首页> 外文会议>Workshop on Hyperspectral Image and Signal Processing: Evolution in Remote Sensing >Mapping Crop Variability Related to Soil Quality and Crop Stress Within Rainfed Mediterranean Agroecosystems Using Hyperspectral Data
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Mapping Crop Variability Related to Soil Quality and Crop Stress Within Rainfed Mediterranean Agroecosystems Using Hyperspectral Data

机译:使用高光谱数据映射与雨量地中海农业系统内的土壤质量和作物压力相关的作物可变性

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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:培养和土地利用实践在地中海地区历史悠久,利用土壤作为自然资源。土壤是有助于农业生产雨量作物,如谷物,橄榄树林和葡萄园。管理不足正在危及土壤质量和生产力,而作出作物质量和生产率受到影响。该项目的主要目标是将土壤和作物可变性映射到地中海环境中的作物压力和土地管理,基于可见的,近红外,短波红外和热红外线(0.4-12)的高光谱数据(0.4-12 mu { mathrm {m}})$。为此,我们使用CASI和AHS高光谱图像在西班牙中部的Camarena农业领域的生长季节获得,其特点是地中海气候,延长农业雨量用途,大多数发展的土壤和与对比土壤视野相关的侵蚀特征。同时到空中运动,发生了一个密集的野外运动,以进行土壤和作物变异性,包括化学和生物物理变量,土壤退化阶段和选定试验部位的作物生产。在本文中,我们专注于光学VNir-SWIR光谱域,目前的项目目标,选定的领域和空中数据,以及初步分析,在这种地中海农业体系受土壤退化影响的情况下,土壤质量对作物变异性的强烈影响基于高光谱图像的生产和产量数据。

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