The advantages and limitations of remote sensing techniques for collecting synoptic data over large coastal and estuarine areas are reviewed with emphasis on the need for a proper balance between remotely sensed data and “ground truth”. Specific applications include mapping wetland vegetation and coastal land use; monitoring natural and man-induced changes in the coastal zone; charting current circulation, including the movement and dispersion of known water pollutants; and determining the type and concentration of suspended matter in coastal waters. The photo-interpretation of aircraft and satellite imagery with the aid of “ground truth” is illustrated, employing both direct visual and automated computer techniques. For some applications, it is shown that an integrated boat-aircraft-satellite approach can produce better results or cost less, than the deployment of large numbers of boats or field teams without remote sensor support.

/pdf/remote-sensing-of-coastal-wetland-vegetation-and-estuarine-4p6n3da63p.pdf

Remote sensing of coastal wetland vegetation and estuarine water properties

Digital analysis of ERTS-1 imagery was used in an attempt to map and inventory the significant ecological communities of Delaware's coastal zone. Eight vegetation and land use discrimination classes were selected: (1) phragmites communis (Giant Reed grass); (2) spartina alterniflora (Salt marsh cord grass); (3) spartina patens (Salt marsh hay); (4) shallow water and exposed mud; (5) deep water (2 meters); (6) forest; (7) agriculture; and (8) exposed sand and concrete. Canonical analysis showed that classification accuracy was quite good with spartina alterniflora, exposed sand-concrete, and forested land - all discriminated with between 94% and 100% accuracy. The shallow water-mud and deep water categories were classified with accuracies of 88% and 93% respectively. Phragmites communis showed a classification accuracy of 83% with all confusion occurring with spartina patens which may be due to use of mixed stands of these species as training sets. Discrimination of spartina patens was very poor (accuracy 52%).

https://ntrs.nasa.gov/api/citations/19740017736/downloads/19740017736.pdf

Inventories of Delaware's coastal vegetation and land-use utilizing digital processing of ERTS-1 imagery

The author has identified the following significant results. Computer techniques were applied to process ERTS tapes acquired over coal mining operations in southeastern Ohio on 21 August 1972 and 3 September 1973. ERTS products obtained included geometrically-correct map overlays, at scales from 1:24,000 to 1:250,000, showing stripped earth, partially reclaimed earth, water, and natural vegetation. Computer-generated tables listing the area covered by each land-water category in square kilometers were also produced. By comparing these mapping products, the study demonstrates the capability of ERTS to monitor changes in the extent of stripping and reclamation. NASA C-130 photography acquired on 7 September 1973 when compared with the ERTS products generated from the 3 September 1973 tape established the categorization accuracy to be better than 90%. It is estimated that the stripping and reclamation maps and data were produced from the ERTS CCTs at a tenth of the cost of conventional techniques.

Automatic mapping of strip mine operations from spacecraft data

The author has identified the following significant results. LANDSAT 1 and Skylab (S192) data from the Green Swamp area of central Florida were categorized into five classes: water, cypress, other wetlands, pine, and pasture. These categories were compared with similar categories on a detailed vegetative map made using low altitude aerial photography. Agreement of LANDSAT and Skylab categorized data with the vegetation map was 87 percent and 83 percent respectively. The Green Swamp vegetative categories may be widespread but often consist of numerous small isolated areas, because LANDSAT has a greater resolution than Skylab, it is more favorable for mapping the small vegetative categories.

/pdf/an-analysis-and-comparison-of-landsat-1-skylab-s-192-and-dummc66bnb.pdf

An analysis and comparison of LANDSAT-1, Skylab (S-192) and aircraft data for delineation of land-water cover types of the Green Swamp, Florida

The author has identified the following significant results. In response to the need for a faster, more economical means of producing land use maps, this study evaluated the suitability of using ERTS-1 computer compatible tape (CCT) data as a basis for automatic mapping. Significant findings are: (1) automatic classification accuracy greater than 90% is achieved on categories of deep and shallow water, tended grass, rangeland, extractive (bare earth), urban, forest land, and nonforested wet lands; (2) computer-generated printouts by target class provide a quantitative measure of land use; and (3) the generation of map overlays showing land use from ERTS-1 CCTs offers a significant breakthrough in the rate at which land use maps are generated. Rather than uncorrected classified imagery or computer line printer outputs, the processing results in geometrically-corrected computer-driven pen drawing of land categories, drawn on a transparent material at a scale specified by the operator. These map overlays are economically produced and provide an efficient means of rapidly updating maps showing land use.

/pdf/automated-land-use-mapping-from-spacecraft-data-1ehmfkqjjd.pdf

Automated land-use mapping from spacecraft data

Automated land-use mapping from spacecraft data. [Oakland County, Michigan]

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Automated land-use mapping from spacecraft data

Automated land-use mapping from spacecraft data. [Oakland County, Michigan]