A global dataset of noiseless time-series vegetation and water indices for farmland analysis

Institute of Agricultural Resources and Regional Planning of CAAS;Institute of Electrical and electronics Engineers (IEEE) Geoscience and Remote Sensing Society (GRSS);National Agricultural Statistics Service (NASS);Open Geospatial Consortium (OGC);Republic of Turkey Ministry of Food, Agriculture and Live Stock;United States Department of Agriculture (USDA)4th International Conference on Agro-Geoinformatics, Agro-Geoinformatics 2015 --20 July 2015 through 24 July 2015 -- --Time-series vegetation and water indices derived from remote sensing images are crucial materials for farmland analysis based on crop phenology and monitoring such as classification of cropping patterns and monitoring of crop growth and productivities. However, the optical remote-sensing images often contain problematic pixels, such as those affected by thick clouds and its shadows, resulting a noisy time-series data which is inadequate to use for farmland analysis. Lack of the high quality noiseless time-series data products have been a bottleneck for many studies on farmland analysis using remote-sensing data in both of global and local scales. Hence we aims in this study to produce remote-sensing data archives containing noiseless smoothed time-series Normalized Vegetation Index (NDVI), Enhanced Vegetation Index (EVI), Land Surface Water Index (LSWI), and RGB composite (true color) image, covering global wide with the adequately downscaled 250-m resolution in 8-days interval from the period of 2000 to 2014 and up-to-date, derived from based on the Moderate Resolution Imaging Spectroradiometer (MODIS) sensor images. The processing system for generating the global noiseless time-series data in this study is consist of four modules; image acquisition, preprocessing, noise reduction, and data archiving, implemented in Interactive Data Language (IDL) with PDP (Parallel Distributed Processing). Data products are derived from two sets of Terra/MODIS surface-reflectance 8-day composite data (MOD09Q1 v005 (250-m resolution) and MOD09A1 v005 (500-m resolution)) acquired from LP DAAC (Land Processes Distributed Active Archive Center, USGS) on a regular basis automatically to update the latest products. To generate noiseless and smooth time-series data, we applied following well-established procedure: 1) Eliminate cloud and sensor noise pixels by referring the image quality information: 2) Reconstruct daily time-series data by referring the actual date of observation for each pixels: 3) Synthesize daily time-series Terra and Aqua: 4) Interpolate eliminated pixel value on time-series axis by liner interpolation method: 5) Apply the Savitzky-Golay filtering to time-series data to produce smoothed time-series data. Denoised true color image can be used for visually checking the quality of noise reduction. Data products are mapped by MODIS Sinusoidal Tiling System, and archived with Hierarchical Data Format-Earth Observing System (HDF-EOS) format containing various meta-information, which are the standard archive format for MODIS Land products distributed by USGS, so that users can use existing favorite tools such the MODIS Reprojection Tool (MRT) for handling the archives. The advanced noiseless time-series vegetation and water indices data archives produced in this study would contribute significantly to advanced analysis and monitoring of the crop production. © 2015 IEEE

Implication of groundwater fluctuation on the seasonal salt dynamic in the Harran Plain, south-eastern Turkey

Inefficient farm-level water management aggravates groundwater fluctuation and salt accumulation particularly in arid and semi-arid irrigated agriculture. Inappropriate water management practices in the Harran Plain are a good example. A study was carried out to investigate the effect of groundwater fluctuation on the seasonal salt dynamic in four widespread soil series in the Harran Plain with different natural drainage, south-eastern Turkey. Four profiles were excavated and soil samples were collected seasonally up to 100 cm depth with 10 cm intervals. Similarly, irrigation and groundwater samples were collected from the fields where soil sampling was carried out. Significant seasonal variations in the salt dynamic were observed with the fluctuation levels of the groundwater. Total salt content at 1 m soil depth remained constant during the year, however salt fluctuation throughout the root zone in the growing season exceeded the threshold values of corn, wheat and cotton, commonly grown crops in the region, of 1.7, 6.0 and 7.7 dSm1, respectively. However, soils with less water fluctuation showed lower salt accumulation in the root zone from May to October. Results also confirmed that soils can be non-saline, but groundwater salinity, which may not be point specific, requires special attention

12th International Meeting on Soil Micromorphology, 20-26 September 2004, Adana, Turkey. Excursion Book: Field Guide to the Soil Profiles of Adana, Osoaniye, Nizip, Urfa.

Abstract not availableJRC.H-Institute for environment and sustainability (Ispra