Nationwide forestry applications program: Corrections to forest reflectance as a function of low Sun angle and slope
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The development of LANDSAT classification accuracy assessment techniques, and of a computerized system for assessing wildlife habitat from land cover maps are considered. A literature review on accuracy assessment techniques and an explanation for the techniques development under both projects are included along with listings of the computer programs. The presentations and discussions at the National Working Conference on LANDSAT Classification Accuracy are summarized. Two symposium papers which were published on the results of this project are appended.
A forest inventory project employing computerized classification of LANDSAT data to inventory vegetation types in western Nevada is described. The methodology and applicability of the resulting survey are summarized.
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The feasibility of using LANDSAT digital data in conjunction with topographic data to delineate commercial forests by stand size and crown closure in the Tanana River basin of Alaska was tested. A modified clustering approach using two LANDSAT dates to generate an initial forest type classification was then refined with topographic data. To further demonstrate the ability of remotely sensed data in a fire protection planning framework, the timber type data were subsequently integrated with terrain information to generate a fire hazard map of the study area. This map provides valuable assistance in initial attack planning, determining equipment accessibility, and fire growth modeling. The resulting data sets were incorporated into the Alaska Department of Natural Resources geographic information system for subsequent utilization.
The applications of forest clearcut maps derived from LANDSAT data are dicussed. Such maps provide harvest location information useful in general management and indicate the stage of regrowth which helps determine timber stand improvement practices. The clearcut maps are also used in fire control planning and in determining wildlife habitats.
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.
A multistage sampling technique, with probability proportional to size, is developed for a forest volume inventory using remote sensing data. The LANDSAT data, Panchromatic aerial photographs, and field data are collected. Based on age and homogeneity, pine and eucalyptus classes are identified. Selection of tertiary sampling units is made through aerial photographs to minimize field work. The sampling errors for eucalyptus and pine ranged from 8.34 to 21.89 percent and from 7.18 to 8.60 percent, respectively.
In order to understand L-band multipolarization radar measurements of forested areas, a model for the forest polarization signature was developed. The model is based on backscatter from dielectric cylinders which represent branches and trunks. In the model the Stokes matrices corresponding to several different scattering mechanisms is calculated, combining the results to get the total Stokes matrix. Comparison of model predictions with radar measurements shows that the model can accurately predict the forest polarization signature.
A cooperative commercial development project designed to focus on cost-effective and practical applications of satellite remote sensing in forest management is discussed. The project, initiated in September, 1988 is being executed in three phases: (1) development of a forest resource inventory and geographic information system (GIS) updating systems; (2) testing and evaluation of remote-sensing products against forest industry specifications; and (3) integration of remote-sensing services and products in an operational setting. An advisory group represented by eleven major forest-product companies will provide direct involvement of the target market. The advisory group will focus on the following questions: Does the technology work for them? How can it be packaged to provide the needed forest-management information? Can the products and information be provided in a cost-effective manner?
NASA's JPL has completed a feasibility study using infrared technologies for wildland fire suppression and management. The study surveyed user needs, examined available technologies, matched the user needs with technologies, and defined an integrated infrared wildland fire mapping concept system configuration. System component trade-offs were presented for evaluation in the concept system configuration. The economic benefits of using infrared technologies in fire suppression and management were examined. Follow-on concept system configuration development and implementation were proposed.
The City of Albuquerque, New Mexico is experiencing increasing urban heat island(UHI) effects, which impact the health, safety, and comfort of the community. In partnership with the City of Albuquerque Department of Environmental Health, Department of Parks and Recreation, and Let’s Plant Albuquerque!, this project used satellite Earth observations from April 2016–August 2022 to model increases in tree canopy within the City of Albuquerque to help combat the urban heat island in the city’s warmer areas over the next decade. Using Landsat 8’s Thermal Infrared Sensor (TIRS) and the Ecosystem Spaceborne Thermal Radiometer Experiment on the International Space Station (ECOSTRESS), along with the Integrated Valuation of Ecosystem Services and Tradeoffs (InVEST) Urban Cooling and ENVI-Met models, the team modeled tree cover interventions and created land surface temperature maps. These outputs will help the city make data-driven decisions for their tree planting goal in a targeted approach.