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DOI	10.1117/12.2573488
	Emissivity-based vegetation indices to monitor deforestation and forest degradation in the Congo Basin rainforest
	Masiello, Guido; Cersosimo, Angela; Mastro, Pietro; Serio, Carmine; Venafra, Sara; Pasquariello, Pamela
通讯作者	Masiello, G (corresponding author), Univ Basilicata, Sch Engn, Via Ateneo Lucano 10, Potenza, Italy.
会议名称	Conference on Remote Sensing for Agriculture, Ecosystems, and Hydrology XXII held at SPIE Remote Sensing Conference
会议日期	SEP 22-25, 2020
会议地点	ELECTR NETWORK
英文摘要	Vegetation stress is a major widespread problem in many countries because of climate change and anthropogenic activities. Deforestation and forest degradation phenomena may be caused for several reasons such as infrastructure development, agriculture, collection of wood energy, forest exploitation. Over the last decade, a severe decline in vegetation was observed in the Congo Basin rainforest, the second-largest tropical forest in the world, behind the Amazon. Therefore, actions are required to monitor and detect vegetation stresses to mitigate their negative impacts on human life, wildlife, and plant communities. Vegetation stress can be estimated using three different methods: field measurements, meteorological data, and remote sensing. The present study is mainly focused on satellite remote sensing. The main objective is to develop and test new indices of vegetation-soil dryness based on the surface emissivity. Until now, the problem has been attacked through indices such as the normalized differential vegetation index (or NDVI). The problem of NDVI is that it is a greenness index and is not capable to distinguish bare soil from senescent vegetation, whereas this distinction is important especially when forest degradation followed by eventual regeneration occurs and when dealing with semi-arid regions, where we could have desert sand. We propose to follow the strategy of using surface emissivity (epsilon), which is more closely related to surface type and coverage. By properly using surface emissivity in the infrared we can define a set of channels that are particularly sensitive to bare soil, green, and senescent vegetation. From these emissivity channels, we can derive a suitable emissivity contrast index or ECI, which is sensitive to green vegetation, senescent vegetation, and bare soil, therefore overcoming the NDVI limitation concerning its capability to distinguish bares soil from senescent vegetation. The analysis is performed with CAMEL (Combined ASTER and MODIS Emissivity for Land) database from 2000 to 2016.
英文关键词	Vegetation Stress Infrared Emissivity Remote Sensing Retrieval of surface properties Congo CAMEL
来源出版物	REMOTE SENSING FOR AGRICULTURE, ECOSYSTEMS, AND HYDROLOGY XXII
ISSN	0277-786X
EISSN	1996-756X
出版年	2020
卷号	11528
ISBN	978-1-5106-3869-3; 978-1-5106-3870-9
出版者	SPIE-INT SOC OPTICAL ENGINEERING
类型	Proceedings Paper
语种	英语
收录类别	CPCI-S
WOS记录号	WOS:000646355500012
WOS类目	Agronomy ; Environmental Sciences ; Remote Sensing ; Optics
WOS研究方向	Agriculture ; Environmental Sciences & Ecology ; Remote Sensing ; Optics
资源类型	会议论文
条目标识符	http://119.78.100.177/qdio/handle/2XILL650/353174
作者单位	[Masiello, Guido; Cersosimo, Angela; Mastro, Pietro; Serio, Carmine; Venafra, Sara; Pasquariello, Pamela] Univ Basilicata, Sch Engn, Via Ateneo Lucano 10, Potenza, Italy
推荐引用方式 GB/T 7714	Masiello, Guido,Cersosimo, Angela,Mastro, Pietro,et al. Emissivity-based vegetation indices to monitor deforestation and forest degradation in the Congo Basin rainforest[C]:SPIE-INT SOC OPTICAL ENGINEERING,2020.