Discussion of band selection and methodologies for the estimation of precipitable water vapour from AVIRIS data

An Airborne Visible/Infrared Imaging Spectrometer (AVIRIS) data set acquired over Canal Flats, B.C., on 14 Aug. 1990, was used for the purpose of developing methodologies for surface reflectance retrieval using the 5S atmospheric code. A scene of Rogers Dry Lake, California (23 Jul. 1990), acquired within three weeks of the Canal Flats scene, was used as a potential reference for radiometric calibration purposes and for comparison with other studies using primarily LOWTRAN7. Previous attempts at surface reflectance retrieval indicated that reflectance values in the gaseous absorption bands had the poorest accuracy. Modifications to 5S to use 1 nm step size, in order to make fuller use of the 20 cm(sup -1) resolution of the gaseous absorption data, resulted in some improvement in the accuracy of the retrieved surface reflectance. Estimates of precipitable water vapor using non-linear least squares regression and simple ratioing techniques such as the CIBR (Continuum Interpolated Band Ratio) technique or the narrow/wide technique, which relate ratios of combinations of bands to precipitable water vapor through calibration curves, were found to vary widely. The estimates depended on the bands used for the estimation; none provided entirely satisfactory surface reflectance curves

Preface: the environmental mapping and analysis program (EnMAP) mission: preparing for its scientific exploitation

Open access; distributed under the terms and conditions of the Creative Commons Attribution (CC-BY) licenseThe imaging spectroscopy mission EnMAP aims to assess the state and evolution of terrestrialandaquaticecosystems,examinethemultifacetedimpactsofhumanactivities,andsupport a sustainable use of natural resources. Once in operation (scheduled to launch in 2019), EnMAP will provide high-quality observations in the visible to near-infrared and shortwave-infrared spectral range. The scientific preparation of the mission comprises an extensive science program. This special issue presents a collection of research articles, demonstrating the potential of EnMAP for various applications along with overview articles on the mission and software tools developed within its scientific preparation.Ye

Spatial variability mapping of crop residue using hyperion (EO-1) hyperspectral data

Sherpa Romeo green journal; open accessSoil management practices that maintain crop residue cover and reduce tillage improve soil structure, increase organic matter content in the soil, positively influence water infiltration, evaporation and soil temperature, and play an important role in fixing CO2 in the soil. Consequently, good residue management practices on agricultural land have many positive impacts on soil quality, crop production quality and decrease the rate of soil erosion. Several studies have been undertaken to develop and test methods to derive information on crop residue cover and soil tillage using empirical and semi-empirical methods in combination with remote sensing data. However, these methods are generally not sufficiently rigorous and accurate for characterizing the spatial variability of crop residue cover in agricultural fields. The goal of this research is to investigate the potential of hyperspectral Hyperion (Earth Observing-1, EO-1) data and constrained linear spectral mixture analysis (CLSMA) for percent crop residue cover estimation and mapping. Hyperion data were acquired together with ground-reference measurements for validation purposes at the beginning of the agricultural season (prior to spring crop planting) in Saskatchewan (Canada). At this time, only bare soil and crop residue were present with no crop cover development. In order to extract the crop residue fraction, the images were preprocessed, and then unmixed considering the entire spectral range (427 nm–2355 nm) and the pure spectra (endmember). The results showed that the correlation between ground-reference measurements and extracted fractions from the Hyperion data using CLMSA showed that the model was overall a very good predictor for crop residue percent cover (index of agreement (D) of 0.94, coefficient of determination (R2) of 0.73 and root mean square error (RMSE) of 8.7%) and soil percent cover (D of 0.91, R2 of 0.68 and RMSE of 10.3%). This performance of Hyperion is mainly due to the spectral band characteristics, especially the availability of contiguous narrow bands in the short-wave infrared (SWIR) region, which is sensitive to the residue (lignin and cellulose absorption features).Ye

Scene-Based Spectral Response Function Shape Discernibility for the APEX Imaging Spectrometer

Abstract-Scene-based spectrometer calibration is becoming increasingly interesting due to the decreasing cost of computing resources as compared with laboratory calibration costs. Three of the most important instrument parameters needed for deriving surface reflectance products are per-band bandwidths, i.e., full-width at half-maximum, band centers, and spectral response function (SRF) shape. Methods for scene-based bandwidth and band center retrieval based on curve matching in the spectral regions near well-known solar and atmospheric absorption features have been investigated with satisfying results. The goal of this work is to establish the feasibility of per-band SRF shape discernibility. To this end, at-sensor radiances in multiple application configurations have been modeled using Moderate-Resolution Atmospheric Transmission (MODTRAN) 4 configured for the currently being built Airborne Prism Experiment (APEX) imaging spectrometer in its unbinned configuration (i.e., optimized for spectral resolution). To establish SRF shape discernment feasibility, per-band MODTRAN 4 spectral "filter response function" files have been generated for five common theoretical shapes using APEX nominal bandwidth and band center specifications and are provided as MODTRAN 4 input for the instrument model. In several application configurations, the typically used Gaussian SRF is used as reference and compared with radiances resulting from hypothetical instruments based on the four other shapes to detect differences in selected spectral subsets or "windows" near well-known Fraunhofer features. A relative root-mean-square metric is used to show that discernment in some cases is directly feasible, and in others, feasible if noise reduction techniques (e.g., along-track averaging of homogeneous targets) are possible

ANALYSIS OF SPACEBORNE HYPERION IMAGERY FOR THE ESTIMATION OF FRACTIONAL COVER OF RANGELAND ECOSYSTEMS

The goal of this research was to investigate the potential of hyperspectral Hyperion (EO-1) data to derive fractional cover of rangeland components using constrained linear spectral mixture analysis. Hyperion image data were acquired over the Antelope Creek Ranch located in southern Alberta, Canada in July 2005. These image data were first corrected for the sensor artifacts such as spatial mis-registration between the VNIR and SWIR data and striping. These data were then atmospherically corrected and transformed to surface reflectance, corrected for sensor smile/frown and post-processed to remove residual errors. Iterative Error Analysis was utilized to find image endmembers that acted as inputs to the constrained spectral unmixing. The preliminary results show that spectral unmixing was promising for percent cover estimation of green vegetation and litter/soil, but separation of green grass from green shrub was challenging due to their spectral similarity. 1

Environmental Mapping and Analysis Program – A German Hyperspectral Mission

EnMAP (Environmental Mapping and Analysis Program) is a German hyperspectral earth observation satellite. Its spectral measurements will be used to obtain a diagnostic characterization of the earth's surface and to derive quantitative surface parameters on the status of terrestrial and aquatic ecosystems and the changes they undergo. EnMAP data will supply a basis for quantifying and modeling crucial ecosystem processes, thereby making a major contribution toward understanding the complexities of the Earth system. The satellite system is being developed entirely in Germany under the aegis of the Space Administration of the German Aerospace Center (DLR), with the launch scheduled for 2018. EnMAP carries a push broom type hyperspectral instrument with 30 km swath width at a ground sampling distance of 30 m, covering the full range of strong solar irradiation from 420 nm to 2450 nm with two spectrometers, one each for the VNIR and SWIR range. It will be operated for five years on a sun-synchronous orbit with a local time descending node (LTDN) at 11:00. At near nadir orientation (±5°) the repeat rate of EnMAP is 27 days. Using the across track platform pointing capability of ±30° enables frequent access to any global site within four days, allowing short term evolutions of ecosystems to be studied with high precision. Data takes can be acquired with an accumulated length of 5000 km along track per day, with individual segments ranging from 30 km to 1000 km. Image data are down linked via the Neustrelitz ground station using an X-band link at 320 MBit/s