An Assessment of Relations between Vegetation Green FPAR and Vegetation Indices through a Radiative Transfer Model.

The fraction of absorbed photosynthetically active radiation (FPAR) is widely used in remote sensing-based production models to estimate gross or net primary production. The forest canopy is composed primarily of photosynthetically active vegetation (PAV, green leaves) and non-photosynthetic vegetation (NPV e.g.

Assessment of GF3 Full-Polarimetric SAR Data for Dryland Crop Classification with Different Polarimetric Decomposition Methods.

Crop classification is one of the most important agricultural applications of remote sensing. Many studies have investigated crop classification using SAR data, while few studies have focused on the classification of dryland crops by the new Gaofen-3 (GF3) SAR data. In this paper, taking Hengshui city as the study area, the performance of the Freeman-Durden, Sato4, Singh4 and multi-component decomposition methods for dryland crop type classification applications are evaluated, and the potential of full-polarimetric GF3 data in dryland crop type classification are also investigated.

Urban spring phenology in the middle temperate zone of China: dynamics and influence factors.

Urbanization and its resultant urban heat island provide a means for evaluating the impact of climate warming on vegetation phenology. To predict the possible response of vegetation phenology to rise of temperature, it is necessary to investigate factors influencing vegetation phenology in different climate zones. The start of growing season (SOS) in seven cities located in the middle temperate humid, semi-humid, semi-arid, and arid climate zones in China was extracted based on satellite-derived normalized difference vegetation index (NDVI) data.

[Monitoring "green tide" in the Yellow Sea and the East China Sea using multi-temporal and multi-source remote sensing images].

Landsat-TM (Theme Mapper) and EOS (Earth Observing System)-MODIS (MODerate resolution Imaging Spectrora-diometer) Terra/Aqua images were used to monitor the macro-algae (Ulva prolifera) bloom since 2007 at the Yellow Sea and the East China Sea. At the turbid waters of Northern Jiangsu Shoal, there is strong spectral mixing behavior, and satellite images with finer spatical resolution are more effective in detection of macro-algae patches. Macro-algae patches were detected by the Landsat images for the first time at the Sheyang estuary where is dominated by very turbid waters.