PDF(5858 KB)
农林开发等生产建设活动水土保持监管研究——以江西省万年县为例
周乐群, 韩凤翔, 陈剑桥, 姬俊虎, 赵继东, 鲁勇
长江科学院院报 ›› 2025, Vol. 42 ›› Issue (10) : 73-79.
PDF(5858 KB)
PDF(5858 KB)
农林开发等生产建设活动水土保持监管研究——以江西省万年县为例
Soil and Water Conservation Supervision for Agricultural and Forestry Development and Other Production and Construction Activities: A Case Study of Wannian County, Jiangxi Province
为落实中共中央办公厅、国务院办公厅《关于加强新时代水土保持工作的意见》,加强生产建设活动水土保持监管工作,对长江中游地区农林开发等生产建设活动开展了水土保持监管试点研究,以期掌握农林开发等生产建设活动和水土保持监管现状,探索监管技术、方法和体制机制。研究采用3S、计算机、无线网络等先进技术,结合现场核查、调研、空间分析等方法开展。研究表明,2023年江西省万年县生产建设活动扰动面积为6 924.60 hm2,占总面积的6.07%;其中93%以上为林业、自然资源和农村农业等部门的项目或补助项目;约78%的生产建设活动未采取有效的水土保持措施防治水土流失,存在水土流失风险;水土保持监管工作基本未开展。研究认为应加强对政府投资项目的水土保持监管工作,出台农林开发等生产建设活动水土保持监管办法;建立“行业监管、水保协同”的监管体制机制,推行分类监管。
[Objective] Taking Wannian County in Jiangxi Province as a representative case, this study presents the analysis results of the pilot projects on soil and water conservation supervision for agricultural and forestry development and other production and construction activities in five counties (or cities) across four provinces in the middle reaches of the Yangtze River. This study aims to assess the current status of these activities and their soil and water conservation supervision, explore regulatory technologies and methods, and invesstigate effective institutional mechanisms for supervision. [Methods] We employed 3S technology, automated image recognition technology, computer technology, database technology, wireless networks, and mobile terminals, together with field verification, surveys, and spatial analysis. Key technologies included the automatic extraction of remote sensing information, enabling fast, automatic, and accurate identification of disturbance patches and soil erosion problem patches. Based on GIS spatial analysis and processing functions, approved production and construction projects were automatically excluded, and relevant information of agricultural and forestry development was automatically integrated. Additionally, a regulatory app was developed. [Results] (1) The disturbance patches of production and construction activities exhibited high accuracy. Through field verification of 910 patches with an area ≥ 1 hm2, only 28 patches with a total area of 108.89 hm2 were identified as actual production and construction projects. The automatic extraction accuracy for disturbance patches and total area reached 96.92% and 98.41%, respectively. (2) The disturbance caused by agricultural and forestry development was significant. In 2023, a total of 1 048 disturbance patches were extracted in Wannian County, with a total area of 6 924.60 hm2, accounting for 6.07% of the county’s land area. The density of disturbance patches reached 0.92/km2. (3) The scale of disturbance was generally large. The average area of disturbance patches was 6.61 hm2, among which 910 patches were over 1 hm2, with a total area as high as 6 859.12 hm2. (4) Regarding spatial distribution, agricultural and forestry development and other production and construction activities in 2023 were distributed across the entire Wannian County, generally showing a uniform distribution pattern, with slightly more disturbance patches in the east than in the west. (5) In terms of types, the main activities included economic forest projects, land consolidation projects, farmland improvement projects, and land requisition-compensation balance projects. (6) An analysis of investment entities revealed that over 93% were projects or subsidized programs under governmental forestry, natural resources, rural and agriculture, and related departments. (7) Approximately 78% of the production and construction activities had not implemented effective soil and water conservation measures, posing significant soil erosion risks. Furthermore, soil and water conservation supervision was largely absent in practice. [Conclusions] Given the high intensity of agricultural and forestry development activities, limited implementation of conservation measures, and high risks of severe soil erosion, it is essential to strengthen soil and water conservation supervision for these activities, particularly for government-funded projects. Regulatory measures for soil and water conservation in such activities should be developed, supervision systems and mechanisms featuring “industry-based regulation and coordinated soil and water conservation” should be established, and categorized supervision should be implemented.
水土保持监管 / 生产建设活动 / 3S技术 / 农林开发 / 体制机制 / 万年县
soil and water conservation supervision / production and construction activities / 3S technology / agricultural and forestry development / mechanism / Wannian County
| [1] |
黄颖伟, 王岩松, 张野, 等. 生产建设项目水土保持“天地一体化”监管技术应用[J]. 中国水土保持, 2018(2):11-15.
(
|
| [2] |
宋林峰. 长沙市生产建设项目水土保持信息化监管实践与思考[J]. 湖南水利水电, 2023(5): 35-37.
(
|
| [3] |
唐春燕. 生产建设项目水土保持信息化监管实践与分析[J]. 低碳世界, 2023, 13(3): 133-135.
(
|
| [4] |
陈起伟, 熊康宁, 兰安军. 基于GIS技术的贵州省土壤侵蚀危险性评价[J]. 长江科学院院报, 2020, 37(12): 47-52, 66.
针对目前喀斯特区土壤侵蚀潜在危险度研究相对薄弱的现状,以典型喀斯特区贵州省为研究对象,获取研究区土地利用类型、岩性、基岩裸露率等专题因子。基于地理信息系统(GIS)技术,在非喀斯特区和喀斯特区分别采用《土壤侵蚀分类分级标准》和《岩溶地区水土流失综合治理技术标准》解译出研究区土壤侵蚀强度等级分布图。并根据土壤允许流失量和土壤抗蚀年限,利用土壤侵蚀潜在危险度指数(SEPDI)对贵州省土壤侵蚀潜在危险度进行评价,为喀斯特区土壤侵蚀防治提供参考。结果显示:贵州省水土流失面积为47 831.73 km<sup>2</sup>,以轻度侵蚀为主,侵蚀模数为341 t/(km<sup>2</sup>·a),SEPDI为2.52,潜在危险等级较高。贵州25.3%行政村的SEPDI位于2~3之间,其中六盘水、黔西南市和毕节市危险度最高,建议将水土流失防治工作纳入SEPDI指标而非单从水土流失强弱等级进行治理,特别加强对SEPDI高但水土流失等级弱的区域的关注。
(
Research on the potential danger of soil erosion in karst area is weak at present. We interpreted the soil erosion intensity in Guizhou Province, a typical karst region, with land use, lithology, and base rock coverage as semantic factors by Geological Information System(GIS) according to <i>Standards for classification and gradation of soil erosion </i>and <i>Techniques standard for comprehensive control of soil erosion and water loss in karst region. </i> Furthermore, we assessed the potential danger of soil erosion in Guizhou by using the soil erosion potential danger index (SEPDI) based on the allowable soil loss value and the soil anti-erosion life. Results suggest that the area of soil and water loss in Guizhou has amounted to 47 831.73 km<sup>2</sup>, dominated by light erosion, with an erosion modulus of 341 t / (km<sup>2</sup>·a) and a SEPDI of 2.52, indicating high level of potential danger. The SEPDI of 25.3% of villages in Guizhou ranges between 2 and 3, among which Liupanshui, Qianxinan, and Bijie feature the highest risk.We recommend that prevention work should be incorporated into SEPDI rather than merely soil erosion degree, and special attention needs to be given to areas with high SEPDI but weak soil erosion levels.
|
| [5] |
赖杭, 邹显勇, 范光伟, 等. 河湖岸线综合监管系统方法[J]. 长江科学院院报, 2022, 39(5): 153-158.
河湖岸线监管重要而复杂。当前,河湖岸线监管仍然以单独利用空、天、地中的1~2种监管手段为主,存在日常监管效率及总体监管水平均不高的问题。为此,提出综合利用遥感监管、现场监管、测站监管的综合监管模式,研究实施综合监管的关键技术,在此基础上构建河湖岸线智慧监管平台。应用结果表明,平台能够综合利用空天地等监管手段进行河湖岸线监管,提高河湖岸线日常监管效率与水平,为河湖岸线监管提供了一种可行的参考方案,具有一定推广应用价值。
(
The supervision of river and lake shorelines is important and complicated. At present, river and lake shoreline supervision is still mainly based on the use of one or two supervision methods in air, space and ground, resulting in inadequate efficiency of daily supervision and low level of overall supervision. A comprehensive supervision model that integrates remote sensing supervision, on-site supervision, and station supervision is proposed, and the key technologies to realize the comprehensive supervision are studied. On this basis, a smart supervision platform for river and lake shorelines is built. The application of the platform verifies that the platform can comprehensively incorporate air, space, and other supervision methods to improve daily supervision efficiency and supervision level for river and lake shoreline. The present research offers a feasible reference plan for the supervision of river and lake shorelines, and is of promotion and application value.
|
| [6] |
杨桄, 张柏, 边红枫, 等. 基于TM遥感影像的玉米地专题信息自动提取[J]. 资源科学, 2006, 28(4): 91-96.
TM遥感影像中专题信息的自动提取是目前遥感界的研究热点，也已成为遥感信息生产流程中的瓶颈环节。本文分析了耕地专题信息自动提取的研究现状，选取了吉林中部和辽宁省东北部作为研究区，采用监督分类的方法对研究区TM遥感影像进行分类，提取了玉米地专题信息，玉米地信息的提取精度为85.5%。根据遥感影像目视解译的原理，提出了基于多特征空间的遥感影像专题信息自动提取的研究方法，通过对多特征空间的数学描述和计算机处理实现遥感专题信息的自动提取。采用多特征空间的方法将玉米地信息分为光谱特征空间、形状特征空间、区域地学特征空间和干扰特征空间，应用ERDAS8.5遥感图像处理软件中的knowledge engineer模块的开发功能，设计了基于多特征空间的玉米地专题信息自动提取的专家库，使用专家库对玉米地信息进行了自动提取，提取精度为92.9%。从基于多特征空间的分类结果与监督分类结果的比较发现，基于多特征空间的自动提取方法可以提高专题信息的提取效率，对未来实现遥感影像的智能解译是一种研究方法的探索。
(
Many researches have focused on the automatic extraction of information from Landsat/TM remote sensing images.However,many of them seemed to be low effective,and the application of remote sensing technology is limited.Firstly,this paper analysed the current situation about how to extract arable land information from remote sensing images,and middle Jilin province and northeast Liaoning Province were selected as study area.The supervised classification method was adopted in the Landsat/TM image classification and maize land in the study area was extracted from the Landsat/TM images with the precision of up to 85.5%.Secondly,the method of automatic information extraction based on the multicharacters space in remotesensing images was put forward.According to the method,maize fields information space was divided into several subspaces including spectral feature space,shape feature space,interference feature space and local geosciencebased feature space.Automatic classification of thematic information about maize land was carried out based on TM images and use of the method above.An expertise database was created for the automatic extraction of maize land from Landsat/TM images on the basis of multicharacters space with the use of knowledge engineer module from the ERDAS 8.5 software.The extraction of maize fields in the study area from the images was performed again on the basis of the expertise database.It was found that the interpretation was notably improved with the precision of 92.9%.Comparing this classification result with the traditional visual interpretation,it was concluded that the new method adopted in the paper could improve efficiency of thematic information extraction from the remote sensing images.At the same time,the method appears to have wide application perspective and have a great potential to be used in other areas.The method was also theoretically significant for automatic interpretation of remotesensing images in the future.
|
| [7] |
邹利东, 郭航, 朱秀芳, 等. 设施农业空间分布信息自动提取方法研究[J]. 遥感技术与应用, 2014, 29(4):669-674.
准确掌握设施农业的空间分布信息,对于各级政府及农业相关部门进一步制定设施农业发展政策、研究设施农业对环境的影响等具有重要意义。我国是世界上第一大设施农业生产国,长期以来设施农业面积调查主要采用基层单位层层上报的统计方式,该方法只有数量信息没有空间位置信息,因此急需发展一种自动快速的设施农业空间信息提取方法。传统遥感信息基于光谱特征的像元级分类受“同物异谱”、“异物同谱”现象的影响严重,不利于设施农业的高精度快速提取。考虑面向对象分类方法对纹理、几何特征鲜明地物提取中表现出的优势,提出耦合利用面向对象和基于支持向量机的分类方法进行设施农业空间分布信息的自动提取,并在河北省定州县利用航片进行了该方法的测试和验证。验证结果显示设施农业的总体分类精度为95.60%,Kappa系数为0.90,利用该方法可以高精度地提取设施农业的空间分布。
(
|
| [8] |
黄俊, 申邵洪. 结合高分辨遥感影像和GIS数据的土地利用变化监测[J]. 长江科学院院报, 2012, 29(1):49-52.
研究了一种结合高分辨率遥感影像和GIS数据的土地利用自动变化监测方法。分别采用马氏距离、支持向量机、神经网络3种分类方法对研究区域进行模糊分类，然后通过多分类器模糊决策融合分类方法对3种分类结果进行融合，提高总体分类精度。在获得高精度分类结果的基础上，结合历史时期GIS专题数据和分类结果，计算对应的图斑多边形内各类别成份，并与其历史属性对比分析，自动实现土地利用变化监测。实验数据选取Quick Bird高分辨率遥感影像和1∶1万土地利用GIS数据，实验结果表明模糊决策融合分类能够明显改善分类效果，获得比单一分类器更为精准的结果。利用决策分类结果并结合GIS数据进行变化区域判定实验，结果表明,对区域中存在较大变化能够准确自动判定为变化区域，而区域中存在较少部分变化则存在部分误判现象。
(
An automatic landuse change detection approach combining high spatial resolution remotely sensed image with GIS data is proposed. Mahalanobis distance, Support Vector Machine (SVM) and Neural Network (NNT) are used respectively for fuzzy classification. To improve the overall accuracy of classification, a fuzzy decision fusion classification algorithm is designed to combine each fuzzy classification result from the above methods. Based on these accurate classification results and the GIS data in historical period, each classification in the corresponding polygon is calculated. The changed area is automatically detected by comparing the calculated land status ratio with its historical status. QuickBird images and GIS data are taken for an experiment. Polygon which exhibits big change of land status ratio can be automatically detected and judged accurately; while polygon which has little change may be subject to false judgment. Experimental results proved that fusion classification results are more accurate than the individual classification result.
|
| [9] |
张健, 何祺胜, 崔同, 等. 基于遥感和GIS的江苏滨海地区湿地信息提取及动态变化分析[J]. 长江科学院院报, 2017, 34(4):144-150.
掌握湿地分布及动态变化特征能够为更好地保护湿地提供科学依据。以江苏省滨海湿地为研究对象,对研究区1992年、2002年、2012年3个时期的遥感数据进行处理,利用最大似然法分类提取湿地信息,研究滨海地区的湿地信息、动态变化并对驱动因子进行分析。结果表明江苏滨海湿地总面积呈减少趋势,其中人工湿地所占比重增加了22.43%,自然湿地所占比重则相应减少,此外自然湿地呈现以獐茅、盐蒿群落大幅度减少以及米草先大范围扩散后相对稳定的趋势;在转移过程中,转入面积最高的是人工养殖塘,而转出率由光滩变成了浅海水域;滨海湿地变化驱动因素主要是人类活动影响。
(
Mastering the distribution and dynamic change characteristics of wetland could provide scientific basis for better protection of wetland. In this research we processed the remote sensing data of Jiangsu coastal wetlands in 1999, 2002, 2012 and employed maximum likelihood method to extract wetland information. On this basis we investigated the dynamic change of coastal wetland and analyzed the driving factors. Results showed that the total area of wetland in Jiangsu coastal area presented a declining trend. The proportion of artificial wetlands increased by 22.43%, and the proportion of natural wetlands decreased, accordingly. In addition, natural wetland presented a tendency that communities of <i>Aeluropus littoralis</i> and <i>Artemisia</i> <i>halodendron</i> reduced greatly, and <i>Spartina</i> experienced the process from widespread diffusion to relative stabilization. During the process of transfer, the biggest transfer-in area was artificial breeding pond, while the biggest transfer-out ratio changed from barren wetland to shallow waters. The main driving factor of coastal wetland change was the influence of human activities.
|
| [10] |
杨荣欣, 谢烈君. 基于多特征融合的高分辨率遥感影像道路提取方法研究[J]. 测绘与空间地理信息, 2022, 45(9): 157-160.
(
|
| [11] |
蒲慧龙, 陈丹蕾, 张云. 基于解译知识库的地表覆盖自动解译研究及实现[J]. 测绘, 2016, 39(5):209-212,219.
(
|
/
| 〈 |
|
〉 |
