scholarly journals Land Cover Dynamics on the Lower Ganges–Brahmaputra Delta: Agriculture–Aquaculture Transitions, 1972–2017

2021 ◽  
Vol 13 (23) ◽  
pp. 4799
Author(s):  
Daniel Sousa ◽  
Christopher Small
Keyword(s):  
Size Distribution ◽  
Spatial Scales ◽  
Water Area ◽  
Water Bodies ◽  
Spatial Extent ◽  
Spectral Signature ◽  
Standing Water ◽  
Multiple Thresholds ◽  
Land Cover Dynamics ◽  
Decision Boundaries

Aquaculture in tropical and subtropical developing countries has expanded in recent years. This practice is controversial due to its potential for serious economic, food security, and environmental impacts—especially for intensive operations in and near mangrove ecosystems, where many shrimp species spawn. While considerable effort has been directed toward understanding aquaculture impacts, maps of spatial extent and multi-decade spatiotemporal dynamics remain sparse. This is in part because aquaculture ponds (ghers) can be challenging to distinguish from other shallow water targets on the basis of water-leaving radiance alone. Here, we focus on the Lower Ganges–Brahmaputra Delta (GBD), one of the most expansive areas of recent aquaculture growth on Earth and adjacent to the Sundarbans mangrove forest, a biodiversity hotspot. We use a combination of MODIS 16-day EVI composites and 45 years (1972–2017) of Landsat observations to characterize dominant spatiotemporal patterns in the vegetation phenology of the area, identify consistent seasonal optical differences between flooded ghers and other land uses, and quantify the multi-decade expansion of standing water bodies. Considerable non-uniqueness exists in the spectral signature of ghers on the GBD, propagating into uncertainty in estimates of spatial extent. We implement three progressive decision boundaries to explicitly quantify this uncertainty and provide liberal, moderate, and conservative estimates of flooded gher extent on three different spatial scales. Using multiple extents and multiple thresholds, we quantify the size distribution of contiguous regions of flooded gher extent at ten-year intervals. The moderate threshold shows standing water area within Bangladeshi polders to have expanded from less than 300 km2 in 1990 to over 1400 km2 in 2015. At all three scales investigated, the size distribution of standing water bodies is increasingly dominated by larger, more interconnected networks of flooded areas associated with aquaculture. Much of this expansion has occurred in immediate proximity to the Bangladeshi Sundarbans.

Spatial Analysis of Water Resources Data in Selected Districts of Bihar

2019 ◽  
Vol 6 (03) ◽  
Author(s):  
MANIBHUSHAN MANIBHUSHAN ◽  
AKRAM AHMED
Keyword(s):  
Water Resources ◽  
Spatial Data ◽  
Water Bodies ◽  
Tabular Form ◽  
Tabular Data ◽  
Standing Water ◽  
Attribute Data ◽  
State Study ◽  
Scientific Personnel ◽  
Bihar State

The main aim of this study is to apply geographic information system (GIS) and data mining techniques to get the attribute data in a spatial and tabular form related to district wise availability of standing water bodies in their area and number of Bihar state. An analysis has been done on available spatial data and maps to get non-spatial/ tabular data, which are in a more easily understandable form. Data extracted district-wise related to area and number of standing water bodies according to their size of Bihar state. Study shows that the number and area of standing water bodies in Madhubani, East Champaran and Patna districts are 2185, 1753, 350 and 2355.42, 6752.36 and 8429.68 ham respectively. In this way, number and area of standing water bodies of other districts of Bihar are also extracted from geodatabases and digitized maps. This type of information is more useful than the spatial data because a common person is able to understand these tabular data and they can use this data for their own purposes. These data can be utilized by scientific personnel as well as farmers and that will be used in agriculture for better utilization of water resources to enhance agricultural productivity and income of farmers of Bihar state.

scholarly journals Deriving Tree Size Distributions of Tropical Forests from Lidar

2021 ◽  
Vol 13 (1) ◽  
pp. 131
Author(s):  
Franziska Taubert ◽  
Rico Fischer ◽  
Nikolai Knapp ◽  
Andreas Huth
Keyword(s):  
Size Distribution ◽  
Spatial Scales ◽  
Basal Area ◽  
Tree Height ◽  
Tree Size ◽  
Diameter Distribution ◽  
Forest Inventories ◽  
Allometric Relations ◽  
Lidar Measurements ◽  
Derived Data

Remote sensing is an important tool to monitor forests to rapidly detect changes due to global change and other threats. Here, we present a novel methodology to infer the tree size distribution from light detection and ranging (lidar) measurements. Our approach is based on a theoretical leaf–tree matrix derived from allometric relations of trees. Using the leaf–tree matrix, we compute the tree size distribution that fit to the observed leaf area density profile via lidar. To validate our approach, we analyzed the stem diameter distribution of a tropical forest in Panama and compared lidar-derived data with data from forest inventories at different spatial scales (0.04 ha to 50 ha). Our estimates had a high accuracy at scales above 1 ha (1 ha: root mean square error (RMSE) 67.6 trees ha−1/normalized RMSE 18.8%/R² 0.76; 50 ha: 22.8 trees ha−1/6.2%/0.89). Estimates for smaller scales (1-ha to 0.04-ha) were reliably for forests with low height, dense canopy or low tree height heterogeneity. Estimates for the basal area were accurate at the 1-ha scale (RMSE 4.7 tree ha−1, bias 0.8 m² ha−1) but less accurate at smaller scales. Our methodology, further tested at additional sites, provides a useful approach to determine the tree size distribution of forests by integrating information on tree allometries.

scholarly journals Downscaling MODIS Surface Reflectance to Improve Water Body Extraction

2015 ◽  
Vol 2015 ◽  
pp. 1-13 ◽  
Author(s):  
Xianghong Che ◽  
Min Feng ◽  
Hao Jiang ◽  
Jia Song ◽  
Bei Jia
Keyword(s):  
Surface Water ◽  
Water Body ◽  
Terrestrial Ecosystems ◽  
Water Area ◽  
Water Bodies ◽  
Tibet Plateau ◽  
Surface Reflectance ◽  
Discrimination Ability ◽  
Automated Method ◽  
Landsat 7

Inland surface water is essential to terrestrial ecosystems and human civilization. Accurate mapping of surface water dynamic is vital for both scientific research and policy-driven applications. MODIS provides twice observation per day, making it perfect for monitoring temporal water dynamic. Although MODIS provides two bands at 250 m resolution, accurately deriving water area always depends on observations from the spectral bands with 500 m resolution, which limits its discrimination ability over small lakes and rivers. The paper presents an automated method for downscaling the 500 m MODIS surface reflectance (SR) to 250 m to improve the spatial discrimination of water body extraction. The method has been tested at Co Ngoin and Co Bangkog in Qinghai-Tibet plateau. The downscaled SR and the derived water bodies were compared to SR and water body mapped from Landsat-7 ETM+ images were acquired on the same date. Consistency metrics were calculated to measure their agreement and disagreement. The comparisons indicated that the downscaled MODIS SR showed significant improvement over the original 500 m observations when compared with Landsat-7 ETM+ SR, and both commission and omission errors were reduced in the derived 250 m water bodies.

scholarly journals Imaging spectroscopy links aspen genotype with below-ground processes at landscape scales

2014 ◽  
Vol 369 (1643) ◽  
pp. 20130194 ◽  
Author(s):  
Michael D. Madritch ◽  
Clayton C. Kingdon ◽  
Aditya Singh ◽  
Karen E. Mock ◽  
Richard L. Lindroth ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Populus Tremuloides ◽  
Spatial Scales ◽  
Imaging Spectroscopy ◽  
Spectral Signature ◽  
Spectral Variation ◽  
Fine Scale ◽  
Below Ground ◽  
Landscape Scales ◽  
Spectrometer Data

Fine-scale biodiversity is increasingly recognized as important to ecosystem-level processes. Remote sensing technologies have great potential to estimate both biodiversity and ecosystem function over large spatial scales. Here, we demonstrate the capacity of imaging spectroscopy to discriminate among genotypes of Populus tremuloides (trembling aspen), one of the most genetically diverse and widespread forest species in North America. We combine imaging spectroscopy (AVIRIS) data with genetic, phytochemical, microbial and biogeochemical data to determine how intraspecific plant genetic variation influences below-ground processes at landscape scales. We demonstrate that both canopy chemistry and below-ground processes vary over large spatial scales (continental) according to aspen genotype. Imaging spectrometer data distinguish aspen genotypes through variation in canopy spectral signature. In addition, foliar spectral variation correlates well with variation in canopy chemistry, especially condensed tannins. Variation in aspen canopy chemistry, in turn, is correlated with variation in below-ground processes. Variation in spectra also correlates well with variation in soil traits. These findings indicate that forest tree species can create spatial mosaics of ecosystem functioning across large spatial scales and that these patterns can be quantified via remote sensing techniques. Moreover, they demonstrate the utility of using optical properties as proxies for fine-scale measurements of biodiversity over large spatial scales.

Unoccupied aerial vehicle-assisted monitoring of benthic vegetation in the coastal zone enhances the quality of ecological data

2021 ◽  
pp. 030913332110520
Author(s):  
Niels Svane ◽  
Troels Lange ◽  
Sara Egemose ◽  
Oliver Dalby ◽  
Aris Thomasberger ◽  
...  
Keyword(s):  
Zostera Marina ◽  
Spatial Scales ◽  
Fucus Vesiculosus ◽  
Ecosystem Dynamics ◽  
Spatial Extent ◽  
Total Biomass ◽  
Ecological Data ◽  
Error Matrix ◽  
Object Based ◽  
Spatio Temporal

Traditional monitoring (e.g., in-water based surveys) of eelgrass meadows and perennial macroalgae in coastal areas is time and labor intensive, requires extensive equipment, and the collected data has a low temporal resolution. Further, divers and Remotely Operated Vehicles (ROVs) have a low spatial extent that cover small fractions of full systems. The inherent heterogeneity of eelgrass meadows and macroalgae assemblages in these coastal systems makes interpolation and extrapolation of observations complicated and, as such, methods to collect data on larger spatial scales whilst retaining high spatial resolution is required to guide management. Recently, the utilization of Unoccupied Aerial Vehicles (UAVs) has gained popularity in ecological sciences due to their ability to rapidly collect large amounts of area-based and georeferenced data, making it possible to monitor the spatial extent and status of SAV communities with limited equipment requirements compared to ROVs or diver surveys. This paper is focused on the increased value provided by UAV-based, data collection (visual/Red Green Blue imagery) and Object Based Image Analysis for gaining an improved understanding of eelgrass recovery. It is demonstrated that delineation and classification of two species of SAV ( Fucus vesiculosus and Zostera marina) is possible; with an error matrix indicating 86–92% accuracy. Classified maps also highlighted the increasing biomass and areal coverage of F. vesiculosus as a potential stressor to eelgrass meadows. Further, authors derive a statistically significant conversion of percentage cover to biomass ( R2 = 0.96 for Fucus vesiculosus, R2 = 0.89 for Zostera marina total biomass, and R2 = 0.94 for AGB alone, p < 0.001). Results here provide an example of mapping cover and biomass of SAV and provide a tool to undertake spatio-temporal analyses to enhance the understanding of eelgrass ecosystem dynamics.

scholarly journals Methods of GI modeling of biogenic substances removal to the Gulf of Finland from forest vegetation cover

2020 ◽  
Vol 26 (2) ◽  
pp. 137-150
Author(s):  
Alexey Osipov ◽  
Georgy Osipov ◽  
Vasily Kovyazin
Keyword(s):  
Vegetation Cover ◽  
Catchment Area ◽  
Water Area ◽  
Forest Vegetation ◽  
Natural Vegetation ◽  
Water Bodies ◽  
Gulf Of Finland ◽  
Economic Activities ◽  
Biogenic Substances ◽  
The Gulf Of Finland

Biogenic pollution of water bodies and their eutrophication is one of the most serious environmental problems of our time. One of the sources of water pollution with biogenic substances is forests, which belong to the background sources of biogenic load. Currently available methods for assessing the removal of nutrients from the forest vegetation cover do not provide the desired results, which causes an urgent need for their improvement. This article describes the method developed by the authors of geoinformation modeling of removal of biogenic substances from the forest vegetation cover to water bodies, taking into account the spatial distribution of vegetation in the catchment area, its species composition and absorption of biogenic substances during their migration. The Eastern part of the Gulf of Finland was adopted as the object of testing of the developed method. this is due to the fact that eutrophication processes are actively manifested within its water area. The volume of the background biogenic load on the Gulf of Finland, formed during the decomposition of the fall of the natural vegetation cover in the catchment area, was determined based on the specific removal of biogenic substances from plant communities and their absorption during migration “plant community — water object”. The total background biogenic load on the eastern part of the Gulf of Finland, formed as a result of decomposition of natural vegetation cover, was 170.21 t/year for the northern catchment for nitrogen, 12.14 t/year for phosphorus, and 207.31 t/year for the southern catchment for nitrogen , and 15.68 t/year for phosphorus. The data obtained do not contradict the results of other authors who study the background biogenic load on the Gulf of Finland. The method can be effectively used in the development of measures to reduce the nutrient load on water bodies and planning of economic activities in catchments.

scholarly journals LAND COVER DYNAMICS AND LANDSCAPE STRUCTURE IN THE AREA SURROUNDING WATER RESERVOIRS, MOUNTAINOUS REGION OF RIO DE JANEIRO

FLORESTA ◽  
2020 ◽  
Vol 50 (4) ◽  
pp. 1808
Author(s):  
Lucas De Siqueira Cardinelli ◽  
José Marinaldo Gleriani ◽  
Sebastião Venâncio Martins
Keyword(s):  
Land Cover ◽  
Landscape Structure ◽  
Rio De Janeiro ◽  
Forest Cover ◽  
Water Area ◽  
Mountainous Region ◽  
Water Reservoirs ◽  
Landsat Images ◽  
Surrounding Water ◽  
Land Cover Dynamics

The aim of this study is to evaluate land cover dynamics and landscape structure in the area surrounding two water reservoirs built-in 2009 for energy production, in the mountainous region of the State of Rio de Janeiro (Serra Fluminense). The analysis was developed through the interpretation of Landsat images from 2003, 2009, and 2013, considering the following land cover classes: early successional forest, mid successional forest, pasture, pasture with shrubs and trees, geological outcrop, urban area, and water area. We used thematic maps to determine landscape metrics of size and proximity in the reservoirs catchment area and the Permanent Preservation Area (PPA). At catchment level, pasture was predominant, a consequence of the extensive livestock production carried out in the whole watershed. During the evaluated period, the forest area remained consistent, however, fragmented in many small patches of mid successional forest. The average patch area of mid successional forest is three times the size of the early successional forest patches. For neither forest land cover classes, no significant variations through time in area or isolation were identified. On the PPA, an overall reduction of the forest cover was registered before the construction of the reservoir. However, from 2009 to 2013, after the enclosure of PPA areas, the forest cover increased 35% via assisted natural regeneration, suggesting a high potential for cost-effective restoration in the region.

Remote Sensing of Surface Water Dynamics Between 2015 and 2020 in the Prairie Pothole Region 

2021 ◽  
Author(s):  
Stefan Schlaffer ◽  
Marco Chini ◽  
Wouter Dorigo
Keyword(s):  
Surface Water ◽  
Prairie Pothole Region ◽  
Water Area ◽  
Water Bodies ◽  
Water Dynamics ◽  
Drought Indices ◽  
Prairie Pothole ◽  
Small Water ◽  
Wide Range ◽  
Small Water Bodies

&lt;p&gt;The North American Prairie Pothole Region (PPR) consists of millions of wetlands and holds great importance for biodiversity, water storage and flood management. The wetlands cover a wide range of sizes from a few square metres to several square kilometres. Prairie hydrology is greatly influenced by the threshold behaviour of potholes leading to spilling as well as merging of adjacent wetlands. The knowledge of seasonal and inter-annual surface water dynamics in the PPR is critical for understanding this behaviour of connected and isolated wetlands. Synthetic aperture radar (SAR) sensors, e.g. used by the Copernicus Sentinel-1 mission, have great potential to provide high-accuracy wetland extent maps even when cloud cover is present. We derived water extent during the ice-free months May to October from 2015 to 2020 by fusing dual-polarised Sentinel-1 backscatter data with topographical information. The approach was applied to a prairie catchment in North Dakota. Total water area, number of water bodies and median area per water body were computed from the time series of water extent maps. Surface water dynamics showed strong seasonal dynamics especially in the case of small water bodies (&lt;&amp;#160;1&amp;#160;ha) with a decrease in water area and number of small water bodies from spring throughout summer when evaporation rates in the PPR are typically high. Larger water bodies showed a more stable behaviour during most years. Inter-annual dynamics were strongly related to drought indices based on climate data, such as the Palmer Drought Severity Index. During the extremely wet period of late 2019 to 2020, the dynamics of both small and large water bodies changed markedly. While a larger number of small water bodies was encountered, which remained stable throughout the wet period, also the area of larger water bodies increased, partly due to merging of smaller adjacent water bodies. The results demonstrate the potential of Sentinel-1 data for long-term monitoring of prairie wetlands while limitations exist due to the rather low temporal resolution of 12 days over the PPR.&lt;/p&gt;

scholarly journals Anatomical Constraints on Lateral Competition in Columnar Cortical Architectures

2014 ◽  
Vol 26 (8) ◽  
pp. 1624-1666 ◽  
Author(s):  
Dylan R. Muir ◽  
Matthew Cook
Keyword(s):  
Network Architecture ◽  
Network Effects ◽  
Coupling Effect ◽  
Spatial Scales ◽  
Spatial Relationship ◽  
Strong Support ◽  
Spatial Extent ◽  
Signal Restoration ◽  
Noise Rejection ◽  
Inhibitory Coupling

Competition is a well-studied and powerful mechanism for information processing in neuronal networks, providing noise rejection, signal restoration, decision making and associative memory properties, with relatively simple requirements for network architecture. Models based on competitive interactions have been used to describe the shaping of functional properties in visual cortex, as well as the development of functional maps in columnar cortex. These models require competition within a cortical area to occur on a wider spatial scale than cooperation, usually implemented by lateral inhibitory connections having a longer range than local excitatory connections. However, measurements of cortical anatomy reveal that the spatial extent of inhibition is in fact more restricted than that of excitation. Relatively few models reflect this, and it is unknown whether lateral competition can occur in cortical-like networks that have a realistic spatial relationship between excitation and inhibition. Here we analyze simple models for cortical columns and perform simulations of larger models to show how the spatial scales of excitation and inhibition can interact to produce competition through disynaptic inhibition. Our findings give strong support to the direct coupling effect—that the presence of competition across the cortical surface is predicted well by the anatomy of direct excitatory and inhibitory coupling and that multisynaptic network effects are negligible. This implies that for networks with short-range inhibition and longer-range excitation, the spatial extent of competition is even narrower than the range of inhibitory connections. Our results suggest the presence of network mechanisms that focus on intra-rather than intercolumn competition in neocortex, highlighting the need for both new models and direct experimental characterizations of lateral inhibition and competition in columnar cortex.

Do current stem size distributions predict future population changes? An empirical test of intraspecific patterns in tropical trees at two spatial scales

2007 ◽  
Vol 23 (2) ◽  
pp. 191-198 ◽  
Author(s):  
Kenneth J. Feeley ◽  
Stuart J. Davies ◽  
Md. Nur Supardi Noor ◽  
Abdul Rahman Kassim ◽  
Sylvester Tan
Keyword(s):  
Size Distribution ◽  
Population Change ◽  
Empirical Test ◽  
Spatial Scales ◽  
Demographic Data ◽  
Relative Proportion ◽  
Size Distributions ◽  
Population Changes ◽  
Stem Size ◽  
Large Trees

It is critical to understand the responses of tropical tree species to ongoing anthropogenic disturbances. Given the longevity of large trees and the scarcity of appropriately long-term demographic data, standing size distributions are a potential tool for predicting species' responses to disturbances and resultant changes in population structure. Here we test the utility of several different measures of size distribution for predicting subsequent population changes at the intraspecific level using demographic records from two subsampled 50-ha tree plots in Malaysia (Pasoh and Lambir). Most measures of size distribution failed to successfully predict population change better than random; however, the ‘coefficient of skewness’ (a measure of the relative proportion of small vs. large stems in a population) was able to correctly predict the direction of population change for approximately three-quarters of species at both sites. At Pasoh, the magnitude of this relationship decreased with adult stature and rate of turnover, but was unrelated to sapling growth rates at either site. Finally, using data for species common at both forests, we found that size distributions were generally uninformative of subsequent differences in population change between sites (only median dbh correctly predicted the direction of change for more species than random). Based on these results we conclude that some measures of intraspecific differences in size distribution are potentially informative of population trends within forests but have limited utility across broader spatial scales.

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