ArticlesT he consequences of land use, disturbance, and climate change in the world's ecosystems have created increased demand for remote sensing data at all scales. A wide range of information is needed to predict the consequences of climate change and to monitor carbon, water, and nutrient cycles, from land cover, land-use history, and estimates of standing biomass to succession, biodiversity, and sustainability. Traditional field-based sampling methods are prohibitively expensive and time-consuming at large spatial scales, and such methods are inadequate for today's needs. Satellite observations provide the only practical means to obtain a synoptic view of Earth's ecosystems, including their spatial distribution, extent, and temporal dynamics (Cohen and Goward 2004).Accurate maps of the spatial distribution, percentage cover, and variability of global ecosystems are essential to improve ecosystem process models (Running et al. 2004, Turner et al. 2004. Current vegetation maps contain significant classification errors, and there is little understanding of how to scale mixed land cover, variable stand age, and density classes from local estimates. Normalized difference vegetation index (NDVI) data are used for estimating carbon fluxes, stores, and turnover rates, as well as other land-cover characteristics affecting the carbon budget. However, ecosystem and biogeochemical models could significantly benefit from independently derived information about terrestrial biomes. Several new types of data that could improve model results, including quantitative estimates of canopy and soil biochemistry, canopy structural information, and improved land-cover classifications, can be produced by imaging spectrometers.A wide range of new instrument capabilities are available or planned, based on airborne and satellite platforms that measure all parts of the electromagnetic spectrum, from ultraviolet to radar (Treuhaft et al. 2004). Imaging spectrometers are instruments that measure a detailed spectrum of reflected solar energy for each pixel. Spectroscopy data have already significantly improved theoretical understanding of the interactions of electromagnetic radiation with matter and are changing the way remotely sensed data are analyzed

No abstract

Methane (CH 4 ) impacts climate as the second strongest anthropogenic greenhouse gas and air quality by influencing tropospheric ozone levels. Space-based observations have identified the Four Corners region in the Southwest United States as an area of large CH 4 enhancements. We conducted an airborne campaign in Four Corners during April 2015 with the next-generation Airborne Visible/Infrared Imaging Spectrometer (near-infrared) and Hyperspectral Thermal Emission Spectrometer (thermal infrared) imaging spectrometers to better understand the source of methane by measuring methane plumes at 1-to 3-m spatial resolution. Our analysis detected more than 250 individual methane plumes from fossil fuel harvesting, processing, and distributing infrastructures, spanning an emission range from the detection limit ∼ 2 kg/h to 5 kg/h through ∼ 5,000 kg/h. Observed sources include gas processing facilities, storage tanks, pipeline leaks, and well pads, as well as a coal mine venting shaft. Overall, plume enhancements and inferred fluxes follow a lognormal distribution, with the top 10% emitters contributing 49 to 66% to the inferred total point source flux of 0.23 Tg/y to 0.39 Tg/y. With the observed confirmation of a lognormal emission distribution, this airborne observing strategy and its ability to locate previously unknown point sources in real time provides an efficient and effective method to identify and mitigate major emissions contributors over a wide geographic area. With improved instrumentation, this capability scales to spaceborne applications [Thompson DR, et al. (2016)

The Permian Basin is the largest and fastest growing oil and gas (O&G) producing region in the United States. We conducted an extensive airborne campaign across the majority of the Permian in September−November, 2019 with imaging spectrometers to quantify strong methane (CH 4 ) point source emissions at facility-scales, including high frequency sampling to evaluate intermittency. We identified 1100 unique and heavy-tailed distributed sources that were sampled at least 3 times (average 8 times), showing 26% average persistence. Sources that were routinely persistent (50−100%) make up only 11% of high emitting infrastructure but 29% of quantified emissions from this population, potentially indicative of leaking equipment that merits repair. Sector attribution of plumes shows that 50% of detected emissions result from O&G production, 38% from gathering and boosting, and 12% from processing. This suggests a 20% relative shift from upstream to midstream compared to other US O&G basins for large emitters. Simultaneous spectroscopic identification of flares found that 12% of detected Permian CH 4 plume emissions were associated with either active or inactive flares. Frequent, high-resolution monitoring is necessary to accurately understand intermittent methane superemitters across large, heterogeneous O&G basins and efficiently pinpoint persistent leaks for mitigation.

No abstract

thickness, we estimate that the volume of oil, including oil thicker than can be probed in the AVIRIS imagery, is possibly as high as 150,000 barrels in the AVIRIS scenes. When this value is projected to the entire spill, it gives a volume of about 500,000 barrels for thick oil remaining on the sea surface as of May 17. AVIRIS data cannot be used to confirm this higher volume, and additional field work including more in-situ measurements of oil thickness would be required to confirm this higher oil volume. Both the directly detected minimum range of oil volume, and the higher possible volume projection for oil thicker than can be probed with NIR spectroscopy imply a significantly higher total volume of oil relative to that implied by the early NOAA (National Oceanic and Atmospheric Administration) estimate of 5,000 barrels per day reported on their Web site.

A variation of the modified Langley plot algorithm is reported here and applied to the retrieval of atmospheric water column abundance from a filtered sunphotometer. In this new methodology an absorption data base (LOWTRAN 7) is used to compute a water abundance versus transmittance curve of growth, rather than the square‐root dependence previously assumed. Validation of the technique is provided from an uncertainty analysis, and plans to further validate using Fourier transform spectrometers are detailed. The new sunphotometer technique is used to report total column water vapor during the First ISLSCP Field Experiment (FIFE), and comparisons are made with abundances retrieved via FIFE radiosonde observations. The sunphotometer data can best be utilized, however, to in turn validate data from airborne or in‐orbit measurements of water vapor. With these flight sensors, horizontal and topographic variability within the scene can be viewed. An example of the airborne data set is given using an image from the airborne visible infrared imaging spectrometer (AVIRIS), as acquired on August 31, 1990.

The design, characteristics, and first test flight results are described of the Portable Remote Imaging Spectrometer, an airborne sensor specifically designed to address the challenges of coastal ocean remote sensing. The sensor incorporates several technologies that are demonstrated for the first time, to the best of our knowledge, in a working system in order to achieve a high performance level in terms of uniformity, signal-to-noise ratio, low polarization sensitivity, low stray light, and high spatial resolution. The instrument covers the 350-1050 nm spectral range with a 2.83 nm sampling per pixel, and a 0.88 mrad instantaneous field of view, with 608 cross-track pixels in a pushbroom configuration. Two additional infrared channels (1240 and 1610 nm) are measured by a spot radiometer housed in the same head. The spectrometer design is based on an optically fast (F/1.8) Dyson design form coupled to a wide angle two-mirror telescope in a configuration that minimizes polarization sensitivity without the use of a depolarizer. A grating with minimum polarization sensitivity and broadband efficiency was fabricated as well as a slit assembly with black (etched) silicon surface to minimize backscatter. First flight results over calibration sites as well as Monterey Bay in California have demonstrated good agreement between in situ and remotely sensed data, confirming the potential value of the sensor to the coastal ocean science community.