数据资源

2023年新疆塔城地区草地类型Landsat8影像训练数据集

  • 杨延晓 ,
  • 李全胜 ,
  • 胡林 ,
  • 张鲜花 ,
  • 孙伟
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  • 1.新疆农业大学计算机与信息工程学院,乌鲁木齐 830052
    2.中国农业科学院农业信息研究所,北京 100081
    3.国家农业科学数据中心,北京 100081
    4.新疆农业大学草业学院,乌鲁木齐 830052
杨延晓,E-mail:2645835163@qq.com
张鲜花,E-mail: zxh@xjau.edu.cn
孙伟,E-mail:sunwei02@caas.cn

收稿日期: 2024-12-17

  录用日期: 2025-02-14

  网络出版日期: 2025-06-23

基金资助

国家自然科学基金项目(32271880);国家自然科学基金项目(32060321)

Landsat8 Image Training Data Set of Grassland Types in Tarbagatay Prefecture in 2023

  • YANG YanXiao ,
  • LI QuanSheng ,
  • HU Lin ,
  • ZHANG XianHua ,
  • SUN Wei
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  • 1. College of Computer and Information Engineering, Xinjiang Agricultural University, Urumqi 830052, China
    2. Agricultural Information Institute of CAAS, Beijing 100081, China
    3. National Agriculture Science Data Center, Beijing 100081, China
    4. College of Grassland Science, Xinjiang Agricultural University, Urumqi 830052, China

Received date: 2024-12-17

  Accepted date: 2025-02-14

  Online published: 2025-06-23

摘要

草地资源是畜牧业生产的物质基础和生物多样性的基因库,具有防风固沙、涵养水源的生态功能,草地资源调查及监测意义重大。基于卫星遥感的草地分类不仅能够为草地资源调查提供数据支持,也可为草地物种多样性研究提供依据。基于野外调查数据获取真实样地草地类型信息,利用辐射定标、大气校正、图像融合等预处理后的Landsat8遥感影像,通过目视解译遥感判读的方式,使用ArcGIS软件构建了塔城地区8类草地类型共3360张多光谱遥感图像分类训练数据集。本数据集可为塔城地区草地类型遥感图像分类研究提供数据基础,同时可为其他地区相关领域的科研人员提供数据参考。

数据摘要:

项目 描述
数据库(集)名称 2023年新疆塔城地区草地类型Landsat8影像训练数据集
所属学科 农业科学
研究主题 草地类型
数据时间范围 2023年
数据地理空间覆盖 新疆塔城地区,82°16'-87°21′E,43˚25΄-47°15′′N,包括:额敏县、托里县、裕民县、和布克赛尔蒙古自治县、塔城市、沙湾市、乌苏市。
空间分辨率 15 m
数据类型与技术格式 .tif
数据库(集)组成 数据集共包含8个以草地类命名的文件夹,每个文件夹中包含相应草地类型的遥感影像,共3360幅。
数据量 5.74 GB
主要数据指标 低地草甸,温性草原化荒漠,温性草甸草原,温性荒漠草原,山地草甸,温性草原,高寒草甸,温性荒漠
数据可用性 CSTR:17058.11.sciencedb.agriculture.00135; https://cstr.cn/17058.11.sciencedb.agriculture.00135
DOI:10.57760/sciencedb.agriculture.00135; https://doi.org/10.57760/sciencedb.agriculture.00135
经费支持 国家自然科学基金项目(32271880,32060321)

本文引用格式

杨延晓 , 李全胜 , 胡林 , 张鲜花 , 孙伟 . 2023年新疆塔城地区草地类型Landsat8影像训练数据集[J]. 农业大数据学报, 2025 , 7(2) : 255 -260 . DOI: 10.19788/j.issn.2096-6369.100052

Abstract

Grassland resources are the material basis of animal husbandry production and the gene pool of biodiversity, which have the ecological functions of preventing wind, fixing sand and conserving water. Grassland classification based on satellite remote sensing can not only provide data support for the investigation of grassland resources, but also provide a basis for the study of grassland species diversity. Based on the field survey data, the grassland classification information of real sample plots was obtained. Based on field survey data, the grassland type information of real sample plots is obtained. Landsat8 remote sensing images that have been preprocessed by radiation calibration, atmospheric correction, image fusion, seamless mosaic, etc. are used. After the operation process of dataset sample labeling, sample data clipping, result inspection, data enhancement, etc., combined with visual interpretation of remote sensing interpretation, ArcGIS software is used to construct 8 types of grassland in Tarbagatay Prefecture, a total of 3360 multispectral remote sensing image classification training datasets, and the number of sample images in each category is between 300-580.This data set can not only provide data basis for remote sensing image classification of grassland in Tarbagatay Prefecture, but also provide data reference for researchers in related fields in other areas.

Data summary:

Item Description
Dataset name Landsat8 Image Training Data Set of Grassland Types in Tarbagatay Prefecture in 2023
Specific subject area Agricultural science
Research topic Grassland types
Time range 2023 year
Geographical scope Tarbagatay Prefecture 82°16'-87°2′E,43˚25΄-47°15′N; specific areas include: Emin County, Toli County, Yumin, Mongolian Autonomous County of Hoboksar, Tacheng City, Shawan, Wusu City
Spatial resolution 15 m
Data types and technical formats .tif
Dataset structure The dataset consists of 8 folders named after grassland, each containing 3360 remote sensing images of the corresponding grassland category.
Volume of data 5.74 GB
Key index in dataset Lowland meadow, temperate steppe desert, temperate meadow steppe, temperate desert steppe, montane meadow, temperate steppe, alpine meadow, temperate desert
Data accessibility CSTR:17058.11.sciencedb.agriculture.00135; https://cstr.cn/17058.11.sciencedb.agriculture.00135
DOI:10.57760/sciencedb.agriculture.00135; https://doi.org/10.57760/sciencedb.agriculture.00135
Financial support National Natural Science Foundation of China(32271880,32060321)

参考文献

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[6] 常楚晨, 王洁, 杨吉林, 等. 基于Landsat和Sentinel-2卫星的草地利用率遥感监测——以不同草地类型放牧平台为例. 科学通报, 2025, 70(11):1486-1503.
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