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Most crop classification work use the ground reference data to training the classifier; but sometimes, the ground reference data cannot be obtained. In this paper, we tried to use the NDVI time series obtained during 2006 and 2013 to classify crop types in 2014 at 30 m spatial resolution. The experiment was conducted in Southeast Kansas, USA. Firstly, we extracted the NDVI time series using ground...
A fast and efficient estimation of crop biophysical parameters is significantly important in many agricultural, ecological, and meteorological applications. This study investigated the potential of airborne LiDAR and satellite GF-1 data for estimating three biophysical parameters of maize: 1) leaf area index (LAI); 2) average canopy height $\left({{{\bf H}_{{\bf canopy}}}} \right)$; and 3) aboveground...
This research aims at evaluating the potential of multi-temporal images acquired in April-June period for crop mapping before harvest in Kashgar China. Firstly, images of both Landsat-5 TM and Huan Jing (HJ)-1 CCD data were used to acquire an image time series with 30 m spatial resolution and 15 day temporal resolution during the entire growing season. Subsequently, period-by-period separability of...
Satellites sensors, e.g., MODIS, NOAA-AVHRR, SEAWIFS, are widely used satellite data. However, the coarse spatial resolution of these data limited the application. In this paper, we propose a novel approach for the simulation of high spatial resolution image from mutil-temporal coarser resolution satellite data that will has both high spatial resolution and temporal resolution. Through detecting temporal...
This paper evaluated the capability of FLAASH in ENVI software to make atmospheric correction for Hyperion hyperspectral image and ALI image. Hyperion and ALI sensors are two of the three instruments onboard NASA EO-1 satellite, New Millennium Program (NMP) launched on November 21, 2000, and Hyperion is the first spaceborne hyperspectral imaging spectrometer. The study area is Zhangye city (37deg28'N-39deg57'N,...
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