- 标题
- 摘要
- 关键词
- 实验方案
- 产品
-
[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Dense Fully Convolutional Networks for Crop Recognition from Multitemporal SAR Image Sequences
摘要： This work presents a dense fully convolutional architecture for crop type recognition from multitemporal RS images. Basically, we adapted a dense fully convolutional net to deal with stacks of multitemporal data. The proposed approach was tested upon a public dataset comprising two Sentinel-1A sequences from a tropical region in South America. We took as baseline a dense convolutional network designed for patch classification. Thematic and spatial accuracy, as well as the computational load were evaluated experimentally. The proposed architecture matched the baseline in terms of recognition rates and proved to be very efficient computationally in the inference phase.
关键词： crop type classification,Deep Learning,fully convolutional networks,SAR,multitemporal analysis
更新于2025-09-09 09:28:46
-
Assessing the Reliability of Thermal and Optical Imaging Techniques for Detecting Crop Water Status under Different Nitrogen Levels
摘要： Efficient management of irrigation water is fundamental in agriculture to reduce the environmental impacts and to increase the sustainability of crop production. The availability of adequate tools and methodologies to easily identify the crop water status in operating conditions is therefore crucial. This work aimed to assess the reliability of indices derived from imaging techniques—thermal indices (Ig (stomatal conductance index) and CWSI (Crop Water Stress Index)) and optical indices (NDVI (Normalized Difference Vegetation Index) and PRI (Photochemical Reflectance Index))—as operational tools to detect the crop water status, regardless the eventual presence of nitrogen stress. In particular, two separate experiments were carried out in a greenhouse, on two spinach varieties (Verdi F1 and SV2157VB), with different microclimatic conditions and under different levels of water and nitrogen application. Statistical analysis based on ANOVA test was carried out to assess the independence of thermal and optical indices from the crop nitrogen status. These imaging indices were successively compared through correlation analysis with reference destructive and non-destructive measurements of crop water status (stomatal conductance, chlorophyll a fluorescence, and leaf and soil water content), and linear regression models of thermal and optical indices versus reference measurements were calibrated. All models were significant (Fisher p-value lower than 0.05), and the highest R2 values (greater than 0.6) were found for the regression models between CWSI and the soil water content, NDVI and the leaf water content, and PRI and the stomatal conductance. Further analysis showed that imaging indices acquired by thermal cameras (especially CWSI) can be used as operational tools to detect the crop water status, since no dependence on plant nitrogen conditions was observed, even when the soil water depletion was very limited. Our results confirmed that imaging indices such as CWSI, NDVI and PRI can be used as operational tools to predict soil water status and to detect drought stress under different soil nitrogen conditions.
关键词： crop water status,crop water stress prediction,optical imaging sensor,thermal camera,spectral imaging index
更新于2025-09-04 15:30:14
-
[IEEE IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Valencia, Spain (2018.7.22-2018.7.27)] IGARSS 2018 - 2018 IEEE International Geoscience and Remote Sensing Symposium - Crop Lodging Analysis from Uas Orthophoto Mosaic, Sentinel-2 Image and Crop Yield Monitor Data
摘要： Crop lodging is surveyed from different image sources and from the crop yield map. Crop lodging has effect on remotely sensed and field level measurements when indirectly measuring, for example, soil variation, nutrients, or crop condition. The interpretation of results may be incorrect especially in the case when it is not possible to detect lodging from the analyzed dataset. Such situation may arise, for example, when analyzing Sentinel-2 (S2) images or crop yield monitor data. In this study crop lodging is inspected from UAS-based orthophotomosaic taken 50 meters above the ground level, S2 image and crop yield monitor connected to a combine harvester.
关键词： orthophoto,Sentinel-2,UAS,crop yield monitor,precision agriculture,lodging
更新于2025-09-04 15:30:14
-
[Sustainable Energy Developments] Geothermal,Wind and Solar Energy Applications in Agriculture and Aquaculture || Chapter 7: Fundamentals of solar energy
摘要： Modern agricultural systems are characterized by the intensive and optimal use of land and water, turning agricultural exploitation into a semi-industrial concept. Greenhouses are systems suitable both for zones with unfavorable climatic conditions – allowing crop growth regardless of the ambient temperature – and for regions with less restrictive weather – with the aim of increasing crop productivity and improving fruit quality. In this context, a secure and environmentally friendly energy supply must be considered, for any power range or circumstance, including for stand-alone installations. Crop growth is primarily determined by climate and the amount of water and fertilizers applied through irrigation. Therefore, greenhouses are ideal for farming because they allow one to optimize these physical parameters, via the photosynthetic process (Ramírez-Arias et al., 2012), to enhance biomass production. This manipulation requires energy consumption, depending on the crop’s physiological requirements, and the production patterns adopted for yield quantity and timing. The present general concern on the development of more efficient and sustainable productive activities has increased interest in the evaluation of alternatives to the conventional energy sources in the sector; presently many are involved in processes for assessing the environmental feasibility and technological development of such alternatives (Antón et al., 2007; Bojacá et al., 2014; Martínez-Blanco et al., 2011; Page et al., 2012; Romero-Gámez et al., 2012; Torrellas et al., 2013; van der Werf et al., 2014). This work aims to provide an overview of the existing options for the integration of renewable sources in greenhouses located in semi-arid regions where, for example, the high availability of solar radiation facilitates its use for the fulfillment of a certain percentage of the heat and/or electricity loads of greenhouses. Accordingly, this overview contains the basic technological aspects of the main renewable technologies applicable in greenhouses, some simplified design tools and criteria for their selection. Finally, it includes a summary of selected experiences in this field. The main objective is to contribute to a better understanding of the technologies that should support the promotion and development of projects for the implementation of renewable energies in agriculture.
关键词： biomass,geothermal energy,wind energy,semi-arid climates,crop growth control,renewable energy,photovoltaic,greenhouses,energy efficiency,solar energy
更新于2025-09-04 15:30:14