scenario (Nautiyal and Kaechele 2007a). During the development of theoretical
model we have analyzed the whole landscape characteristics and interaction among
the different branches of the landscape/ecosystems management.
3.2 Analysis of Existing Data Sets
This was an interdisciplinary study to bring together ecological sciences with social
sciences. The data analysis was conducted in a detailed way for the whole region
over three points of time; this enabled us to form the study from a microscopic
viewpoint to understand the basic idea of how farmers make their own decisions on
the landscape. The analysis approach was particularly exemplary because it has
tried to analyze different food production systems of the landscape such as agriculture, medicinal plants cultivation, forest resource collection, and animal husbandry using the currencies in ecological, economical, and social terms of scenario
development. Further, it also analyzes the interlinkages and interdependencies of all
the branches of the landscape management. The methodology pertaining to the
study of agriculture, animal husbandry, forest, and natural resource utilization
pattern, and the whole in Sects. 4.2 and 4.3 village ecosystem function is described
in detail in Nautiyal (1998), Nautiyal et al. (2003a, b, 2007), Rao et al. (2005),
Nautiyal and Kaechele (2007a, b, c).
3.3 Analysis of Remote Sensing Imagery
To understand that how the sustainable ecosystems (including the interaction
between anthropogenic and natural resource systems) are altered from past decades,
we need to emphasize a holistic or integrating approach. The analysis of remote
sensing imagery gives geographic and temporal information for land use and land
cover change analysis and is helpful in understanding the degree and extent of
human dimensions on environmental change and the outcome of human actions
across the landscape. The imagery for the current study is used twice a year,
particularly during a two-crop calendar (winter and summer) of the region in a
decade interval starting in 1972–2005. The remote sensing data are in use to
analyze the spatiotemporal dimension of the Himalayan landscape. Remote sensing
provides opportunities to measure the biophysical parameters in multi-temporal
dimensions (Holz 1985; Lo 1986; Jensen 1996; Campbell 1997; Wang and
Moskovits 2001) and is especially noteworthy when empirical historical ground
data are not available (Nautiyal and Kaechele 2007b). A detailed description on
remote sensing data analysis for landscape is presented in Nautiyal and Kaechele
(2006, 2007a, b, c).
602
S. Nautiyal et al.
model we have analyzed the whole landscape characteristics and interaction among
the different branches of the landscape/ecosystems management.
3.2 Analysis of Existing Data Sets
This was an interdisciplinary study to bring together ecological sciences with social
sciences. The data analysis was conducted in a detailed way for the whole region
over three points of time; this enabled us to form the study from a microscopic
viewpoint to understand the basic idea of how farmers make their own decisions on
the landscape. The analysis approach was particularly exemplary because it has
tried to analyze different food production systems of the landscape such as agriculture, medicinal plants cultivation, forest resource collection, and animal husbandry using the currencies in ecological, economical, and social terms of scenario
development. Further, it also analyzes the interlinkages and interdependencies of all
the branches of the landscape management. The methodology pertaining to the
study of agriculture, animal husbandry, forest, and natural resource utilization
pattern, and the whole in Sects. 4.2 and 4.3 village ecosystem function is described
in detail in Nautiyal (1998), Nautiyal et al. (2003a, b, 2007), Rao et al. (2005),
Nautiyal and Kaechele (2007a, b, c).
3.3 Analysis of Remote Sensing Imagery
To understand that how the sustainable ecosystems (including the interaction
between anthropogenic and natural resource systems) are altered from past decades,
we need to emphasize a holistic or integrating approach. The analysis of remote
sensing imagery gives geographic and temporal information for land use and land
cover change analysis and is helpful in understanding the degree and extent of
human dimensions on environmental change and the outcome of human actions
across the landscape. The imagery for the current study is used twice a year,
particularly during a two-crop calendar (winter and summer) of the region in a
decade interval starting in 1972–2005. The remote sensing data are in use to
analyze the spatiotemporal dimension of the Himalayan landscape. Remote sensing
provides opportunities to measure the biophysical parameters in multi-temporal
dimensions (Holz 1985; Lo 1986; Jensen 1996; Campbell 1997; Wang and
Moskovits 2001) and is especially noteworthy when empirical historical ground
data are not available (Nautiyal and Kaechele 2007b). A detailed description on
remote sensing data analysis for landscape is presented in Nautiyal and Kaechele
(2006, 2007a, b, c).
602
S. Nautiyal et al.