Development of a Rapid Mangrove Zonation Mapping Workflow Using Sentinel 2-Derived Indices and Biophysical Dataset

Moderate to high resolution satellite imageries are commonly used in mapping mangrove cover from local to global scales. In addition to extent information, studies such as mangrove composition, ecology, and distribution analysis require further information on mangrove zonation. Mangrove zonation refers to unique sections within a mangrove forest being dominated by a similar family, genus, or species. This can be observed both in natural and planted mangrove forests. In this study, a mapping workflow was developed to detect zonation in test mangrove forest sites in Katunggan-It Ibajay (KII) Ecopark (Aklan), Bintuan (Coron), Bogtong, and Sagrada (Busuanga) in the Philippines and Fukido Mangrove Park (Ishigaki, Japan) using Sentinel-2 imagery. The methodology was then applied to generate a nationwide mangrove zonation map of the Philippines for year 2020. Combination of biophysical products, water, and vegetation indices were used as classification inputs including leaf area index (LAI), fractional vegetation cover (FVC), fraction of photosynthetically-active radiation (FAPAR), Canopy chlorophyll content (Cab), canopy water content (Cw), Normalized Difference Vegetation Index (NDVI), modified normalized difference water index (MNDWI), modified chlorophyll absorption in reflectance index (MCARI), and red-edge inflection point (REIP). Mangrove extents were first mapped using either the Maximum Likelihood Classification (MLC) algorithm or the Mangrove Vegetation Index (MVI)-based methodology. The biophysical and vegetation indices within these areas were stacked and transformed through Principal Component Analysis (PCA). Regions of Interest (ROIs) were selected on the PCA bands as training input to the MLC. Results show that mangrove zonation maps can highlight the major mangrove zones in the study sites, commonly limited up to genera level only except for genera with only one known species thriving in the area. Four zones were detected in KII Ecopark: Avicennia zone, Nypa zone, Avicennia mixed with Nypa zone, and mixed mangroves zones. For Coron and Busuanga, the mapped mangrove zones are mixed mangroves, Rhizophora zone and sparse/damaged zones. Three zones were detected in Fukido site: Rhizophora stylosa-dominant zone, Bruguiera gymnorrhiza-dominant zone, and mixed mangrove zones. The zonation maps were validated using field plot data and orthophotos generated from Unmanned Aerial System (UAS) surveys, with accuracies ranging from 75 to 100%.

The Comparison Between Certainty Factor Method and Index of Entropy Method For Landslide Hazard Assessment: South Western Chamba District, Himachal Pradesh, India

The present study reflects the contributions of geo-environmental factors that were analyzed for the development of landslide hazard zonation map using certainty factor method and index of entropy method. Heavy rainfall, unscientific excavation of slopes during road construction, expansion of infrastructure, and unplanned growth in urban population were the major factors for unstable slopes in the Lesser Himalayan region. Historical database, interpretation of satellite and Google earth images were used to identification of 248 landslides. The data collected using remote sensing images have been verified by conducting ground truth surveys undertaken from January 2018 to October 2020 in preparing the landslide inventory of the study area. Inventory thus generated was divided into 70% training and 30% validation datasets. Relationships between slope failure and its causative factors (relief, slope, aspect, curvature, lithology, soil, weathering, land use, lineament density, rainfall, and density of drainage networks) were analyzed by using certainty factor (CF) and index of entropy (IOE) methods. The analysis of all causative factors and assigning relative weightage values by using the index of entropy and certainty factor models leads to the generation of Landslide hazard zonation maps of the region. Finally, the landslide prediction accuracy of hazard zonation maps was calculated by drawing Successive Rate Curve (SRC) curves for both training and validation datasets. The outcomes of this study will be useful to government agencies, planners, decision-makers, researchers, and general land-use planners for sustainable development of the study area.

Landslide Susceptibility Analysis: A Case Study of Nainital Municipal Area

Landslides are one of the most recurrent natural phenomena that are of overwhelming significance in the Himalayas. The Himalayan terrain being under severe transmutation by human interference and excess urban penetration has led to triggering of landslides along with causing colossal damage to property and loss of life. Immense risk looms large all along the Himalayas with cumulating conditions that build the potentiality to landslides. The study of landslides has drawn worldwide attention mainly due to the aggravating socio-economic consequences as well as the increasing pressure of urbanization on the mountain environment. In order to reduce the damage and manage vulnerable areas, there is imperative need to formulate comprehensive Landslide Vulnerability and Susceptibility Zonation maps for different areas of the Himalayan region emphasizing the urbanized and burgeoning pockets. The concept of landslide susceptibility and landslide susceptibility assessment have been introduced in the past couple of decades and various methodologies have been developed for evaluating the devastating power of landslides and its associated processes. The ultimate aim is to evolve a method suitable for specific areas through which appropriate management measures can be taken to reduce the risk from potential landslides. Any approach towards LSZ would require identification of the conditions leading to slope failure, their systematic mapping and evaluation of their relative contributions by amalgamation of all factors in the ultimatum. The aim of this paper is to assess the various landslide vulnerability factors in Nainital Municipality area on raster-based GIS platform and generate landslide vulnerability and susceptibility maps. To achieve the objective, a detailed inventory of maps based on all parameters assessed has been generated of the study area from the satellite imageries and field data. The accuracy of results is being validated by constant observation and prediction accuracies.

Landslide Hazard Assessment Using Probabilistic and Statistical Approaches: A Case Study of Chamba Region, Himachal Pradesh, India

Landslides have adversely affected the southern region of Chamba district during past three decades. To minimize the damage to ecology and environment due to such natural calamities, landslide hazard zonation and mitigation measures are essential component to stabilize the natural slopes and other physiographic features. In order to remodeling lopsidedness in study area analytical hierarchy process and information value methods with applications of remote sensing and geographic information system (GIS) are utilized to delineate the most recumbent landslide hazard zones. Eleven-factor maps like slope gradient, slope aspect, relative relief, land use/ cover etc., were delineated using different sets of data like satellite images and field investigations etc. Depending upon the severity, landslide hazard maps (LHZ) were further divided based upon information value method and analytical hierarchy process models respectively, into five different categories very low (1.2% and 2.95%), low (5.31% and 4.27%), moderate (24.40% and 20.03%), high (29.26% and 31.03%), and very high (40.30% and 44.2%). These hazard maps obtained through both information value and analytical hierarchy process (AHP) were compared for accuracy using success rate curve (SRC) method. Accuracy of the hazard zonation maps was found to be 78.62% for AHP and 85.17% for Inf. Value models.

Private-land control and deforestation dynamics in the context of implementing the Native Forest Law in the Northern Argentinian Dry Chaco

SummarySubtropical dry forests are among the largest and most threatened terrestrial biomes worldwide. In Argentina, the Native Forest Law (NFL) was passed in 2007 to regulate deforestation by mandating the provincial zonation of forested areas, while the erection of fences has been an increasingly common mechanism of private-land control reinforcement in the region; this is mainly fuelled by imminent land-use changes, recent land transactions or subsidies from the NFL. We explored the dynamics between the erection of fences and deforestation in the Northern Argentinian Dry Chaco (NADC) during the implementation of the NFL. We found that a third of land deforested during 2000–2017 had been previously fenced, with the highest percentage (44%) occurring during the sanction of the NFL (2007) and the completion of the forest-zonation maps (2011). Only 34% of deforestation within fenced areas occurred in zones where deforestation was legally permitted. In total, 327 386 ha of forests had been fenced within NADC by 2017, representing areas of potential access restriction for local people, who historically used forest resources for survival. Additionally, 57% of the fenced area occurred in zones where deforestation was restricted. A novel remote-sensing application can serve as an early-warning tool for deforestation.

Performance of asmetric structures reviewed with based plastic design performance (case study of application on building in Pekan Baru)

Performance-Based Plastic Design (PBPD) is a structural analysis that can be used to review structural performance. This method is increasingly popular to be used in the earthquake-prone area. This method is based on energy method that can be applied to steel or concrete structures. Meanwhile, Indonesia has already SNI 1726:2102 to be used as a guide in designing the thrust load to review the level of structural performance. Both of these things need to be used as a reference in areas that were initially considered safe from the earthquake but based on the development of earthquake micro zonation maps, it is very possible to become potential areas that also become earthquake regions. For this reason, the case of the structure that was built in the Pekanbaru area was taken. From the analyses of structural behavior, the structure that applied PBPD has greater displacement than the structures that apply the thrust load of SNI 1726: 2012. The percentage of displacement that occurred was 8-37 %. Based on performance analysis, the structures according to PBPD shows a better level of performance to the application of SNI 1726: 2012 thrust load.

Landforms and rural development: The evolution of human settlements at alpine alluvial fans in the Admont Valley, Austria, since 1784 AD

We used two historical maps that cover vast areas of central and eastern Europe at rather large scale dating to 1784 (First Military Survey of the Habsburg Empire; total extent 640,000 km²; scale 1: 28,800) and 1824 (cadastral land register of Francis I; 670,000 km²; 1: 2,880) to extracted individual buildings located at several alluvial fans in one valley in Austria (Admont Valley). Historic buildings were mapped and compared with present building (airborne–laserscanning based; 2008–2017), geomorphic (landform distribution), geomorphodynamic (documented damaging events at torrents), and spatial planning (hazard zonation maps) data. Results show that 69.2% of all present buildings are located at only 7% of the study area. Whereas the 1784–data are too inaccurate and unprecise for detailed spatial analyses, the 1824–data are very accurate and precise allowing spatial and socio–economic insight into the population and building evolution over a 190–year period. Results show for instance that despite a tremendous increase in buildings (911 in 1824; 3554 in 2008–2017), the proportion of buildings exposed to torrents–related natural hazards significantly decreased by 10.4% for yellow (moderate–risk) and by 13.7% for red (high–risk) zones. Similar historio–geomorphological studies as presented here might be accomplished in other countries in central and eastern Europe covered by the indicated historical map products.