Large Area Crop Inventory Experiment (LACIE). Experiment plan for evaluation of LANDSAT agronomic variables using wheat intensive test sites

There are no author-identified significant results in this report

Adjusting the tasseled cap brightness and greenness factors for atmospheric path radiance and absorption on a pixel by pixel basis

A radiative transfer model was used to convert ground measured reflectances into the radiance at the top of the atmosphere, for several levels of atmospheric path radiance. The radiance in MSS7 (0.8 to 1.1 m) was multiplied by the transmission fraction for atmospheres having different levels of precipitable water. The radiance values were converted to simulated LANDSAT digital counts for four path radiance levels and four levels of precipitable water. These values were used to calculate the Kauth-Thomas brightness, greenness, yellowness, and nonsuch factors. Brightness was affected by surface conditions and path radiance. Greenness was affected by surface conditions, path radiance, and precipitable water. Yellowness was affected by path radiance and nonsuch by precipitable water, and both factors changed only slightly with surface conditions. Yellowness and nonsuch were used to adjust brightness and greenness to produce factors that were affected only by surface conditions such as soils and vegetation, and not by path radiance and precipitable water

A look at the commonly used LANDSAT vegetation indices

The origins, development, and logic of the indices are discussed. The relationships of the indices to ground-based measurements of vegetation are highlighted. An effort was made to preserve the order in which the various indices appeared in the literature in order to historically trace their underlying concepts

Quantitative estimation of plant characteristics using spectral measurement: A survey of the literature

There are no author-identified significant results in this report

Investigation of radiometric properties of the LANDSAT-4 multispectral scanner

The radiometric data quality of the LANDSAT 4 multispectral scanner (MSS) was examined using several LANDSAT 4 frames. It was found that LANDSAT 4 MSS produces high-quality data of the caliber experienced with previous LANDSATS. For example, the detector equalization procedure worked well, leaving a residual banding effect of about 0.3 digital counts RMS, close to the theoretical minimum value of quantization error. Nevertheless, artifacts of the data were found, two of which were not experienced in previous MSS data. A low-level coherent noise effect was observed in all bands, with a magnitude of about 0.5 digital counts and a frequency of approximately 28 KHz (representing a wavelength of about 3.6 pixels); a substantial increase in processing complexity would be required to reduce this artifact in the data. Also, a substantial scan-length variation (of up to six pixels) was noted in MSS data when the TM sensor was operating; the LANDSAT 4 correction algorithms being applied routinely by the EROS Data Center to produce a p-type data should remove most of this variation. Between-satellite calibrations were examined in paired LANDSAT 3 and LANDSAT 4 MSS data sets, which were closely matched in acquisition time and place. Radiometric comparisons showed that all bands were highly linear in digital counts, and a well-determined linear transformation between the MSS's was established

MIDAS prototype Multispectral Interactive Digital Analysis System for large area earth resources surveys. Volume 2: Charge coupled device investigation

MIDAS is a third-generation, fast, low cost, multispectral recognition system able to keep pace with the large quantity and high rates of data acquisition from large regions with present and projected sensors. MIDAS, for example, can process a complete ERTS frame in forty seconds and provide a color map of sixteen constituent categories in a few minutes. A principal objective of the MIDAS Program is to provide a system well interfaced with the human operator and thus to obtain large overall reductions in turn-around time and significant gains in throughput. The need for advanced onboard spacecraft processing of remotely sensed data is stated and approaches to this problem are described which are feasible through the use of charge coupled devices. Tentative mechanizations for the required processing operations are given in large block form. These initial designs can serve as a guide to circuit/system designers

Data compression in remote sensing applications

A survey of current data compression techniques which are being used to reduce the amount of data in remote sensing applications is provided. The survey aspect is far from complete, reflecting the substantial activity in this area. The purpose of the survey is more to exemplify the different approaches being taken rather than to provide an exhaustive list of the various proposed approaches

Linear feature selection with applications

There are no author-identified significant results in this report

Recent advancements in information extraction methodology and hardware for Earth Resources Survey Systems

There are no author-identified significant results in this report

A labeling technology for LANDSAT imagery

There are no author-identified significant results in this report