基于多源数据融合产品的黄河中游多沙粗沙区耕地时空动态变化

李舒畅; 郭正; 张风宝; 罗佳茹; 李玄添; 申楠; 杨明义

doi:10.13870/j.cnki.stbcxb.2024.05.005

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基于多源数据融合产品的黄河中游多沙粗沙区耕地时空动态变化

更新时间：2025-02-18

- 基于多源数据融合产品的黄河中游多沙粗沙区耕地时空动态变化
- Spatiotemporal Dynamic Changes of Cropland in Rich and Coarse Sediment Areas of Middle Yellow River Basin Based on Multi-source Data Fusion Products
- 水土保持学报 2024年38卷第5期页码：139-150
- 作者机构：
  
  1. 西北农林科技大学水土保持科学与工程学院黄土高原土壤侵蚀与旱地农业国家重点实验室, 陕西杨凌,712100
  2. 中国科学院水利部水土保持研究所, 陕西杨凌,712100
- 作者简介：
  
  [ "李舒畅(1998—),女,硕士研究生,主要从事GIS应用与土地资源研究。E-mail:lishuchang21@163.com" ]
- 基金信息：
  
  国家重点研发计划项目(2022YFF1300805);国家自然科学基金项目(U22A20613,42361144707,42077071);中央高校基本科研业务费专项(2023HHZX001)
- DOI：10.13870/j.cnki.stbcxb.2024.05.005
  中图分类号： TP79
- 纸质出版：2024
- 稿件说明：
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李舒畅, 郭正, 张风宝, 等. 基于多源数据融合产品的黄河中游多沙粗沙区耕地时空动态变化[J]. 水土保持学报, 2024,38(5):139-150.

LI Shuchang, GUO Zheng, ZHANG Fengbao, et al. Spatiotemporal Dynamic Changes of Cropland in Rich and Coarse Sediment Areas of Middle Yellow River Basin Based on Multi-source Data Fusion Products[J]. 2024, 38(5): 139-150.
李舒畅, 郭正, 张风宝, 等. 基于多源数据融合产品的黄河中游多沙粗沙区耕地时空动态变化[J]. 水土保持学报, 2024,38(5):139-150. DOI： 10.13870/j.cnki.stbcxb.2024.05.005.

LI Shuchang, GUO Zheng, ZHANG Fengbao, et al. Spatiotemporal Dynamic Changes of Cropland in Rich and Coarse Sediment Areas of Middle Yellow River Basin Based on Multi-source Data Fusion Products[J]. 2024, 38(5): 139-150. DOI： 10.13870/j.cnki.stbcxb.2024.05.005.

摘要

[目的] 黄河中游多沙粗沙区是我国典型的生态脆弱区

准确量化该区耕地时空动态变化对评估区域粮食安全、生态修复效益、水土流失状况及黄河下游安澜等都具有重要意义。[方法] 基于5种30 m高分辨率土地利用/覆被数据集产品(CNLUCC、GLC_FCS30、CLCD、AGLC-2000-2015、GlobeLand30)

运用耕地利用动态度、偏差系数、转移矩阵、空间一致性分析等方法对比分析多源产品耕地在多沙粗沙区的时空特征

形成30 m分辨率高精度融合数据集产品

并对其进行验证

在此基础上基于融合产品分析1990—2020年黄河中游多沙粗沙区耕地的数量、分布、结构特征。[结果] 现有多源数据集产品之间耕地特征存在较大差异

而融合产品精度均优于单独使用5种现有产品。基于融合产品分析发现

1990—2020年耕地面积呈先增加后波动式降低的趋势

退耕还林(草)工程实施为分界线;1990—2020年耕地面积净减少3 170.59 km2

减少17.63%

且＞15°的坡耕地面积占比逐年减少;耕地的动态转移类型主要为草地

其次为人工地表。退耕还林(草)等生态工程的实施和城镇化建设是导致耕地减少的主要原因。[结论] 综合分析多源产品的优劣

基于目标地类融合和解释多源数据探究的有效方法

以深入研究某区域的地类特征

从而获得更为精确的研究结论。

Abstract

[Objective] The rich and coarse sediment areas of middle Yellow River basin is a typical ecologically fragile area in China. Accurately quantifying the spatiotemporal dynamic changes of cropland in this region is crucial for evaluating regional food security

ecological restoration benefits

soil erosion conditions

and the downstream tranquility of the Yellow River. [Methods] Based on five high-resolution (30 m) land use/cover dataset products (CNLUCC

GLC_FCS30

CLCD

AGLC-2000-2015

GlobeLand30)

this study employed methods such as cropland dynamic degree

deviation coefficient

transfer matrix

and spatial consistency analysis to comparatively analyze the spatiotemporal characteristics of cropland in the rich and coarse sediment areas. A high-precision fused dataset with a 30 m resolution was formed and validated. Based on this fused product

an analysis of the quantity

distribution

and structural characteristics of cropland in rich and coarse sediment areas of middle Yellow River basin in 1990—2020 years was conducted. [Results] There are significant differences in cropland characteristics among existing multi-source dataset products

with the fused products demonstrating higher accuracy compared to using any of the five existing products individually. Analysis based on the fused products reveals a trend of initially increasing followed by fluctuating decline in cropland area in 1990—2020

with the implementation of the Grain for Green project serving as a turning point. In 1990—2020

there has been a net decrease of 3 170.59 km2 in cropland area

representing a reduction of 17.63%. Furthermore

the proportion of cropland with slopes greater than 15° has been decreasing annually. The main types of dynamic transfer of cropland are into grassland

followed by artificial surfaces. The implementation of ecological projects such as the Grain for Green program

along with urbanization construction

is the primary cause of the decrease in cropland. [Conclusion] Researchers are encouraged to comprehensively analyze the strengths and weaknesses of multi-source products based on their research objectives. Exploring effective methods for fusing and interpreting multi-source data

with a focus on target land classes

can lead to a more in-depth understanding of the land characteristics in a specific region and

consequently

more precise research conclusions.

关键词

Keywords

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