Earth Resources: A continuing bibliography with indexes, issue 29, April 1981

This bibliography lists 308 reports, articles, and other documents introduced into the NASA scientific and technical information system between January 1, 1981 and March 31, 1981. Emphasis is placed on the use of remote sensing and geophysical instrumentation in spacecraft and aircraft to survey and inventory natural resources and urban areas. Subject matter is grouped according to agriculture and forestry, environmental changes and cultural resources, geodesy and cartography, geology and mineral resources, hydrology and water management, data processing and distribution systems, instrumentation and sensors, and economic analysis

Impact of impurities and cryoconite on the optical properties of the Morteratsch Glacier (Swiss Alps)

Abstract. The amount of reflected energy by snow and ice plays a fundamental role in their melting processes. Different non-ice materials (carbonaceous particles, mineral dust (MD), microorganisms, algae, etc.) can decrease the reflectance of snow and ice promoting the melt. The object of this paper is to assess the capability of field and satellite (EO-1 Hyperion) hyperspectral data to characterize the impact of light-absorbing impurities (LAIs) on the surface reflectance of ice and snow of the Vadret da Morteratsch, a large valley glacier in the Swiss Alps. The spatial distribution of both narrow-band and broad-band indices derived from Hyperion was analyzed in relation to ice and snow impurities. In situ and laboratory reflectance spectra were acquired to characterize the optical properties of ice and cryoconite samples. The concentrations of elemental carbon (EC), organic carbon (OC) and levoglucosan were also determined to characterize the impurities found in cryoconite. Multi-wavelength absorbance spectra were measured to compare the optical properties of cryoconite samples and local moraine sediments. In situ reflectance spectra showed that the presence of impurities reduced ice reflectance in visible wavelengths by 80–90 %. Satellite data also showed the outcropping of dust during the melting season in the upper parts of the glacier, revealing that seasonal input of atmospheric dust can decrease the reflectance also in the accumulation zone of the glacier. The presence of EC and OC in cryoconite samples suggests a relevant role of carbonaceous and organic material in the darkening of the ablation zone. This darkening effect is added to that caused by fine debris from lateral moraines, which is assumed to represent a large fraction of cryoconite. Possible input of anthropogenic activity cannot be excluded and further research is needed to assess the role of human activities in the darkening process of glaciers observed in recent years

A ground based investigation of snow metamorphism using an energy flux model and hyperspectral imaging across cropland, grassland and barren surface in northeast Iowa

Snow is unstable under natural environmental conditions; it undergoes metamorphism that can be measurable with an energy flux model. The demand for snow research is increasing due to its importance for maintaining Earth’s energy balance and hydrological applications. Snow metamorphism is a process of transformation of snow particles with an expense of surface free energy. Very few studies have been completed on snow metamorphism in grassland, cropland and barren surfaces that needs farther investigation. In this study, an attempt was made to measure winter snow metamorphism with physical based model and detecting snow metamorphism by using hyperspectral imaging spectroradiameter in grassland, cropland and barren surfaces. The questions proposed in this research were: Can snow metamorphism be estimated from a ground based investigation using physical properties of snow across cropland, grassland and barren surface? Do the characteristics of snow metamorphism vary between cropland, grassland and barren surface?Can ground based hyperspectral imaging detect differences in snow metamorphism characteristics between cropland, grassland and barren surface? The instruments used to collect field data on snow physical properties in this research were ASD FieldSpec 3 Spectroradiometer, Fluke 561 IR Thermometer, gridded mesh cards of various size, ruler, portable weighing scale, graduated measuring cylinder and magnifying glass respectively. The study indicated that by considering physical properties of snow such as, snow grain size; snow surface temperature; snow depth and snow volume coupled with meteorological parameters like, wind speed; air temperature; atmospheric pressure and temperature at dew point derived from weather station on different days at specific time period used in an energy flux model, it is possible to measure snow metamorphism across cropland, grassland and barren surfaces. The results further showed that snow metamorphism characteristics such as: estimated amounts of snowmelt and snow grain size varied during different field days in different land types which indicate an increase – decrease in snowpack cold content respectively. Mean estimated amounts of snowmelt in grassland, cropland and barren surface found were 0.065 mm/day, 0.066 mm/day and 0.061 mm/day respectively. Diverse weather phenomenon altered the characteristics of snow metamorphism in different land types observed from this study. Results of statistical analysis with different methods showed there was no significant difference in the amounts of snow melt between three different land types under study. Reflectance of snow from hyperspectral imaging device showed difference in spectral signatures from different land types for different snow grain size on particular field day in specific time. After comparing all the snow reflectance spectra from three land types, the grassland showed the highest snow reflectance followed by cropland and barren surface which had the lowest snow reflectance according to different grain size on particular field day during specific time. Beside this, when PCA was applied to the combined datasets collected during different dates with ASD FIeldSpec 3 spectroradiometer it revealed components 1 and 2 with the following hyperspectral bands with component loading \u3e 0.9: 1014.5, 1024.5, 1034.5 and 355, 356, 374.5 and 394.5 nm at wavelength range between 350nm –1039nm bands were important for identifying snow metamorphism characteristics . Additional instances of snow metamorphism were observed from this study such as, icy structures in three different land classes on a particular day with varied amounts of snow melt and grain sizes that require further investigation. During icy condition the estimated amounts of snow melt found in three different land types as, cropland: 0.0536 (mm/day); grassland: 0.0544 (mm/day) and barren surface: 0.0491(mm/day) having snow grain size .5mm, 1mm and 2mm respectively. This study provided valuable insights about snow surface energy balance regulation and its effect on seasonal snow metamorphism in cropland, grassland and barren surfaces respectively. The importance of hyper spectral imaging spectroradiometer in detecting snow metamorphism was determined. Snow spectral libraries were created according to grain size, which can serve as future references for corresponding studies on snow metamorphismin three different land classes under study respectivel

Remote Sensing of the Aquatic Environments

The book highlights recent research efforts in the monitoring of aquatic districts with remote sensing observations and proximal sensing technology integrated with laboratory measurements. Optical satellite imagery gathered at spatial resolutions down to few meters has been used for quantitative estimations of harmful algal bloom extent and Chl-a mapping, as well as winds and currents from SAR acquisitions. The knowledge and understanding gained from this book can be used for the sustainable management of bodies of water across our planet

Changing Arctic snow cover: A review of recent developments and assessment of future needs for observations, modelling, and impacts

Open Access Journal (SHERPA RoMEO Green) DOI: 10.1007/s13280-016-0770-0Snow is a critically important and rapidly changing feature of the Arctic. However, snow-cover and snowpack conditions change through time pose challenges for measuring and prediction of snow. Plausible scenarios of how Arctic snow cover will respond to changing Arctic climate are important for impact assessments and adaptation strategies. Although much progress has been made in understanding and predicting snow-cover changes and their multiple consequences, many uncertainties remain. In this paper, we review advances in snow monitoring and modelling, and the impact of snow changes on ecosystems and society in Arctic regions. Interdisciplinary activities are required to resolve the current limitations on measuring and modelling snow characteristics through the cold season and at different spatial scales to assure human well-being, economic stability, and improve the ability to predict manage and adapt to natural hazards in the Arctic region

Using Long Time Series of Satellite Remote Sensing Data to Assess the Impact of Climate and Anthropogenic Changes in the Mesopotamian Marshes, Iraq

In the recent past, the Mesopotamia region has been rich in all forms of biological diversity, characterized by a fertile living environment and natural habitats full of rare birds, wild animals, aquatic animals, and diverse plants. Its natural abundance and geographical location have allowed it to be break or transit point for millions of migratory birds from Russia to South Africa. It is a breeding ground for many species of Persian Gulf fish. Despite all this historical, environmental and economic richness, they have been neglected as a result of the combination of a number of human and climatic factors, which in 16 years (1988-2003) has modified them to a land where vegetation, water, and biodiversity have been clearly reduced. This is a great environmental loss, not only for West Asia but for the whole world. This dissertation explores the changes in the vegetation coverage and water bodies in the Mesopotamian marshes, Iraq over more than three decades (36 years) using different sources of satellite remote sensing datasets. Firstly, we utilized Normalized Difference Vegetation Index (NDVI) from the Land Long Term Data Record (LTDR) Version 5 which has a 0.05o x 0.05o in spatial resolution and daily temporal repeat to monitor the fluctuations of vegetation together with hydrological variables such precipitation, surface temperature, and evapotranspiration. In this research, we studied the impact of climate change and anthropogenic activities on vegetation and water coverage changes. Secondly, we compared Normalized Difference Vegetation Index from various satellite sensors - Moderate Resolution Imaging Spectroradiometer (MODIS), Advanced Very High-Resolution Radiometer (AVHRR), and Landsat over the Mesopotamian marshlands for 17 years. We selected this time series (2002-2018) to monitor the changes in vegetation area. The time series (2002-2018) is considered as a period of rehabilitation for the Mesopotamian marshes. Thirdly, as a result of human factors and local and regional climate changes, the marshes and Iraq are in general vulnerable to face a large number of dust storms annually. According to local sources (Iraq news) and National Aeronautics and Space Administration, the time period from June 29 to July 8, 2009, is considered the longest dust storm period in Iraq during last decade. In this research, we utilized the Moderate Resolution Imagining Spectroradiometer, surface reflectance daily data to calculate the Normalized Difference Dust Index. Additionally, brightness temperature data from Aqua thermal band 31 were used to separate sand on the ground from atmospheric dust. The main reasons for the degradation of the Mesopotamian marshes were due to anthropogenic activities. In the comparison research, we found that the NDVI derived from MODIS, AVHRR and Landsat sensors are correlated with high precision. This paper investigates the utility of combining low spatial resolution with frequent temporal repeat and long-term coverage and a high spatial resolution with infrequent temporal repeat and similar long-term coverage. This study also proves that we can use the low-resolution Advance Very High- resolution Radiometer data for studies on land cover change

Cryoconite:The dark biological secret of the cryosphere

Cryoconite is granular sediment found on glacier surfaces comprising both mineral and biological material. Despite long having been recognised as an important glaciological and biological phenomenon cryoconite remains relatively poorly understood. Here, we appraise the literature on cryoconite for the first time, with the aim of synthesising and evaluating current knowledge to direct future investigations. We review the properties of cryoconite, the environments in which it is found, the biology and biogeochemistry of cryoconite, and its interactions with climate and anthropogenic pollutants. We generally focus upon cryoconite in the Arctic in summer, with Antarctic and lower latitude settings examined individually. We then compare the current state-of-the-science with that at the turn of the twentieth century, and suggest directions for future research including specific recommendations for studies at a range of spatial scales and a framework for integrating these into a more holistic understanding of cryoconite and its role in the cryosphere