Proceedings
Authors
| Filter results4 paper(s) found. |
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1. CropSAT - a Public Satellite-based Decision Support System for Variable-rate Nitrogen Fertilization in ScandinaviaCropSAT is a free-to-use web application for satellite-based production of variable-rate application (VRA) files of e.g. nitrogen (N) and fungicides currently available in Sweden and Denmark. Even in areas frequently covered by clouds, vegetation index maps from data derived from low-cost or freely available optical satellites can be used in practice as a cost-efficient tool in time-critical applications such as optimized nitrogen use. During the very cloudy year 2015, or more useable images... M. Söderström, H. Stadig, J. Martinsson, M. Stenberg, K. Piikki |
2. The New Digital Soil Map of Sweden -Derived for Free Use in Precision AgricultureThe Digital Soil Map of Sweden (DSMS) was finalized in 2015. The present paper describes the mapping strategy, the estimated uncertainty of the primary map layers and its potential use in precision agriculture. The DSMS is a geodatabase with information on the topsoil of the arable land in Sweden. The spatial resolution is 50 m × 50 m and it covers > 90% of the arable land of the country (~2.5 million ha). Non-agriculture land and areas with organic soil are excluded. Access to a number... K. Piikki, M. Söderström |
3. Micro-climate Prediction System Using IoT Data and AutoMLMicroclimate variables like temperature, humidity are sensitive to land surface properties and land-atmosphere connections. They can vary over short distances and even between sections of the farm. Getting the accurate microclimate around the crop canopy allows farmers to effectively manage crop growth. However, most of the weather forecast services available to farmers globally, either by the meteorological department or universities or some weather app, provide weather forecasts for larger... A. Sharma, R.S. Jalem, M. Dash |
4. Cloud Correction of Sentinel-2 NDVI Using S2cloudless PackageOptical satellite-derived Normalized Difference Vegetation Index (NDVI) is by far the most commonly used vegetation index value for crop monitoring. However, it is quite sensitive to the cloud, and cloud shadows and significantly decreases its usability, especially in agricultural applications. Therefore, an accurate and reliable cloud correction method is mandatory for its effective application. To address this issue, we have developed an approach to correct the NDVI values of each and every... A. Saxena, M. Dash, A.P. Verma |