Airborne imaging spectrometer for applications (AISA)

Mäkisara, Kai; Meinander, M.; Rantasuo, Markku; Okkonen, Jukka; Aikio, Mauri; Sipola, K.

doi:10.1109/igarss.1993.322291

Cited by 17 publications

(6 citation statements)

References 3 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…One dataset was derived from a hyperspectral sensor, named AISA (Airborne Imaging Spectrometer for Applications), with 258 narrow contiguous bands ranging from 400 to 2400 nm [23-24]. The bandwidth is approximately 4.08 nm and 11.40 nm over the VNIR and SWIR spectral wavelength ranges, respectively.…”

Section: A Case Study For Testing Topographic Effects On Evi and Ndvimentioning

confidence: 99%

Sensitivity of the Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI) to Topographic Effects: A Case Study in High-density Cypress Forest

Matsushita

Yang

Chen

et al. 2007

Sensors

603

297

View full text Add to dashboard Cite

Vegetation indices play an important role in monitoring variations in vegetation. The Enhanced Vegetation Index (EVI) proposed by the MODIS Land Discipline Group and the Normalized Difference Vegetation Index (NDVI) are both global-based vegetation indices aimed at providing consistent spatial and temporal information regarding global vegetation. However, many environmental factors such as atmospheric conditions and soil background may produce errors in these indices. The topographic effect is another very important factor, especially when the indices are used in areas of rough terrain. In this paper, we theoretically analyzed differences in the topographic effect on the EVI and the NDVI based on a non-Lambertian model and two airborne-based images acquired from a mountainous area covered by high-density Japanese cypress plantation were used as a case study. The results indicate that the soil adjustment factor “L” in the EVI makes it more sensitive to topographic conditions than is the NDVI. Based on these results, we strongly recommend that the topographic effect should be removed in the reflectance data before the EVI was calculated—as well as from other vegetation indices that similarly include a term without a band ratio format (e.g., the PVI and SAVI)—when these indices are used in the area of rough terrain, where the topographic effect on the vegetation indices having only a band ratio format (e.g., the NDVI) can usually be ignored.

show abstract

Section: A Case Study For Testing Topographic Effects On Evi and Ndvimentioning

confidence: 99%

Sensitivity of the Enhanced Vegetation Index (EVI) and Normalized Difference Vegetation Index (NDVI) to Topographic Effects: A Case Study in High-density Cypress Forest

Matsushita

Yang

Chen

et al. 2007

Sensors

603

297

View full text Add to dashboard Cite

show abstract

“…The main remote sensing instrument employed during the campaigns was the Airborne Imaging Spectrometer for Application (AISA) [9] .…”

Section: Methodsmentioning

confidence: 99%

Atmospheric correction of AISA based on MODTRAN4

Cheng

Pan²,

Mao³

2006

Geoinformatics 2006: Remotely Sensed Data and Information

View full text Add to dashboard Cite

A combination of good spatial and spectral resolution makes visible to shortwave infrared spectral imaging from aircraft a highly valuable technology for remote sensing of the earth's surface. Many applications require the elimination of atmospheric effects caused by molecular and particulate scattering; a process known as atmospheric correction, compensation, or removal. The Fast Line-of-sight Atmospheric Analysis of Spectral Hypercubes (FLAASH) atmospheric correction code derives its physics-based algorithm from the MODTRAN4 radiative transfer code. A new spectral recalibration algorithm, which has been incorporated into FLAASH, is described. AISA (Airborne Imaging Spectrometer for Application) data covering the Eastern Sea in China was acquired and the results from processing AISA data with FLAASH are discussed.

show abstract

“…The AISA imaging spectrometer (Mäkisara et al, 1993) was flown over the study area onboard a twin-engine cargo plane on the 14th of September, 1999. The bushbroom sensor was mounted on the nosecone of the aircraft.…”

Section: Imaging Spectroscopic Datamentioning

confidence: 99%