Decision Agriculture

In this chapter, the latest developments in the field of decision agriculture are discussed. The practice of management zones in digital agriculture is described for efficient and smart faming. Accordingly, the methodology for delineating management zones is presented. Modeling of decision support systems is explained along with discussion of the issues and challenges in this area. Moreover, the precision agriculture technology is also considered. Moreover, the chapter surveys the state of the decision agriculture technologies in the countries such as Bulgaria, Denmark, France, Israel, Malaysia, Pakistan, United Kingdom, Ukraine, and Sweden. Finally, different field factors such as GPS accuracy and crop growth are also analyzed

Processing and Analyzing Advanced Hyperspectral Imagery Data for Identifying Clay Minerals .A Case Study

Abstract: Spectral analyses as one of the most advanced remote sensing techniques were used to identify mineralogy of the clay fractions in South Port Said plain, Egypt. Different spectral processes have been used to execute the prospective spectral analyses. These processes include 1-The reflectance calibration of Hyperspectral data belonging to the studied area, 2-Using the Minimum Noise Fraction (MNF) transformation.3-Creating the pixel purity index (PPI) which used as a mean of finding the most "spectrally pure", extreme, pixel in hyperspectral images. Making conjunction between the Minimum Noise Fraction Transform (MNF) and Pixel Purity Index (PPI) tools through 3-D visualization offered capabilities to locate, identify and cluster the purest pixels and most extreme spectral responses in a data set. To identify the clay minerals of the studied area the extracted unknown spectra of the purest pixels was matched to pre-defined (library) spectra providing score with respect to the library spectra. Three methods namely, Spectral Feature Fitting (SFF),Spectral Angle Mapper (SAM) and Binary Encoding (BE) were used to produce score between 0 and 1, where the value of 1 equal a perfect match showing exactly the mineral type. In the investigated area four clay minerals could be identified i.e. Vermiculite, Kaolinite, Montmorillinite and Illite recording different scores related to their abundance in the soils. In order to check the validity and accuracy of the obtained results, X ray diffraction analysis was applied on surface soil samples covering the same locations of the signature endmembers that derived from hyperspectral image. Highly correlated and significant results were obtained using the two approaches (spectral signatures and x-ray diffraction)

Soil Degradation Assessment in North Nile Delta Using Remote Sensing and GIS Techniques

The present work aims at monitoring soil degradation process within the last two decades in the northern part of Nile Delta. The investigated area lies between longitudes 31° 00- & 31° 15- E and latitudes 31° 00' & 31° 37' N., covering an area of about 161760 feddans. Detecting soil degradation and recognizing its various types is a necessity to take the practical measures for combating it as well as conserving and keeping the agricultural soil healthy. Land degradation was assessed by adopting new approach through the integration of GLASOD/FAO approach and Remote Sensing / GIS techniques .The main types of human induced soil degradation that observed in the studied area are salinity, alkalinity (sodicity), compaction and water logging .On the other hand water erosion because of sea rise is assessed. The obtained data showed that, areas that were affected by compaction increment have been spatially enlarged by 40.9 % and those affected by compaction decrease have been spatially reduced by 22.6 % of the total area ,meanwhile areas that have been unchanged were estimated by 36.5% of the total area. The areas that were affected by water logging increase have been spatially enlarged by 52.2 % and those affected by water logging decrease have been spatially reduced by 10.1 % of the total area, meanwhile the areas which have been unchanged were represented by 37.7 % of the total area. Areas that were affected by salinity increase have been spatially enlarged by 31.4 % of the total area and those affected by salinity decrease have been reduced by 43.3 % of the total area. An area represented by 25.2 % of the total area has been unchanged. Alkalinization (sodicity) was expressed by the exchangeable sodium percentage (ESP).Areas that were affected by sodicity increase have been spatially enlarged by 33.7 %, meanwhile those affected by sodicity decrease have been spatially reduced by 33.6 % of the total area. An area represented by 32.6 % of the total area has been unchanged. Multi-dates satellite data from Landsat TM & ETM+ images dated 1983 and 2003 were used to detect the changes of shoreline during the last two decades. The obtained results showed that, the eroded areas were determined by 547.4 feddans , meanwhile the accreted areas were detected by 476.5 feddans during the twenty years period