Factors Affecting the Spatial Distribution of Black Mangrove on the Dredged-Material or “Spoil” Islands in the Lower Laguna Madre of Texas

Research was conducted to evaluate the spatial distribution of black mangrove (Avicennia germinans) on the dredged-material or “spoil” islands of the Lower Laguna Madre of Texas. Aerial color-infrared (CIR) photographs revealed the presence of black mangrove stands on many of the islands located south of the Arroyo Colorado (a distributary of the Rio Grande which empties into the Laguna Madre), but failed to detect significant mangrove stands on islands located north of the Arroyo. Analysis of CIR photographs and supervised image classifications for individual islands suggested a concentration of black mangrove along western shorelines and relatively low interior areas of islands, although relatively small and localized mangrove stands were clearly evident along eastern shorelines at several locations. These observations were consistent with ground surveys which indicated significantly higher mangrove densities along western vs eastern shorelines of selected islands (0.6 and 0.1 plants/m2, respectively; P \u3c 0.05), but no difference between ratios of small to large plants in stands located along western vs eastern shorelines (1.6 and 1.4, respectively; P\u3e0.05). The most plausible explanation for these trends is that wave action caused by prevailing southeasterly winds during most of the year may impede or prevent the establishment of black mangrove propagules (germinated „seeds‟) along eastern shorelines of islands which otherwise constitute suitable habitat for A. germinans. If this interpretation is correct, development of planting strategies designed to facilitate establishment of black mangrove stands along shorelines subject to turbulent wave action will be a requisite to the use of this important native plant species for erosion prevention and mitigation on spoil islands in the Lower Laguna Madre

The Biological Flora of Coastal Dunes and Wetlands: Avicennia germinans (L.) L.

Avicennia germinans (L.) L. is a pantropical, subtropical, and occasionally warm-temperate mangrove species that occurs on shorelines that have a broad horizontal tidal range. Also known as black mangrove, stands typically develop under anoxic, water-logged conditions in substrates of silt or clay. Black mangrove can tolerate salinity values ranging from 0 to 90 parts per thousand. Salt is excreted from salt glands on both leaf epidermal surfaces, and aerosol salt spray and salt crystals are frequently observed on the upper leaf epidermis. Avicennia germinans is viviparous. The embryos have no dormancy requirements, and there is no seed bank. This mangrove species has the northernmost distributional range of any mangrove species in North America. It occurs in Louisiana and northern Florida. Color-infrared photography and airborne video imagery techniques have been used successfully to map stands of black mangrove on subtropical coastal shorelines. Reforestation efforts using seedlings and saplings have been successful in several areas of the tropics and subtropics. Avicennia germinans stands play an important role in ecosystem functions as a natural barrier to coastal erosion caused by tropical storms, as habitat for a wide range of organisms in intertidal food chains, and as a carbon repository

Detection of Temporal Changes in Vegetative Cover on South Padre Island, Texas Using Image Classifications Derived from Aerial Color-Infrared Photographs

Supervised image classifications developed from 23 x 23 cm aerial color-infrared aerial photographs (1:5,000 scale) were used to evaluate temporal changes in vegetative cover occurring within three 150 x 300-m research sites on South Padre Island, Texas. Use of high-resolution digitized imagery (ground pixel resolution of ca. 0.1 m) and survey-grade GPS for positional measurements of ground control points (20-25 1.0m2 targets within each research site) resulted in consistently high levels of geometric accuracy, with root mean square errors (RMSEs) ranging between 0.397 – 2.867. Similarly, use of relatively simple information categories (dry and wet sand, live and dead vegetative cover, and water) resulted in supervised image classifications with consistently high levels of overall thematic accuracy (90.0 – 98.0%). Temporal comparisons of image classifications using a cross-tabulation procedure indicated that changes in total vegetative cover had been minimal at most locations during the course the two-year study (2003-2005). However, a localized but significant disruption of native vegetation caused by the dumping of sand by highway maintenance crews was detected in one of the study sites (2004), and ground inspection revealed numerous other sand-dumping sites at various locations on the barrier island. In the first situation, comparison of CIR aerial photographs acquired before and after the sand-dumping incident provided a reliable means by which to evaluate the extent of damage caused by the dumped sand, and to monitor its eventual recovery as a result of recolonization by native plant species

A remote sensing approach to the quantification of local to global scale social-ecological impacts of anthropogenic landscape changes

A thesis submitted in partial fulfillment of the requirements for the degree of Doctor in Information Management, specialization in Geographic Information SystemsLanduse and Landcover (LULC) is the common aspect that influences several ecological issues, environmental degradations, changes in Land Surface Temperature (LST), hydrological changes and ecosystem function at regional to global level. Research on the drivers and progressions of LULC change has been key to developing models that can project and predict future LULC extent, level and patterns under different assumptions of socioeconomic, ecological and environmental situations. Rapid and extensive urbanization and Urban Sprawl (US), propelled by rapid population growth leads to the shrinkage of productive agricultural lands, boosting mining, decrease in surface permeability and the emergence of Urban Heat Islands (UHI), and in turn, adversely affects the provision of ecosystem services. Mining for resources extraction may lead to geological and associated environmental changes due to ground movements, collision with mining cavities, and deformation of aquifers. Geological changes may continue in a reclaimed mine area, and the deformed aquifers may entail a breakdown of substrates and an increase in ground water tables, which may cause surface area inundation. Consequently, a reclaimed mine area may experience surface area collapse, i.e., subsidence, and degradation of vegetation productivity. The greater changes in LULC, US, LST and vegetation dynamics due to increasing human population not only affects inland forest and wetland, it also directly influences coastal forest lands such as mangroves, peat swamps and riparian forest and threats to ecosystem services. Mangroves provide valuable provisioning (e.g. aquaculture, fisheries, fuel, medicine, textiles), regulation (e.g. shoreline protection, erosion control, climate regulation), supporting (nutrient cycling, nursery habitat), and cultural (recreation and tourism) ecosystem services with an important impact on human well-being. However, the mangrove forest is highly threatened due to climate changes, and human activities which ignore the ecological and economic value of these habitats, contributing to its degradation. There is an increasing number of studies about mangrove distribution, changes and re-establishment activities, denoting a growing attentiveness on the value of these coastal wetland ecosystems. Most of these studies address mangrove degradation drivers at regional or local levels. However, there has not been yet enough assessment on the drivers of mangrove degradation at global level. Thus, complexity of inland and coastal landscape degradation should be addressed using multidisciplinary methodology and conditions. Therefore, this dissertation aimed to assess the impact of LULC associated with vegetation, temperature and wetland changes. To understand the relation among three different types of landscape changes associated with anthropogenic activities: Urbanization, Geological changes and Forest degradation at local to global level, we have selected thirty-three global regions. In chapter 2, We employed the Random Forest (RF) classification on Landsat imageries from 1991, 2003, and 2016, and computed six landscape metrics to delineate the extent of urban areas within a 10km suburban buffer of Chennai city, Tamilnadu, India. The level of US was then quantified using Renyi’s entropy. A land change model was subsequently used to project land cover for 2027. A 70.35% expansion in urban areas was observed mainly towards the suburban periphery of Chennai between 1991 and 2016. The Renyi’s entropy value for year 2016 was 0.9, exhibiting a two-fold level of US when compared to 1991. The spatial metrics values indicate that the existing urban areas became denser and the suburban agricultural, forests and particularly barren lands were transformed into fragmented urban settlements. The forecasted land cover for 2027 indicates a conversion of 13,670.33 ha (16.57% of the total landscape) of existing forests and agricultural lands into urban areas with an associated increase in the entropy value to 1.7, indicating a tremendous level of US. Our study provides useful metrics for urban planning authorities to address the social-ecological consequences of US and to protect ecosystem services. In chapter 3, We studied landscape dynamics in Kirchheller Heide, Germany, which experienced extensive soil movement due to longwall mining without stowing, using Landsat imageries between 2013 and 2016. A Random Forest image classification technique was applied to analyse landuse and landcover dynamics, and the growth of wetland areas was assessed using a Spectral Mixture Analysis (SMA). We also analyzed the changes in vegetation productivity using a Normalized Difference Vegetation Index (NDVI). We observed a 19.9% growth of wetland area within four years, with 87.2% growth in the coverage of two major waterbodies in the reclaimed mine area. NDVI values indicate that the productivity of 66.5% of vegetation of the Kirchheller Heide was degraded due to changes in ground water tables and surface flooding. Our results inform environmental management and mining reclamation authorities about the subsidence spots and priority mitigation areas from land surface and vegetation degradation in Kirchheller Heide. In chapter 4, We demonstrated the advantage of fusing imageries from multiple sensors for LULC change assessments as well as for assessing surface permeability and temperature and UHI emergence in a fast-growing city, i.e. Tirunelveli, Tamilnadu, India. IRS-LISSIII and Landsat-7 ETM+ imageries were fused for 2007 and 2017, and classified using a Rotation Forest (RF) algorithm. Surface permeability and temperature were then quantified using Soil-Adjusted Vegetation Index (SAVI) and Land Surface Temperature (LST) index, respectively. Finally, we assessed the relationship between SAVI and LST for entire Tirunelveli as well as for each LULC zone, and also detected UHI emergence hot spots using a SAVI-LST combined metric. Our fused images exhibited higher classification accuracies, i.e. overall kappa coefficient values, than non-fused images. We observed an overall increase in the coverage of urban (dry, real estate plots and built-up) areas, while a decrease for vegetated (cropland and forest) areas in Tirunelveli between 2007 and 2017. The SAVI values indicated an extensive decrease in surface permeability for Tirunelveli overall and also for almost all LULC zones. The LST values showed an overall increase of surface temperature in Tirunelveli with the highest increase for urban built-up areas between 2007 and 2017. LST also exhibited a strong negative association with SAVI. South-eastern built-up areas in Tirunelveli were depicted as a potential UHI hotspot, with a caution for the Western riparian zone for UHI emergence in 2017. Our results provide important metrics for surface permeability, temperature and UHI monitoring, and inform urban and zonal planning authorities about the advantages of satellite image fusion. In chapter 5, We identified mangrove degradation drivers at regional and global levels resulted from decades of research data (from 1981 to present) of climate variations (seal-level rising, storms, precipitation, extremely high water events and temperature), and human activities (pollution, wood extraction, aquaculture, agriculture and urban expansion). This information can be useful for future research on mangroves, and to help delineating global planning strategies which consider the correct ecological and economic value of mangroves protecting them from further loss.O uso e a cobertura da Terra (UCT) são o aspeto comum que influencia várias questões ecológicas, degradações ambientais, mudanças na temperatura da superfície terrestre, mudanças hidrológicas, e de funções dos ecossistemas a nível regional e global. A investigação sobre os determinantes e progressão da mudança de UCT tem sido fundamental para o desenvolvimento de modelos que podem projetar e prever a extensão, o nível e os padrões futuros de UCT sob diferentes hipóteses de situações socioeconómicas, ecológicas e ambientais. A rápida e extensa urbanização e expansão urbana impulsionada pelo rápido crescimento populacional, levou ao encolhimento de terras agrícolas produtivas, impulsionando a mineração, a diminuição da permeabilidade da superfície e o surgimento de ilhas urbanas. Por outro lado, tem afetado negativamente a produção de serviços de ecossistemas. A mineração para extração de recursos pode levar a mudanças geológicas e ambientais devido a movimentos do solo, colisão com cavidades de mineração e deformação de aquíferos. As mudanças geológicas podem continuar numa área de mina recuperada, e os aquíferos deformados podem acarretar uma quebra de substratos e um aumento nos lençóis freáticos, causando a inundação na superfície. Consequentemente, uma área de mina recuperada pode sofrer um colapso à superfície, provocando o afundamento e a degradação da produtividade da vegetação. As mudanças na UCT, no crescimento urbano rápido, na temperatura da superfície terrestre e na dinâmica da vegetação devido ao aumento da população humana não afetam apenas a floresta interior e as zonas húmidas. Estas também influenciam diretamente as terras florestais costeiras, tais como mangais, pântanos e florestas ribeirinhas, ameaçando os serviços de ecossistemas. Os mangais proporcionam um aprovisionamento valioso (por exemplo, aquacultura, pesca, combustível, medicamentos, têxteis), a regulação (por exemplo, proteção da linha de costa, controlo da erosão, regulação do clima), os serviços de ecossistema de apoio (ciclo de nutrientes, habitats) e culturais (recreação e turismo) com um impacto importante no bem-estar humano. No entanto, a floresta de mangal é altamente ameaçada devido às mudanças climáticas e às atividades humanas que ignoram o valor ecológico e económico desses habitats, contribuindo para a sua degradação. Há um número crescente de estudos sobre distribuição, mudança e atividades de restabelecimento de mangais, denotando uma crescente atenção sobre o valor desses ecossistemas costeiros de zonas húmidas. A maioria desses estudos aborda os fatores de degradação dos mangais a nível regional ou local. No entanto, ainda não há avaliação suficiente sobre os determinantes da degradação dos mangais a nível global. Assim, a complexidade da degradação da paisagem interior e costeira deve ser abordada usando uma metodologia multidisciplinar. Portanto, esta dissertação teve, também, como objetivo avaliar o impacto do UCT associado à vegetação, temperatura e mudanças de zonas húmidas. Para compreender a relação entre a dinâmica da paisagem associada às atividades antrópicas a nível local e global, selecionámos quatro áreas de estudo, duas da Ásia, uma da Europa e outro estudo a nível global. No capítulo 2, empregamos a classificação Random Forest (RF) nas imagens Landsat de 1991, 2003 e 2016, e computamos seis métricas de paisagem para delinear a extensão das áreas urbanas numa área de influência suburbana de 10 km da cidade de Chennai, Tamil Nadu, Índia. O nível de crescimento urbano rápido foi quantificado usando a entropia de Renyi. Um modelo de UCT foi posteriormente usado para projetar a cobertura de terra para 2027. Uma expansão de 70,35% nas áreas urbanas foi observada principalmente para a periferia suburbana de Chennai entre 1991 e 2016. O valor de entropia do Renyi para 2016 foi de 0,9, exibindo uma duplicação do nível de crescimento urbano rápido quando comparado com 1991. Os valores das métricas espaciais indicam que as áreas urbanas existentes se tornaram mais densas e as terras agrícolas, florestas e terras particularmente áridas foram transformadas em assentamentos urbanos fragmentados. A previsão de cobertura da Terra para 2027 indica uma conversão de 13.670,33 ha (16,57% da paisagem total) de florestas e terras agrícolas existentes em áreas urbanas, com um aumento associado no valor de entropia para 1,7, indicando um tremendo nível de crescimento urbano rápido. O nosso estudo fornece métricas úteis para as autoridades de planeamento urbano para lidarem com as consequências socio-ecológicas do crescimento urbano rápido e para proteger os serviços de ecossistemas. No capítulo 3, estudamos a dinâmica da paisagem em Kirchheller Heide, Alemanha, que experimentou um movimento extensivo do solo devido à mineração, usando imagens Landsat entre 2013 e 2016. Uma técnica de classificação de imagem Random Forest foi aplicada para analisar dinâmicas de UCT e o crescimento das áreas de zonas húmidas foi avaliado usando uma Análise de Mistura Espectral. Também analisámos as mudanças na produtividade da vegetação usando um Índice de Vegetação por Diferença Normalizada (NDVI). Observámos um crescimento de 19,9% da área húmida em quatro anos, com um crescimento de 87,2% de dois principais corpos de água na área de mina recuperada. Valores de NDVI indicam que a produtividade de 66,5% da vegetação de Kirchheller Heide foi degradada devido a mudanças nos lençóis freáticos e inundações superficiais. Os resultados informam as autoridades de gestão ambiental e recuperação de mineração sobre os pontos de subsidência e áreas de mitigação prioritárias da degradação da superfície e da vegetação da terra em Kirchheller Heide. No capítulo 4, demonstramos a vantagem de fusionar imagens de múltiplos sensores para avaliações de mudanças de UCT, bem como para avaliar a permeabilidade, temperatura da superfície e a emergência do ilhas de calor numa cidade em rápido crescimento, Tirunelveli, Tamilnadu, Índia. As imagens IRS-LISSIII e Landsat-7 ETM + foram fusionadas para 2007 e 2017, e classificadas usando um algoritmo de Random Forest (RF). A permeabilidade de superfície e a temperatura foram então quantificadas usando-se o Índice de Vegetação Ajustada pelo Solo (SAVI) e o Índice de Temperatura da Superfície Terrestre (LST), respectivamente. Finalmente, avaliamos a relação entre SAVI e LST para Tirunelveli, bem como para cada zona de UCT, e também detetamos a emergência de pontos quentes de emergência usando uma métrica combinada de SAVI-LST. As nossas imagens fusionadas exibiram precisões de classificação mais altas, ou seja, valores globais do coeficiente kappa, do que as imagens não fusionadas. Observámos um aumento geral na cobertura de áreas urbanas (áreas de terrenos secos e construídas), e uma diminuição de áreas com vegetação (plantações e florestas) em Tirunelveli entre 2007 e 2017. Os valores de SAVI indicaram uma extensa diminuição na superfície de permeabilidade para Tirunelveli e também para quase todas as classes de UCT. Os valores de LST mostraram um aumento global da temperatura da superfície em Tirunelveli, sendo o maior aumento para as áreas urbanas entre 2007 e 2017. O LST também apresentou uma forte associação negativa com o SAVI. As áreas urbanas do Sudeste de Tirunelveli foram representadas como um potencial ponto quente, com uma chamada de atenção para a zona ribeirinha ocidental onde foi verificada a emergência de uma ilha de calor em 2017. Os nossos resultados fornecem métricas importantes sobre a permeabilidade da superfície, temperatura e monitoramento de ilhas de calor e informam as autoridades de planeamento sobre as vantagens da fusão de imagens de satélite. No capítulo 5, identificamos os fatores de degradação dos mangais a nível regional e global resultantes de décadas de dados de investigação (de 1981 até o presente) de variações climáticas (aumento do nível das águas do mar, tempestades, precipitação, eventos extremos de água e temperatura) e atividades humanas (poluição, extração de madeira, aquacultura, agricultura e expansão urbana). Estas informações podem ser úteis para investigações futuras sobre mangais e para ajudar a delinear estratégias de planeamento global que considerem o valor ecológico e económico dos mangais, protegendo-os de novas perdas

Remotely sensed imagery data application in mangrove forest: a review

The mangrove forest ecosystem acts as a shield against the destructive tidal waves, preventing the coastal areas and other properties nearby from severe damages; this protective function certainly deserves attention from researchers to undertake further investigation and exploration. Mangrove forest provides different goods and services. The unique environmental factors affecting the growth of mangrove forest are as follows: distance from the sea or the estuary bank, frequency and duration of tidal inundation, salinity, and composition of the soil. These crucial factors may under certain circumstances turn into obstacles in accessing and managing the mangrove forest. One effective method to circumvent this shortcoming is by using remotely sensed imagery data, which offers a more accurate way of measuring the ecosystem and a more efficient tool of managing the mangrove forest. This paper attempts to review and discuss the usage of remotely sensed imagery data in mangrove forest management, and how they will improve the accuracy and precision in measuring the mangrove forest ecosystem. All types of measurements related to the mangrove forest ecosystem, such as detection of land cover changes, species distribution mapping and disaster observation should take advantage of the advanced technology; for example, adopting the digital image processing algorithm coupled with high-resolution image available nowadays. Thus, remote sensing is a highly efficient, low-cost and time-saving technique for mangrove forest measurement. The application of this technique will further add value to the mangrove forest and enhance its in-situ conservation and protection programmes in combating the effects of the rising sea level due to climate change

Coastal and Inland Aquatic Data Products for the Hyperspectral Infrared Imager (HyspIRI)

The HyspIRI Aquatic Studies Group (HASG) has developed a conceptual list of data products for the HyspIRI mission to support aquatic remote sensing of coastal and inland waters. These data products were based on mission capabilities, characteristics, and expected performance. The topic of coastal and inland water remote sensing is very broad. Thus, this report focuses on aquatic data products to keep the scope of this document manageable. The HyspIRI mission requirements already include the global production of surface reflectance and temperature. Atmospheric correction and surface temperature algorithms, which are critical to aquatic remote sensing, are covered in other mission documents. Hence, these algorithms and their products were not evaluated in this report. In addition, terrestrial products (e.g., land use land cover, dune vegetation, and beach replenishment) were not considered. It is recognized that coastal studies are inherently interdisciplinary across aquatic and terrestrial disciplines. However, products supporting the latter are expected to already be evaluated by other components of the mission. The coastal and inland water data products that were identified by the HASG, covered six major environmental and ecological areas for scientific research and applications: wetlands, shoreline processes, the water surface, the water column, bathymetry and benthic cover types. Accordingly, each candidate product was evaluated for feasibility based on the HyspIRI mission characteristics and whether it was unique and relevant to the HyspIRI science objectives

Multiple stable states and catastrophic shifts in coastal wetlands: Progress, challenges, and opportunities in validating theory using remote sensing and other methods

open5siThe analysis by K.B. Moffett was partially supported by National Science Foundation grant EAR-1013843 to Stanford University. Any opinions, findings, and onclusions or recommendations expressed in this material are those of the authors and do not necessarily reflect the views of the National Science Foundation. The analysis by W. Nardin was partially supported by Office of Naval Research Award N00014-14-1-0114 to Boston University. The analysis by C. Wang was partially supported by National Natural Science Funds of China (41376120 and 41401413). The analysis by C. Wang and S. Temmerman was also partially supported by the European Union Programme Erasmus Mundus External Cooperation Window (EMECW)-Lot 14-China. K.B. Moffett thanks B.C. Smith for the analysis for the Wax Lake Delta example of Section 4.2 and S.M. Gorelick for the funding leading to the San Francisco Bay example of Section 4.3. W. Nardin thanks S. Fagherazzi and C. Woodcock for the funding leading to the Mekong River Delta example of Section 4.1. S. Silvestri thanks M. Marani for inspiring ideas and research on coastal wetland processes.Multiple stable states are established in coastal tidal wetlands (marshes, mangroves, deltas, seagrasses) by ecological, hydrological, and geomorphological feedbacks. Catastrophic shifts between states can be induced by gradual environmental change or by disturbance events. These feedbacks and outcomes are key to the sustainability and resilience of vegetated coastlines, especially as modulated by human activity, sea level rise, and climate change. Whereas multiple stable state theory has been invoked to model salt marsh responses to sediment supply and sea level change, there has been comparatively little empirical verification of the theory for salt marshes or other coastal wetlands. Especially lacking is long-term evidence documenting if or how stable states are established and maintained at ecosystem scales. Laboratory and field-plot studies are informative, but of necessarily limited spatial and temporal scope. For the purposes of long-term, coastal-scale monitoring, remote sensing is the best viable option. This review summarizes the above topics and highlights the emerging promise and challenges of using remote sensing-based analyses to validate coastal wetland dynamic state theories. This significant opportunity is further framed by a proposed list of scientific advances needed to more thoroughly develop the field.openMoffett K.B.; Nardin W.; Silvestri S.; Wang C.; Temmerman S.Moffett K.B.; Nardin W.; Silvestri S.; Wang C.; Temmerman S

Remote sensing of mangrove composition and structure in the Galapagos Islands

Mangroves are unique inter-tidal ecosystems that provide valuable ecosystem goods and services. This dissertation investigates new methods of characterizing mangrove forests using remote sensing with implications for mapping and modeling ecosystem goods and services. Specifically, species composition, leaf area, and canopy height are investigated for mangroves in the Galapagos Islands. The Galapagos Islands serve as an interesting case study where environmental conditions are highly variable over short distances producing a wide range of mangrove composition and structure to examine. This dissertation reviews previous mangrove remote sensing studies and seeks to address missing gaps. Specifically, this research seeks to examine pixel and object-based methods for mapping mangrove species, investigate the usefulness of spectral and spatial metrics to estimate leaf area, and compare existing global digital surface models with a digital surface model extracted from new very high resolution imagery. The major findings of this research include the following: 1) greater spectral separability between true mangrove and mangrove associate species using object-based image analysis compared to pixel-based analysis, but a lack of separability between individual mangrove species, 2) the demonstrated necessity for novel machine-learning classification techniques rather than traditional clustering classification algorithms, 3) significant but weak relationships between spectral vegetation indices and leaf area, 4) moderate to strong relationships between grey-level co-occurrence matrix image texture and leaf area at the individual species level, 5) similar accuracy between a very high resolution stereo optical digital surface model a coarse resolution InSAR product to estimate canopy height with improved accuracy using a hybrid model of these two products. The results demonstrate advancements in remote sensing technology and technique, but further challenges remain before these methods can be applied to monitoring and modeling applications. Based on these results, future research should focus on emerging technologies such as hyperspectral, very high resolution InSAR, and LiDAR to characterize mangrove forest composition and structure