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At least 667 records · Page 37Linked to original sources
USGS1987

New techniques for the quantification and modeling of remotely sensed alteration and linear features in mineral resource assessment studies

Linear structural features and hydrothermally altered rocks that were interpreted from Landsat data have been used by the U.S. Geological Survey (USGS) in regional mineral resource appraisals for more than a decade. In the past, linear features and alterations have been incorporated into models for assessing mineral resources potential by manually overlaying these and other data sets. Recently, USGS research into computer-based geographic information systems (GIS) for mineral resources assessment programs has produced several new techniques for data analysis, quantification, and integration to meet assessment objectives.

Pecora XI Symposium↗
USGS2015

Global Cropland Area Database (GCAD) derived from Remote Sensing in Support of Food Security in the Twenty-first Century: Current Achievements and Future Possibilities

The precise estimation of the global agricultural cropland- extents, areas, geographic locations, crop types, cropping intensities, and their watering methods (irrigated or rainfed; type of irrigation) provides a critical scientific basis for the development of water and food security policies (Thenkabail et al., 2012, 2011, 2010). By year 2100, the global human population is expected to grow to 10.4 billion under median fertility variants or higher under constant or higher fertility variants (Table 1) with over three quarters living in developing countries, in regions that already lack the capacity to produce enough food. With current agricultural practices, the increased demand for food and nutrition would require in about 2 billion hectares of additional cropland, about twice the equivalent to the land area of the United States, and lead to significant increases in greenhouse gas productions (Tillman et al., 2011). For example, during 1960-2010 world population more than doubled from 3 billion to 7 billion. The nutritional demand of the population also grew swiftly during this period from an average of about 2000 calories per day per person in 1960 to nearly 3000 calories per day per person in 2010. The food demand of increased population along with increased nutritional demand during this period (1960-2010) was met by the “green revolution” which more than tripled the food production; even though croplands decreased from about 0.43 ha/capita to 0.26 ha/capita (FAO, 2009). The increase in food production during the green revolution was the result of factors such as: (a) expansion in irrigated areas which increased from 130 Mha in 1960s to 278.4 Mha in year 2000 (Siebert et al., 2006) or 399 Mha when you do not consider cropping intensity (Thenkabail et al., 2009a, 2009b, 2009c) or 467 Mha when you consider cropping intensity (Thenkabail et al., 2009a; Thenkabail et al., 2009c); (b) increase in yield and per capita food production (e.g., cereal production from 280 kg/person to 380 kg/person and meat from 22 kg/person to 34 kg/person (McIntyre, 2008); (c) new cultivar types (e.g., hybrid varieties of wheat and rice, biotechnology); and (d) modern agronomic and crop management practices (e.g., fertilizers, herbicide, pesticide applications). However, some of the factors that lead to the green revolution have stressed the environment to limits leading to salinization and decreasing water quality. For example, from 1960 to 2000, the phosphorous use doubled from 10 million tons to 20 MT, pesticide use tripled from near zero to 3 MT, and nitrogen use as fertilizer increased to a staggering 80 MT from just 10 MT (Foley et al., 2007; Khan and Hanjra, 2008). Further, diversion of croplands to bio-fuels is already taking water away from food production; the economics, carbon sequestration, environmental, and food security impacts of biofuel production are net negative (Lal and Pimentel, 2009), leaving us with a carbon debt (Gibbs et al., 2008; Searchinger et al., 2008). Climate models predict that in most regions of the world the hottest seasons on record will become the norm by the end of the century-an outcome that bodes ill for feeding the world (Kumar and Singh, 2005). Also, crop yield increases of the green revolution era have now stagnated (Hossain et al., 2005). Thereby, further increase in food production through increase in cropland areas and\or increased allocations of water for croplands are widely considered unsustainable and\or infeasible. Indeed, cropland areas have even begun to decrease in many 3 parts of the World due to factors such as urbanization, industrialization, and salinization. Furthermore, ecological and environmental imperatives such as biodiversity conservation and atmospheric carbon sequestration have put a cap on the possible expansion of cropland areas to other lands such as forests and rangelands. Other important factors limit food security. These include factors such as diversion of croplands to biofuels (Bindraban et al., 2009), limited water resources for irrigation expansion (Turral et al., 2009), limits on agricultural intensifications, loss of croplands to urbanization (Khan and Hanjra, 2008), increasing meat consumption (and associated demands on land and water) (Vinnari and Tapio, 2009), environmental infeasibility for cropland expansion (Gordon et al., 2009), and changing climate have all put pressure on our continued ability to sustain global food security in the twenty-first century. So, how does the World continue to meet its food and nutrition needs?. Solutions may come from bio-technology and precision farming, however developments in these fields are not currently moving at rates that will ensure global food security over next few decades. Further, there is a need for careful consideration of possible harmful effects of bio-technology. We should not be looking back 30– 50 years from now, like we have been looking back now at many mistakes made during the green revolution. During the green revolution the focus was only on getting more yield per unit area. Little thought was put about serious damage done to our natural environments, water resources, and human health as a result of detrimental factors such as uncontrolled use of herbicides-pesticides-nutrients, drastic groundwater mining, and salinization of fertile soils due to over irrigation. Currently, there is talk of a “second green revolution” or even an “ever green revolution”, but clear ideas on what these terms actually mean are still debated and are evolving. One of the biggest issues that are not given adequate focus is the use of large quantities of water for food production. Indeed, an overwhelming proportion (60-90%) of all human water use in India goes for producing their food (Falkenmark, M., & Rockström, 2006). But such intensive water use for food production is no longer tenable due to increasing pressure for water use alternatives such as increasing urbanization, industrialization, environmental flows, bio-fuels, and recreation. This has brought into sharp focus the need to grow more food per drop of water leading to a “blue revolution”

Book chapter↗
USGS2015

Gully annealing by fluvially-sourced Aeolian sand: remote sensing investigations of connectivity along the Fluvial-Aeolian-hillslope continuum on the Colorado River

Processes contributing to development of ephemeral gully channels are of great importance to landscapes worldwide, and particularly in dryland regions where soil loss and land degradation from gully erosion pose long-term, land-management problems. Whereas gully formation has been relatively well studied, much less is known of the processes that anneal gullies and impede their growth. This work investigates gully annealing by aeolian sediment, along the Colorado River downstream of Glen Canyon Dam in Glen, Marble, and Grand Canyons, Arizona, USA (Figure 1). In this segment of the Colorado River, gully erosion potentially affects the stability and preservation of archaeological sites that are located within valley margins. Gully erosion occurs as a function of ephemeral, rainfall-induced overland flow associated with intense episodes of seasonal precipitation. Measurements of sediment transport and topographic change have demonstrated that fluvial sand in some locations is transported inland and upslope by aeolian processes to areas affected by gully erosion, and aeolian sediment activity can be locally effective at counteracting gully erosion (Draut, 2012; Collins and others, 2009, 2012; Sankey and Draut, 2014). The degree to which specific locations are affected by upslope wind redistribution of sand from active channel sandbars to higher elevation valley margins is termed “connectivity”. Connectivity is controlled spatially throughout the river by (1) the presence of upwind sources of fluvial sand within the contemporary active river channel (e.g., sandbars), and (2) bio-physical barriers that include vegetation and topography that might impede aeolian sediment transport. The primary hypothesis of this work is that high degrees of connectivity lead to less gullying potential.

Colorado river; Grand Canyon↗
USGS2015

Long-term monitoring of sandbars on the Colorado River in Grand Canyon using remote sensing

Closure of Glen Canyon Dam in 1963 dramatically changed discharge and sediment supply to the downstream Colorado River in Marble and Grand Canyons. Magnitudes of seasonal flow variation have been suppressed, while daily fluctuations have increased because of hydropower generation. Lake Powell, the upstream reservoir, traps all sediment, leaving the Paria and Little Colorado Rivers as the main suppliers of fine sediment to the system below Glen Canyon Dam. The reduction in sediment supply, along with changes in discharge, have resulted in finesediment deficit (Topping et al., 2000), leading to a decrease in the size and number of alluvial sandbars (Schmidt and Graf, 1990; Schmidt et al., 2004). However, the understanding of these important spatial and temporal changes in sandbars located along the banks of the river have been limited to infrequent measurements mostly made by direct visitation and topographic surveying (Hazel et al., 2010). Aerial photographs are the only data available from which it is possible to evaluate changes in alluvial deposits at a large number of sites and compare recent conditions with those that existed prior to the initiation of ground-based monitoring in the early 1990s. Previous studies have evaluated the effects of Glen Canyon Dam on sandbars by analysis of comprehensive maps of surficial geology that are based on seven sets of aerial imagery taken between 1935 and 1996 for selected reaches in the first 120 km downstream from Lees Ferry, Arizona (Figure 1). These studies showed that the area of exposed sand in eddy-deposition zones was less in the post-dam period than in the pre-dam period (Leschin and Schmidt, 1995; Schmidt et al., 1999b; Sondossi, 2001, Sondossi and Schmidt, 2001, Schmidt et al., 2004). In this study, we extend these analyses to encompass a 74-year period by including maps of sand deposits visible in aerial imagery taken in 2002, 2005, and 2009 for the same reaches that were mapped in the earlier studies. Results are analyzed for two post-dam periods, based on the implementation of the first controlled flood in March 1996. The period from 1965 to March 1996 is the pre-controlled flood period and was dominated by flows that fluctuated up to the maximum capacity of the Glen Canyon Dam powerplant. Beginning in 1991, fluctuations were constrained such that maximum daily flows were typically less than 65 percent of powerplant capacity. Thus, the pre-controlled flood period also includes five years of restricted dam operations. This period also included unplanned spills from the reservoir in 1983, 1984, and 1986. We refer to the period from April 1996 to 2009 as the controlled-flood period. This period consisted entirely of restricted dam operations and included three controlled floods conducted as sandbar-building experiments. We show that the areal extent of exposed sand was greater in the images taken in the controlled-flood period than in the pre-controlled flood period. We also show that in the controlled-flood period, the area of exposed sand is negatively correlated with the elapsed time since the most recent controlled flood.

Arizona↗