Review of machine learning approaches for biomass and soil moisture retrievals from remote sensing data

I Ali, F Greifeneder, J Stamenkovic, M Neumann… - Remote Sensing, 2015 - mdpi.com
The enormous increase of remote sensing data from airborne and space-borne platforms, as
well as ground measurements has directed the attention of scientists towards new and …

Satellite remote sensing of mangrove forests: Recent advances and future opportunities

BW Heumann - Progress in Physical Geography, 2011 - journals.sagepub.com
Mangroves are salt tolerant woody plants that form highly productive intertidal ecosystems in
tropical and subtropical regions. Despite the established importance of mangroves to the …

Development and application of a new mangrove vegetation index (MVI) for rapid and accurate mangrove mapping

AB Baloloy, AC Blanco, RRCS Ana… - ISPRS Journal of …, 2020 - Elsevier
Abstract Advancement in Remote Sensing allows rapid mangrove mapping without the need
for data-intensive methodologies, complex classifiers, and skill-dependent classification …

China's wetlands loss to urban expansion

D Mao, Z Wang, J Wu, B Wu, Y Zeng… - Land degradation & …, 2018 - Wiley Online Library
Humans benefit from multiple ecosystem services of wetlands, but massive wetland loss has
occurred worldwide due to rapid urbanization. To assess the problem, it is necessary to …

Decision tree and random forest classification algorithms for mangrove forest mapping in Sembilang National Park, Indonesia

AD Purwanto, K Wikantika, A Deliar, S Darmawan - Remote Sensing, 2022 - mdpi.com
Sembilang National Park, one of the best and largest mangrove areas in Indonesia, is very
vulnerable to disturbance by community activities. Changes in the dynamic condition of …

Use of machine learning and remote sensing techniques for shoreline monitoring: A review of recent literature

CAD Tsiakos, C Chalkias - Applied Sciences, 2023 - mdpi.com
Climate change and its effects (ie, sea level rise, extreme weather events) as well as
anthropogenic activities, determine pressures to the coastal environments and contribute to …

Identifying mangroves through knowledge extracted from trained random forest models: An interpretable mangrove mapping approach (IMMA)

C Zhao, M Jia, Z Wang, D Mao, Y Wang - ISPRS Journal of …, 2023 - Elsevier
Black-box algorithms are among the dominant mangrove mapping approaches with
complex decision-making procedures. Model internals and tacit knowledge were neglected …

Remote sensing of wetlands: applications and advances

RW Tiner, MW Lang, VV Klemas - 2015 - books.google.com
This book provides a thorough introduction to the use of remotely sensed data for wetland
classification and mapping, as well as information on the latest technological advancements …

Mapping of mangrove forest land cover change along the Kenya coastline using Landsat imagery

KB Kirui, JG Kairo, J Bosire, KM Viergever… - Ocean & Coastal …, 2013 - Elsevier
Mangroves in Kenya provide a wide range of valuable services to coastal communities
despite their relatively small total area. Studies at single sites show reductions in extent and …

10-m-resolution mangrove maps of China derived from multi-source and multi-temporal satellite observations

C Zhao, CZ Qin - ISPRS Journal of Photogrammetry and Remote …, 2020 - Elsevier
China has lost 50% of its mangroves since the 1950s, while the remaining mangroves are
exhibiting an increase in fragmentation. While a detailed mangrove map of China derived …