ENVIRONMENTAL AUDITING: Use of Landsat Thematic Mapper Data to Assess Seasonal Rangeland Changes in the Southeast Kalahari, Botswana

Environ Manage. 1999 Jan;23(1):125-138. doi: 10.1007/s002679900173.

Abstract

/ Management problems arise in semiarid rangeland that are characterized by marked wet and dry seasons because of forage deficiencies in the dry season. These natural vegetation rangelands can sustain livestock all year long when forage and senesced grass are available into the dry season. Seasonal range condition data are required to provide a basis for pasture management to help locate dry season cover and thereby minimize overstocking and degradation. The generation of seasonal data using Thematic Mapper (TM) imagery was undertaken to assess changes in natural vegetation cover in the southern Botswana Kalahari. Visual analysis of spectral reflectance curves, the development of spectral separability indexes, and conventional classification analysis techniques were used to identify and differentiate rangeland features. Results from reflectance curves indicated that most rangeland cover types could be preferentially distinguished using mainly wet season data, especially on the longer TM wavebands, and that range feature differentiation was more problematic on darker soils than on lighter soils. Spectral separability indexes (SSIs) confirmed that range feature separation varied considerably as a function of waveband and was more effective in the wet than the dry season. The SSIs also showed that range feature differentiation in both seasons was most effective using a combination of the chlorophyll absorpance band (TM3) and two mid-infrared bands (TM5 and TM7). Wet season data were more effectively classified in terms of range features than dry season data although some class similarity was inferred across the two classified data sets. The work shows that overall trends may be generated by comparing seasonal data sets, thereby providing an overall basis for dry season decision making. However, particular problems arise within the dry season data sets probably because of spectral similarities between shadow and darkened vegetation cover, thereby implying that further work is needed. KEY WORDS: Semiarid rangelands; Botswana; Kalahari; Spectral differentiation; Seasonal change; Darkened vegetation cover