气候变化领域集成服务门户(CCPortal): Mapping smallholder and large-scale cropland dynamics with a flexible classification system and pixel-based composites in an emerging frontier of Mozambique

CCPortal

DOI	10.1016/j.rse.2019.111611
	Mapping smallholder and large-scale cropland dynamics with a flexible classification system and pixel-based composites in an emerging frontier of Mozambique
	Bey A.; Jetimane J.; Lisboa S.N.; Ribeiro N.; Sitoe A.; Meyfroidt P.
发表日期	2020
ISSN	00344257
卷号	239
英文摘要	Remote sensing assessments of land use and land cover change (LULCC) are critical to improve understanding of socio-economic, institutional and ecological processes that lead to and stem from land use change. This is particularly crucial in the emerging frontiers of Southern Africa, where there is a paucity of LULCC studies relative to the humid tropics. This study focuses on Gurué District (5606 km2) of Zambezia province of Mozambique, one of many countries in the region that has experienced a recent growth in foreign investments in agriculture through large-scale land acquisitions, often resulting in land use conversions and modifications. Previous LULCC assessments covering Mozambique have focused on dynamics between natural and anthropogenic land categories, with limited efforts to distinguish the different land use agents associated with these changes, and relating this with social, economic and technological processes. In this study we built a new LULC assessment methodology that leverages the power of open remote sensing data and tools to integrate categorical and continuous training and validation data obtained from field surveys and Collect Earth software within Google Earth Engine. We then examined the suitability of five pixel-based compositing techniques for generating cloud-free Landsat images that can support analysis of land use dynamics in persistently cloudy, mosaic landscapes with more limited Landsat archives. Drawing upon the spectral and textural features of Landsat data in pixel-based composites, we classified land use over three time periods, 2006, 2012 and 2016, and characterized land use change, focusing on changes between small-scale cropland, large-scale mechanized cropland, and other land uses. This method can be upscaled and applied in many parts of Africa with similar historic image availability challenges, and similar economic contexts with great disparities between small-scale unmechanized cropland and very large-scale mechanized cropland, to explore land consolidation dynamics and agent-specific pathways of land use change. © 2019 Elsevier Inc.
英文关键词	Collect Earth; Google Earth Engine; Land use change; Mozambique; Pixel-based compositing
语种	英语
scopus关键词	Dynamics; Engines; Investments; Pixels; Remote sensing; Assessment methodologies; Classification system; Compositing; Compositing techniques; Google earths; Land use and land cover change; Land-use change; Mozambique; Land use; agricultural land; classification; composite; humid environment; investment; land cover; land use change; mapping method; pixel; remote sensing; smallholder; software; Mozambique; Zambezia
来源期刊	Remote Sensing of Environment
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/179460
作者单位	UCLouvain, Earth and Life Institute, Georges Lemaître Centre for Earth and Climate Research (TECLIM), Louvain-La-Neuve, Belgium; Universidade Eduardo Mondlane, Faculty of Agronomy and Forest Engineering, Maputo, Mozambique; University of Virginia, Charlottesville, United States; FNRS - Fonds de la Recherche Scientifique, Brussels, Belgium
推荐引用方式 GB/T 7714	Bey A.,Jetimane J.,Lisboa S.N.,et al. Mapping smallholder and large-scale cropland dynamics with a flexible classification system and pixel-based composites in an emerging frontier of Mozambique[J],2020,239.
APA	Bey A.,Jetimane J.,Lisboa S.N.,Ribeiro N.,Sitoe A.,&Meyfroidt P..(2020).Mapping smallholder and large-scale cropland dynamics with a flexible classification system and pixel-based composites in an emerging frontier of Mozambique.Remote Sensing of Environment,239.
MLA	Bey A.,et al."Mapping smallholder and large-scale cropland dynamics with a flexible classification system and pixel-based composites in an emerging frontier of Mozambique".Remote Sensing of Environment 239(2020).