PE&RS Journals
In Press Peer Reviewed Articles
As a convenience to ASPRS members, in-press peer reviewed articles approved for publication in forthcoming issues of PE&RS have been made available for members of the society.
July 2013 Issue
Comparison of Simulated HyspIRI with Two Multispectral Sensors for Invasive Species Mapping
Aaryn D. Olsson and Jeffrey T. Morisette
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This paper assesses the potential of a single HYSPIRI scene to estimate cover of the non-native invasive buffelgrass (Pennisetum ciliare) in a heterogeneous Sonoran Desert scrub ecosystem. We simulated HYSPIRI (60 m) along with two multispectral sensors, Thematic Mapper (TM; 30 m) and Advanced Spaceborne Thermal Emission and Refl ection Spectrometer (ASTER; 15 m), from high-resolution Airborne Visible/Infrared Imaging Spectrometer (AVIRIS; 3.2 m) imagery in an area infested by buffelgrass near Tucson, Arizona. We compared classifi cation accuracies of all simulated sensors at spatial resolutions of 15 m, 30 m, and 60 m to evaluate tradeoffs of spectral and spatial resolution across the sensors. Although spectroscopically superior to Landsat TM and ASTER, ASTER easily outperformed HYSPIRI for small infestations (225 m2) on account of its spatial resolution. Shortwave-infrared bands near 2.2 µm were key indicators for both HYSPIRI and ASTER, highlighting the benefit of narrow-wave SWIR for mapping invasive species in arid ecosystems.
Assessing Lidar Accuracy with Hexagonal Retro-Reflective Targets
Roberto Canavosio-Zuzelski, James Hogarty, Craig Rodarmel, Mark Lee, and Aaron Braun
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Airborne lidar systems have the potential to produce extremely accurate terrain information at high spatial densities. However, to meet stringent accuracy requirements and minimize systematic errors, proper calibration of the lidar system is required. “Boresighting” is a technique used to correct for some of these systematic errors and improve the spatial alignment of lidar passes. One challenge with boresighting is the mensuration accuracy to which a known point can be located in overlapping low density lidar strips. To address this issue, a raised Hexagonal Retro-Reflective Lidar ground Target (HRRT) is introduced. The target was optimized for precise mensuration at low point densities. The mensuration model is based on a least squares hexagon fitting approach and is proven to produce mensuration accuracies of 5 cm horizontal and 4 cm vertical (1-sigma) at ~2 pts/m2. To demonstrate a practical application, the HRRT’s are used as tie points in a rigorous boresight adjustment to compute lidar strip misalignment parameters (roll, pitch, heading, and range bias). The adjustment results show that accurate boresight parameters are recovered along with their associated uncertainties. .
Geolocation Algorithm for Earth Observation Sensors Onboard the International Space Station
Changyong Dou, Xiaodong Zhang, Hojin Kim, Jaganathan Ranganathan, Doug Olsen, and Huadong Guo
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As a near orbit space platform, the International Space Station (ISS) has been increasingly used for Earth observing applications. This paper presents a quaternion-based forward geolocation algorithm for Earth observing sensors onboard the ISS. The input parameters include the orbital state and attitude information of the ISS and the look vector of the sensor. The proposed algorithm agrees with the commercial navigation product, Satellite Tool Kit®, within 0.5 m in ideal situations. The inherent uncertainties in ISS attitude and state determinations, and the International Space Station Agriculture Camera (ISSAC) tilting angle were estimated to introduce an error less than 800 m. However, the actual geolocation error evaluated using the images obtained by the ISSAC is roughly 4 km, much greater than the inherent uncertainty and mainly due to (a) delay caused by the Windows® operating system in acquiring images, and (b) the misalignment of the ISSAC sensor coordinate system with the ISS body-fixed coordinate system. A preliminary cal/val process using the Google Earth™ as reference was performed to quantify these two errors, the correction of which improved the geolocation accuracy to 500 m, well within the inherent uncertainty.
The Effects of Data Selection and Thematic Detail on the Accuracy of High Spatial Resolution Wetland Classifications
Joseph F. Knight, Bryan P. Tolcser, Jennifer M. Corcoran, and Lian P. Rampi
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Accurate wetland maps are of critical importance for preserving the ecosystem functions provided by these valuable landscape elements. Though extensive research into wetland mapping methods using remotely sensed data exists, questions remain as to the effects of data type and classification scheme on classification accuracy when high spatial resolution data are used. The goal of this research was to examine the effects on wetland mapping accuracy of varying input datasets and thematic detail in two physiographically different study areas using a decision tree classifier. The results indicate that: topographic data and derivatives significantly increase mapping accuracy over optical imagery alone, the source of the elevation data and the type of topographic derivatives used were not major factors, the inclusion of radar and leaf-off imagery did not improve mapping accuracy, and increasing thematic detail resulted in significantly lower mapping accuracies i.e., particularly in more diverse wetland areas.
Land Subsidence Characteristics in Bandung City, Indonesia as Revealed by Spaceborne Geodetic Techniques and Hydrogeological Observations
R.S. Chatterjee, Moh. Fifik Syafiudin, and Hasanuddin Z. Abidin
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Bandung, the capital city of West Java Province, Indonesia has been subsiding as reported by a series of Global Positioning Systems (GPS) observations and field evidence. In this work, an integrated satellite-based approach has been adopted using DINSAR and GPS observations to spatially delineate the subsidence-affected areas and cross-validate the subsidence rates using two collateral geodetic techniques. Multifrequency DINSAR using C- and L-band SAR data facilitates to monitor land subsidence scenario in totality. C-band DINSAR has been found particularly useful to identify slowly subsiding areas with a sub-centimeter level of precision. Furthermore, the initial hypothesis that land subsidence in Bandung Basin has been occurring due to excessive groundwater withdrawal has been established in this study. A predictive modeling approach has been adopted to estimate the rates of potential subsidence due to elastic and inelastic deformations of the aquifer and overlying strata in response to the lowering of groundwater level.
Utility of the Wavelet Transform for LAI Estimation Using Hyperspectral Data
Asim Banskota, Randolph H. Wynne, Shawn P. Serbin, Nilam Kayastha, Valerie A. Thomas, and Philip A. Townsend
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We employed the discrete wavelet transform to reflectance spectra obtained from hyperspectral data to improve estimation of LAI in temperate forests. We estimated LAI for 32 plots across a range of forest types in Wisconsin using hemispherical photography. Plot spectra were extracted from AVIRIS data and transformed into wavelet features using the Haar wavelet. Separately, subsets of spectral bands and the Haar features selected by a genetic algorithm were used as independent variables in linear regressions. Models using wavelet coefficients explained the most variance for both broadleaf plots (R2 = 0.90 for wavelet features versus R2 = 0.80 for spectral bands) and all plots independent of forest type (R2 = 0.79 for wavelet features vs. R2 = 0.58 for spectral bands). The forest-type specific models were better than the models using all plots combined. Overall, wavelet features appear superior to band reflectances alone for estimating temperate forest LAI using hyperspectral data.
