scholarly journals Infrared Spectroscopy of Jupiter and Saturn

2002 ◽  
Vol 12 ◽  
pp. 96-98
Author(s):  
Pierre Drossart
Keyword(s):  
Remote Sensing ◽  
Infrared Spectroscopy ◽  
Thermal Emission ◽  
Temporal Evolution ◽  
Imaging Spectroscopy ◽  
Giant Planets ◽  
Infrared Range ◽  
Physical Parameters ◽  
Temperature Structure ◽  
Reflected Light

AbstractThe spectroscopy of giant planets in the infrared range gives access to a remote sensing of many physical parameters. The composition, pressure/temperature structure, and the cloud structure all contribute to the spectrum, in solar reflected light below 3 micrometer as well as thermal emission above, from atmospheric levels ranging from the mesosphere down to the troposphere. Imaging spectroscopy revealing the variability of the atmosphere gives access to spatial and temporal evolution of these parameters, constraining the meteorological evolution of the planets.

Application of Remote Sensing in Agriculture

2014 ◽  
Vol 13 (1) ◽  
Author(s):  
Jan Piekarczyk
Keyword(s):  
Remote Sensing ◽  
Precision Agriculture ◽  
Crop Production ◽  
Satellite Images ◽  
Crop Yields ◽  
Spatial Scales ◽  
Strong Relationship ◽  
Physical Parameters ◽  
Agricultural Crop ◽  
Remote Sensing Methods

AbstractWith increasing intensity of agricultural crop production increases the need to obtain information about environmental conditions in which this production takes place. Remote sensing methods, including satellite images, airborne photographs and ground-based spectral measurements can greatly simplify the monitoring of crop development and decision-making to optimize inputs on agricultural production and reduce its harmful effects on the environment. One of the earliest uses of remote sensing in agriculture is crop identification and their acreage estimation. Satellite data acquired for this purpose are necessary to ensure food security and the proper functioning of agricultural markets at national and global scales. Due to strong relationship between plant bio-physical parameters and the amount of electromagnetic radiation reflected (in certain ranges of the spectrum) from plants and then registered by sensors it is possible to predict crop yields. Other applications of remote sensing are intensively developed in the framework of so-called precision agriculture, in small spatial scales including individual fields. Data from ground-based measurements as well as from airborne or satellite images are used to develop yield and soil maps which can be used to determine the doses of irrigation and fertilization and to take decisions on the use of pesticides.

scholarly journals Imaging Spectroscopy for Conservation Applications

2021 ◽  
Vol 13 (2) ◽  
pp. 292
Author(s):  
Megan Seeley ◽  
Gregory P. Asner
Keyword(s):  
Remote Sensing ◽  
Decision Making ◽  
Case Studies ◽  
Spatial Scales ◽  
Imaging Spectroscopy ◽  
Remote Sensing Data ◽  
Decision Makers ◽  
High Spectral Resolution ◽  
Conservation Areas ◽  
Broad Array

As humans continue to alter Earth systems, conservationists look to remote sensing to monitor, inventory, and understand ecosystems and ecosystem processes at large spatial scales. Multispectral remote sensing data are commonly integrated into conservation decision-making frameworks, yet imaging spectroscopy, or hyperspectral remote sensing, is underutilized in conservation. The high spectral resolution of imaging spectrometers captures the chemistry of Earth surfaces, whereas multispectral satellites indirectly represent such surfaces through band ratios. Here, we present case studies wherein imaging spectroscopy was used to inform and improve conservation decision-making and discuss potential future applications. These case studies include a broad array of conservation areas, including forest, dryland, and marine ecosystems, as well as urban applications and methane monitoring. Imaging spectroscopy technology is rapidly developing, especially with regard to satellite-based spectrometers. Improving on and expanding existing applications of imaging spectroscopy to conservation, developing imaging spectroscopy data products for use by other researchers and decision-makers, and pioneering novel uses of imaging spectroscopy will greatly expand the toolset for conservation decision-makers.

scholarly journals Imaging spectroscopy links aspen genotype with below-ground processes at landscape scales

2014 ◽  
Vol 369 (1643) ◽  
pp. 20130194 ◽  
Author(s):  
Michael D. Madritch ◽  
Clayton C. Kingdon ◽  
Aditya Singh ◽  
Karen E. Mock ◽  
Richard L. Lindroth ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Populus Tremuloides ◽  
Spatial Scales ◽  
Imaging Spectroscopy ◽  
Spectral Signature ◽  
Spectral Variation ◽  
Fine Scale ◽  
Below Ground ◽  
Landscape Scales ◽  
Spectrometer Data

Fine-scale biodiversity is increasingly recognized as important to ecosystem-level processes. Remote sensing technologies have great potential to estimate both biodiversity and ecosystem function over large spatial scales. Here, we demonstrate the capacity of imaging spectroscopy to discriminate among genotypes of Populus tremuloides (trembling aspen), one of the most genetically diverse and widespread forest species in North America. We combine imaging spectroscopy (AVIRIS) data with genetic, phytochemical, microbial and biogeochemical data to determine how intraspecific plant genetic variation influences below-ground processes at landscape scales. We demonstrate that both canopy chemistry and below-ground processes vary over large spatial scales (continental) according to aspen genotype. Imaging spectrometer data distinguish aspen genotypes through variation in canopy spectral signature. In addition, foliar spectral variation correlates well with variation in canopy chemistry, especially condensed tannins. Variation in aspen canopy chemistry, in turn, is correlated with variation in below-ground processes. Variation in spectra also correlates well with variation in soil traits. These findings indicate that forest tree species can create spatial mosaics of ecosystem functioning across large spatial scales and that these patterns can be quantified via remote sensing techniques. Moreover, they demonstrate the utility of using optical properties as proxies for fine-scale measurements of biodiversity over large spatial scales.

scholarly journals From Geometric-Optical Remote Sensing Modeling to Quantitative Remote Sensing Science—In Memory of Academician Xiaowen Li

2018 ◽  
Vol 10 (11) ◽  
pp. 1764 ◽  
Author(s):  
Qinhuo Liu ◽  
Guangjian Yan ◽  
Ziti Jiao ◽  
Qing Xiao ◽  
Jianguang Wen ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Thermal Emission ◽  
Scale Effects ◽  
Remote Sensing Data ◽  
Geometric Optic ◽  
Optical Remote Sensing ◽  
Research Activities ◽  
Quantitative Remote Sensing ◽  
Vegetation Canopies ◽  
High Regard

The academician Xiaowen Li devoted much of his life to pursuing fundamental research in remote sensing. A pioneer in the geometric-optical modeling of vegetation canopies, his work is held in high regard by the international remote sensing community. He codeveloped the Li–Strahler geometric-optic model, and this paper was selected by a member of the International Society for Optical Engineering (SPIE) milestone series. As a chief scientist, Xiaowen Li led a scientific team that made outstanding advances in bidirectional reflectance distribution modeling, directional thermal emission modeling, comprehensive experiments, and the understanding of spatial and temporal scale effects in remote sensing information, and of quantitative inversions utilizing remote sensing data. In addition to his broad research activities, he was noted for his humility and his dedication in making science more accessible for the general public. Here, the life and academic contributions of Xiaowen Li to the field of quantitative remote sensing science are briefly reviewed.

scholarly journals 1/4 Ke V Diffuse Background and the Local Interstellar Medium

1989 ◽  
Vol 120 ◽  
pp. 536-536
Author(s):  
S.L. Snowden
Keyword(s):  
Interstellar Medium ◽  
Filling Factor ◽  
Thermal Emission ◽  
Mean Free Path ◽  
Physical Parameters ◽  
X Rays ◽  
Local Interstellar Medium ◽  
X Ray ◽  
Diffuse Background ◽  
X Ray Background

The 1/4 keV diffuse X-ray background (SXRB) is discussed in relation to the local interstellar medium (LISM). The most likely source for these soft X-rays is thermal emission from a hot diffuse plasma. The existence of a non-zero flux from all directions and the short ISM mean free path of these X-rays (1020HI cm-2), coupled with ISM pressure constraints, imply that the plasma has a local component and that it must, at least locally (nearest hundred parsecs), have a large filling factor. Our understanding of the geometry and physical parameters of the LISM is therefore directly tied to our understanding of the SXRB.

scholarly journals Role of host star variability in the detectability of planetary phase curves

2019 ◽  
Vol 621 ◽  
pp. A44
Author(s):  
D. Hidalgo ◽  
R. Alonso ◽  
E. Pallé
Keyword(s):  
Effective Temperature ◽  
Thermal Emission ◽  
Total Duration ◽  
Phase Curve ◽  
Single Orbit ◽  
Reflected Light ◽  
Planetary Orbits ◽  
Minimum Number ◽  
Temperature Ranges ◽  
Low Amplitude

Phase curves, or the change in observed illumination of the planet as it orbits around its host star, help us to characterize their atmospheres. However, the variability of the host star can make their detection challenging. The presence of starspots, faculae, flares, and rotational effects introduce brightness variations that can hide other flux variations related to the presence of an exoplanet: ellipsoidal variation, Doppler boosting, and a combination of reflected light and thermal emission from the planet. Here we present a study to quantify the effect of stellar variability on the detectability of phase curves in the optical. In the first stage we simulated ideal data, with different white noise levels, and with cadences and total duration matching a quarter of the Kepler mission. We performed injection and recovery tests to evaluate the minimum number of planetary orbits that need to be observed in order to determine the amplitude of the phase curve with an accuracy of 15%. We also evaluate the effect of a simplistic stellar variability signal with low amplitude in order to provide strong constraints on the minimum number of orbits needed under these ideal conditions. In the second stage we applied these methods to data from Q9 of the Kepler mission, known for its low instrumental noise. The injection and recovery tests are performed on a selected sample of the less noisy stars in different effective temperature ranges. Even for the shortest explored planet period of 1 day, we find that observing a single orbit of the planet fails to detect accurately more than 90% of the inserted amplitude. The best recovery rates, close to 48%, are obtained after 10 orbits of a 1 day period planet with the largest explored amplitude of 150 ppm. The temperature range of the host stars providing better recovery ratios is 5500 K < Teff < 6000 K. Our results provide guidelines to selecting the best targets in which phase curves can be measured to the greatest accuracy, given the variability and effective temperature of its host star, which is of interest for the upcoming TESS, CHEOPS, and PLATO space missions.

scholarly journals Imaging spectroscopy: Earth and planetary remote sensing with the USGS Tetracorder and expert systems

2003 ◽  
Vol 108 (E12) ◽  
Author(s):  
Roger N. Clark ◽  
Gregg A. Swayze ◽  
K. Eric Livo ◽  
Raymond F. Kokaly ◽  
Steve J. Sutley ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Expert Systems ◽  
Imaging Spectroscopy

scholarly journals APLIKASI SIG UNTUK PENETAPAN KESESUAIAN WILAYAH PENERAPAN MEKANISASI PERTANIAN TANAMAN PANGAN

2016 ◽  
Vol 10 (1) ◽  
pp. 31
Author(s):  
Mubekti Mubekti
Keyword(s):  
Remote Sensing ◽  
Limiting Factors ◽  
Limiting Factor ◽  
Physical Parameters ◽  
Know How ◽  
Agricultural Mechanization ◽  
Preliminary Research

The study is the preliminary research aiming to apply the usefulness of the GISsystem for classifying suitability of region to the agricultural mechanization. Simplebasic theory of GIS and classification of agricultural mechanization were presented.Nine physical and non-physical parameters as limiting factors were defined and aweight of each parameter was calculated in order to know how far its effect to theagricultural mechanization practice. Data coming from several types, ie: numeric,vector and remote sensing (raster) were prepared to support the process. Twoordoes consisting of five classes were employed to extract suitability classificationof each District in Jawa Barat dan Banten Province. The results show that tendistricts are classified into suitable for applying agricultural mechanization, and therest ten districts are classified into not suitable. Depending on the dynamic characterof limiting factor, suitability class would possibly change along the time. Saveralconclusions and advices for improving research are given.

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