[1] The Moderate Resolution Imaging Spectroradiometer (MODIS) currently provides the most extensive aerosol retrievals on a global basis, but validation is limited to a small number of ground stations. This study presents a comprehensive evaluation of Collection 4 and 5 MODIS aerosol products using ground measurements from the Chinese Sun Hazemeter Network (CSHNET). The Collection 5 product use...

Moderate Resolution Imaging Spectroradiometer (MODIS) data have been widely applied for the remote sensing of aerosol optical depth (AOD) because the MODIS sensor features a short revisit period and a moderate spatial resolution. The Dense Dark Vegetation (DDV) method is the most popular retrieval method. However, the DDV method can only be used to retrieve the AOD with high precision when the ...

Various classification methods have been applied for low resolution of the entire Earth's surface from recorded satellite images, but insufficient study has determined which method, for which satellite data, is economically viable for tropical forest land use mapping. This study employed Iterative Self Organizing Data Analysis Techniques (ISODATA) and K-Means classification techniques to classi...

Moderate Resolution Imaging Spectroradiometer (MODIS) has a potential for more detailed daily monitoring of land covers and their change than ever because two bands, red and near-infrared bands, have 250m spatial resolutions. On the other hand, the use of MODIS data requires attention to Bidirectional Reflectance Distribution Function (BRDF) effect, which is one of the most important factors to...

Long-term PM2.5 exposure has been associated with various adverse health outcomes. However, most ground monitors are located in urban areas, leading to a potentially biased representation of true regional PM2.5 levels. To facilitate epidemiological studies, accurate estimates of the spatiotemporally continuous distribution of PM2.5 concentrations are important. Satellite-retrieved aerosol optic...

Within the framework of air quality monitoring, measurements by Earth-observing satellite sensors are combined here with regional meteorological and chemical transport models. Two satellite-derived products developed within the QUITSAT project, regarding significant pollutants including PM(2.5) and NO(2), are presented. Estimates of PM(2.5) concentrations at ground level were obtained using mod...

[1] This paper compares by land cover type seasonal and spatial variations of MODIS leaf area index (LAI) and fraction of photosynthetically active radiation (0.4–0.7 mm) absorbed by vegetation (FPAR) from 2.5 years with those from the Common Land Model (CLM) and investigates possible reasons for notable differences. The FPAR value is mainly determined by LAI in MODIS and both LAI and stem area...

As both a central task in Remote Sensing and a common problem in many other situations involving time series data, change point detection boasts a thorough and well-documented history of study. However, the treatment of missing data and proper exploitation of the structure in multivariate time series during change point detection remains lacking. Multispectral, high temporal resolution time ser...

[1] Meteorological observations, in situ data, and satellite images of dust episodes were used already in the 1970s to estimate that 100 Tg of dust are transported from Africa over the Atlantic Ocean every year between June and August and are deposited in the Atlantic Ocean and the Americas. Desert dust is a main source of nutrients to oceanic biota and the Amazon forest, but it deteriorates ai...

The quick and accurate extraction of information on woodland resources and distributions using remote sensing technology is a key step in the management, protection, and sustainable use of woodlands. This paper presents a low-cost and high-precision extraction method for large woodland areas based on the fractal features of the Moderate Resolution Imaging Spectroradiometer (MODIS) normalized di...