Behara Satyanarayana

Bio: Behara Satyanarayana is an academic researcher from Universiti Malaysia Terengganu. The author has contributed to research in topics: Mangrove & Vegetation. The author has an hindex of 19, co-authored 67 publications receiving 1064 citations. Previous affiliations of Behara Satyanarayana include International Union for Conservation of Nature and Natural Resources & Marine Biological Laboratory.

Assessment of mangrove vegetation based on remote sensing and ground-truth measurements at Tumpat, Kelantan Delta, East Coast of Peninsular Malaysia

Abstract: The lower reaches of River Kelantan form a vast delta (1200 ha) consisting of bay, mangrove and estuary on the northeast coast of Peninsular Malaysia. The present study was conducted to assess the mangrove vegetation at Tumpat based on ground-truth and remote sensing measurements. The mangroves are composed of several species including Nypa fruticans, Sonneratia caseolaris, Avicennia alba, Rhizophora apiculata, R. mucronata and Bruguiera gymnorrhiza, in order of dominance. The point-centred quarter method (PCQM) was used to estimate the stem density (number of stems/0.1 ha) and basal area (m2/0.1 ha) at selected sites on the ground. Recent high-resolution multispectral satellite data (QuickBird 2006, 2.4 m spatial resolution of the multispectral image) were used to produce land-use/cover classification and Normalized Differential Vegetation Index (NDVI) mapping for the delta. The area statistics reveal that mangroves occupy 339.6 ha, while coconut plantation dominates the vegetation (715.2 ha), followed by settlements (621.6 ha), sandbar (148.4 ha), agriculture (89 ha) and aquaculture (42.7 ha). Although the relationship between the spectral indices and dendrometric parameters was weak, we found a very high significance between the (mean) NDVI and stem density (p = 1.3 × 10-8). The sites with young/growing and also mature trees with lush green cover showed greater NDVI values (0.40-0.68) indicating healthy vegetation, while mature forests under environmental stress due to sand deposition and/or poor tidal inundation showed low NDVI values (0.38-0.47) and an unhealthy situation. Overall, a combination of ground survey and remote sensing provided valuable information for the assessment of mangrove vegetation types (i.e. young/growing or mature forest) and their health in Tumpat, Kelantan Delta.

Is Matang Mangrove Forest in Malaysia sustainably rejuvenating after more than a century of conservation and harvesting management

Abstract: Matang Mangrove Forest Reserve (MMFR) in Peninsular Malaysia is under systematic management since 1902 and still considered as the best managed mangrove forest in the world. The present study on silvimetrics assessed the ongoing MMFR forest management, which includes a first thinning after 15 years, a second thinning after 20 years and clear-felling of 30-year old forest blocks, for its efficiency and productivity in comparison to natural mangroves. The estimated tree structural parameters (e.g. density, frequency) from three different-aged mangrove blocks of fifteen (MF15), twenty (MF20), and thirty (MF30) years old indicated that Bruguiera and Excoecaria spp. did not constitute a significant proportion of the vegetation (<5%), and hence the results focused majorly on Rhizophora apiculata. The density of R. apiculata at MF15, MF20 and MF30 was 4,331, 2,753 and 1,767 stems ha−1, respectively. In relation to ongoing practices of the artificial thinnings at MMFR, the present study suggests that the first thinning could be made earlier to limit the loss of exploitable wood due to natural thinning. In fact, the initial density at MF15 was expected to drop down from 6,726 to 1,858 trees ha−1 before the first thinning. Therefore the trees likely to qualify for natural thinning, though having a smaller stem diameter, should be exploited for domestic/commercial purposes at an earlier stage. The clear-felling block (MF30) with a maximum stem diameter of 30 cm was estimated to yield 372 t ha−1 of the above-ground biomass and suggests that the mangrove management based on a 30-year rotation is appropriate for the MMFR. Since Matang is the only iconic site that practicing sustainable wood production, it could be an exemplary to other mangrove locations for their improved management.

The advantages of using drones over space-borne imagery in the mapping of mangrove forests.

Abstract: Satellite data and aerial photos have proved to be useful in efficient conservation and management of mangrove ecosystems. However, there have been only very few attempts to demonstrate the ability of drone images, and none so far to observe vegetation (species-level) mapping. The present study compares the utility of drone images (DJI-Phantom-2 with SJ4000 RGB and IR cameras, spatial resolution: 5cm) and satellite images (Pleiades-1B, spatial resolution: 50cm) for mangrove mapping—specifically in terms of image quality, efficiency and classification accuracy, at the Setiu Wetland in Malaysia. Both object- and pixel-based classification approaches were tested (QGIS v.2.12.3 with Orfeo Toolbox). The object-based classification (using a manual rule-set algorithm) of drone imagery with dominant land-cover features (i.e. water, land, Avicennia alba, Nypa fruticans, Rhizophora apiculata and Casuarina equisetifolia) provided the highest accuracy (overall accuracy (OA): 94.0±0.5% and specific producer accuracy (SPA): 97.0±9.3%) as compared to the Pleiades imagery (OA: 72.2±2.7% and SPA: 51.9±22.7%). In addition, the pixel-based classification (using a maximum likelihood algorithm) of drone imagery provided better accuracy (OA: 90.0±1.9% and SPA: 87.2±5.1%) compared to the Pleiades (OA: 82.8±3.5% and SPA: 80.4±14.3%). Nevertheless, the drone provided higher temporal resolution images, even on cloudy days, an exceptional benefit when working in a humid tropical climate. In terms of the user-costs, drone costs are much higher, but this becomes advantageous over satellite data for long-term monitoring of a small area. Due to the large data size of the drone imagery, its processing time was about ten times greater than that of the satellite image, and varied according to the various image processing techniques employed (in pixel-based classification, drone >50 hours, Pleiades <5 hours), constituting the main disadvantage of UAV remote sensing. However, the mangrove mapping based on the drone aerial photos provided unprecedented results for Setiu, and was proven to be a viable alternative to satellite-based monitoring/management of these ecosystems. The improvements of drone technology will help to make drone use even more competitive in the future.

Mangrove floristic and zonation patterns of Coringa, Kakinada Bay, East Coast of India

Abstract: Studies (1996–'99) on the community structure of a mangrove forest in Coringa Wildlife Sanctuary in the Godavari estuarine system on the East Coast of India revealed altogether 15 species of mangroves represented by 8 families and 10 genera besides, 6 associate plant species and 6 of marshgrass. Description of forest structure (PCQM method) included measures of species composition, tree density, basal area and spatial distribution patterns of component vegetation at 75 GPS fixed locations. Avicennia marina, A. officinalis, Excoecaria agallocha, Aegiceras corniculatum, Sonneratia apetala, Ceriops decandra, Rhizophora apiculata and R. mucronata were the important mangrove species. Tree density varied between 47 and 1731 stems/0.1 ha and basal area 0.1 and 10.9 m2/0.01 ha. With the help of multivariate analysis (PRIMER) and based on species composition and tree density, it was possible to subdivide the sites into five groups that showed characteristic zonation patterns. For example, E. agallocha was typical of landward locations. A. marina (along with A. officinalis and A. alba) represented sites at the bed level and neap high tide level. There was a large group of sites inhabited by diverse species (14) indicative of spring high tide level conditions. Tidal elevation and ambient salinity appeared important in determining the observed zonation.

Rates and drivers of mangrove deforestation in Southeast Asia, 2000–2012

Abstract: The mangrove forests of Southeast Asia are highly biodiverse and provide multiple ecosystem services upon which millions of people depend. Mangroves enhance fisheries and coastal protection, and store among the highest densities of carbon of any ecosystem globally. Mangrove forests have experienced extensive deforestation owing to global demand for commodities, and previous studies have identified the expansion of aquaculture as largely responsible. The proportional conversion of mangroves to different land use types has not been systematically quantified across Southeast Asia, however, particularly in recent years. In this study we apply a combined geographic information system and remote sensing method to quantify the key proximate drivers (i.e., replacement land uses) of mangrove deforestation in Southeast Asia between 2000 and 2012. Mangrove forests were lost at an average rate of 0.18% per year, which is lower than previously published estimates. In total, more than 100,000 ha of mangroves were removed during the study period, with aquaculture accounting for 30% of this total forest change. The rapid expansion of rice agriculture in Myanmar, and the sustained conversion of mangroves to oil palm plantations in Malaysia and Indonesia, are identified as additional increasing and under-recognized threats to mangrove ecosystems. Our study highlights frontiers of mangrove deforestation in the border states of Myanmar, on Borneo, and in Indonesian Papua. To implement policies that conserve mangrove forests across Southeast Asia, it is essential to consider the national and subnational variation in the land uses that follow deforestation.

The Vegetation of Wisconsin: An Ordination of Plant Communities.

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Internet-of-Things (IoT)-Based Smart Agriculture: Toward Making the Fields Talk

Abstract: Despite the perception people may have regarding the agricultural process, the reality is that today's agriculture industry is data-centered, precise, and smarter than ever. The rapid emergence of the Internet-of-Things (IoT) based technologies redesigned almost every industry including “smart agriculture” which moved the industry from statistical to quantitative approaches. Such revolutionary changes are shaking the existing agriculture methods and creating new opportunities along a range of challenges. This article highlights the potential of wireless sensors and IoT in agriculture, as well as the challenges expected to be faced when integrating this technology with the traditional farming practices. IoT devices and communication techniques associated with wireless sensors encountered in agriculture applications are analyzed in detail. What sensors are available for specific agriculture application, like soil preparation, crop status, irrigation, insect and pest detection are listed. How this technology helping the growers throughout the crop stages, from sowing until harvesting, packing and transportation is explained. Furthermore, the use of unmanned aerial vehicles for crop surveillance and other favorable applications such as optimizing crop yield is considered in this article. State-of-the-art IoT-based architectures and platforms used in agriculture are also highlighted wherever suitable. Finally, based on this thorough review, we identify current and future trends of IoT in agriculture and highlight potential research challenges.

On the Use of Unmanned Aerial Systems for Environmental Monitoring

Abstract: Environmental monitoring plays a central role in diagnosing climate and management impacts on natural and agricultural systems; enhancing the understanding of hydrological processes; optimizing the allocation and distribution of water resources; and assessing, forecasting, and even preventing natural disasters. Nowadays, most monitoring and data collection systems are based upon a combination of ground-based measurements, manned airborne sensors, and satellite observations. These data are utilized in describing both small- and large-scale processes, but have spatiotemporal constraints inherent to each respective collection system. Bridging the unique spatial and temporal divides that limit current monitoring platforms is key to improving our understanding of environmental systems. In this context, Unmanned Aerial Systems (UAS) have considerable potential to radically improve environmental monitoring. UAS-mounted sensors offer an extraordinary opportunity to bridge the existing gap between field observations and traditional air- and space-borne remote sensing, by providing high spatial detail over relatively large areas in a cost-effective way and an entirely new capacity for enhanced temporal retrieval. As well as showcasing recent advances in the field, there is also a need to identify and understand the potential limitations of UAS technology. For these platforms to reach their monitoring potential, a wide spectrum of unresolved issues and application-specific challenges require focused community attention. Indeed, to leverage the full potential of UAS-based approaches, sensing technologies, measurement protocols, postprocessing techniques, retrieval algorithms, and evaluation techniques need to be harmonized. The aim of this paper is to provide an overview of the existing research and applications of UAS in natural and agricultural ecosystem monitoring in order to identify future directions, applications, developments, and challenges.

The Botany Of Mangroves

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