A comparative study on cloud parameter estimation among GOSAT/CAI, MODIS, CALIPSO/CALIOP and Landsat-8/OLI is carried out using Laser Radar: Lidar as a truth data. Optical depth, size distribution, as well as cirrus type of clouds are cloud parameters. In particular, cirrus cloud detection is tough issue. 1.38 μm channel is required for its detection. Although MODIS and Landsat-8/OLI have such ...

The Operational Land Imager (OLI) is a multi-spectral radiometer hosted on the recently launched Landsat-8 satellite. OLI includes a suite of relatively narrow spectral bands at 30-meter spatial resolution in the visible to shortwave infrared that make it a potential tool for ocean color radiometry: measurement of the reflected spectral radiance upwelling from beneath the ocean surface that car...

The Operational Land Imager (OLI) is a new Landsat sensor being developed by the joint USGS-NASA Landsat Data Continuity Mission (LDCM) that exhibits the potential to be a state-of-the-art instrument for studying inland and coastal waters. With upgrades such as a new Coastal Aerosol band, 12 bit quantization, and improved signal-to-noise, OLI will be spectrally and radiometrically superior to i...

Road feature extraction from the remote sensing images is an arduous task and has a significant role in various applications of urban planning, updating maps, traffic management, etc. In this paper, new band combination (B652) to form road index (RI) OLI multispectral bands based on spectral reflectance asphalt, presented for extraction. The B652 converted by normalization. morphological operat...

Landsat 8, the most recently launched satellite of the series, promises to maintain the continuity of Landsat 7. However, in addition to subtle differences in sensor characteristics and vegetation index (VI) generation algorithms, VIs respond differently to the seasonality of the various types of vegetation cover. The purpose of this study was to elucidate the effects of these variations on VIs...

This paper discusses the application of the Cross-Correlation Analysis (CCA) technique to multi-spatial resolution Earth Observation (EO) data for detecting and quantifying changes in forest ecosystems in two different protected areas, located in Southern Italy and Southern India. The input data for CCA investigation were elaborated from the forest layer extracted from an existing Land Cover/La...