Scot E. Smith

Textural Discrimination of an Invasive Plant, Schinus terebinthifolius, from Low Altitude Aerial Digital Imagery

Schinus terebinthifolius, known as Brazilian pepper, is an exotic, invasive plant species in Florida that displaces native plant species and disrupts wildlife habitat. Aerial surveys typically used to monitor ecosystem change may be augmented with texture analyses to improve the speed and consistency with which S. terebinthifolius is detected in the images. Image processing using high-resolution imagery can take advantage of high spectral variability in adjacent pixels of the same cover type by measuring spatial patterns of texture in neighborhoods of pixels. Texture features derived from first and second-order statistics and edge components in high-resolution digital color infrared images were tested for their ability to discriminate S. terebinthifolius. Multiple linear logistic regressions found a best subset combination of texture features that consistently identified core areas of S. terebinthifolius. Misclassification of other cover types as S. terebinthifolius was low except where Sabal palmetto was present in the images.

THE BLUE NILE: POTENTIAL FOR CONFLICT AND ALTERNATIVES FOR MEETING FUTURE DEMANDS

ABSTRACT Despite nearly a century of water regulation projects on the Nile Basin, today Egypt faces a genuine crisis with respect to water supply. The crisis has been brought on by a combination of drought and greatly increased usage by all riparian nations along the Nile. It is highly probable that Egypt will need to search for new sources of water, reallocate existing water supply and reduce demand simultaneously in order to stave off major water shortfalls. It is unlikely that these measures can be accomplished without both internal and external conflict. This paper describes the current state of water supply and usage in Egypt. Further we examine potential sources of conflict over water allocation decisions. Finally, the paper presents a method for evaluating alternative strategies that could be implemented by Egypt to avoid future conflict.

Classifying spatially heterogeneous wetland communities using machine learning algorithms and spectral and textural features

Mapping of wetlands (marsh vs. swamp vs. upland) is a common remote sensing application.Yet, discriminating between similar freshwater communities such as graminoid/sedge from remotely sensed imagery is more difficult. Most of this activity has been performed using medium to low resolution imagery. There are only a few studies using high spatial resolution imagery and machine learning image classification algorithms for mapping heterogeneous wetland plant communities. This study addresses this void by analyzing whether machine learning classifiers such as decision trees (DT) and artificial neural networks (ANN) can accurately classify graminoid/sedge communities using high resolution aerial imagery and image texture data in the Everglades National Park, Florida. In addition to spectral bands, the normalized difference vegetation index, and first- and second-order texture features derived from the near-infrared band were analyzed. Classifier accuracies were assessed using confusion tables and the calculated kappa coefficients of the resulting maps. The results indicated that an ANN (multilayer perceptron based on back propagation) algorithm produced a statistically significantly higher accuracy (82.04 %) than the DT (QUEST) algorithm (80.48 %) or the maximum likelihood (80.56 %) classifier (α<0.05). Findings show that using multiple window sizes provided the best results. First-order texture features also provided computational advantages and results that were not significantly different from those using second-order texture features.

A tool for rapid post-hurricane urban tree debris estimates using high resolution aerial imagery

Abstract Coastal communities in the southeast United States have regularly experienced severe hurricane impacts. To better facilitate recovery efforts in these communities following natural disasters, state and federal agencies must respond quickly with information regarding the extent and severity of hurricane damage and the amount of tree debris volume. A tool was developed to detect downed trees and debris volume to better aid disaster response efforts and tree debris removal. The tool estimates downed tree debris volume in hurricane affected urban areas using a Leica Airborne Digital Sensor (ADS40) and very high resolution digital images. The tool employs a Sobel edge detection algorithm combined with spectral information based on color filtering using 15 different statistical combinations of spectral bands. The algorithm identified downed tree edges based on contrasts between tree stems, grass, and asphalt and color filtering was then used to establish threshold values. Colors outside these threshold values were replaced and excluded from the detection processes. Results were overlaid and an “edge line” was placed where lines or edges from longer consecutive segments and color values within the threshold were met. Where two lines were paired within a very short distance in the scene a polygon was drawn automatically and, in doing so, downed tree stems were detected. Tree stem diameter–volume bulking factors were used to estimate post-hurricane tree debris volumes. Images following Hurricane Ivan in 2005 and Hurricane Ike in 2008 were used to assess the error of the tool by comparing downed tree counts and subsequent debris volume estimates with post-hurricane photo-interpreted downed tree counts and actual field measured estimates of downed tree debris volume. The errors associated with the use of the tool and potential applications are also presented.

Locating regions of high probablility for groundwater in the Wadi EI-Arish Basin, Sinai, Egypt

Abstract A method which incorporates satellite imagery and a geographic information system (GIS) to detect areas of likely groundwater has been applied to the northern Sinai Penisula. The technique involves integration of bifurcation ratio, drainage density, stream frequency, slope and precipitation. The unique aspect of this research is both the use of Landsat satellite imagery and the study area itself. Aerial photography is normally used for delineation of the variables, but the unique desert environment of northern Sinai gave sufficient detail from satellite images. These physical features when combined in a GIS yield a highly reliable prediction of occurrence of groundwater sources. The results of the prediction map were compared with ground measurements based on vertical electrical sounding (VES) and the Shallow Seismic techniques. It was found that all of the areas predicted to yield groundwater had positive VES and Shallow Seismic readings. These results demonstrate that satellite remote sensing when used in a GIS can be a useful tool in detecting and mapping groundwater in a desert environment.

A revised estimate of the life span for Lake Nasser

A number of estimates of the potential life span of Lake Nasser located in Egypt and Sudan have been made in the past several years. Published estimates range from as little as 20 years (Sterling 1970) to over 1500 years (Makary 1982). The wide range of differing values is a function of many variables, including computation method, input data, and theoretical assumptions underlying the mathematical approach taken. Such a broad range of values is typical of sedimentation studies performed for areas that lack an adequate historic data base.One of the chief constraints to development of a reliable estimate the Lake Nassers case has been lack of sufficient historical data on which to construct a useful data base. Enough information of this type has been collected since the reservoirs formation in 1964 to permit a realistic assessment of its life span. Granted the obvious need to determine the useful lifetime of this or any other reservoir, it is now possible to assess the reliability of the current official estimate for Lake Nasser. By applying appropriate modifications and additional data to the official estimate, an improved estimate was made.The time forecasted for filling of the reservoir by the official estimate is 362 years, somewhat less than the original design life of 500 years. By taking into account changes in the hydrological regime of the Nile after 1964 and another compaction factor, an estimate of 535 years was made. The additional time before filling estimated in the revision is significant for decision rules governing operation of the Aswan High Dam.

Mapping orangutan habitat and agricultural areas using Landsat OLI imagery augmented with unmanned aircraft system aerial photography

ABSTRACT Conservation of the Sumatran orangutans’ (Pongo abelii) habitat is threatened by change in land use/land cover (LULCC), due to the logging of its native primary forest habitat, and the primary forest conversion to oil palm, rubber tree, and coffee plantations. Frequent LULCC monitoring is vital to rapid conservation interventions. Due to the costs of high-resolution satellite imagery, researchers are forced to rely on cost-free sources (e.g. Landsat), those, however, provide images at a moderate-to-low resolution (e.g. 15–250 m), permitting identification only general LULC classes, and limit the detection of small-scale deforestation or degradation. Here, we combine Landsat imagery with very high-resolution imagery obtained from an unmanned aircraft system (UAS). The UAS imagery was used as ‘drone truthing’ data to train image classification algorithms. Our results show that UAS data can successfully be used to help discriminate similar land-cover/use classes (oil palm plantation vs. reforestation vs. logged forest) with consistently high identification of over 75% on the generated thematic map, where the oil palm detection rate was as high as 89%. Because UAS is employed increasingly in conservation proWjects, this approach can be used in a large variety of them to improve land-cover classification or aid-specific mapping needs.

Geomorphological Changes along the Nile Delta Coastline between 1945 and 2015 Detected Using Satellite Remote Sensing and GIS

ABSTRACT Darwish, K.; Smith, S.E.; Torab, M.; Monsef, H., and Hussein, O., 2017. Geomorphological changes along the Nile Delta coastline between 1945 and 2015 detected using satellite remote sensing and GIS. This study describes geomorphologic changes along the Nile Delta coastline between 1945 and 2015. The study used topographic maps produced by the Egyptian Geological Survey in 1945 and Landsat satellite imagery taken between 1973 and 2015. The study found that the coastlines geomorphology greatly changed during this time period, especially at Damietta and Rosetta promontories, which were highly eroded after construction of the Aswan High Dam. Other stretches of the coastline also eroded, while some accretion occurred along the coastline down-drift from the promontories. The trend has been erosion of the beaches along the Nile promontories and accretion within the embayments between the promontories, resulting in an overall smoothing of the coastline. A portion of the eroded material has accreted in the form of spits or shoals near the inlets. The principal causal factors of coastline change were the impacts of the Aswan High Dam, sea-level rise, land subsidence, storms, and coastal protection devices. Efforts to stop erosion have had mixed results. Seawalls built along the city of Alexandria have maintained the coastline, while other coastal protection devices have not impeded erosion. Areas of cultivated land are highly susceptible to saltwater intrusion due to sea-level rise and the fact that much of the delta is at or near sea level.

A new approach for estimating mangrove canopy cover using Landsat 8 imagery

Sparse canopy vegetation is hardly mapped using moderate spatial resolution images.To avoid the soil effect on vegetation mapping seven vegetation indices were used.The new approach showing remarkable increase in sparse canopy vegetation mapping. Due to background reflectance, it is difficult to accurately map sparse canopy vegetation using moderate-resolution satellite imagery. Information contained in virtually all the pixels is a mix of leaf vegetation, soil, branches and shadow. Presented in this paper is a novel approach to improving the accuracy of mapping mangrove canopy using Landsat 8 imagery by incorporating seven indices: Normalized Difference Vegetation Index, Infrared Index, Leaf Area Index, Green Atmospherically Resistant Index, Optimized Soil Adjusted Vegetation Index, Normalized Difference Built-up Index and Normalized Difference Water Index. Results demonstrated that the accuracy of mapping mangrove can be significantly improved using this approach.

Using satellite imagery and LIDAR data to corroborate an adjudicated ordinary high water line

Determination of the ordinary high water line (OHWL) has been and continues to be an important issue. The OHWL defines the separation of sovereignty lands and private ownership on non‐tidal water bodies. Determination of OHWL is conducted on a case‐by‐case basis in Florida through court challenges. A judge makes the decision on where the line exists based upon several criteria—including remote sensing data. This study investigated the possibility of using various remote sensing technologies to provide an efficient and accurate means of determining OHWL for a lake in central Florida. Landsat Enhanced Thematic Mapper (ETM) satellite imagery was compared with the higher resolution imagery IKONOS and Light Detection And Ranging (LIDAR) imagery in order to determine the waters edge and location of vegetation communities that may be correlated with OHWL. It was found that ETM imagery could be used only for mapping vegetation community transition zones and that this zone provided limited insight to OHWL. IKONOS imagery, on the other hand, was more promising for land cover mapping, but requires further study in order to draw general conclusions regarding its application to OHWL. LIDAR data provided the best results for determining OHWL, but also need further study over a larger area in order to draw final conclusions.