Crop Phenology Detection Using High Spatio-Temporal Resolution Data Fused from SPOT5 and MODIS Products

Crop Phenology Detection Using High Spatio-Temporal Resolution Data Fused from SPOT5 and MODIS Products

Timely and efficient monitoring of crop phenology at a high spatial resolution are crucial for the precise and effective management of agriculture. Recently, satellite-derived vegetation indices (VIs), such as the Normalized Difference Vegetation Index (NDVI), have been widely used for the phenology detection of terrestrial ecosystems. In this paper, a framework is proposed to detect crop pheno...

Detecting Rice Crop Phenology from Time-series Modis Data

Information on rice crop phenology is important for crop management. This study aimed to detect rice crop phenology in the Vietnamese Mekong Delta using time-series MODIS data in 2007. Data processing steps included: (1) constructing time-series MODIS NDVI data, (2) filtering noise from the time-series data using empirical mode decomposition (EMD) and wavelet transform, (3) detecting rice crop ...

Operational Prediction of Crop Yields Using Modis Data and Products

Official crop progress, condition and production estimates for the United States are responsibilities of the U.S. Department of Agriculture’s, National Agricultural Statistics Service (NASS). In addition to weekly and monthly survey-based data, biweekly composite maps of the normalized difference vegetation index (NDVI) from the NOAA AVHRR sensor (1 km resolution) are produced by NASS’s Researc...

Winter wheat area estimation from MODIS-EVI time series data using the Crop Proportion Phenology Index

Classification of C3 and C4 Vegetation Types Using MODIS and ETM+ Blended High Spatio-Temporal Resolution Data

The distribution of C3 and C4 vegetation plays an important role in the global carbon cycle and climate change. Knowledge of the distribution of C3 and C4 vegetation at a high spatial resolution over local or regional scales helps us to understand their ecological functions and climate dependencies. In this study, we classified C3 and C4 vegetation at a high resolution for spatially heterogeneo...