基于道路网络的贵州小坝村耕地细碎化测度数据集(2017)

以贵州省贵阳市修文县洒坪镇小坝村为研究区域，采用2017年7月无人机获取的村庄的航拍影像图，运用基于样本的面向对象分类方法提取土地利用中宅基地、耕地、道路（村间路、机耕路、田埂）等地理要素信息，并对解译结果进行了验证和分析。数据研发过程包括：通过运用农户宅基地到其耕作地块的道路网络距离，计算农户地块道路通达性指数，然后基于Simmons（1964）提出的方法，计算农户地块面积指数和农户地块形状指数，最后取各指标之和作为农户耕地细碎化指数，最后得到基于道路网络的小坝村耕地细碎化测度数据集。该数据集包括：（1）研究区地理位置数据；（2）研究区及其附近道路网数据；（3）农户耕地细碎化指数及其分段统计数据；（4）农户道路通达性指数、农户地块面积指数和形状指数；（5）各评价指标对村庄耕地细碎化指数的贡献率数据；（6）基于不同模型得到的农户耕地细碎化指数数据。该数据集存储为.shp和.xlsx格式，由15个数据文件组成，数据量为530 KB（压缩为1个文件，334 KB）。基于该数据集的研究成果发表在《资源科学》2019年41卷第4期。

Taking Xiaoba Village, Saping Town, Xiuwen County, Guiyang City, Guizhou Province as the study area, this research adopted the aerial images of the village acquired by unmanned aerial vehicle (UAV) in July 2017, and used the sample-based object-oriented classification method to extract geographic feature information such as homesteads, cultivated land, roads (village paths, motorized tractor roads, field ridges) in land use, and verified and analyzed the interpretation results. The data development process is as follows: first, calculate the road accessibility index of farmers' plots using the road network distance from farmers' homesteads to their cultivated plots; then, calculate the plot area index and plot shape index based on the method proposed by Simmons (1964); finally, take the sum of these indices as the farmers' cultivated land fragmentation index, and obtain the road network-based cultivated land fragmentation measurement dataset for Xiaoba Village. This dataset includes: (1) Geographic location data of the study area; (2) Road network data of the study area and its surrounding areas; (3) Farmers' cultivated land fragmentation indices and their segmented statistical data; (4) Farmers' road accessibility indices, plot area indices and shape indices; (5) Contribution rates of each evaluation index to the village's cultivated land fragmentation index; (6) Farmers' cultivated land fragmentation indices derived from different models. This dataset is stored in .shp and .xlsx formats, consisting of 15 data files, with a total size of 530 KB (compressed into a single file of 334 KB). Research findings based on this dataset were published in *Resources Science*, Vol.41, No.4, 2019.

搜集汇总

背景与挑战

背景概述

该数据集基于2017年无人机航空影像，采用面向对象分类方法提取贵州小坝村的地理要素，通过道路网络分析计算耕地细碎化指数，包括道路可达性、地块面积和形状等指标。数据集包含地理位置、道路网络、细碎化指数等15个文件，存储为.shp和.xlsx格式，数据量530 KB，相关研究发表于《资源科学》。