基于地块级时序遥感的喀斯特石漠化地区撂荒地时空演变

王玲玉; 周忠发; 赵馨; 孔杰; 张淑

doi:10.13870/j.cnki.stbcxb.2020.01.014

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基于地块级时序遥感的喀斯特石漠化地区撂荒地时空演变

更新时间：2025-03-12

- 基于地块级时序遥感的喀斯特石漠化地区撂荒地时空演变
- Spatiotemporal Evolution of Karst Rocky Desertification Abandoned Cropland Based on Farmland-parcels Time-series Remote Sensing
- 水土保持学报 2020年34卷第1期页码：92-99
- 作者机构：
  
  1. 贵州师范大学喀斯特研究院,贵阳,550001
  2. 贵州师范大学地理与环境科学学院,贵阳,550001
- 作者简介：
- 基金信息：
  
  国家自然科学基金地区项目（41661088）贵州省高层次创新型人才培养计划——"百"层次人才项目（黔科合平台人才〔2016〕5674）贵州省石漠化耕地调查、五千亩以上坝区耕地调查专题研究项目（GTGHY2018）
- DOI：10.13870/j.cnki.stbcxb.2020.01.014
  中图分类号： TP79
- 纸质出版：2020
- 稿件说明：
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王玲玉, 周忠发, 赵馨, 等. 基于地块级时序遥感的喀斯特石漠化地区撂荒地时空演变[J]. 水土保持学报, 2020,34(1):92-99.

WANG Lingyu, ZHOU Zhongfa, ZHAO Xin, et al. Spatiotemporal Evolution of Karst Rocky Desertification Abandoned Cropland Based on Farmland-parcels Time-series Remote Sensing[J]. 2020, 34(1): 92-99.
王玲玉, 周忠发, 赵馨, 等. 基于地块级时序遥感的喀斯特石漠化地区撂荒地时空演变[J]. 水土保持学报, 2020,34(1):92-99. DOI： 10.13870/j.cnki.stbcxb.2020.01.014.

WANG Lingyu, ZHOU Zhongfa, ZHAO Xin, et al. Spatiotemporal Evolution of Karst Rocky Desertification Abandoned Cropland Based on Farmland-parcels Time-series Remote Sensing[J]. 2020, 34(1): 92-99. DOI： 10.13870/j.cnki.stbcxb.2020.01.014.

摘要

撂荒地在全球呈扩散趋势，传统的调查方法已无法满足及时、精确掌握撂荒情况的需求。针对喀斯特石漠化耕地的撂荒因光学影像的不足和严重的混合像元不易精确识别和提取，以贵州省息烽县为例，运用高精度影像精确识别提取耕地地块，再叠加通过MVC方法计算Landsat数据得到的2003—2018年时序NDVI数据，得到撂荒和复垦时空分布。结果表明：（1）地块和时序NDVI组合能够精准地识别提取撂荒地，该方法对于光学数据缺乏的和耕地破碎的多云雨山区有很好的适用效果；（2）2003—2018年息烽县撂荒地呈随机散点状分布，主要分布在有岩石裸露潜在、轻度、中度石漠化地区，2008年撂荒面积最大2 545.6 hm2，撂荒率最高7.7%；有7块耕地持续撂荒时间最长12年，有8块地累计撂荒最多15年。（3）2003—2018年息烽县复垦率与撂荒率波动趋势基本-致，复垦率的响应延后1年，较高的石漠化等级负面影响复垦行为。研究结果为喀斯特多云雨山区撂荒地的精准识别提取提供高效、可行的思路和方法，为撂荒地的驱动因子分析、趋势监测和风险评价、效应评估及政策设计提供精确的基础数据。

Abstract

The abandoned cropland is spreading widely all over the world. Traditional survey methods can not meet the need of timely and accurate grasp of abandoned cropland. In view of the insufficiency of optical remote sensing images

and that it is difficult to accurately identify and extract the abandoned cropland in karst rocky desertification land from the serious mixed pixels

taking Xifeng County of Guizhou Province as an example

the high-resolution image and rocky desertification grade data were used to identify and extract different rocky desertification grade cultivated land plots. The time series NDVI data of 2003-2018 obtained by calculating the Landsat data by MVC method was superimposed

and the spatial and temporal distribution of the abandoned cropland and reclamation in Xifeng County in 2003-2018 was extracted. The results showed:(1) The combination of cultivated land plot and time series NDVI could accurately identify and extract abandoned cropland. This method had a good application in the area lacking of optical data and the cloudy rainy mountain area where the cultivated land is broken. (2) In 2003-2018

the abandoned cropland in Xifeng County was randomly scattered and mainly distributed in the potential

mild and moderate rocky desertification area in the north and east. In 2008

the largest abandoned area was 2 545.6 hm2 and the highest rate of abandonment was 7.7%. In the period of 2003-2018

there were 7 plots of abandoned land that lasted for a maximum of 12 years

and 8 plots accumulated for up to 15 years. (3) In 2003-2018

the reclamation rate of Xifeng County was basically consistent with the fluctuation trend of the abandonment rate

but the response to the reclamation rate was delayed by one year. There was a certain difference between the non-karst cultivated land reclamation behavior and the rocky desertification cultivated land reclamation behavior. The higher rock desertification grade negatively affected the reclamation behavior. The research results could provide an efficient and feasible idea and method for the accurate identification and extraction of abandoned cropland in karst cloudy and rainy mountainous areas

also provide the accurate and basic data for driving factor analysis

trend monitoring and risk assessment

effect assessment and policy design in abandoned cropland.

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