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Open AccessArticle

A Multi-Temporal Object-Based Image Analysis to Detect Long-Lived Shrub Cover Changes in Drylands

1
Andalusian Center for Assessment and Monitoring of Global Change (CAESCG), University of Almería, 04120 Almería, Spain
2
Multidisciplinary Institute for Environment Studies “Ramon Margalef”, University of Alicante, San Vicente del Raspeig, 03690 Alicante, Spain
3
Department of Botany, Faculty of Science, University of Granada Campus Fuentenueva, 18071 Granada, Spain
4
Remote Sensing of Environmental Dynamics Lab, University of Milano – Bicocca, Piazza della Scienza 1, 20126 Milan, Italy
5
Department of Biology and Geology, University of Almería, 04120 Almería, Spain
6
Inter-university Institute for Earth System Research (IISTA), University of Granada, Av. Mediterráneo, s/n. 18006, Granada, Spain
*
Author to whom correspondence should be addressed.
Remote Sens. 2019, 11(22), 2649; https://doi.org/10.3390/rs11222649
Received: 10 October 2019 / Revised: 7 November 2019 / Accepted: 10 November 2019 / Published: 13 November 2019
(This article belongs to the Special Issue Remote Sensing Applications in Monitoring of Protected Areas)
Climate change and human actions condition the spatial distribution and structure of vegetation, especially in drylands. In this context, object-based image analysis (OBIA) has been used to monitor changes in vegetation, but only a few studies have related them to anthropic pressure. In this study, we assessed changes in cover, number, and shape of Ziziphus lotus shrub individuals in a coastal groundwater-dependent ecosystem in SE Spain over a period of 60 years and related them to human actions in the area. In particular, we evaluated how sand mining, groundwater extraction, and the protection of the area affect shrubs. To do this, we developed an object-based methodology that allowed us to create accurate maps (overall accuracy up to 98%) of the vegetation patches and compare the cover changes in the individuals identified in them. These changes in shrub size and shape were related to soil loss, seawater intrusion, and legal protection of the area measured by average minimum distance (AMD) and average random distance (ARD) analysis. It was found that both sand mining and seawater intrusion had a negative effect on individuals; on the contrary, the protection of the area had a positive effect on the size of the individuals’ coverage. Our findings support the use of OBIA as a successful methodology for monitoring scattered vegetation patches in drylands, key to any monitoring program aimed at vegetation preservation. View Full-Text
Keywords: arid zones; drylands; object-based; seawater intrusion; soil loss; time series classification; very high-resolution images; Ziziphus lotus; Cabo de Gata-Níjar Natural Park; Southeast Spain arid zones; drylands; object-based; seawater intrusion; soil loss; time series classification; very high-resolution images; Ziziphus lotus; Cabo de Gata-Níjar Natural Park; Southeast Spain
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MDPI and ACS Style

Guirado, E.; Blanco-Sacristán, J.; Rigol-Sánchez, J.P.; Alcaraz-Segura, D.; Cabello, J. A Multi-Temporal Object-Based Image Analysis to Detect Long-Lived Shrub Cover Changes in Drylands. Remote Sens. 2019, 11, 2649.

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