动荡中的景观:印度梅迪尼普尔沿海平原咸水养殖十多年发展轨迹的特点

Mrinmoyee Naskar, S. Neogy, Asit Kumar Roy, Debajit Datta
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引用次数: 0

摘要

本研究主要通过应用地理统计、景观度量和地理空间技术,评估印度普尔巴梅迪尼布尔沿海地区沿海咸水养殖(CBA)的时空增长轨迹及其对周边环境的潜在影响。研究考虑了三个社区发展(CD)区块,即 Contai-I、Deshapran 和 Ramnagar-II,以分析 CBA 地区的增长模式。评估年份(1991 年、2001 年、2011 年、2021 年和 2023 年)的陆地卫星数据集用于绘制土地利用/土地覆被 (LULC) 地图,并得出该地区相关的斑块和等级景观指标。这使得整个研究区域的 CBA 农场在空间上高度分散且不成体系。此外,还通过空间自相关性分析,分析了人口普查村的 CBA 增长模式。结果表明,在过去三十年中,CBA 一直在持续增长,但由于疾病频发、生产成本上升以及市场价格急剧下降,CBA 出现了急剧下降。使用细胞自动机和人工神经网络(CA-ANN)模型预测了 2025 年 CBA 的增长和/或衰退性质。经过仔细校准和验证,该模型预测 CBA 面积将进一步缩小,废弃水产养殖将继续扩大。因此,为有效监测这些高度脆弱的热带生态系统,提出了生态上可行的生计替代方案和环境上可持续的管理措施。
本文章由计算机程序翻译,如有差异,请以英文原文为准。
A landscape in turmoil: characterizing the multi-decadal growth trajectory of brackishwater aquaculture in Medinipur Coastal Plain, India
The spatio-temporal growth trajectory of coastal brackishwater aquaculture (CBA) in the coastal tracts of Purba Medinipur, India and its impending repercussions on the immediate environs, was primarily assessed in this study through application of geostatistics, landscape metrics, and geospatial technologies. Three Community Development (CD) Blocks, namely, Contai-I, Deshapran, and Ramnagar-II were considered to analyze the growth pattern of the area under CBA. Landsat datasets of the assessment years (1991, 2001, 2011, 2021, and 2023) were used to prepare the land use/ land cover (LULC) maps and to derive pertinent landscape metrics of patch and class levels for this region. This brought forward a highly fragmented and dispersive spatial concentration of the CBA farms in the entire study area. Additionally, Census Village-wise growth pattern of CBA was analyzed by conducting a spatial autocorrelation analysis which depicted prominent clustering of villages with a higher concentration of CBA. Results showed that there has been an incessant growth of CBA in the last three decades, however, a sharp drop has been recorded owing to recurrent bouts of diseases, swelling production costs, and a sharp drop-in market rate. The nature of growth and/ or decay of the CBA was predicted for the year 2025 using Cellular Automata and Artificial Neural Network (CA-ANN) model. After careful calibration and validation, the model projected further lessening of the CBA area along with a continued expansion of abandoned aquaculture. Accordingly, ecologically viable livelihood alternatives and environmentally sustainable management measures were suggested for the efficient monitoring of these highly fragile tropical ecosystems.
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