Evaluation of ERTS-1 data for inventory of forest and rangeland and detection of forest stress

The author has identified the following significant results. Results of photointerpretation indicated that ERTS is a good classifier of forest and nonforest lands (90 to 95 percent accurate). Photointerpreters could make this separation as accurately as signature analysis of the computer compatible tapes. Further breakdowns of cover types at each site could not be accurately classified by interpreters (60 percent) or computer analysts (74 percent). Exceptions were water, wet meadow, and coniferous stands. At no time could the large bark beetle infestations (many over 300 meters in size) be detected on ERTS images. The ERTS wavebands are too broad to distinguish the yellow, yellow-red, and red colors of the dying pine foliage from healthy green-yellow foliage. Forest disturbances could be detected on ERTS color composites about 90 percent of the time when compared with six-year-old photo index mosaics. ERTS enlargements (1:125,000 scale, preferably color prints) would be useful to forest managers of large ownerships over 5,000 hectares (12,500 acres) for broad area planning. Black-and-white enlargements can be used effectively as aerial navigation aids for precision aerial photography where maps are old or not available

Geologic and mineral and water resources investigations in western Colorado, using Skylab EREP data

The author has identified the following significant results. Skylab photographs are superior to ERTS images for photogeologic interpretation, primarily because of improved resolution. Lithologic contacts can be detected consistently better on Skylab S190A photos than on ERTS images. Color photos are best; red and green band photos are somewhat better than color-infrared photos; infrared band photos are worst. All major geologic structures can be recognized on Skylab imagery. Large folds, even those with very gentle flexures, can be mapped accurately and with confidence. Bedding attitudes of only a few degrees are recognized; vertical exaggeration factor is about 2.5X. Mineral deposits in central Colorado may be indicated on Skylab photos by lineaments and color anomalies, but positive identification of these features is not possible. S190A stereo color photography is adequate for defining drainage divides that in turn define the boundaries and distribution of ground water recharge and discharge areas within a basin

Cloud Shadow Detection and Removal from Aerial Photo Mosaics Using Light Detection and Ranging (LIDAR) Reflectance Images

The process of creating aerial photo mosaics can be severely affected by clouds and the shadows they create. In the CZMIL project discussed in this work, the aerial survey aircraft flies below the clouds, but the shadows cast from clouds above the aircraft cause the resultant mosaic image to have sub-optimal results. Large intensity variations, caused both from the cloud shadow within a single image and the juxtaposition of areas of cloud shadow and no cloud shadow during the image stitching process, create an image that may not be as useful to the concerned research scientist. Ideally, we would like to be able to detect such distortions and correct for them, effectively removing the effects of the cloud shadow from the mosaic. In this work, we present a method for identifying areas of cloud shadow within the image mosaic process, using supervised classification methods, and subsequently correcting these areas via several image matching and color correction techniques. Although the available data contained many extreme circumstances, we show that, in general, our decision to use LIDAR reflectance images to correctly classify cloud and not cloud pixels has been very successful, and is the fundamental basis for any color correction used to remove the cloud shadows. We also implement and discuss several color transformation methods which are used to correct the cloud shadow covered pixels, with the goal of producing a mosaic image which is free from cloud shadow effects

S190 interpretation techniques development and application to New York State water resources

The author has identified the following significant results. The program has demonstrated that Skylab imagery can be utilized to regularly monitor eutrophication indices of lakes, such as chlorophyll concentration and photic zone depth. The relationship between the blue to green reflectance ratio and chlorophyll concentration was shown, along with changes in lake properties caused by chlorophyll, lignin, and humic acid using reflectance ratios and changes. A data processing technique was developed for detecting atmospheric fluctuations occurring over a large lake

Long-Term Urban Forest Cover Change Detection with Object Based Image Analysis and Random Point Based Assessment

The urban forest provides various ecosystem services. Urban tree canopy cover measurement is the most basic quantification of ecosystem services. There have been few studies focused on long-term high-resolution urban forest change analysis. Further, few if any of these studies have compared object based image analysis (OBIA) and random point based assessment for determination of urban forest cover. The research objective is to define the urban forest canopy area, location, and height within the City of St Peter, MN boundary between 1938 and 2019 using both the OBIA and random point based methods with high spatial-resolution aerial photographic images and Light Detection and Ranging (LiDAR) data. One facet of this project is to examine the impact of natural disasters, such as the 1998 tornado, and tree diseases on the urban canopy cover area. LiDAR data was used to determine the height and canopy cover density of the urban forest canopy. The results were used to compare and contrast the methods, with verification via ground truthing. Results show that both methods gave comparable accurate results. The total canopy cover area remained consistent until 1995, then increased post-tornado. The location of canopy cover areas has changed throughout St Peter over time due to the tornado, the increase in size of the City of St Peter, and land use change within the City of St Peter. The canopy change due to diseases was not detectable

Development of cloud removal and land cover Change extraction algorithms for remotely-sensed Landsat imagery

Land cover change monitoring requires the analysis of remotely-sensed data. In the tropics this is difficult because of persistent cloud cover, and data availability. This research focuses on the elimination of cloud cover as an important step towards addressing the issue of change detection. The result produced clearer images, whereas some persistent cloud remains. This persistent cloud and the cloud adjacency effects diminish the quality of image product and affect the change detection quality

Proposed characterization of tornadoes and hurricanes by area and intensity

Results of the 1968 through 1970 Tornado Watch Experiment conducted jointly by NASA and NOAA suggested the necessity of characterizing individual tornadoes in order to improve the identity of tornado-producing nephsystems. An attempt was made, therefore, to categorize each tornado by its intensity and area. Fujita-scale wind and corresponding damage categories were devised to classify tornadoes as Gale (F0), Weak (F1), Strong (F2), Severe (F3), Devastating (F4), and Incredible (F5). Additionally, individual tornado areas were also categorized as Trace (TR), Decimicro (DM), Micro (MI), Meso (ME), Marco (MA), Giant (GI), and Decagiant (DG), thus permitting characterizing of a tornado by a combination of intensity and area, such as weak decimicro tornado, severe meso tornado, or incredible giant tornado. A test characterization of 156 Japanese tornadoes in 1950-69 was accomplished for comparison with 893 U.S. tornadoes in 1965. Unexpectedly, the percentage distribution of intensity and individual area of U.S. and Japanese tornadoes is very similar except for large and/or intense ones. Intensity distribution within the Dallas and Fargo tornadoes of 1957 was also studied in detail. It was also found that the F-scale variation along the paths of family tornadoes shows an intensity oscillation with a 45-min interval

Structure-From-Motion Photogrammetry of Antarctic Historical Aerial Photographs in Conjunction with Ground Control Derived from Satellite Data

A longer temporal scale of Antarctic observations is vital to better understanding glacier dynamics and improving ice sheet model projections. One underutilized data source that expands the temporal scale is aerial photography, specifically imagery collected prior to 1990. However, processing Antarctic historical aerial imagery using modern photogrammetry software is difficult, as it requires precise information about the data collection process and extensive in situ ground control is required. Often, the necessary orientation metadata for older aerial imagery is lost and in situ data collection in regions like Antarctica is extremely difficult to obtain, limiting the use of traditional photogrammetric methods. Here, we test an alternative methodology to generate elevations from historical Antarctic aerial imagery. Instead of relying on pre-existing ground control, we use structure-from-motion photogrammetry techniques to process the imagery with manually derived ground control from high-resolution satellite imagery. This case study is based on vertical aerial image sets collected over Byrd Glacier, East Antarctica in December 1978 and January 1979. Our results are the oldest, highest resolution digital elevation models (DEMs) ever generated for an Antarctic glacier. We use these DEMs to estimate glacier dynamics and show that surface elevation of Byrd Glacier has been constant for the past ∼40 years