Operator and organizational maintenance : water quality analysis/sets, preventive medicine, NSN 6630-00-140-7826, engineer, NSN 6630-00-140-7820.

"9 July 1981."

Analysis of fractured terrain using remote sensing and geographic information systems : establishing a correlation between fracture network properties and vegetation

This research analyzed the spatial relationship between a mega-scale fracture network and the occurrence of vegetation in an arid region. High-resolution aerial photographs of Arches National Park, Utah were used for digital image processing. Four sets of large-scale joints were digitized from the rectified color photograph in order to characterize the geospatial properties of the fracture network with the aid of a Geographic Information System. An unsupervised landcover classification was carried out to identify the spatial distribution of vegetation on the fractured outcrop. Results of this study confirm that the WNW-ESE alignment of vegetation is dominantly controlled by the spatial distribution of the systematic joint set, which in turn parallels the regional fold axis. This research provides insight into the spatial heterogeneity inherent to fracture networks, as well as the effects of jointing on the distribution of surface vegetation in desert environments.

Mapping water quality and substrate cover in optically complex coastal and reef waters: an integrated approach

Sustainable management of coastal and coral reef environments requires regular collection of accurate information on recognized ecosystem health indicators. Satellite image data and derived maps of water column and substrate biophysical properties provide an opportunity to develop baseline mapping and monitoring programs for coastal and coral reef ecosystem health indicators. A significant challenge for satellite image data in coastal and coral reef water bodies is the mixture of both clear and turbid waters. A new approach is presented in this paper to enable production of water quality and substrate cover type maps, linked to a field based coastal ecosystem health indicator monitoring program, for use in turbid to clear coastal and coral reef waters. An optimized optical domain method was applied to map selected water quality (Secchi depth, Kd PAR, tripton, CDOM) and substrate cover type (seagrass, algae, sand) parameters. The approach is demonstrated using commercially available Landsat 7 Enhanced Thematic Mapper image data over a coastal embayment exhibiting the range of substrate cover types and water quality conditions commonly found in sub-tropical and tropical coastal environments. Spatially extensive and quantitative maps of selected water quality and substrate cover parameters were produced for the study site. These map products were refined by interactions with management agencies to suit the information requirements of their monitoring and management programs. (c) 2004 Elsevier Ltd. All rights reserved.

Case study: object and ground point separation on a river bank using airborne based LIDAR data

In the past decade, airborne based LIght Detection And Ranging (LIDAR) has been recognised by both the commercial and public sectors as a reliable and accurate source for land surveying in environmental, engineering and civil applications. Commonly, the first task to investigate LIDAR point clouds is to separate ground and object points. Skewness Balancing has been proven to be an efficient non-parametric unsupervised classification algorithm to address this challenge. Initially developed for moderate terrain, this algorithm needs to be adapted to handle sloped terrain. This paper addresses the difficulty of object and ground point separation in LIDAR data in hilly terrain. A case study on a diverse LIDAR data set in terms of data provider, resolution and LIDAR echo has been carried out. Several sites in urban and rural areas with man-made structure and vegetation in moderate and hilly terrain have been investigated and three categories have been identified. A deeper investigation on an urban scene with a river bank has been selected to extend the existing algorithm. The results show that an iterative use of Skewness Balancing is suitable for sloped terrain.

Season changes in water quality and Sargassum biomass in Southwest Australia

Sargassum C. Agardh is one of the most diverse genera of marine macro-algae and commonly inhabits shallow tropical and sub-tropical waters. This study aimed to investigate the effect of seasonality and the associated water quality changes on the distribution, canopy cover, mean thallus length and the biomass of Sargassum beds around Point Peron, Shoalwater Islands Marine Park, Southwest Australia. Samples of Sargassum and seawater were collected every three months from summer 2012 to summer 2014 from four different reef zones. A combination of in situ observations and WorldView-2 satellite remote-sensing images were used to map the spatial distribution of Sargassum beds and other associated benthic habitats. The results demonstrated a strong seasonal variation in the environmental parameters, canopy cover, mean thallus length, and biomass of Sargassum, which were significantly (P < 0.05) influenced by the nutrient concentration (PO43-, NO3-, NH4+) and rainfall. However, no variation in any studied parameter was observed among the four reef zones. The highest Sargassum biomass peaks occurred between late spring and early summer (from September to January). The results provide essential information to guide effective conservation and management, as well as sustainable utilisation of this coastal marine renewable resource.

Water productivity assessment by using MODIS images and agrometeorological data in the Petrolina municipality, Brazil

The municipality of Petrolina, located in the semi-arid region of Brazil, is highlighted as an important agricultural growing region, however the irrigated areas have cleared natural vegetation inducing a loss of biodiversity. To analyze the contrast between these two ecosystems the large scale values of biomass production (BIO), evapotranspiration (ET) and water productivity (WP) were quantified. Monteithś equation was applied for estimating the absorbed photosynthetically active radiation (APAR), while the new SAFER (Simple Algorithm For Evapotranspiration Retrieving) algorithm was used to retrieve ET. The water productivity (WP) was analysed by the ratio of BIO by ET at monthly time scale with four bands of MODIS satellite images together with agrometeorological data for the year of 2011. The period with the highest water productivity values were from March to April in the rainy period for both irrigated and not irrigated conditions. However the largest ET rates were in November for irrigated crops and April for natural vegetation. More uniformity of the vegetation and water variables occurs in natural vegetation, evidenced by the lower values of standard deviation when comparing to irrigated crops, due to the different crop stages, cultural and irrigation managements. The models applied with MODIS satellite images on a large scale are considered to be suitable for water productivity assessments and for quantifying the effects of increasing irrigated areas over natural vegetation on regional water consumption in situations of quick changing land use pattern. © 2012 SPIE.

Urban expansion and its impact on urban agriculture – remote sensing based change analysis of Kizinga and Mzinga Valley – Dar Es Salaam, Tanzania

Urban agriculture is a phenomenon that can be observed world-wide, particularly in cities of devel-oping countries. It is contributing significantly to food security and food safety and has sustained livelihood of the urban and peri-urban low income dwellers in developing countries for many years. Population increase due to rural-urban migration and natural, coupled with formal as well as infor-mal urbanization are competing with urban farming for available space and scarce water resources. A multitemporal multisensoral urban change analysis over the period of 25 years (1982-2007) was performed in order to measure and visualize the urban expansion along the Kizinga and Mzinga valley in the South of Dar es Salaam. Airphotos and VHR satellite data were analyzed by using a combination of a composition of anisotropic textural measures and spectral information. The study revealed that unplanned built-up area is expanding continuously and vegetation covers and agricultural lands decline at a fast rate. The validation showed that the overall classification accuracy varied depending on the database. The extracted built-up areas were used for visual in-terpretation mapping purposes and served as information source for another research project. The maps visualize an urban congestion and expansion of nearly 18% of the total analyzed area that had taken place in the Kizinga valley between 1982 and 2007. The same development can be ob-served in the less developed and more remote Mzinga valley between 1981 and 2002. Both areas underwent fast changes where land prices still tend to go up and an influx of people both from rural and urban areas continuously increase density with the consequence of increasing multiple land use interests.

Water-quality assessment of the Lower Susquehanna River Basin, Pennsylvania and Maryland : sources, characteristics, anaylsis, and limitations of nutrient and suspended-seditment data, 1975-90 /

"National Water-Quality Assessment Program"

Fox River watershed investigation, Stratton Dam to the Illinois River : water quality issues and data report to the Fox River Study Group, Inc. /

CD-ROM includes corresponding database and GIS datasets.

A REMOTE SENSING APPROACH TO CHARACTERIZE THE HYDROGEOLOGY OF MOUNTAINOUS AREAS: APPLICATION TO THE QUITO AQUIFER SYSTEM (QAS), ECUADOR

Climate change, intensive use, and population growth are threatening the availability of water resources. New sources of water, better knowledge of existing ones, and improved water management strategies are of paramount importance. Ground water is often considered as primary water source due to its advantages in terms of quantity, spatial distribution, and natural quality. Remote sensing techniques afford scientists a unique opportunity to characterize landscapes in order to assess groundwater resources, particularly in tectonically influenced areas. Aquifers in volcanic basins are considered the most productive aquifers in Latin America. Although topography is considered the primary driving force for groundwater flows in mountainous terrains, tectonic activity increases the complexity of these groundwater systems by altering the integrity of sedimentary rock units and the overlying drainage networks. Structural controls affect the primary hydraulic properties of the rock formations by developing barriers to flow in some cases and zones of preferential infiltration and subterranean in others. The study area focuses on the Quito Aquifer System (QAS) in Ecuador. The characterization of the hydrogeology started with a lineament analysis based on a combined remote sensing and digital terrain analysis approach. The application of classical tools for regional hydrogeological evaluation and shallow geophysical methods were useful to evaluate the impact of faulting and fracturing on the aquifer system. Given the spatial extension of the area and the complexity of the system, two levels of analysis were applied in this study. At the regional level, a lineament map was created for the QAS. Relationships between fractures, faults and lineaments and the configuration of the groundwater flow on the QAS were determined. At the local level, on the Plateaus region of the QAS, a detailed lineament map was obtained by using high-spatial-resolution satellite imagery and aspect map derived from a digital elevation model (DEM). This map was complemented by the analysis of morphotectonic indicators and shallow geophysics that characterize fracture patterns. The development of the groundwater flow system was studied, drawing upon data pertaining to the aquifer system physical characteristics and topography. Hydrochemistry was used to ascertain the groundwater evolution and verify the correspondence of the flow patterns proposed in the flow system analysis. Isotopic analysis was employed to verify the origin of groundwater. The results of this study show that tectonism plays a very important role for the hydrology of the QAS. The results also demonstrate that faults influence a great deal of the topographic characteristics of the QAS and subsequently the configuration of the groundwater flow. Moreover, for the Plateaus region, the results demonstrate that the aquifer flow systems are affected by secondary porosity. This is a new conceptualization of the functioning of the aquifers on the QAS that will significantly contribute to the development of better strategies for the management of this important water resource.

Water quality in lakes and reservoirs in China

Dissertation elaborated for the partial fulfilment of the requirements of the Master Degree in Civil Engineering in the Speciality Area of Hydarulics

Geostatistics and remote sensing methods in the classification of images of areas cultivated with citrus

This study compares the precision of three image classification methods, two of remote sensing and one of geostatistics applied to areas cultivated with citrus. The 5,296.52ha area of study is located in the city of Araraquara - central region of the state of São Paulo (SP), Brazil. The multispectral image from the CCD/CBERS-2B satellite was acquired in 2009 and processed through the Geographic Information System (GIS) SPRING. Three classification methods were used, one unsupervised (Cluster), and two supervised (Indicator Kriging/IK and Maximum Likelihood/Maxver), in addition to the screen classification taken as field checking.. Reliability of classifications was evaluated by Kappa index. In accordance with the Kappa index, the Indicator kriging method obtained the highest degree of reliability for bands 2 and 4. Moreover the Cluster method applied to band 2 (green) was the best quality classification between all the methods. Indicator Kriging was the classifier that presented the citrus total area closest to the field check estimated by -3.01%, whereas Maxver overestimated the total citrus area by 42.94%.

Land-cover classification from airborne LIDAR data fused with aerial optical images

Airborne LIght Detection And Ranging (LIDAR) provides accurate height information for objects on the earth, which makes LIDAR become more and more popular in terrain and land surveying. In particular, LIDAR data offer vital and significant features for land-cover classification which is an important task in many application domains. In this paper, an unsupervised approach based on an improved fuzzy Markov random field (FMRF) model is developed, by which the LIDAR data, its co-registered images acquired by optical sensors, i.e. aerial color image and near infrared image, and other derived features are fused effectively to improve the ability of the LIDAR system for the accurate land-cover classification. In the proposed FMRF model-based approach, the spatial contextual information is applied by modeling the image as a Markov random field (MRF), with which the fuzzy logic is introduced simultaneously to reduce the errors caused by the hard classification. Moreover, a Lagrange-Multiplier (LM) algorithm is employed to calculate a maximum A posteriori (MAP) estimate for the classification. The experimental results have proved that fusing the height data and optical images is particularly suited for the land-cover classification. The proposed approach works very well for the classification from airborne LIDAR data fused with its coregistered optical images and the average accuracy is improved to 88.9%.