Spatial correlation and impact mechanism analysis of cultivated land fragmentation and quality in the Central Plain of Liaoning Province, Northeast China

耕地 碎片(计算) 空间分布 中国 土地利用 地理 质量(理念) 共同空间格局 自然地理学 环境科学 生态学 统计 数学 遥感 生物 物理 考古 量子力学
作者
Ranran Pang,Huan Xu,Meiyu Zhang,Fengkui Qian
出处
期刊:Land Degradation & Development [Wiley]
卷期号:34 (15): 4623-4634 被引量:11
标识
DOI:10.1002/ldr.4797
摘要

Abstract Further exploration of the spatial correlation and mechanism of action between cultivated land fragmentation (CLF) and quality, which have guiding roles in improving cultivated land quality, is needed. However, the mechanism that determines how CLF affects quality has not yet been thoroughly investigated. The Central Plain of Liaoning Province was utilized as the research's study area, and the spatial autocorrelation analysis method was used to investigate the correlations between CLF and quality. The precise effects of different CLF indices on cultivated land quality have been specifically examined using the spatial error model (SEM). According to the findings, there is a “low in the west and high in the east” distribution tendency for CLF in the Central Plain area, and “high in the middle and low on both sides” for cultivated land quality. Furthermore, CLF and quality have a significant negative spatial link, with a correlation coefficient of −0.186. A rise in some CLF indices may enhance the difficulty of improving land quality. The quality of cultivated land declines by 0.275, 1.306, and 1.085 units for each unit rise in the number of patches (NP), edge density (ED), and aggregation index (AI) values, respectively. Therefore, it is possible to improve the degree of fragmentation of cultivated land according to local conditions, thereby improving the quality of cultivated land. The research results can provide a reference for achieving the trinity protection of cultivated land, in order to better improve the sustainability of cultivated land.

科研通智能强力驱动
Strongly Powered by AbleSci AI
科研通是完全免费的文献互助平台,具备全网最快的应助速度,最高的求助完成率。 对每一个文献求助,科研通都将尽心尽力,给求助人一个满意的交代。
实时播报
难过龙猫发布了新的文献求助10
1秒前
ym发布了新的文献求助10
1秒前
华仔应助蟹鱼橙子采纳,获得10
1秒前
1秒前
123完成签到,获得积分10
1秒前
澜冰完成签到,获得积分10
2秒前
2秒前
2秒前
科研通AI6.2应助0812采纳,获得10
2秒前
3秒前
3秒前
852应助iiiorange采纳,获得10
4秒前
爆米花应助大佬采纳,获得10
4秒前
傲娇谷秋发布了新的文献求助10
4秒前
肉脸小鱼发布了新的文献求助10
5秒前
5秒前
王大侠关注了科研通微信公众号
5秒前
赘婿应助张靖松采纳,获得10
6秒前
东南方应助kiyo采纳,获得10
7秒前
东南方应助kiyo采纳,获得10
7秒前
7秒前
逸尘发布了新的文献求助10
8秒前
隐形曼青应助潇洒寒烟采纳,获得10
8秒前
10秒前
顾矜应助hyodong采纳,获得10
10秒前
我是老大应助山屿采纳,获得10
11秒前
小蘑菇应助dl采纳,获得10
11秒前
12秒前
BowieHuang应助曾经的凌青采纳,获得10
12秒前
刘十三发布了新的文献求助10
13秒前
13秒前
14秒前
14秒前
家欣发布了新的文献求助10
16秒前
111发布了新的文献求助10
16秒前
张靖松发布了新的文献求助10
17秒前
雨村完成签到,获得积分10
17秒前
妥妥酱发布了新的文献求助10
17秒前
FashionBoy应助火星上的海亦采纳,获得10
17秒前
MchemG应助DrWho1985采纳,获得10
18秒前
高分求助中
(应助此贴封号)【重要!!请各用户(尤其是新用户)详细阅读】【科研通的精品贴汇总】 10000
Kinesiophobia : a new view of chronic pain behavior 2000
Research for Social Workers 1000
Mastering New Drug Applications: A Step-by-Step Guide (Mastering the FDA Approval Process Book 1) 800
The Social Psychology of Citizenship 600
Signals, Systems, and Signal Processing 510
Discrete-Time Signals and Systems 510
热门求助领域 (近24小时)
化学 材料科学 生物 医学 工程类 计算机科学 有机化学 物理 生物化学 纳米技术 复合材料 内科学 化学工程 人工智能 催化作用 遗传学 数学 基因 量子力学 物理化学
热门帖子
关注 科研通微信公众号,转发送积分 5912187
求助须知:如何正确求助?哪些是违规求助? 6831436
关于积分的说明 15785215
捐赠科研通 5037204
什么是DOI,文献DOI怎么找? 2711599
邀请新用户注册赠送积分活动 1661950
关于科研通互助平台的介绍 1603905