This study presents our methods to produce multi-day Terra, Aqua, and Terra-Aqua moderate resolution imaging spectroradiometer (MODIS) snow cover composite images respectively from daily Terra MODIS, Aqua MODIS, and both Terra and Aqua MODIS snow cover products, with flexible starting and ending dates and a user-defined cloud cover threshold. The methods are applied to Colorado Plateau, USA and...

This study demonstrates the feasibility of small satellite, namely PROBA platform with the compact high resolution imaging spectrometer (CHRIS), for aerosol retrieval in Hong Kong. The rationale of our technique is to estimate the aerosol reflectances by decomposing the Top of Atmosphere (TOA) reflectances from surface reflectance and Rayleigh path reflectances. For the determination of surface...

NDVI time series imagery are commonly used as a reliable source for land use and land cover mapping and monitoring. However long duration cloud can significantly influence its precision in areas where persistent clouds prevails. Therefore quantifying errors related to cloud contamination are essential for accurate land cover mapping and monitoring. This study aims to detect long duration cloud ...

The goal of our project is to develop and evaluate image analysis methodologies for use on the ground or on-board spacecraft, particularly spacecraft constellations. Our focus is on developing methods to perform automatic registration and fusion of multisensor data representing multiple spatial, spectral and temporal resolutions, as well as dimension reduction of hyperspectral data. Feature ext...

MODIS LAI product has been increasingly important for analyzing the process and productivity of terrestrial ecosystems at global scale. This study was aimed to assess the quality of global MODIS LAI product for applications in regional and even in local scales. To examine the quality of MODIS LAI data, we produced a reference LAI map that was derived by relating the ground-measured LAI to Lands...

Time series of images are required to extract and separate information on vegetation change due to phenological cycles, inter-annual climatic variability, and long-term trends. While images from the Landsat Thematic Mapper (TM) sensor have the spatial and spectral characteristics suited for mapping a range of vegetation structural and compositional properties, its 16-day revisit period combined...

This paper address the problem of dust storm detection based on multispectral image analysis from a probabilistic point of view. Two classifiers are designed, one based on classic probability theory and other based on a probabilistic computational intelligence approach. The first classifier is designed under the Maximum Likelihood Estimation (MLE) model, and the second with a Probabilistic Neur...

This study investigated the performances of the Moderate Resolution Imaging Spectroradiometer (MODIS) and GEOLAND2 Version 1 (GEOV1) Leaf Area Index (LAI) products using ground measurements and LAI reference maps over four sites in North China for 2011-2013. The Terra + Aqua MODIS and Terra MODIS LAI retrieved by the main algorithm and GEOV1 LAI within the valid range were evaluated and interco...

The Landsat ETM+ has shown great potential in agricultural mapping and monitoring due to its advantages over traditional receive procedures in terms of cost effectiveness and timeliness in availability of information over larger areas and ingredient the temporal dependence of multitemporal image data to identify the changing pattern of vegetation cover and consequently enhance the interpretatio...

We reported earlier [1] on efforts to reduce the so-called “cloud fringe” problem. Here the fringes of certain snow fields are labeled as “cloud” whereas close inspection of the data indicates that the correct labeling is a non-cloud category such as snow or land. Noting that the labeling of image pixels as cloud is done without any regard to spatial context, we investigated utilizing image seg...