Data4Land: How to enrich land-use/land-cover with historical vector(s)

IF 2.4 4区计算机科学 Q2 COMPUTER SCIENCE, SOFTWARE ENGINEERING

SoftwareX Pub Date : 2025-07-17 DOI:10.1016/j.softx.2025.102226

V. Kriukov, R. Rahman, L. Bastin

引用次数: 0

Abstract

Land-use/land-cover (LULC) datasets produced from remote sensing may not consistently capture small/linear features of interest, including ecological barriers, eg. roads, railways and water objects. To overcome this challenge, a flexible workflow was developed to enrich the LULC with vector data (OpenStreetMap and World Database on Protected Areas). Users apply the Data4Land tool through a series of Jupyter Notebooks that address different mandatory and optional functions. The tool was used to enrich example LULC datasets and compute habitat connectivity indices for Catalonia (Spain) and Northern England. If vector data represent ecological barriers, connectivity indices tend to drop at all scales once the enriched LULC datasets are implemented.

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Data4Land：如何用历史向量丰富土地利用/土地覆盖

遥感产生的土地利用/土地覆盖（LULC）数据集可能无法始终如一地捕捉到感兴趣的小/线性特征，包括生态屏障。公路、铁路和水上物体。为了克服这一挑战，开发了一个灵活的工作流程，用矢量数据（OpenStreetMap和世界保护区数据库）丰富LULC。用户通过一系列Jupyter notebook应用Data4Land工具，这些notebook处理不同的强制和可选功能。该工具用于丰富示例LULC数据集，并计算加泰罗尼亚（西班牙）和英格兰北部的栖息地连通性指数。如果向量数据代表生态屏障，那么在丰富的LULC数据集实施后，连通性指数在所有尺度上都趋于下降。

本文章由计算机程序翻译，如有差异，请以英文原文为准。

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来源期刊

SoftwareX COMPUTER SCIENCE, SOFTWARE ENGINEERING-

CiteScore

5.50

自引率

2.90%

发文量

184

审稿时长

9 weeks

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