Image time series processing for agriculture monitoring

被引：70

作者：

Eerens, Herman ^{[1
]}

Haesen, Dominique ^{[1
]}

Rembold, Felix ^{[2
]}

Urbano, Ferdinando ^{[2
]}

Tote, Carolien ^{[1
]}

Bydekerke, Lieven ^{[1
]}

机构：

[1] VITO, B-2400 Mol, Belgium

[2] Commiss European Communities, Joint Res Ctr, I-21027 Ispra, VA, Italy

来源：

ENVIRONMENTAL MODELLING & SOFTWARE | 2014年 / 53卷

关键词：

Remote sensing; Early warning; Environmental monitoring; Yield forecasting system; Crop and vegetation monitoring; SERVICE; IMPLEMENTATION; SYSTEMS;

D O I：

10.1016/j.envsoft.2013.10.021

中图分类号：

TP39 [计算机的应用];

学科分类号：

081203 ; 0835 ;

摘要：

Given strong year-to-year variability, increasing competition for natural resources, and climate change impacts on agriculture, monitoring global crop and natural vegetation conditions is highly relevant, particularly in food insecure areas. Data from remote sensing image series at high temporal and low spatial resolution can help to assist in this monitoring as they provide key information in near-real time over large areas. The SPIRITS software, presented in this paper, is a stand-alone toolbox developed for environmental monitoring, particularly to produce clear and evidence-based information for crop production analysts and decision makers. It includes a large number of tools with the main aim of extracting vegetation indicators from image time series, estimating the potential impact of anomalies on crop production and sharing this information with different audiences. SPIRITS offers an integrated and flexible analysis environment with a user-friendly graphical interface, which allows sequential tasking and a high level of automation of processing chains. It is freely distributed for non-commercial use and extensively documented. (C) 2013 The Authors. Published by Elsevier Ltd. All rights reserved.

引用

页码：154 / 162

页数：9

共 33 条

[21] GRASS GIS: A multi-purpose open source GIS [J].