Daily, or more frequent, maps of surface water have important applications in environmental and water resource management. In particular, surface water maps derived from remote sensing imagery play a useful role in the derivation of spatial inundation patterns over time. MODIS data provide the most realistic means to achieve this since they are daily, although they are often limited by cloud co...

Current remote sensing techniques fail to address the task of air quality monitoring over complex regions where multiple pollution sources produce high spatial variability. This is due to a lack of suitable satellite-sensor combinations and appropriate aerosol optical thickness (AOT) retrieval algorithms. The new generation of small satellites, with their lower costs and greater flexibility has...

The Moderate Resolution Imaging Spectroradiometer (MODIS) will add a significant new capability for investigating the 70% of the earth’s surface that is covered by oceans, in addition to contributing to the continuation of a decadal scale time series necessary for climate change assessment in the oceans. Sensor capabilities of particular importance for improving the accuracy of ocean products i...

This work presents a methodology that uses digital fraction images derived from Linear Spectral Mixture Model and wavelets transform from MODIS satellite sensor time-series for land cover change analysis. Our approach uses MODIS surface reflectance images acquired from 2000 to 2006 time period. For this study, a test site was selected in the Mato Grosso State, Brazilian Amazonia. This site has ...

Advanced remote sensing techniques and algorithms are combined to produce and analyse an improved 12-year multi-sensor time series of bio-optical properties for the Adriatic Sea. First, a multi-sensor series of normalized water-leaving radiance is created with an optically-based merging technique applied to SeaWiFS and MODIS data. Then, two empirical algorithms, embedded in a dynamic algorithm ...

Cloud and Aerosol Imager (CAI) onboard the Greenhouse Gases Observing Satellite (GOSAT) is a multi-band sensor designed to observe and acquire information on clouds and aerosols. In order to retrieve aerosol optical depth (AOD) over land from the CAI sensor, a Dark Target (DT) algorithm for GOSAT CAI was developed based on the strategy of the Moderate Resolution Imaging Spectroradiometer (MODIS...

Given that many operational satellite sensors are not calibrated, while a handful of research sensors are, cross-calibration between the two types of sensor is a cost-effective means of calibration. A new method of sensor crosscalibration is demonstrated here using the Chinese Multi-channel Visible Infrared Scanning radiometer (MVIRS) and the US Moderate Resolution Imaging Spectrometer (MODIS)....

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To evaluate accuracy of low resolution vegetation mapping for hydrological purposes, a comparative study of NDVI images derived from MODIS and Landsat 7 ETM+ data has been done. Main goal is to understand how effective MODIS images can be for vegetation characterization on large areas, as compared to the Landsat 7 ETM+ ones. In this paper a methodology is proposed with the aim of measuring the ...

Mean snow cover duration was derived for the entire continent of Europe based on the MODIS daily snow cover products MOD10A1 and MYD10A1 for the period from 2000 to 2011. Dates of snow cover start and snow cover melt were also estimated. Polar darkness north of ~62°N and extensive cloud coverage affected the daily snow cover, preventing a direct derivation of the desired parameters. Combining s...