The new Landsat-8 Operational Land Imager (OLI) is intended to be broadly compatible with the previous Landsat-7 Enhanced Thematic Mapper Plus (ETM+). The spectral response of the OLI is slightly different to the ETM+, and so there may be slight differences in the reflectance measurements. Since the differences are a function not just of spectral responses, but also of the target pixels, there ...

Expectations of the Operational Land Imager (OLI) radiometric performance onboard Landsat-8 have been met or exceeded. The calibration activities that occurred prior to launch provided calibration parameters that enabled ground processing to produce imagery that met most requirements when data were transmitted to the ground. Since launch, calibration updates have improved the image quality even...

Impervious surface area (ISA) is a key factor for monitoring urban environment and land development. Automatic mapping of impervious surfaces has attracted growing attention in recent years. Spectral built-up indices are considered promising to map ISA distributions due to their easy, parameter-free implementations. This study explores the potentials of impervious surface indices for ISA mappin...

Over Himalayas, the detection of seasonal snow cover variations via remote sensing is challenging due to presence rugged terrain and shadow effects. Moreover, traditional per-pixel-based change methods less competent identify inner-pixel subtle with coarse resolution satellite imagery. In present work, we have proposed subpixel-based (SCD) algorithm examine impact topographic correction (TC) on...

The objective of this study was to evaluate the separability potential Sentinel-2A (MultiSpectral Instrument, MSI) and Landsat (Operational Land Imager, OLI Thermal Infrared Sensor, TIRS) derived indices for detecting small-extent (<25 ha) forest fires areas severity degrees. Three remote sensing [differenced Normalized Burn Ratio (dNBR), differenced Different Vegetation Index (dNDVI), surfa...

The optical complexity of urban waters makes the remote retrieval of chlorophyll-a (Chl-a) concentration a challenging task. In this study, Chl-a concentration was retrieved using reflectance data of Landsat OLI images. Chl-a concentration in the Haihe River of China was obtained using mathematical regression analysis (MRA) and an artificial neural network (ANN). A regression model was built ba...