Arid regions of the world were classified by Gamo et al. [11] into four
categories:
• Category A, severe deserts, where both aridity and vegetation indices are very
small
• Category G, semiarid regions, where the VI is proportionally related to the AI
• Category I, irrigated areas and oases, where the vegetation is relatively abundant
despite severe dryness
• Category S, soil degradation areas, where the vegetation is poor despite relatively humid conditions
The standard deviation of NDVI (ymx) is very small for severe deserts and much
larger in semiarid areas. Thus, the Sahara desert (Category A) was clearly distinguished from the Sahel; the latter belongs to Category G and drought occurs
frequently there between rainy seasons. Desert areas were further classified into
severe deserts (Category A), grassland deserts (Category G), and soil degradation
deserts (Category S). As a result, a map was produced showing the global distribution of arid regions using these unified criteria with both physical and biological
meaning [11].
3 Detecting and Mapping Inland Surface Waters
Surface waters include streams, rivers, ponds, lakes, and other exposed inland water
bodies. Remote sensing provides an effective means for mapping the location,
extent, and changes of surface water bodies over time [12, 13]. For example,
remotely sensed seasonal changes of lake water extent can be combined with
available topographic data to estimate water volumetric storage changes and thus
more accurately manage water resources [14–16].
A variety of passive and active remote sensors with visible and microwave bands
can be used to estimate inundation area and delineate water boundaries [17]. The
land–water boundary can be easily defined using the near-infrared radiation (NIR)
region of the electromagnetic spectrum. Land appears much brighter than water
because water strongly absorbs the NIR. Most multispectral and hyperspectral
sensors include suitable NIR bands. Moderate resolution satellites, such as Landsat
Thematic Mapper (TM) and SPOT (Satellite Pour l’Observation de la Terre), have
been used to study surface water bodies and determine their extent in arid and
semiarid regions. For example, Sharma et al. [2] used the Landsat TM to map small
surface water bodies in arid areas of India and compared them to Survey of India
topographical maps. They found major reductions in areal extent of the water
bodies over 28 years, mainly due to cultivation and urbanization in these desert
regions. Data from high-resolution commercial satellites, such as IKONOS and
QuickBird, have been used to produce more detailed maps of small freshwater
areas. Figure 1 shows a high-resolution NIR IKONOS satellite image, containing
bogs, lakes, and wetlands in northern Wisconsin, USA.
36
V. Klemas and A. Pieterse
categories:
• Category A, severe deserts, where both aridity and vegetation indices are very
small
• Category G, semiarid regions, where the VI is proportionally related to the AI
• Category I, irrigated areas and oases, where the vegetation is relatively abundant
despite severe dryness
• Category S, soil degradation areas, where the vegetation is poor despite relatively humid conditions
The standard deviation of NDVI (ymx) is very small for severe deserts and much
larger in semiarid areas. Thus, the Sahara desert (Category A) was clearly distinguished from the Sahel; the latter belongs to Category G and drought occurs
frequently there between rainy seasons. Desert areas were further classified into
severe deserts (Category A), grassland deserts (Category G), and soil degradation
deserts (Category S). As a result, a map was produced showing the global distribution of arid regions using these unified criteria with both physical and biological
meaning [11].
3 Detecting and Mapping Inland Surface Waters
Surface waters include streams, rivers, ponds, lakes, and other exposed inland water
bodies. Remote sensing provides an effective means for mapping the location,
extent, and changes of surface water bodies over time [12, 13]. For example,
remotely sensed seasonal changes of lake water extent can be combined with
available topographic data to estimate water volumetric storage changes and thus
more accurately manage water resources [14–16].
A variety of passive and active remote sensors with visible and microwave bands
can be used to estimate inundation area and delineate water boundaries [17]. The
land–water boundary can be easily defined using the near-infrared radiation (NIR)
region of the electromagnetic spectrum. Land appears much brighter than water
because water strongly absorbs the NIR. Most multispectral and hyperspectral
sensors include suitable NIR bands. Moderate resolution satellites, such as Landsat
Thematic Mapper (TM) and SPOT (Satellite Pour l’Observation de la Terre), have
been used to study surface water bodies and determine their extent in arid and
semiarid regions. For example, Sharma et al. [2] used the Landsat TM to map small
surface water bodies in arid areas of India and compared them to Survey of India
topographical maps. They found major reductions in areal extent of the water
bodies over 28 years, mainly due to cultivation and urbanization in these desert
regions. Data from high-resolution commercial satellites, such as IKONOS and
QuickBird, have been used to produce more detailed maps of small freshwater
areas. Figure 1 shows a high-resolution NIR IKONOS satellite image, containing
bogs, lakes, and wetlands in northern Wisconsin, USA.
36
V. Klemas and A. Pieterse