基于RapidEye影像的蚂蝗田小流域土壤侵蚀与岩溶石漠化分析

刘超群; 亢 庆; 邝高明; 王敬贵; 俞国松

doi:10.11932/karst20160514

基于RapidEye影像的蚂蝗田小流域土壤侵蚀与岩溶石漠化分析

doi: 10.11932/karst20160514

1.
珠江水利科学研究院
2.
珠江水利科学研究院；珠江流域水土保持监测中心站

基金项目: 水利部预算项目“岩溶地区石漠化现状及变化趋势监测”（1261420610833）；国家自然基金项目“天然林演替为人工林对林地水量平衡及土壤水影响作用机制”（41501019）

计量
- 文章访问数: 1327
- HTML浏览量: 341
- PDF下载量: 629
- 被引次数: 0
出版历程
- 发布日期: 2016-10-25

Analysis of soil erosion and karst rocky desertification in the Mahuangtian small watershed based on RapidEye remote sensing images

1.
Pearl River Hydraulic Research Institute
2.
Pearl River Hydraulic Research Institute；Soil and Water Conservation Monitoring Center of Pearl River Basin

摘要

摘要: 依据《岩溶地区水土流失综合治理技术标准》(SL461-2009)，以蚂蝗田岩溶小流域为研究对象，实地测量了22组典型地物光谱，发现岩石和土壤在红光-近红外二维光谱特征空间具有线性分布规律，由此推导出土壤—岩石指数方程，并构建了岩溶区土壤侵蚀与石漠化强度分析技术流程。在此基础上，利用研究区RapidEye卫星遥感影像，通过提取土地利用、植被覆盖度、基岩裸露率和坡度等指标因子信息，实现了土壤侵蚀与岩溶石漠化强度的分析评价。研究发现：岩溶区土壤侵蚀与植被覆盖度呈负相关性，与坡度和基岩裸露率无单向相关性；岩溶石漠化与植被覆盖度呈负相关性，与坡度呈正相关性，与基岩裸露率呈线性相关。
- RapidEye遥感影像 /
- 土壤—岩石指数 /
- 土壤侵蚀 /
- 岩溶石漠化 /
- 相关性
Abstract: The Mahuangtian small watershed, located at Huajiang town of Guanling county in Guizhou Province, covers an area of 16.51 km2which extends about 5.78 km in north-south and 6.63 km in east-west directions, respectively. As a developed karst region where limestone outcrops widely, its karst area is 12.68 km2while the rest is 3.83 km2. Based on field spectral reflectance measurements in 22 study regions by FieldSpec@3 spectroradiometer, spectral features of typical ground objects (e.g. rock, dry soil, wet soil, forest, grassland, crop, water) were analyzed and a linear distribution of soil and rock spectral was found in the red-nir dimensional feature space. We defined the linear relationship as the rock-soil index and further derived the formula of this index to get the exposed bedrock fraction of the karst area using remote sensing images. According to Techniques standard for comprehensive control of soil erosion and water loss in the karst region (SL461-2009), the technical process was designed to evaluate the soil erosion (SE for short) and karst rocky desertification(KRD for short) in the karst area. Applying this method, we carried out the intensity classification of SE and KRD on the basis of index factors, such as land use, vegetation coverage, exposed bedrock fractions and gradients, generated from RapidEye images, geographical map (1∶200,000) and topographic map (1∶10,000). Results demonstrate that the correct ratios of SE and KRD are respectively 86% and 89%, which can satisfy the specification requirement. By analyzing the interpretation, the SE area is 857.27 hm2, accounting for 51.92% of the research region. Among them, the area of SE in the karst is 695.60 hm2 which accounts for a higher proportion of 54.85% in the Mahuangtian watershed while the non-karst area is 161.67 hm2 which accounts for 42.23% and has a major part of the severe SE. For the 1,268.30 hm2 KRD area, the constituent ratio decreases by 38.89% of inconspicuous KRD, 31.51% of potential KRD, 16.73% of slight KRD, 10.21% of moderate KRD and 2.67% of intense KRD. And their areas are, in order, 493.26 hm2, 399.58 hm2, 212.20 hm2, 129.44 hm2 and 33.83 hm2. Obviously, the slight and moderate KRD are predominant in this karst region. In addition, our study indicates that the SE is inversely associated with vegetation coverage but has no common bond with gradients and exposed bedrock fractions in this area. And the KRD is negatively related with vegetation coverage and positively correlated with gradients and the rate of exposed bedrock.
- RapidEye image /
- soil-rock index /
- soil erosion /
- karst rocky desertification /
- correlation

HTML

参考文献(18)

[1]	张殿发,王世杰,周德全，等.贵州省喀斯特地区土地石漠化的内动力作用机制［J］.水土保持通报,2001,21(4): 1-5.
[2]	王世杰.喀斯特石漠化概念演绎及其科学内涵的探讨［J］ .中国岩溶,2002,21(2):101-105.
[3]	袁道先.对南方岩溶石山地区地下水资源及生态环境地质调查的一些意见［J］.中国岩溶,2000,19(2):103-108.
[4]	张学俭,陈泽健.珠江喀斯特地区石漠化防治对策［M］. 北京:中国水利水电出版社,2007.
[5]	周忠发,黄路迦,肖丹. 贵州高原喀斯特石漠化遥感调查研究：以贵州省清镇市为例［J］.贵州地质,2001, 67 (2):93-98.
[6]	Li W H, Yu D Q. A study of the technology for remote sensing investigation of rocky desertification in areas of karst stony hills［J］.Remote Sensing of Land & Resources,2002,(1):34-37.
[7]	苏锋,何丙辉,熊友胜,等. 基于“3S”技术的奉节县喀斯特石漠化调查及精度评价［J］.西南师范大学学报(自然科学版),2007,32 (6):61-65.
[8]	李丽,童立强,李小慧. 基于植被覆盖度的石漠化遥感信息提取方法研究［J］ .国土资源遥感,2010,84(2):59-62.
[9]	Xia X Q, Tian Q J, Du F L. Analysis of hyperspectral remote sensing image using a simplex methods［ J］.Journal of Image and Graphics, 2004,9(12): 1486-1490.
[10]	Tong L Q. A method for extracting remote sensing information from rocky desertification areas in southwest China［J］.Remote Sensing of Land & Resources, 2003,(4): 33-35.
[11]	童立强. 西南岩溶石山地区石漠化信息自动提取技术研究［J］.国土资源遥感,2003,58 (4):35-38.
[12]	岳跃民,王克林,张兵,等.喀斯特石漠化信息遥感提取的不确定性［J］.地球科学进展, 2011,26 (3):266-273.
[13]	涂杰楠,杨亮,梁丽新,等.基于RapidEye遥感影像的比值密度分割法在岩溶石漠化调查中的应用:以云南鹤庆县为例［J］.中国岩溶,2015,34(3):298-307.
[14]	杨奇勇,蒋忠诚,李晖,等.基于Google Earth的果化示范区石漠化评估［J］.中国岩溶,2013,32(1):95-99.
[15]	水利部水土保持司.岩溶地区水土流失综合治理技术标准 (SL461-2009)［M］.北京:中国水利水电出版社,2009.
[16]	水利部水土保持司.土壤侵蚀分类分级标准(SL190-2007)［M］.北京:中国水利水电出版社,2007.
[17]	祖琪,袁希平,莫源富，等.基于面向对象分类方法在SPOT影像中的地物信息提取［J］.中国岩溶,2011,30 (2):227-232.
[18]	李雪冬,杨广斌,李蔓，等.面向对象的喀斯特地区土地利用遥感分类信息提取:以贵州毕节地区为例［J］.中国岩溶,2013,32(2):231-237.