outcropping of groundwater can usually be identified in remotely sensed images by
its vegetative spectral signature. The problem in arid environments is that much of
the groundwater flow emerging at the surface is intermittent. Therefore, time series
of ground data and multiple remotely sensed images are required to distinguish
steady groundwater flow from storm-driven or seasonal behavior [9].
Topographically driven groundwater flow implies that groundwater will be
recharged over broad upland areas and discharged at relatively focused lowlands
as surface water. In arid areas, evapotranspiration may also play a role. From a
remote sensing point of view, water can thus be present in many forms, where each
requires a different remote sensing approach in order to be detected and mapped.
Exposed surface water can be mapped using visible, near-infrared and radar
imagers. Soil moisture is best measured with microwave radiometers or radar.
Vegetation indicating the presence of springs can be mapped with multispectral
imagers, while freshwater springs entering water bodies can be detected with
thermal infrared (TIR) sensors. Gravitational surveys from satellites have been
used to estimate groundwater aquifer storage.
The objective of this chapter is to review the most effective remote sensing
techniques for detecting and mapping water resources in arid and semiarid environments. This chapter has been divided into sections addressing application of
remote sensing technologies to detecting exposed surface waters, groundwater, soil
moisture, freshwater springs, wetlands, and monitoring drought and potential
drought conditions in arid and semiarid regions.
2 Identification and Mapping of Arid and Semiarid
Regions
Identification and mapping of arid and semiarid regions is a prerequisite for water
availability, accessibility, fair utilization, and rational management. Gamo
et al. [11] developed a method for classifying arid lands. The objective of that
project was to prepare internally consistent maps of arid regions on a global scale in
an effort to understand the conditions of existing arid regions, especially deserts and
soil degradation areas. They delimited arid regions on a global scale by combining
climate data, i.e., aridity index (AI), and vegetation data, i.e., vegetation index (VI).
The AI shows the degree of climatic dryness and the VI denotes the abundance of
vegetation. The annual AI was estimated by the ratio of mean annual precipitation
to mean annual potential evapotranspiration, using the Thornthwaite method. The
VI was derived on a global scale in real time from satellite remote sensing images
produced by the NASA/NOAA Advanced Very High Resolution Radiometer
(AVHRR) visible and near-infrared bands. The long-term mean of yearly maximum
normalized difference vegetation index (NDVI) (ymx) was used as an indicator of
vegetation condition.
Using Remote Sensing to Map and Monitor Water Resources in Arid and Semiarid. . .
35
its vegetative spectral signature. The problem in arid environments is that much of
the groundwater flow emerging at the surface is intermittent. Therefore, time series
of ground data and multiple remotely sensed images are required to distinguish
steady groundwater flow from storm-driven or seasonal behavior [9].
Topographically driven groundwater flow implies that groundwater will be
recharged over broad upland areas and discharged at relatively focused lowlands
as surface water. In arid areas, evapotranspiration may also play a role. From a
remote sensing point of view, water can thus be present in many forms, where each
requires a different remote sensing approach in order to be detected and mapped.
Exposed surface water can be mapped using visible, near-infrared and radar
imagers. Soil moisture is best measured with microwave radiometers or radar.
Vegetation indicating the presence of springs can be mapped with multispectral
imagers, while freshwater springs entering water bodies can be detected with
thermal infrared (TIR) sensors. Gravitational surveys from satellites have been
used to estimate groundwater aquifer storage.
The objective of this chapter is to review the most effective remote sensing
techniques for detecting and mapping water resources in arid and semiarid environments. This chapter has been divided into sections addressing application of
remote sensing technologies to detecting exposed surface waters, groundwater, soil
moisture, freshwater springs, wetlands, and monitoring drought and potential
drought conditions in arid and semiarid regions.
2 Identification and Mapping of Arid and Semiarid
Regions
Identification and mapping of arid and semiarid regions is a prerequisite for water
availability, accessibility, fair utilization, and rational management. Gamo
et al. [11] developed a method for classifying arid lands. The objective of that
project was to prepare internally consistent maps of arid regions on a global scale in
an effort to understand the conditions of existing arid regions, especially deserts and
soil degradation areas. They delimited arid regions on a global scale by combining
climate data, i.e., aridity index (AI), and vegetation data, i.e., vegetation index (VI).
The AI shows the degree of climatic dryness and the VI denotes the abundance of
vegetation. The annual AI was estimated by the ratio of mean annual precipitation
to mean annual potential evapotranspiration, using the Thornthwaite method. The
VI was derived on a global scale in real time from satellite remote sensing images
produced by the NASA/NOAA Advanced Very High Resolution Radiometer
(AVHRR) visible and near-infrared bands. The long-term mean of yearly maximum
normalized difference vegetation index (NDVI) (ymx) was used as an indicator of
vegetation condition.
Using Remote Sensing to Map and Monitor Water Resources in Arid and Semiarid. . .
35