LANDSAT-D investigations in snow hydrology

Work undertaken during the contract and its results are described. Many of the results from this investigation are available in journal or conference proceedings literature - published, accepted for publication, or submitted for publication. For these the reference and the abstract are given. Those results that have not yet been submitted separately for publication are described in detail. Accomplishments during the contract period are summarized as follows: (1) analysis of the snow reflectance characteristics of the LANDSAT Thematic Mapper, including spectral suitability, dynamic range, and spectral resolution; (2) development of a variety of atmospheric models for use with LANDSAT Thematic Mapper data. These include a simple but fast two-stream approximation for inhomogeneous atmospheres over irregular surfaces, and a doubling model for calculation of the angular distribution of spectral radiance at any level in an plane-parallel atmosphere; (3) incorporation of digital elevation data into the atmospheric models and into the analysis of the satellite data; and (4) textural analysis of the spatial distribution of snow cover

Analysis of Land Use/Land Cover Change Impacts Upon Ecosystem Services in Montane Tropical Forest of Rwanda: Forest Carbon Assessment and REDD+ Preparedness

Changes in forest cover especially changes within tropical forests, affect global climate change, together with ecosystems and forest carbon. Forests play a key role in both carbon emission and carbon sequestration. Efforts to reduce emissions through reduced deforestation and degradation of forests have become a common discussion among scientists and politicians under the auspices of the United Nations Programme on Reducing Emissions from Deforestation and Forest Degradation (UN-REDD Programme). This dissertation research assessed the impacts of land use land cover change upon ecosystem services from a protected area focusing on forest carbon distribution and vegetation mapping using remote sensing and geographical information systems (GIS). I also assessed Rwanda’s preparedness in the United Nations global program, Reducing Emissions from Deforestation and forest Degradation, Measuring, Monitoring, Reporting, and Verifying (REDD+MMRV). I carried out research in Nyungwe National Park (NNP), one of four National Parks of Rwanda. NNP is a montane tropical forest located in the Albertine Rift, one of the most biodiverse places in central and east Africa. I used remote sensing and field data collection from December 2011 and July 2012 in the western part of the Park to assess distribution and quantities of aboveground (ABG) forest carbon using generalized allometric functions. Using Landsat data together with 2009 high resolution color orthophotos and groundtruthing, I analyzed land cover changes between 1986 and 2011 for NNP. The land-use land cover change analysis showed that between 1986 and 1995 there was a minor increase in forest cover from 53% to 58% while from 1995-2003 a substantial decrease in forest cover occurred. Between 2003 and 2011 was a period of recovery with forest cover increasing by 59%. Vegetation analysis based on a 2009 Park biodiversity survey yielded 13 vegetation communities based on dominant and co-dominant species. Macaranga kilimandscharica was found to be dominant in three communities, representing 42% of the Park, and co-dominant in one community, representing 7% of the Park. While ~50% of the Park is secondary forest, the change in protection status has had a positive impact upon forest cover change within the Park. . Assessment of REDD+-MMRV readiness revealed that Rwanda has higher capacity and readiness in remote sensing and GIS than in forest inventory and carbon pools inventory. Lack of data to support development of emission models is a major problem at the national level which needs to be addressed

An information adaptive system study report and development plan

The purpose of the information adaptive system (IAS) study was to determine how some selected Earth resource applications may be processed onboard a spacecraft and to provide a detailed preliminary IAS design for these applications. Detailed investigations of a number of applications were conducted with regard to IAS and three were selected for further analysis. Areas of future research and development include algorithmic specifications, system design specifications, and IAS recommended time lines

Forest road decommissioning: modelling the effect on hydrological connectivity

The decommissioning of forest roads is occurring in many forest environments, with the aim of reducing the negative impacts of road runoff on water quality and aquatic habitat. Prioritisation of decommissioning options is however problematic, as the relative merits of competing options are difficult to assess. This dissertation presents a method of quantifying the degree to which a road is hydrologically connected to the stream network and the uncertainty associated with this. The method permits comparisons between different roads network management options and is useful for assessing the likely result of decommissioning works. To demonstrate its utility, the model was applied to an actual road decommissioning and replacement project in south-eastern Australia. Road areas and drainage outlets were surveyed in the field and flow path lengths to streams derived from a 1 metre resolution LIDAR based digital elevation model (DEM). The results of the case study demonstrate that the road decommissioning was not effective in reducing runoff to the stream network and that the overall result of the works was counterproductive. The procedures developed in this dissertation are an extension of the ‘volume to breakthrough’ model presented by Hairsine et al. (2002) and allow the quantification of road/stream connectivity without the need for extensive parameterisation. Comparisons with empirical road-derived sediment deposition models developed in the US suggest that the methodology used here may readily translate beyond its original geographical context

Assessment of the Predictive Reliability of a SWAT Flow Model and the Evaluation of Runoff Generation and BMP effectiveness in a Shale-Gas Impacted Watershed Using a Modeling Approach

In order to ensure a harmonious harness of shale-gas resources while ensuring minimal damage to the environment, it is imperative that studies to conduct to inform various aspects of managing the environment. This includes the development of reliable hydrologic models to inform in decisions concerning water and the environment. The first objective of this study was to evaluate the predictive reliability of the Soil and Water Assessment Tool (SWAT) model based on respective methods of LULC data classification and data type spatial resolution. Results showed that the high-resolution data classified with object-oriented image method does not provide any significant advantage in terms of the model\u27s flow predictive reliability. The second goal focused on an application of the object-oriented image analysis technique for change detection related to shale-gas infrastructure and subsequently evaluates the impact of shale-gas infrastructure on stream-flow in the South Fork of the Little Red River (SFLRR). Results showed that since the upsurge in shale-gas related activities in the Fayetteville Shale Play (between 2006 and 2010), shale-gas related infrastructure in the SFLRR have increased by 78% corresponding to a differential increase on storm water flow by approximately 10% over a projected period of simulation. The last objective deals with the evaluation of BMP effectiveness in a shale-gas watershed using a modeling approach. Three BMPs identified to control flow were introduced and simulated for a simulation (2000 to 2009) and projected (2010 to 2020) periods. The differences in the flow output at the watershed outlet for each BMP scenario were derived by comparing baseline and respective BMP scenarios. Results indicate that the BMPs have an average effectiveness of approximately 80% in reducing storm water flow attributable to shale-gas

Automatic Main Road Extraction from High Resolution Satellite Imagery

Road information is essential for automatic GIS (geographical information system) data acquisition, transportation and urban planning. Automatic road (network) detection from high resolution satellite imagery will hold great potential for significant reduction of database development/updating cost and turnaround time. From so called low level feature detection to high level context supported grouping, so many algorithms and methodologies have been presented for this purpose. There is not any practical system that can fully automatically extract road network from space imagery for the purpose of automatic mapping. This paper presents the methodology of automatic main road detection from high resolution satellite IKONOS imagery. The strategies include multiresolution or image pyramid method, Gaussian blurring and the line finder using 1-dimemsional template correlation filter, line segment grouping and multi-layer result integration. Multi-layer or multi-resolution method for road extraction is a very effective strategy to save processing time and improve robustness. To realize the strategy, the original IKONOS image is compressed into different corresponding image resolution so that an image pyramid is generated; after that the line finder of 1-dimemsional template correlation filter after Gaussian blurring filtering is applied to detect the road centerline. Extracted centerline segments belong to or do not belong to roads. There are two ways to identify the attributes of the segments, the one is using segment grouping to form longer line segments and assign a possibility to the segment depending on the length and other geometric and photometric attribute of the segment, for example the longer segment means bigger possibility of being road. Perceptual-grouping based method is used for road segment linking by a possibility model that takes multi-information into account; here the clues existing in the gaps are considered. Another way to identify the segments is feature detection back-to-higher resolution layer from the image pyramid

Earth Resources: A continuing bibliography with indexes, issue 11, October 1976

This bibliography lists 714 reports, articles, and other documents introduced into the NASA scientific and technical information system between July 1976 and September 1976. 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

Earth resources: A continuing bibliography with indexes (issue 59)

This bibliography lists 518 reports, articles, and other documents introduced into the NASA scientific and technical information system between July 1 and September 30, 1988. 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, oceanography and marine resources, hydrology and water management, data processing and distribution systems, and instrumentation and sensors