Abstract The advances achieved during the last 30 years demonstrate the aptitude of the remote sensing-based vegetation indices (VI) for the assessment of crop evapotranspiration (ETc) and irrigation requirements in a simple, robust and operative manner. The foundation of these methodologies is the well-established relationship between the VIs and the basal crop coefficient (Kcb), resulting from the ability of VIs to measure the radiation absorbed by the vegetation, as the main driver of the evapotranspiration process. In addition, VIs have been related with single crop coefficient (Kc), assuming constant rates of soil evaporation. The direct relationship between VIs and ET is conceptually incorrect due to the effect of the atmospheric demand on this relationship. The rising number of Earth Observation Satellites potentiates a data increase to feed the VI-based methodologies for estimating and mapping either the Kc or Kcb, with improved temporal coverage and spatial resolution. The development of operative platforms, including satellite constellations like Sentinels and drones, usable for the assessment of Kcb through VIs, opens new possibilities and challenges. This work analyzes some of the questions that remain inconclusive at scientific and operational level, including: (i) the diversity of the Kcb-VI relationships defined for different crops, (ii) the integration of Kcb-VI relationships in more complex models such as soil water balance, and (iii) the operational application of Kcb-VI relationships using virtual constellations of space and aerial platforms that allow combining data from two or more sensors.

中文翻译：

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遥感估算和制图单一和基础作物系数：光谱植被指数方法综述

摘要 过去 30 年取得的进展证明了基于遥感的植被指数 (VI) 以简单、稳健和可操作的方式评估作物蒸散量 (ETc) 和灌溉需求的能力。这些方法的基础是 VI 与基本作物系数 (Kcb) 之间已建立的关系，这是由于 VI 能够测量植被吸收的辐射，作为蒸发蒸腾过程的主要驱动因素。此外，假设土壤蒸发速率恒定，VI 与单一作物系数 (Kc) 相关。由于大气需求对这种关系的影响，VI 和 ET 之间的直接关系在概念上是不正确的。地球观测卫星数量的增加推动了数据的增加，以支持基于 VI 的方法来估计和绘制 Kc 或 Kcb，并提高时间覆盖范围和空间分辨率。可用于通过 VI 评估 Kcb 的操作平台（包括哨兵和无人机等卫星星座）的开发开辟了新的可能性和挑战。这项工作分析了一些在科学和操作层面仍然没有定论的问题，包括：(i) 为不同作物定义的 Kcb-VI 关系的多样性，(ii) Kcb-VI 关系在更复杂的模型中的整合，例如土壤水分平衡，