Remote sensing of forest and nonforest land classes are discussed, using microscale photointerpretation. Results include: (1.) Microscale IR color photography can be interpreted within reasonable limits of error to estimate forest area. (2.) Forest interpretation is best on winter photography with 97 percent or better accuracy. (3.) Broad forest types can be classified on microscale photography. (4.) Active agricultural land is classified most accurately on early summer photography. (5.) Six percent of all nonforest observations were misclassified as forest.


    Access

    Access via TIB

    Check availability in my library


    Export, share and cite



    Title :

    Microscale photo interpretation of forest and nonforest land classes


    Contributors:


    Publication date :

    1972-01-21


    Type of media :

    Conference paper


    Type of material :

    No indication


    Language :

    English