The highlands of northern Thailand have changed over the last few decades, due
to population growth, changing political paradigms and economic development
(see Chap. 1). A soil database is crucial for sound land use planning, but is currently
lacking in the highlands of northern Thailand; therefore, one objective of the soil
sciences element of the Uplands Program was to establish a regional soil map based
on stepwise up-scaling and using innovative mapping approaches. Gamma-ray
spectrometry has proved to be a useful tool for soil mapping on all scales, given a
sound process understanding to infer the detected signals. Section 2.2 introduces the
principles of gamma-ray spectrometry, explains its use for soil mapping, and
presents its application at the soil profile and landscape scale.
The soil resources of northern Thailand play an important role in the mostly
agrarian-based livelihoods of the local populations there; hence, site-adapted
land management strategies are necessary that require detailed soil information.
As comprehensive and intensive soil mapping activities are not affordable,
alternative mapping approaches need to be utilized. Several soil mapping
approaches on a meso-scale (>1:100,000 scale) have been developed, namely
the catena-based, grid-based randomized and indigenous knowledge approaches
(see Sect. 2.3). Comparisons of these approaches in northern Thailand have
shown that the catena approach is accurate, but labor intensive and time consuming. The grid-based randomized mapping approach is fairly accurate; however, it is quite difficult to locate the predefined sampling points in steep terrain
and with high vegetation density. The local knowledge approach is quite accurate and rapid, yet restricted to the village level and its ethnic context, meaning
the results are thus not transferable across sites, with mapping criteria based on
local experiences. An alternative is scale-independent soil prediction approaches
based on statistics and the use of airborne gamma–ray data. These comprise inter
alia the application of (a) maximum likelihood, (b) classification trees, (c) and
random forest algorithms. Comparing these approaches when used in northern
Thailand, the random forest approach performed the best (Sect. 2.3),
demonstrating the feasibility of producing meso-scale soil maps for almost the
whole of Thailand using airborne radiometric data sets.
The search for measures and policies to mitigate the negative effects of land use
intensification in mountainous areas of SEA is based mostly on simple economic
indicators, which do not account for an efficient and comprehensive analysis of the
natural and socio-economic context, and so often neglect the needs and interests of
local people. They also do not integrate indigenous knowledge. Spatial information
needed for the qualitative and quantitative evaluation of soil and land resources, a
prerequisite for the development of sustainable resource management, is poor and/
or not available on the necessary scale. The question therefore arises as to whether
local soil knowledge can help to overcome this shortcoming. The case study detailed
in Sects. 2.3 and 2.4 investigated the potential for local soil knowledge to help
gather spatial soil information across various parts of SEA and various ethnic
groups, using Participatory Rural Appraisal (PRA) tools, then compared this with
soil information obtained using conventional scientific methods. Despite its geographical restriction, the identification of local soil knowledge through PRA can be
2 Beyond the Horizons: Challenges and Prospects for Soil Science and Soil. . .
33
to population growth, changing political paradigms and economic development
(see Chap. 1). A soil database is crucial for sound land use planning, but is currently
lacking in the highlands of northern Thailand; therefore, one objective of the soil
sciences element of the Uplands Program was to establish a regional soil map based
on stepwise up-scaling and using innovative mapping approaches. Gamma-ray
spectrometry has proved to be a useful tool for soil mapping on all scales, given a
sound process understanding to infer the detected signals. Section 2.2 introduces the
principles of gamma-ray spectrometry, explains its use for soil mapping, and
presents its application at the soil profile and landscape scale.
The soil resources of northern Thailand play an important role in the mostly
agrarian-based livelihoods of the local populations there; hence, site-adapted
land management strategies are necessary that require detailed soil information.
As comprehensive and intensive soil mapping activities are not affordable,
alternative mapping approaches need to be utilized. Several soil mapping
approaches on a meso-scale (>1:100,000 scale) have been developed, namely
the catena-based, grid-based randomized and indigenous knowledge approaches
(see Sect. 2.3). Comparisons of these approaches in northern Thailand have
shown that the catena approach is accurate, but labor intensive and time consuming. The grid-based randomized mapping approach is fairly accurate; however, it is quite difficult to locate the predefined sampling points in steep terrain
and with high vegetation density. The local knowledge approach is quite accurate and rapid, yet restricted to the village level and its ethnic context, meaning
the results are thus not transferable across sites, with mapping criteria based on
local experiences. An alternative is scale-independent soil prediction approaches
based on statistics and the use of airborne gamma–ray data. These comprise inter
alia the application of (a) maximum likelihood, (b) classification trees, (c) and
random forest algorithms. Comparing these approaches when used in northern
Thailand, the random forest approach performed the best (Sect. 2.3),
demonstrating the feasibility of producing meso-scale soil maps for almost the
whole of Thailand using airborne radiometric data sets.
The search for measures and policies to mitigate the negative effects of land use
intensification in mountainous areas of SEA is based mostly on simple economic
indicators, which do not account for an efficient and comprehensive analysis of the
natural and socio-economic context, and so often neglect the needs and interests of
local people. They also do not integrate indigenous knowledge. Spatial information
needed for the qualitative and quantitative evaluation of soil and land resources, a
prerequisite for the development of sustainable resource management, is poor and/
or not available on the necessary scale. The question therefore arises as to whether
local soil knowledge can help to overcome this shortcoming. The case study detailed
in Sects. 2.3 and 2.4 investigated the potential for local soil knowledge to help
gather spatial soil information across various parts of SEA and various ethnic
groups, using Participatory Rural Appraisal (PRA) tools, then compared this with
soil information obtained using conventional scientific methods. Despite its geographical restriction, the identification of local soil knowledge through PRA can be
2 Beyond the Horizons: Challenges and Prospects for Soil Science and Soil. . .
33