fusion approach based on correspondence analysis (CA) is introduced for high spatial and spectral resolution satellite data. Principal component analysis (PCA) is a well-known multivariate data analysis and fusion technique in the remote sensing community. Related to PCA but a more recent multivariate technique, correspondence analysis, is applied to fuse panchromatic data with multispectral data in order to improve the quality of the final fused image. In the CA-based fusion approach, fusion takes place in the last component as opposed to the first component of the PCA-based approach. This new approach is then quantitatively compared to the PCA fusion approach using Landsat ETM� , QuickBird, and two Ikonos (with and without dynamic range adjustment) test imagery. The new approach provided an excellent spectral accuracy when synthesizing images from multispectral and high spatial resolution panchromatic imagery.}, number={2}, journal={PHOTOGRAMMETRIC ENGINEERING AND REMOTE SENSING}, author={Cakir, Halil I. and Khorram, Siamak}, year={2008}, month={Feb}, pages={183–192} }
 @article{cakir_khorram_nelson_2006, title={Correspondence analysis for detecting land cover change}, volume={102}, ISSN={0034-4257}, url={http://dx.doi.org/10.1016/j.rse.2006.02.023}, DOI={10.1016/j.rse.2006.02.023}, abstractNote={The correspondence analysis (CA) method was applied to two multitemporal Landsat images of Raleigh, North Carolina for land use land cover (LULC) change detection. After the spectral transformation of the individual date images into component space using CA, the first component (PC1) of the date 1 image was subtracted from the PC1 of the date 2 image to produce difference image highlighting change areas. Accuracy curves based on the cumulative Producer's and User's accuracies were then used to optimally locate threshold (cutoff) values in the high-end and low-end tails of the difference image's histogram. Results were then compared to the standardized and non-standardized Principal Component Analysis (PCA) differencing and Normalized Difference Vegetation Index (NDVI) differencing methods for change detection. Results showed that there was 6.8% increase in urban related cover types in Raleigh metropolitan area between 1993 and 1999. Also, maps based on the CA differencing method were found to be thematically more accurate than maps based on PCA component differencing methods. Overall accuracy of change map produced by the CA method for the Raleigh metropolitan area was 92.5% with overall Kappa value of 0.88. In general, CA was found to be a powerful multivariate analysis technique when applied to change detection.}, number={3-4}, journal={Remote Sensing of Environment}, publisher={Elsevier BV}, author={Cakir, Halil Ibrahim and Khorram, Siamak and Nelson, Stacy A.C.}, year={2006}, month={Jun}, pages={306–317} }
 @book{hester_cakir_nelson_khorram_2006, title={Integration of high resolution imagery in cost-effective assessment of land use practices influencing erosion and sediment yield}, volume={221}, journal={Water Resource Research Institute final report (Center for Earth Observation Technical Report)}, author={Hester, D. B. and Cakir, H. I. and Nelson, S. A. C. and Khorram, S.}, year={2006} }
 @book{khorram_nelson_cakir_hester_2005, title={Integration of high resolution imagery in cost-effective assessment of land use practices influencing erosion and sediment yield}, volume={221}, journal={Water Resource Research Institute final report (Center for Earth Observation Technical Report)}, author={Khorram, S. and Nelson, S. A. C. and Cakir, H. and Hester, D. B.}, year={2005} }
 @article{cakir_nix_1999, title={The influence of early thinning on stem taper in Piedmont upland hardwood stands}, number={-30}, journal={Proceedings of the Tenth Biennial Southern Silvicultural Research Conference : Shreveport, Louisiana, February 16-18, 1999}, publisher={Asheville, NC : U.S. Dept. of Agriculture, Forest Service, Southern Research Station}, author={Cakir, H. I. and Nix, L. E.}, year={1999}, pages={47} }