Spectral Characterization of a Digital Still Camera's NIR Modification to Enhance Archaeological Observation

Scholars using still cameras to take (mostly) oblique imagery from a low-flying aircraft of various possible archaeologically related anomalies can be defined as aerial archaeologists. At present, as well as in the past, aerial/air archaeology has been acquiring data almost exclusively in the visible range of the electromagnetic spectrum. This phenomenon can largely be attributed to the critical imaging process and sometimes unconvincing results related to the film-based approach of near-infrared (NIR) photography. To overcome the constraints of detecting and interpreting only the varying visible colors in vegetation (the so-called crop marks), while still maintaining the flexible and low-cost approach characteristic for aerial archaeology, a consumer digital still camera was modified to capture NIR radiation. By its spectral characterization, more insight was gained into its imaging properties and necessary guidelines for data processing, and future improvements could be formulated, all in an attempt to better capture the archaeologically induced anomalous growth stresses in crops.

[1]  Kevin E. Spaulding,et al.  Color processing in digital cameras , 1998, IEEE Micro.

[2]  Andrew J. Young,et al.  Carotenoids and stress , 1990 .

[3]  Characteristics of NICMOS Detector Dark Observations , 1997 .

[4]  Geert Verhoeven Becoming a NIR-sensitive aerial archaeologist , 2007, SPIE Remote Sensing.

[5]  R. Person Remote mapping of standing crop biomass for estimation of the productivity of the short-grass Prairie, Pawnee National Grasslands, Colorado , 1972 .

[6]  M. Schlerf,et al.  Remote sensing of forest biophysical variables using HyMap imaging spectrometer data , 2005 .

[7]  W. Budde Definition of the linearity range of Si photodiodes. , 1983, Applied optics.

[8]  D. Horler,et al.  The red edge of plant leaf reflectance , 1983 .

[9]  F. Van de Wiele,et al.  Photodiode quantum efficiency , 1976 .

[10]  Safwat H. Shakir Hanna,et al.  Spectral characterization of water stress impact on some agricultural crops: III. Studies on Sudan grass and other different crops using handheld radiometer , 1999, Remote Sensing.

[11]  Richard Berry,et al.  The Handbook of Astronomical Image Processing , 2000 .

[12]  D. Cowley,et al.  From the Air: Understanding Aerial Archaeology , 2005 .

[13]  Y. Reibel,et al.  CCD or CMOS camera noise characterisation , 2003 .

[14]  R.J.A. Jones,et al.  Crop marks and soils at two archaeological sites in Britain , 1977 .

[15]  G. Birth,et al.  Measuring the Color of Growing Turf with a Reflectance Spectrophotometer1 , 1968 .

[16]  H. Gausman,et al.  LEAF REFLECTANCE OF NEAR-INFRARED , 1974 .

[17]  H. Poilvé,et al.  Hyperspectral Imaging and Stress Mapping in Agriculture , 1998 .

[18]  Dong-Hwan Har,et al.  SLR digital camera for forensic photography , 2004, IS&T/SPIE Electronic Imaging.

[19]  Sidney Ray,et al.  Applied photographic optics , 1998 .

[20]  Gregory A. Carter,et al.  General Spectral Characteristics of Leaf Reflectance Responses to Plant Stress and Their Manifestation at the Landscape Scale , 2002 .

[21]  Rastislav Lukac,et al.  Demosaicked image postprocessing using local color ratios , 2004, IEEE Transactions on Circuits and Systems for Video Technology.

[22]  D. King,et al.  Airborne Digital Frame Camera Imaging for Elevation Determination , 1994 .

[23]  Geert Verhoeven Imaging the invisible using modified digital still cameras for straightforward and low-cost archaeological near-infrared photography , 2008 .

[24]  L. C. Cui,et al.  Characterization of digital image noise properties based on RAW data , 2006 .

[25]  H. Gausman,et al.  Reflectance of cotton leaves and their structure , 1969 .

[26]  Jeanny Hérault,et al.  Practical implementation of LMMSE demosaicing using luminance and chrominance spaces , 2007, Comput. Vis. Image Underst..

[27]  Jennifer L. Dungan,et al.  High spectral resolution reflectance of Douglas fir grown under different fertilization treatments : Experiment design and treatment effects , 1996 .

[28]  Gregory H. Bearman,et al.  Imaging the past: recent applications of multispectral imaging technology to deciphering manuscripts , 2003, Antiquity.

[29]  G. Carter,et al.  Narrow-band Reflectance Imagery Compared with ThermalImagery for Early Detection of Plant Stress , 1996 .

[30]  Geert Verhoeven,et al.  It's all about the format – unleashing the power of RAW aerial photography , 2010 .

[31]  Gerald C. Holst,et al.  CCD arrays, cameras, and displays , 1996 .

[32]  Christine Stone,et al.  Chlorophyll content in eucalypt vegetation at the leaf and canopy scales as derived from high resolution spectral data. , 2003, Tree physiology.

[33]  Josep Peñuelas,et al.  Visible and near-infrared reflectance techniques for diagnosing plant physiological status , 1998 .

[34]  D. Lobell,et al.  View angle effects on canopy reflectance and spectral mixture analysis of coniferous forests using AVIRIS , 2002 .

[35]  Jerome D. Tietz,et al.  Linear Models for Digital Cameras , 1997 .

[36]  A. Gitelson,et al.  Non-destructive determination of chlorophyll content of leaves of a green and an aurea mutant of tobacco by reflectance measurements , 1996 .

[37]  C. Jordan Derivation of leaf-area index from quality of light on the forest floor , 1969 .

[38]  D. F. Wanjura,et al.  Vegetative and optical characteristics of four-row crop canopies , 1988 .

[39]  J. Woolley Reflectance and transmittance of light by leaves. , 1971, Plant physiology.

[40]  The Technique of Air-Archaeology , 1944 .

[41]  R. Alscher,et al.  Stress responses in plants: Adaptation and acclimation mechanisms. , 1990 .

[42]  Miroslav Goljan,et al.  Digital camera identification from sensor pattern noise , 2006, IEEE Transactions on Information Forensics and Security.

[43]  A. Stephenson,et al.  Air Photo Interpretation for Archaeologists , 1984 .

[44]  Peter G. Dorrell,et al.  Photography in archaeology and conservation , 1989 .

[45]  M. A. Pizarro,et al.  An adequate band positioning to enhance NDVI contrasts among green vegetation, senescent biomass, and tropical soils , 2000 .

[46]  Anatoly A. Gitelson,et al.  Why and What for the Leaves Are Yellow in Autumn? On the Interpretation of Optical Spectra of Senescing Leaves (Acerplatanoides L.)* , 1995 .

[47]  Steve B. Howell,et al.  Handbook of CCD Astronomy , 2000 .

[48]  V. Kakani,et al.  Selection of Optimum Reflectance Ratios for Estimating Leaf Nitrogen and Chlorophyll Concentrations of Field-Grown Cotton , 2005 .

[49]  Remote Sensing - Aerial and Terrestrial Photography for Archeologists , 1981 .

[50]  AERIAL RECONNAISSANCE FOR ARCHAEOLOGY: USES OF THE PHOTOGRAPHIC EVIDENCE , 2006 .

[51]  Toyokazu Mizoguchi Evaluation of Image Sensors , 2005 .

[52]  R. Heller,et al.  Imaging with photographic sensors. , 1970 .

[53]  P. Thenkabail,et al.  Hyperspectral Vegetation Indices and Their Relationships with Agricultural Crop Characteristics , 2000 .

[54]  Takeshi Koyama Optics in Digital Still Cameras , 2005 .

[55]  D. P. Groeneveld,et al.  Broadband vegetation index performance evaluated for a low‐cover environment , 2006 .

[56]  R. Colwell Spectrometric considerations involved in making rural land use studies with aerial photography , 1965 .

[57]  Brent Clothier,et al.  Effect of water stress on the canopy architecture and spectral indices of irrigated alfalfa , 1989 .

[58]  Junichi Nakamura,et al.  Image Sensors and Signal Processing for Digital Still Cameras , 2005 .

[59]  A. Gitelson,et al.  Signature Analysis of Leaf Reflectance Spectra: Algorithm Development for Remote Sensing of Chlorophyll , 1996 .

[60]  R. Lasaponara,et al.  Detection of archaeological crop marks by using satellite QuickBird multispectral imagery , 2007 .

[61]  William D. Philpot,et al.  Yellowness index: An application of spectral second derivatives to estimate chlorosis of leaves in stressed vegetation , 1999 .

[62]  B. Datt,et al.  Visible/near infrared reflectance and chlorophyll content in Eucalyptus leaves , 1999 .

[63]  C. Tucker Red and photographic infrared linear combinations for monitoring vegetation , 1979 .

[64]  Friedrich Dierks,et al.  Sensitivity and Image Quality of Digital Cameras , 2004 .

[65]  Soil, water, and plant relations. , 1970 .

[66]  L. D. Miller,et al.  Remote mapping of standing crop biomass for estimation of the productivity of the shortgrass prairie, Pawnee National Grasslands, Colorado , 1972 .

[67]  Stanley B. Brown,et al.  THE DEGRADATION OF CHLOROPHYLL - A BIOLOGICAL ENIGMA. , 1987, The New phytologist.

[68]  J. Peñuelas,et al.  The reflectance at the 950–970 nm region as an indicator of plant water status , 1993 .

[69]  Yap-Peng Tan,et al.  Effective use of spatial and spectral correlations for color filter array demosaicking , 2004, IEEE Transactions on Consumer Electronics.

[70]  G. Carter,et al.  Early detection of plant stress by digital imaging within narrow stress-sensitive wavebands , 1994 .

[71]  Dache M. Reeves Aerial Photography and Archaeology , 1936, American Antiquity.

[72]  C. S. French,et al.  THE ABSORPTION AND REFLECTION SPECTRA OF LEAVES, CHLOROPLAST SUSPENSIONS, AND CHLOROPLAST FRAGMENTS AS MEASURED IN AN ULBRICHT SPHERE , 1946 .

[73]  A. Mann Infrared Optics and Zoom Lenses , 2000 .

[74]  Bisun Datt,et al.  Remote Sensing of Water Content in Eucalyptus Leaves , 1999 .

[75]  Safwat H. Shakir Hanna,et al.  Spectral characterization of water stress impact on some agricultural crops: II. Studies on alfalfa using handheld radiometer , 1998, Remote Sensing.

[76]  R.W. Schafer,et al.  Demosaicking: color filter array interpolation , 2005, IEEE Signal Processing Magazine.

[77]  Looking through Black-Tinted Glasses – A Remotely Controlled Infrared Eye in the Sky , 2006 .

[78]  J. N. Hampton AN EXPERIMENT IN MULTISPECTRAL AIR PHOTOGRAPHY FOR ARCHAEOLOGICAL RESEARCH , 2006 .

[79]  Gregory A. Carter,et al.  Responses of leaf spectral reflectance to plant stress. , 1993 .

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

[81]  Steve B. Howell,et al.  Handbook of CCD Astronomy: Contents , 2006 .

[82]  Sidney F. Ray,et al.  Applied Photographic Optics: Lenses and optical systems for photography, film, video, electronic and digital imaging , 2002 .

[83]  David H. Brainard,et al.  Reconstructing Images from Trichromatic Samples: From Basic Research to Practical Applications , 1995, CIC.

[84]  Moon S. Kim,et al.  Ratio analysis of reflectance spectra (RARS): An algorithm for the remote estimation of the concentrations of chlorophyll A, chlorophyll B, and carotenoids in soybean leaves , 1992 .

[85]  Thomas W. Parks,et al.  Adaptive homogeneity-directed demosaicing algorithm , 2005, IEEE Transactions on Image Processing.

[86]  A. Gitelson,et al.  Detection of Red Edge Position and Chlorophyll Content by Reflectance Measurements Near 700 nm , 1996 .

[87]  Antonio Roberto Formaggio,et al.  Narrow band spectral indexes for chlorophyll determination in soybean canopies [Glycine max (L.) Merril] , 2004 .

[88]  G. Carter Ratios of leaf reflectances in narrow wavebands as indicators of plant stress , 1994 .

[89]  Ken Parulski,et al.  Color image processing for digital cameras , 2002 .

[90]  E. B. Knipling Physical and physiological basis for the reflectance of visible and near-infrared radiation from vegetation , 1970 .

[91]  C. J. Tucker,et al.  A comparison of satellite sensor bands for vegetation monitoring , 1978 .

[92]  A. Theuwissen,et al.  Solid-State Imaging with Charge-Coupled Devices , 1995 .

[93]  G. Verhoeven,et al.  Helikite aerial photography – a versatile means of unmanned, radio controlled, low‐altitude aerial archaeology , 2009 .