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Mapping Crop Variability Related to Soil Quality and Crop Stress Within Rainfed Mediterranean Agroecosystems Using Hyperspectral Data

机译:使用高光谱数据绘制与旱作地中海农业生态系统内与土壤质量和作物胁迫相关的作物变异性

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Cultivation and land use practices have a long history within the Mediterranean region exploiting soils as a natural resource. The soils are an essential factor contributing to agricultural production of rainfed crops such as cereals, olive groves and vineyards. Inadequate management is endangering soil quality and productivity, and in turn crop quality and productivity are affected. The main objective of this project is to map soil and crop variability related to crop stress and land management within a Mediterranean environment based on hyperspectral data within the visible, near-infrared, short-wave infrared as well as thermal infrared $(0.4-12 mu{mathrm {m}})$. For this, we use CASI and AHS hyperspectral imagery acquired during the growing season within the Camarena agricultural area in central Spain, characterized by Mediterranean climate, extended agricultural rainfed uses, mostly evolved soils, and erosion features associated to contrasting soil horizons. Simultaneous to the airborne campaign, an intensive field campaign took place for the characterization of soil and crop variability including chemical and biophysical variables, soil degradation stages, and crop production in selected test sites. In this paper, we focus on the optical VNIR-SWIR spectral domain and present project objectives, selected field and airborne data, and preliminary analyses that show, in this Mediterranean agroecosystem affected by soil degradation, the strong influence of soil quality on crop variability and production based on hyperspectral imagery and yield data.
机译:在地中海地区,利用土壤作为自然资源进行耕种和土地使用已有很长的历史。土壤是促进雨养作物如谷物,橄榄树和葡萄园的农业生产的重要因素。管理不善正威胁着土壤质量和生产力,进而影响了作物质量和生产力。该项目的主要目的是基于可见,近红外,短波红外以及热红外$(0.4-12 \ mu {\ mathrm {m}})$。为此,我们使用在西班牙中部卡马雷纳农业区生长季节内获得的CASI和AHS高光谱图像,其特征是地中海气候,农业雨养用途扩展,土壤大多为改良土壤以及与土壤层对比形成对比的侵蚀特征。与空运活动同时,进行了密集的野外活动,以表征土壤和农作物的变异性,包括化学和生物物理变量,土壤退化阶段以及选定测试地点的农作物产量。在本文中,我们着眼于光学VNIR-SWIR光谱域,并介绍了项目目标,选定的田间数据和机载数据,以及初步分析表明,在这个受到土壤退化影响的地中海农业生态系统中,土壤质量对作物变异性和基于高光谱图像和产量数据的生产。

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