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1. Automated Segmentation and Classification of Land Use from Overhead ImageryReliable land cover or habitat maps are an important component of any long-term landscape planning initiatives relying on current and past land use. Particularly in regions where sustainable management of natural resources is a goal, high spatial resolution habitat maps over large areas will give guidance in land-use management. We propose a computational approach to identify habitats based on the automated analysis of overhead imagery. Ultimately, this approach could be used to assist expert... C. Pradalier, A. Richard, V. Perez, R. Van couwenberghe, A. Benbihi, P. Durand |
2. Identifying and Filtering Out Outliers in Spatial DatasetsOutliers present in the dataset is harmful to the information quality contained in the map and may lead to wrong interpretations, even if the number of outliers to the total data collected is small. Thus, before any analysis, it is extremely important to remove these errors. This work proposes a sequential process model capable of identifying outlier data when compared their neighbors using statistical parameters. First, limits are determined based on the median range of the values of all the... L. Maldaner, J. Molin, T. Tavares, L. Mendez, L. Corrêdo, C. Duarte |
3. Development of a High Resolution Soil Moisture for Precision Agriculture in IndiaSoil moisture and temperature are key inputs to several precision agricultural applications such as irrigation scheduling, identifying crop health, pest and disease prediction, yield and acreage estimation, etc. The existing remote sensing satellites based soil moisture products such as SMAP are of coarse resolution and physics based land surface model such as NLDAS, GLDAS are of coarse resolution as well as not available for real time applications. Keeping this in focus, we are d... K. Das, J. Singh, J. Hazra |
4. Agricultural Remote Sensing Information for Farmers in GermanyThe European Copernicus program delivers optical and radar satellite imagery at a high temporal frequency and at a ground resolution of 10m worldwide with an open data policy. Since July 2017 the satellite constellation of the Sentinel-1 and -2 satellites is fully operational, allowing e.g. coverage of Germany every 1-2 days by radar and every 2-3 days with optical sensors. This huge data source contains a variety of valuable input information for farmers to monitor the in-field variability a... H. Lilienthal, H. Gerighausen, E. Schnug |
5. Using Geospatial Data to Assess How Climate Change May Affect Land Suitability for Agriculture ProductionFinding solutions to the challenge of sustainably feeding the world’s growing population is a pressing research need that cuts across many disciplines including using geospatial data. One possible area could be developing agricultural frontiers. Frontiers are defined as land that is currently not cultivated but that may become suitable for agriculture under climate change. Climate change may drive large-scale geographic shifts in agriculture, including expansion in cultivation at the th... K. Kc, L. Hannah, P. Roehrdanz, C. Donatti, E. Fraser, A. Berg, L. Saenz, T.M. Wright, R.J. Hijmans, M. Mulligan |
6. Development of an Overhead Optical Yield Monitor for a Sugarcane Harvester in LouisianaA yield monitor is a device used to measure harvested crop weight per unit area for a specific location within a field. The device documents yield variability in harvested fields and ultimately can be used to create a geographical-referenced yield map. Yield maps can be used to identify low yielding areas where poor soil fertility, disease, or pests may adversely affect yield. Management practices can then be adjusted to correct these issues, resulting in an increase in yields and... R.R. Price, R.M. Johnson, R.P. Viator |
7. Application of Routines for Automation of Geostatistical Analysis Procedures and Interpolation of Data by Ordinary KrigingOrdinary kriging (OK) is one of the most suitable interpolation methods for the construction of thematic maps used in precision agriculture. However, the use of OK is complex. Farmers/agronomists are generally not highly trained to use geostatistical methods to produce soil and plant attribute maps for precision agriculture and thus ensure that best management approaches are used. Therefore, the objective of this work was to develop and apply computational routines using procedures and geosta... N.M. Betzek, E.G. Souza, C.L. Bazzi, P.G. Magalhães, A. Gavioli, K. Schenatto, R.W. Dall'agnol |
8. Analysis of Soil Properties Predictability Using Different On-the-Go Soil Mapping SystemsUnderstanding the spatial variability of soil chemical and physical attributes allows for the optimization of the profitability of nutrient and water management for crop development. Considering the advantages and accessibility of various types of multi-sensor platforms capable of acquiring large sensing data pertaining to soil information across a landscape, this study compares data obtained using four common soil mapping systems: 1) topography obtained using a real-time kinematic (RTK) glob... H. Huang, V. Adamchuk, A. Biswas, W. Ji, S. Lauzon |
9. GIS Web and Mobile Development with Interfaces in QGIS for Variable Rate FertilizationIn this paper we described the implementation of a GIS for Precision Agriculture for sugarcane crop in Colombia. An spatial equation for Variable Rate Fertilization Model was defined using as inputs estimated harvest data, nutrients in soil and fertilizer efficiently. Models for soil and harvest variability are also defined. A personalized plugin for precision agriculture was developed into QGIS software, there is the option of upload maps to a Web and mobile app using the Desktop software an... R. Cuitiva baracaldo, O. Munar vivas, G. Carrillo romero |
10. Experiences in the Development of Commercial Web-Based Data Engines to Support UK Growers Within an Industry-Academic PartnershipThe lifecycle of Precision Agriculture data begins the moment that the measurement is taken, after which it may pass through each multiple data processes until finally arriving as an output employed back in the production system. This flow can be hindered by the fact that many farm datasets have different spatial resolutions. This makes the process to aggregate or analyse multiple Precision Agriculture layers arduous and time consuming. Precision Decisions Ltd located in Yorks... J. Taylor, Y. Shahar, P. James, C. Blacker, S. Leese, R. Sanderson, R. Kavanagh |