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Desertification in the south Junggar Basin, 2000-2009: Part Ⅱ. Model development and trend analysis

机译:准Jung尔盆地南部的荒漠化,2000-2009年:第二部分。模型开发和趋势分析

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The substantial objective of desertification monitoring is to derive its development trend, which facilitates pre-making policies to handle its potential influences. Aiming at this extreme goal, previous studies have proposed a large number of remote sensing (RS) based methods to retrieve multifold indicators, as reviewed in Part I. However, most of these indicators individually capable of characterizing a single aspect of land attributes, e.g., albedo quantifying land surface reflectivity, cannot show a full picture of desertification processes; few comprehensive RS-based models have either been published. To fill this gap, this Part II was dedicated to developing a RS information model for comprehensively characterizing the desertification and deriving its trend, based on the indicators retrieved in Part I in the same case of the south Junggar Basin, China in the last decade (2000-2009). The proposed model was designed to have three dominant component modules, i.e., the vegetation-relevant sub-model, the soil-relevant sub-model, and the water-relevant sub-model, which synthesize all of the retrieved indicators to integrally reflect the processes of desertification; based on the model-output indices, the desertification trends were derived using the least absolute deviation fitting algorithm. Tests indicated that the proposed model did work and the study area showed different development tendencies for different desertification levels. Overall, this Part II established a new comprehensive RS information model for desertification risk assessment and its trend deriving, and the whole study comprising Part I and Part II advanced a relatively standard framework for RS-based desertification monitoring. (C) 2018 COSPAR. Published by Elsevier Ltd. All rights reserved.
机译:荒漠化监测的主要目标是得出其发展趋势,这有助于制定政策来处理其潜在影响。针对这一极端目标,先前的研究提出了许多基于遥感(RS)的方法来检索多重指标,如第一部分所述。但是,这些指标中的大多数能够单独表征土地属性的一个方面,例如,反照率量化了地表反射率,无法显示出荒漠化过程的全貌;很少有基于RS的综合模型发表。为了填补这一空白,第二部分致力于根据过去十年中在中国准Jung尔盆地南部同一案例中从第一部分中获得的指标,来开发一种RS信息模型,以全面表征荒漠化及其趋势。 2000-2009)。所提出的模型被设计为具有三个主要组成模块,即与植被有关的子模型,与土壤有关的子模型和与水有关的子模型,它们综合了所有检索到的指标以完整地反映出荒漠化进程;基于模型输出指标,使用最小绝对偏差拟合算法推导了荒漠化趋势。试验表明,该模型确实有效,研究区域针对不同荒漠化程度显示了不同的发展趋势。总的来说,第二部分建立了一个新的综合RS信息模型,用于荒漠化风险评估及其趋势推导,整个研究包括第一部分和第二部分,为基于RS的荒漠化监测提供了一个相对标准的框架。 (C)2018年COSPAR。由Elsevier Ltd.出版。保留所有权利。

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