Land Degradation Vulnerability in Central India: A Multidimensional Assessment Using Biophysical and Socioeconomic Indicators

IF 3.7 2区 农林科学 Q2 ENVIRONMENTAL SCIENCES
Amit Kumar, Gowtham Govindaraj, Muthu Rajkumar, T. Mohanasundari
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Abstract

Land degradation poses a significant environmental challenge to ecological sustainability and rural livelihoods, especially in the central Indian state of Madhya Pradesh. This study used a multidimensional approach by integrating biophysical and socioeconomic indicators under six dimensions: soil, climate, terrain, land use, hazards, and socioeconomic conditions. All variables were normalised using a min-max method and combined through an equal-weight composite index to maintain consistency and avoid subjective bias for creating the district-level land degradation vulnerability index (LDVI). Spatial statistical validation was conducted using Spatial Autocorrelation (Global Moran's I) and Hot Spot Analysis (Local Getis-Ord Gi*). The LDVI findings demonstrated a strong spatial pattern, with western and southwestern districts showing consistently high vulnerability across multiple indices. Districts such as Barwani (0.728), Alirajpur (0.655), Jhabua (0.587), and Dhar (0.578) ranked among the most vulnerable, mainly due to high soil erosion, greater exposure to climate hazards, and agricultural dependence. However, districts like Datia (0.283), Bhind (0.320), and Tikamgarh (0.337) were categorised as lowest vulnerability, benefiting from relatively stable terrain, lower hazard exposure, better vegetation cover, and moderate socioeconomic stress. The LDVI showed a significant clustered pattern across districts (Moran's I = 0.612). The Local Getis-Ord Gi* analysis identified statistically significant hotspot districts in western Madhya Pradesh and cold spot clusters in the northern region, supporting the spatial consistency and reliability of the index. These findings identify priority districts for targeted soil conservation, climate adaptation, watershed management, and livelihood support, offering a replicable, policy-relevant LDVI framework that supports evidence-based land restoration efforts and advances India's progress toward SDG-15.
印度中部土地退化脆弱性:使用生物物理和社会经济指标的多维评估
土地退化对生态可持续性和农村生计构成了重大的环境挑战,特别是在印度中部的中央邦。本研究采用了多维度方法,在土壤、气候、地形、土地利用、灾害和社会经济条件六个维度下整合了生物物理和社会经济指标。采用最小-最大归一化方法对所有变量进行归一化,并通过等权重复合指数进行组合,以保持一致性,避免在创建区级土地退化脆弱性指数(LDVI)时出现主观偏差。采用空间自相关(Global Moran’s I)和热点分析(Local Getis-Ord Gi*)进行空间统计验证。LDVI结果显示出较强的空间格局,西部和西南部地区在多个指数中均表现出较高的脆弱性。Barwani(0.728)、Alirajpur(0.655)、Jhabua(0.587)和Dhar(0.578)等地区位居最脆弱地区之列,主要原因是土壤侵蚀严重、气候灾害暴露程度较高以及对农业的依赖。然而,Datia(0.283)、bind(0.320)和Tikamgarh(0.337)等地区被归为脆弱性最低的地区,受益于相对稳定的地形、较低的灾害暴露、较好的植被覆盖和适度的社会经济压力。区域间LDVI呈显著聚集型(Moran’s I = 0.612)。Local Getis-Ord Gi*分析发现,中央邦西部的热点地区和北部地区的冷点集群具有统计学意义,支持了该指数的空间一致性和可靠性。这些研究结果确定了有针对性的土壤保持、气候适应、流域管理和生计支持的优先地区,提供了一个可复制的、与政策相关的LDVI框架,支持基于证据的土地恢复工作,并推动印度在实现可持续发展目标15方面取得进展。
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来源期刊
Land Degradation & Development
Land Degradation & Development 农林科学-环境科学
CiteScore
7.70
自引率
8.50%
发文量
379
审稿时长
5.5 months
期刊介绍: Land Degradation & Development is an international journal which seeks to promote rational study of the recognition, monitoring, control and rehabilitation of degradation in terrestrial environments. The journal focuses on: - what land degradation is; - what causes land degradation; - the impacts of land degradation - the scale of land degradation; - the history, current status or future trends of land degradation; - avoidance, mitigation and control of land degradation; - remedial actions to rehabilitate or restore degraded land; - sustainable land management.
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