Assessment of post-fire changes in land surface temperature and surface albedo, and their relation with fire-burn severity using multitemporal MODIS imagery

This study evaluates the effects of the large 2007 Peloponnese (Greece) wildfires on changes in broadband surface albedo (a), daytime land surface temperature (LSTd) and night-time LST (LSTn) using a 2-year post-fire time series of Moderate Resolution Imaging Spectroradiometer satellite data. In addition, it assesses the potential of remotely sensed a and LST as indicators for fire-burn severity. Immediately after the fire event, mean a dropped up to 0.039 (standard deviation = 0.012) (P < 0.001), mean LSTd increased up to 8.4 (3.0) K (P < 0.001), and mean LSTn decreased up to -1.2 (1.5) K (P < 0.001) for high-severity plots (P < 0.001). After this initial alteration, fire-induced changes become clearly smaller and seasonality starts governing the a and LST time series. Compared with the fire-induced changes in a and LST, the post-fire NDVI drop was more persistent in time. This temporal constraint restricts the utility of remotely sensed a and LST as indicators for fire-burn severity. For the times when changes in a and LST were significant, the magnitude of changes was related to fire-burn severity, revealing the importance of vegetation as a regulator of land surface energy fluxes

An Analysis of the Early Regeneration of Mangrove Forests using Landsat Time Series in the Matang Mangrove Forest Reserve, Peninsular Malaysia

Time series of satellite sensor data have been used to quantify mangrove cover changes at regional and global levels. Although mangrove forests have been monitored using remote sensing techniques, the use of time series to quantify the regeneration of these forests still remains limited. In this study, we focus on the Matang Mangrove Forest Reserve (MMFR) located in Peninsular Malaysia, which has been under silvicultural management since 1902 and provided the opportunity to investigate the use of Landsat annual time series (1988-2015) for (i) detecting clear-felling events that take place in the reserve as part of the local management, and (ii) tracing back and quantifying the early regeneration of mangrove forest patches after clear-felling. Clear-felling events were detected for each year using the Normalized Difference Moisture Index (NDMI) derived from single date (cloud-free) or multi-date composites of Landsat sensor data. From this series, we found that the average period for the NDMI to recover to values observed prior to the clear-felling event between 1988 and 2015 was 5.9 ± 2.7 years. The maps created in this study can be used to guide the replantation strategies, the clear-felling planning, and the management and monitoring activities of the MMFR.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Spatial analysis of early mangrove regeneration in the Matang Mangrove Forest Reserve, Peninsular Malaysia, using geomatics

Successful mangrove tree regeneration is required to maintain the provision of wood for silviculturally managed mangrove forest areas and to ensure mangrove rehabilitation in disturbed areas. Successful natural regeneration of mangroves after disturbance depends on the dispersal, establishment, early growth and survival of propagules. Focusing on the Matang Mangrove Forest Reserve (MMFR) in Peninsular Malaysia, we investigated how the location of a mangrove forest patch might influence the early regeneration of mangroves after clear-felling events that regularly take place on an approximately 30-year rotation as part of local management. We used Landsat-derived Normalized Difference Moisture Index (NDMI) annual time series from 1988 to 2015 to indicate the recovery of canopy cover during early regeneration, which was determined as the average time (in years) for the NDMI to recover to values associated with the mature forests prior to their clear felling. We found that clear-felled mangrove patches closer to water and/or to already established patches of Rhizophora regenerated more rapidly than those farther away. In contrast, patches located closer to dryland forests regenerated slower compared to patches that were farther away. The study concludes that knowledge of the distribution of water, hydro-period and vegetation communities across the landscape can indicate the likely regeneration of mangrove forests through natural processes and identify areas where active planting is needed. Furthermore, time-series comparisons of the NDMI during the early years of regeneration can assist monitoring of mangrove establishment and regeneration, inform on the success of replanting, and facilitate higher productivity within the MMFR.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Monitoring Matang's Mangroves in Peninsular Malaysia through Earth Observations: A Globally Relevant Approach

Expansion of rotational timber harvesting of mangroves is set to increase, particularly given greater recognition of the economic, societal and environmental benefits. Generic and standardized procedures for monitoring mangroves are, therefore, needed to ensure their long-term sustainable utilisation. Focusing on the Matang Mangrove Forest Reserve (MMFR), Perak State, Peninsular Malaysia, thematic and continuous environmental descriptors with defined codes or units, including lifeform, forest age (years), canopy cover (%), above-ground biomass (Mg ha−1) and relative amounts of woody debris (%), were retrieved from time-series data from spaceborne optical and single/dual polarimetric and interferometric RADAR. These were then combined for multiple points in time to generate land cover and evidence-based change maps according to the Food and Agriculture Organisation (FAO) Land Cover Classification System (LCCS) and using the framework of the Earth Observation Data for Ecosystem Monitoring (EODESM). Change maps were based on a pre-defined taxonomy, with focus on clear cutting and regrowth. Uncertainties surrounding the land cover and change maps were based on those determined for the environmental descriptors used for their generation and through comparison with independent retrieval from other EO data sources. For the MMFR and also for other mangroves worldwide where harvesting is occurring or being considered, a new approach and opportunity for supporting management of mangroves is presented, which has application for future planning of mangrove resources.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Structural characterisation of mangrove forests achieved through combining multiple sources of remote sensing data

Temporal information on mangrove extent, age, structure and biomass provides an important contribution towards understanding the role of these ecosystems in terms of the services they provide (e.g. in relation to storage of carbon, conservation biodiversity), particularly given the diversity of influences of human activity and natural events and processes. Focusing on the Matang Mangrove Forest Reserve (MMFR) in Perak Province, Peninsular Malaysia, this study aimed to retrieve comprehensive information on the biophysical properties of mangroves from spaceborne optical and Synthetic Aperture Radar (SAR) to support better understanding of their dynamics in a managed setting. For the period 1988 to 2016 (29 years), forest age was estimated on at least an annual basis by combining time-series of Landsat-derived Normalised Difference Moisture Index (NDMI) and Japanese L-band Synthetic Aperture Radar (SAR) data. The NDMI was further used to retrieve canopy cover (%). Interferometric Shuttle Radar Topographic Mission (SRTM) X/C-band (2000), TanDEM-X-band (2010–2016) and stereo WorldView-2 stereo (2016) data were evaluated for their role in estimating canopy height (CH), from which above ground biomass (AGB, Mg ha−1) was derived using pre-established allometry. Whilst both L-band HH and HV data increased with AGB after about 8–10 years of growth, retrieval was compromised by mixed scattering from varying amounts of dead woody debris following clearing and wood material within regenerating forests, thinning of trees at ~15 and 20 years, and saturation of L-band SAR data after approximately 20 years of growth. Reference was made to stereo Phantom-3 DJI stereo imagery to support estimation of canopy cover (CC) and validation of satellite-derived CH. AGB estimates were compared with ground-based measurements. Using relationships with forest age, both CH and AGB were estimated for each date of Landsat or L-band SAR observation and the temporal trends in L-band SAR were shown to effectively track the sequences of clearing and regeneration. From these, four stages of the harvesting cycle were defined. The study provided new information on the biophysical properties and growth dynamics of mangrove forests in the MMFR, inputs for future monitoring activities, and methods for facilitating better characterisation and mapping of mangrove areas worldwide.SCOPUS: ar.jinfo:eu-repo/semantics/publishe

Thirty years of land cover and fraction cover changes over the Sudano-Sahel using landsat time series

Historical land cover maps are of high importance for scientists and policy makers studying the dynamic character of land cover change in the Sudano-Sahel, including anthropogenic and climatological drivers. Despite its relevance, an accurate high resolution record of historical land cover maps is currently lacking over the Sudano-Sahel. In this study, 30 m resolution historically consistent land cover and cover fraction maps are provided over the Sudano-Sahel for the period 1986&ndash;2015. These land cover/cover fraction maps are achieved based on the Landsat archive preprocessed on Google Earth Engine and a random forest classification/regression model, while historical consistency is achieved using the hidden Markov model. Using these historical maps, a multitude of variability in the dynamic Sudano-Sahel region over the past 30 years is revealed. On the one hand, Sahel-wide cropland expansion and the re-greening of the Sahel is observed in the discrete land cover classification. On the other hand, subtle changes such as forest degradation are detected based on the cover fraction maps. Additionally, exploiting the 30 m spatial resolution, fine-scale changes, such as smallholder or subsistence farming, can be detected. The historical land cover/cover fraction maps presented in this study are made available via an open-access platform