气候变化领域集成服务门户(CCPortal): A methodology based on GEOBIA and WorldView-3 imagery to derive vegetation indices at tree crown detail in olive orchards

CCPortal

DOI	10.1016/j.jag.2019.101912
	A methodology based on GEOBIA and WorldView-3 imagery to derive vegetation indices at tree crown detail in olive orchards
	Solano F.; Di Fazio S.; Modica G.
发表日期	2019
ISSN	15698432
卷号	83
英文摘要	Precision agriculture (PA) is becoming an essential practice for the implementation of sustainable agriculture that encompasses the efficient use of resources and a systematic crops monitoring. The increasing temporal and spatial resolution of satellite imagery, coupled with their availability and decreasing costs, create new possibilities for generating accurate datasets on different crops variables, more frequently available as ready-to-use data. The availability of very high-resolution (VHR) satellite imagery, such as the WorldView-3 (WV-3), leads to the advanced potential of satellite Remote Sensing (RS), becoming in the last decade one of the main data source in precision agriculture (PA). In the broad overview of these procedures, geographic object-based image classification (GEOBIA) techniques, gained broad interest as methods to produce geographic information in GIS-ready format. In this paper, methodologies for a semiautomatic process workflow is presented, providing olive tree crown detection in two different olive orchards in Calabria (Italy), collected by means of GEOBIA procedures, in order to investigate olive tree spectral behavior and the reliability of WW-3 derived vegetation indices (VIs). The semi-automated classification method, accomplished by imagery pre-processing steps, may constitute an operational processing chain for mapping and monitoring olive orchards at tree scale detail. Five VIs were investigated: Normalized Difference Vegetation Index (NDVI), Modified Soil Adjusted Vegetation Index 2 (MSAVI 2), Normalized Difference Red Edge Vegetation Index (NDRE), Modified Chlorophyll Absorption Ratio Index Improved (MCARI2), and NDVI2. The obtained results were statistically tested and their accuracy assessed. Thematic accuracy ranges from 95.33% to 96% in both study areas with an overall tree detection rate of 96.8%. Statistical analysis showed that the major differences in spectral behavior, over different plots of the investigated olive orchards, are mainly due to the component of the red-infrared regions of the electromagnetic spectrum (EM), where the red-edge becomes important in assessing the state of general vigor. Moreover, the proposed methodology increases the possibility of detecting tree stress at earlier stages and the benefits of using satellite-based approaches in terms of: larger area coverage, less processing and operator interaction coupled with more spectral information, thus reducing the need to collect costly reference data sampling. © 2019 Elsevier B.V.
英文关键词	Geographic object-based image classification (GEOBIA); Olive orchards; Olive trees’ crown extraction; Precision agriculture (PA); Satellite remote sensing; Spectral behavior; Vegetation indices (VIs); Worldview-3 (WV-3)
语种	英语
scopus关键词	agricultural practice; alternative agriculture; canopy architecture; evergreen tree; precision agriculture; remote sensing; satellite data; satellite imagery; vegetation dynamics; Calabria; Italy
来源期刊	International Journal of Applied Earth Observation and Geoinformation
文献类型	期刊论文
条目标识符	http://gcip.llas.ac.cn/handle/2XKMVOVA/156439
作者单位	University of Reggio Calabria, Loc. Feo di Vito, Reggio Calabria, 89129, Italy
推荐引用方式 GB/T 7714	Solano F.,Di Fazio S.,Modica G.. A methodology based on GEOBIA and WorldView-3 imagery to derive vegetation indices at tree crown detail in olive orchards[J],2019,83.
APA	Solano F.,Di Fazio S.,&Modica G..(2019).A methodology based on GEOBIA and WorldView-3 imagery to derive vegetation indices at tree crown detail in olive orchards.International Journal of Applied Earth Observation and Geoinformation,83.
MLA	Solano F.,et al."A methodology based on GEOBIA and WorldView-3 imagery to derive vegetation indices at tree crown detail in olive orchards".International Journal of Applied Earth Observation and Geoinformation 83(2019).