Above Ground Biomass Estimation for Alpine Grasslands of Kashmir Himalayas Using Remote Sensing and Field-Data

IF 2.4 3区 环境科学与生态学 Q2 ECOLOGY Rangeland Ecology & Management Pub Date : 2024-07-17 DOI:10.1016/j.rama.2024.06.001
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Abstract

This study presents a comprehensive analysis of Alpine pastures in the Kashmir Himalayas through a multidisciplinary approach, combining remote sensing and field-based assessments for biomass estimation and time series analysis of the (NDVI) Index for the growing season from May to October 2022. The Alpine and Subalpine region of Kashmir was delineated using ALOS PALSAR Digital Elevation Model, and Landsat 8 imagery was classified using a maximum likelihood algorithm, revealing a total grassland area of 160,974 hectares. After grassland delineation Biomass estimation was carried out based on data collected from 18 pastures, each of which was subjected to a stratified sampling approach to establish four 1 m² quadrats, with two designated for grazed areas and two for ungrazed areas, this yielded average biomass yields of 20.87 t/ha and an average dry weight biomass of 5.16 t/ha. Pastures like Daksum (28.36 t/ha), Tragbal (28.22 t/ha), Krush (27.83 t/ha), Lung Marg (27.03 t/ha), observed high biomass availability, while moderate levels were found in locations like Gangbal (22.75 t/ha), Hangel Marg (22.68 t/ha), Dagwan (21.76 t/ha), Gumri (20.82 t/ha), Bangus (20.66 t/ha), Pir Galli (18.52t/ha), Maalish (18.21 t/ha), In contrast, lower biomass values were recorded in Mohand Marg (11.47 t/ha), and Thajwas (9.81 t/ha). These findings were complemented by (NDVI) metrics, which varied across sites. For example, high NDVI values were observed for sites such as Pir Gilli, Bangus, and Kud Marg, indicating a healthier vegetative profile with less impact of grazing during the grazing season. In contrast, pastures like Mohand Marg, Thajwas, Razdan, and Tragbal recorded moderate NDVI values, suggesting a moderate level of grazing impact. Pasture sites with lower NDVI values and high standard deviation, such as Hangel Marg and Gumari, witnessed high seasonal variability, suggesting a high grazing impact, besides other natural factors responsible, like early snowfall. The study emphasizes the need for ongoing, multifaceted ecological assessments for the sustainable management and conservation of these critical Alpine ecosystems.

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利用遥感和实地数据估算克什米尔喜马拉雅山高山草地的地面生物量
本研究采用多学科方法对克什米尔喜马拉雅山脉的高山牧场进行了全面分析,结合遥感和实地评估,对 2022 年 5 月至 10 月生长季节的生物量进行了估算,并对(NDVI)指数进行了时间序列分析。利用 ALOS PALSAR 数字高程模型对克什米尔的高山和亚高山地区进行了划分,并利用最大似然算法对 Landsat 8 图像进行了分类,结果显示草原总面积为 160,974 公顷。草场划定后,根据从 18 个牧场收集的数据进行了生物量估算,每个牧场都采用分层抽样法建立了四个 1 平方米的四分区,其中两个指定为放牧区,两个为非放牧区,得出的平均生物量产量为 20.87 吨/公顷,平均干重生物量为 5.16 吨/公顷。Daksum (28.36 吨/公顷)、Tragbal (28.22 吨/公顷)、Krush (27.83 吨/公顷)、Lung Marg (27.03 吨/公顷)等牧场的生物量较高,而 Gangbal (22.75 吨/公顷)、Hangel Marg (22.68 吨/公顷)、Dagwan(21.76 吨/公顷)、Gumri(20.82 吨/公顷)、Bangus(20.66 吨/公顷)、Pir Galli(18.52 吨/公顷)、Maalish(18.21 吨/公顷),相比之下,Mohand Marg(11.47 吨/公顷)和 Thajwas(9.81 吨/公顷)的生物量值较低。这些发现得到了(NDVI)指标的补充,不同地点的(NDVI)指标各不相同。例如,在 Pir Gilli、Bangus 和 Kud Marg 等地观察到的 NDVI 值较高,表明植被状况较好,放牧季节受放牧的影响较小。相比之下,Mohand Marg、Thajwas、Razdan 和 Tragbal 等牧场的归一化差异植被指数值适中,表明放牧影响程度适中。NDVI 值较低且标准偏差较高的牧场,如 Hangel Marg 和 Gumari,则具有较高的季节变化性,这表明除了其他自然因素(如早降雪)外,放牧的影响也很大。这项研究强调,有必要持续进行多方面的生态评估,以便对这些重要的阿尔卑斯生态系统进行可持续管理和保护。
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来源期刊
Rangeland Ecology & Management
Rangeland Ecology & Management 农林科学-环境科学
CiteScore
4.60
自引率
13.00%
发文量
87
审稿时长
12-24 weeks
期刊介绍: Rangeland Ecology & Management publishes all topics-including ecology, management, socioeconomic and policy-pertaining to global rangelands. The journal''s mission is to inform academics, ecosystem managers and policy makers of science-based information to promote sound rangeland stewardship. Author submissions are published in five manuscript categories: original research papers, high-profile forum topics, concept syntheses, as well as research and technical notes. Rangelands represent approximately 50% of the Earth''s land area and provision multiple ecosystem services for large human populations. This expansive and diverse land area functions as coupled human-ecological systems. Knowledge of both social and biophysical system components and their interactions represent the foundation for informed rangeland stewardship. Rangeland Ecology & Management uniquely integrates information from multiple system components to address current and pending challenges confronting global rangelands.
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