Optimization of Irrigation Efficiency of Center‐pivot Systems Using Spatial and Temporal Data Integration

The efficiency of a center pivot irrigation system is greatly dependent on the ability to provide the water supply needed to meet the demands of the rowing crop. While limited water supplies may educe crop yield due to water stress, excessive irrigation may result in wasted resources and, if extreme, may also reduce yields. The optimized need for irrigation water changes temporally and spatially. Various methods have been deployed to focus on either level of variability. Thus, soil sensor telemetry and crop modeling frequently allow improved irrigation scheduling. On the other hand, dense‐resolution proximal soil sensing allows identifying spatial variability of topsoil water storage capacity that also affects the needs for irrigated water. The research intends to integrate on‐the-goal soil sensing technology with stationary sensor networks to supplement decision making processes to optimize irrigation scheduling as well as to prescribe site‐specific water management if appropriate for a given site

Optimization of Irrigation Efficiency of Center‐pivot Systems Using Spatial and Temporal Data Integration

The efficiency of a center pivot irrigation system is greatly dependent on the ability to provide the water supply needed to meet the demands of the rowing crop. While limited water supplies may educe crop yield due to water stress, excessive irrigation may result in wasted resources and, if extreme, may also reduce yields. The optimized need for irrigation water changes temporally and spatially. Various methods have been deployed to focus on either level of variability. Thus, soil sensor telemetry and crop modeling frequently allow improved irrigation scheduling. On the other hand, dense‐resolution proximal soil sensing allows identifying spatial variability of topsoil water storage capacity that also affects the needs for irrigated water. The research intends to integrate on‐the-goal soil sensing technology with stationary sensor networks to supplement decision making processes to optimize irrigation scheduling as well as to prescribe site‐specific water management if appropriate for a given site

Multi-spatial and Temporal Data Integration for Understanding Agricultural Activity and Vulnerability: A case study of rural farmer’s villages

This chapter describes field investigations and geo-spatial/temporal analysis of livelihood at the village level, with a particular focus on agricultural activities, using a multi-disciplinary approach. As a basic analysis, the integration of all data collected so far has been carried out to understand the situation at the level of the household or village, in terms of adaptation and capacity to cope with a risk caused by an unexpected ecological or social shock

A segmentation approach to delineate zones for differential nitrogen intervention.

Multi-source and -temporal data integration is expected to support the delineation of within-field management zones that may better conform to unique combinations of crop yield variations. This work addresses the evaluation of zone delineation approaches based on image classification and segmentation methods. An object based segmentation is introduced using ancillary data from multivariate analysis of yield maps. A simple economic evaluation is conducted to compare delineation methods aiming variable-rate Nitrogen applications. Advantages and penalties are suggested for 2, 3, and 4 management zones. Results show that a procedure combining multiresolution, watershed and region grow segmentation algorithms has systematically resulted in greater net worth. It is suggested that segmentation methods have potential application for zone management delineations supporting contiguous patter

Multi-temporal images and 3D dense models for archaeological site monitoring in Hierapolis of Phrygia (TK)

and range-based measurement systems have become increasingly interesting in excavation processes for monitoring purposes and large scale mapping, both from a terrestrial and aerial point of view. The paper will focus on the great challenge of monitoring sites over time, integrating and conforming multiple data coming from previous metric survey projects and image data collected in the past for different purposes. The test-site was the complex archaeological landscape of the ancient city of Hierapolis in Phrygia on which the MAIER – Italian Archaeological Mission of Hierapolis has operated since the 1960s and where the Politecnico di Torino conducted several survey campaigns. A set of multi-temporal datasets acquired in a series of campaigns in 1997, 2002, 2007, 2012, 2015 are presented, as well as their 3D multi-sensor models; the older dense models generated with archival images are intended to be compared and integrated with newer models generated by the LiDAR scans in 2012 and the UAV systems employed in the last mission in 2015. In particular, the case study was the massive complex of the ancient Bath-Church in the northern part of the city below the Northern Necropolis, and Building A of the Apollo Sanctuary, in the central Sacred Area near the Ancient Theatre. In these sites, many different sensors have been experimented with over the years and preliminary multi-temporal data integration has been tested in order to up-date and improve older archival records based on collected images and related to newer and updated documentation projects

Water, Energy and Agriculture Initiative

Rapid expansion of the biofuel industry provides exciting opportunities for economic growth and development in rural Nebraska. Realizing the full benefits of this opportunity and ensuring its long‐term viability depends on continued access to adequate supplies of water, electrical energy, and biofuel feedstock crops at reasonable cost. For example, about 70 percent of all corn and 50 percent of soybeans produced in Nebraska comes from irrigated land, and electrical energy for pumping irrigation water represents a major component of peak‐load energy demand in the state. Reducing this peak‐load electrical demand and consumption is essential for reducing the need for new generating capacity or peak‐load energy purchases, thus avoiding increased costs for power. Similarly, increasing water use efficiency of irrigated crops reduces energy demand for irrigation and decreases water withdrawals to produce adequate feedstock supply, which conserves water resources

Water, Energy and Agriculture Initiative

Rapid expansion of the biofuel industry provides exciting opportunities for economic growth and development in rural Nebraska. Realizing the full benefits of this opportunity and ensuring its long‐term viability depends on continued access to adequate supplies of water, electrical energy, and biofuel feedstock crops at reasonable cost. For example, about 70 percent of all corn and 50 percent of soybeans produced in Nebraska comes from irrigated land, and electrical energy for pumping irrigation water represents a major component of peak‐load energy demand in the state. Reducing this peak‐load electrical demand and consumption is essential for reducing the need for new generating capacity or peak‐load energy purchases, thus avoiding increased costs for power. Similarly, increasing water use efficiency of irrigated crops reduces energy demand for irrigation and decreases water withdrawals to produce adequate feedstock supply, which conserves water resources