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High altitude, color infrared aerial photography as well as imagery from Skylab and LANDSAT were used to inventory timber and assess potential sites for industrial development in New York State. The utility of small scale remotely sensed data for monitoring clearcutting in hardwood forests was also investigated. Consultation was provided regarding the Love Canal Landfill as part of environment protection efforts.
A syllabus and training materials prepared and used in a series of one-day workshops to introduce modern remote sensing technology to selected groups of professional personnel in Vermont are described. Success in using computer compatible tapes, LANDSAT imagery and aerial photographs is reported for the following applications: (1) mapping defoliation of hardwood forests by tent caterpillar and gypsy moth; (2) differentiating conifer species; (3) mapping ground cover of major lake and pond watersheds; (4) inventorying and locating artificially regenerated conifer forest stands; (5) mapping water quality; (6) ascertaining the boat population to quantify recreational activity on lakes and waterways; and (7) identifying potential aquaculture sites.
Computer classified Landsat maps are compared with a recent conventional inventory of forest lands in northern Maine. Over the 196,000 hectare area mapped, estimates of the areas of softwood, mixed wood and hardwood forest obtained by a supervised classification of the Landsat data and a standard inventory based on aerial photointerpretation, probability proportional to prediction, field sampling and a standard forest measurement program are found to agree to within 5%. The cost of the Landsat maps is estimated to be $0.065/hectare. It is concluded that satellite techniques are worth developing for forest inventories, although they are not yet refined enough to be incorporated into current practical inventories.
A land cover classification of Landsat MSS data has been made for the entire state of California. Digital mosaicking of 32 Landsat scenes with registered digital elevation, slope, and aspect was prepared. Stratified unsupervised clustering generated the spectral classes which were identified into 16 categories, mostly forest types, using U-2 CIR photos. A verification using 81 primary sample units resulted in a forest/nonforest accuracy of 80.2% and a commercial conifer and hardwood accuracy of 75.1%. The results are now being used in many projects throughout the state.
Remote sensing methodology developed for the Nationwide Forestry Applications Program utilize computer data processing procedures for performing inventories from satellite imagery. The Ten-Ecosystem Study (TES) was developed to test the processing procedures in an intermediate-sized application study. The results of TES indicate that LANDSAT multispectral imagery and associated automatic data processing techniques can be used to distinguish softwood, hardwood, grassland, and water and make inventory of these classes with an accuracy of 70 percent or better. The technical problems encountered during the TES and the solutions and insights to these problems are discussed. The TES experience is useful in planning subsequent inventories utilizing remote sensing technology.
The development and use of signature packages which provide a forest type map and which identify clearcut areas is discussed. The type map divides the forest land into three categories: softwood, mixed wood, and hardwood. The user defines each of these categories and adjusts the signature package to fit his needs. Success in identifying clearcuts and their stage of regrowth was demonstrated in New Hampshire where clearcuts range in size from 5 to 100 acres with between 30 and 40 acres being the most common.
Based upon observed changes in timber harvest practices partially attributable to forest biomass removable for energy supply purposes, the Adirondack Park Agency began in 1979 a multi-year project to implement a digital geographic information system (GIS). An initial developmental task was an inventory of forest cover information and analysis of forest resource change and availability. While developing the GIS, a pilot project was undertaken to evaluate the usefulness of LANDSAT derived land cover information for this purpose, and to explore the integration of LANDSAT data into the GIS. The prototype LANDSAT analysis project involved: (1) the use of both recent and historic data to derive land cover information for two dates; and (2) comparison of land cover over time to determine quantitative and geographic changes. The "recent data," 1978 full foliage data over portions of four LANDSAT scenes, was classified, using ground truth derived training samples in various forested and non-forested categories. Forested categories include the following: northern hardwoods, pine, spruce-fir, and pine plantation, while nonforested categories include wet-conifer, pasture, grassland, urban, exposed soil, agriculture, and water.
A management construct is described which forms part of an overall landscape ecological planning model which has as a principal objective the extension of the traditional descriptive land use mapping capabilities of geographic information systems into land management realms. It is noted that geographic information systems appear to be moving to more comprehensive methods of data handling and storage, such as relational and hierarchical data management systems, and a clear need has simultaneously arisen therefore for planning assessment techniques and methodologies which can actually use such complex levels of data in a systematic, yet flexible and scenario dependent way. The descriptive of mapping method proposed broaches such issues and utilizes a current New England bioenergy scenario, stimulated by the use of hardwoods for household heating purposes established in the post oil crisis era and the increased awareness of the possible landscape and ecological ramifications of the continued increasing use of the resource.
Computer classification of LANDSAT data was used for forest type mapping in New England. The ability to classify areas of hardwood, softwood, and mixed tree types was assessed along with determining clearcut regions and gypsy moth defoliation. Applications of the information to forest management and locating potential deer yards were investigated. The principal activities concerned with remote sensing of volcanic emissions centered around the development of remote sensors for SO2 and HCl gas, and their use at appropriate volcanic sites. Two major areas were investigated (Masaya, Nicaragua, and St. Helens, Washington) along with several minor ones.
Satellite imagery for the State of Pennsylvania was digitally mosaicked to provide the seed data base for monitoring defoliation of hardwood trees by the gypsy moth. Two separate mosaics for the state were prepared, one before defoliation and one after defoliation, to determine the extent, direction, and impact of gypsy moth activity in the state. The digital mosaic technology used to construct the data base was transferred to Pennsylvania State University to permit periodic updates to the data base and to assist in planning and abatement activities. Participating agencies or institutions included Goddard Space Flight Center and the Pennsylvania State University Office for Remote Sensing of Earth Resources.
Soils in an Amazonian rainforest are observed to release N2O at a rate larger than the global mean by about a factor of 20. Emissions from a New England hardwood forest are approximately 30 times smaller then Brazilian values. Atmospheric methane is consumed by soils in both systems. Tropical forests would provide a major source of atmospheric N2O if the Brazilian results are representative.
A computer-implemented classification has been derived from Landsat-4 Thematic Mapper data acquired over Baldwin County, Alabama on January 15, 1983. One set of spectral signatures was developed from the data by utilizing a 3x3 pixel sliding window approach. An analysis of the classification produced from this technique identified forested areas. Additional information regarding only the forested areas. Additional information regarding only the forested areas was extracted by employing a pixel-by-pixel signature development program which derived spectral statistics only for pixels within the forested land covers. The spectral statistics from both approaches were integrated and the data classified. This classification was evaluated by comparing the spectral classes produced from the data against corresponding ground verification polygons. This iterative data analysis technique resulted in an overall classification accuracy of 88.4 percent correct for slash pine, young pine, loblolly pine, natural pine, and mixed hardwood-pine. An accuracy assessment matrix has been produced for the classification.
In 1869, the gypsy moth caterpillar was introduced in the U.S. in connection with the experiments of a French scientist. Throughout the insect's period of establishment, gypsy moth populations have periodically increased to epidemic proportions. For programs concerned with preventing the insect's spread, it would be highly desirable to be able to employ a survey technique which could provide timely, accurate, and standardized assessments at a reasonable cost. A project was, therefore, initiated with the aim to demonstrate the usefulness of satellite remotely sensed data for monitoring the insect defoliation of hardwood forests in Pennsylvania. A major effort within this project involved the development of a map-registered Landsat digital database. A complete description of the database developed is provided along with information regarding the employed data management system.
The Forest Pest Management Division (FPMD) of the Pennsylvania Bureau of Forestry has the responsibility for conducting annual surveys of the State's forest lands to accurately detect, map, and appraise forest insect infestations. A standardized, timely, and cost-effective method of accurately surveying forests and their condition should enhance the probability of suppressing infestations. The repetitive and synoptic coverage provided by LANDSAT (formerly ERTS) makes such satellite-derived data potentially attractive as a survey medium for monitoring forest insect damage over large areas. Forest Pest Management Division personnel have expressed keen interest in LANDSAT data and have informally cooperated with NASA/Goddard Space Flight Center (GSFC) since 1976 in the development of techniques to facilitate their use. The results of this work indicate that it may be feasible to use LANDSAT digital data to conduct annual surveys of insect defoliation of hardwood forests.
Seasonally compatible data collected by SIR-A and by Landsat 4 TM over the lower coastal plain in Alabama were coregistered, forming a SIR-A/TM multichannel data set with 30 m x 30 m pixel size. Spectral signature plots and histogram analysis of the data were used to observe data characteristics. Radar returns from pine forest classes correlated highly with the tree ages, suggesting the potential utility of microwave remote sensing for forest biomass estimation. As compared with the TM-only data set, the use of SIR-A/TM data set improved classification accuracy of the seven land cover types studied. In addition, the SIR-A/TM classified data support previous finding by Engheta and Elachi (1982) that microwave data appear to be correlated with differing bottomland hardwood forest vegetation as associated with varying water regimens (i.e., wet versus dry).
The fluorescence spectra and fluorescence induction kinetics of green plants excited at 337 nm by a laser were studied. They correlate with plant type, as well as with changes in the physiology of the plant as the result of stress. The plant types studied include herbaceous dicots, monocots, hardwoods, conifers, and algae. These plant types could be identified on the basis of differences in either the number of fluorescent bands or the relative intensity of the bands. Differences in fluorescent spectra which could be related to vigor status are observed in conifers located in an area of high atmospheric deposition. Changes in the fluorescence spectra and induction kinetics are also seen in plants grown under conditions of nutrient deficiency and drought stress.
Fluorescence properties of chlorophyll pigment bearing plant foliage utilizing a 337 nm nitrogen laser and integrating sphere were studied. Measured yields, in terms of number of photons emitted per 100 photons absorbed, range from 1.5 to 0.1 for the 685 nm peak, and from 4.2 to 0.2 for the 730 nm peak. Decreasing order of magnitude puts herbaceous leaves ahead of all others followed by broad leaves of hardwoods and coniferous needles. Meaningful quantization for the fluorescence peaks at 430 and 530 nm could not be attained. Passive monitoring of these fluorescence peaks is successful only for the 685 nm from the ocean surface. Field data show the reflectance changes at 685 nm due to the algae presence amounts to 1% at most.
Measurements were made of direct path with no trees, attenuated direct, and tree scattered signal levels at 1.3 GHz. Signals were received in two small groves of mixed hardwood trees. In the groves studied, average total signal levels were about 13 dB below adjacent no-trees locations, with attenuated direct signal levels about 14.6 dB below the no-trees case and scattered signals about 17.3 dB below the no-trees case. A simple model for land mobile satellite service (LMSS) propagation in groves of trees is proposed. The model assumes a constant scattered signal contribution at 17 dB below no-trees levels added to an attenuated direct signal which varies, depending on the number and density of trees in the direct path. When total signal levels are strong, the attenuated direct signal dominates. When total signal levels are more than 15 dB below no-trees levels, the scattered signals dominate.