technology can enhance the reliability of the automatic detection system for peat fire
occurrence.
For wildlife monitoring, the infrared sensor can be useful in detection of large
animals in the intact peat forest. Most surveys of wildlife populations have been
conducted on foot (walking along the transects), a method that is time-consuming
and expensive. UAVs with cameras mounted on them offer the opportunity for
low-cost and rapid survey of large areas. Surveying with drone-mounted optical
(RGB) and TIR cameras is capable of spotting animals. Primarily, TIR cameras can
be used in day or night, which is especially advantageous for observing nocturnal
species and has potential for use in anti-poaching efforts (Burke et al. 2018). The
potential benefits of integration of a thermal camera with the UAV are evident, and
as such, further improvements need to be made in the future. Because technology
related to UAVs and thermal cameras is rapidly evolving, this method should be
improved to encourage the monitoring of endangered mammals in their natural
habitats.
The infrared sensor is also helpful in detecting illegal logging activities, which are
the major underlying cause of deforestation. The normalized difference vegetation
index (NDVI) is one of the most widely used vegetation indices (VIs) and focuses on
the vegetation cover and its status. NDVI, similar to all VIs, relates the spectral
absorption of chlorophyll in the red region with a reflection phenomenon in the NIR,
as influenced by the leaf structure type (Wang and Tenhunen 2004). In other words,
healthy vegetation (more chlorophyll pigment) or high greenness vegetation tends to
have a high NDVI mean.
5.6.4 Case Study on Tropical Peatland Mapping
Tropical peatlands serve as important carbon pools and form unique ecosystems.
The total area of tropical peatlands is nearly 441,025 km
2 (Page et al. 2011).
Indonesia has the largest area at 206,950 km
2
, and Peru has the second largest area
at approximately 50,000 km
2 . The Ministry of Environment (MINAM) of Peru
reported the total area of wetlands as 63,167 km
2 (MINAM 2017), and tropical peatland areas were not reported separately. Although it is estimated that
21,929 km
2 of tropical peatlands are present in the “Pastaza-Maranon” area, one
of the largest Peruvian Amazon basins (Lahteenoja et al. 2011), other tropical
peatland areas in the Peruvian Amazon have not yet been reported due to limited
accessibility. Peatlands in the Amazon are dominated by Mauritia flexuosa (“aguaje”
in Peruvian local language, Fig. 5.11) which is likely a dominant producer of peat
(Virapongse et al. 2017).
Peatland mapping was conducted using the aguaje features of optical and microwave images in the San Martin Department, which is located in the highland
Peruvian Amazon. Aguaje has a unique spectral reflectance in the visible to nearinfrared (VNIR) and shortwave-infrared (SWIR) regions of the optical images from
Landsat and Sentinel-2 and higher backscatter signals for the L-band microwave
182
N. Tsuji et al.
occurrence.
For wildlife monitoring, the infrared sensor can be useful in detection of large
animals in the intact peat forest. Most surveys of wildlife populations have been
conducted on foot (walking along the transects), a method that is time-consuming
and expensive. UAVs with cameras mounted on them offer the opportunity for
low-cost and rapid survey of large areas. Surveying with drone-mounted optical
(RGB) and TIR cameras is capable of spotting animals. Primarily, TIR cameras can
be used in day or night, which is especially advantageous for observing nocturnal
species and has potential for use in anti-poaching efforts (Burke et al. 2018). The
potential benefits of integration of a thermal camera with the UAV are evident, and
as such, further improvements need to be made in the future. Because technology
related to UAVs and thermal cameras is rapidly evolving, this method should be
improved to encourage the monitoring of endangered mammals in their natural
habitats.
The infrared sensor is also helpful in detecting illegal logging activities, which are
the major underlying cause of deforestation. The normalized difference vegetation
index (NDVI) is one of the most widely used vegetation indices (VIs) and focuses on
the vegetation cover and its status. NDVI, similar to all VIs, relates the spectral
absorption of chlorophyll in the red region with a reflection phenomenon in the NIR,
as influenced by the leaf structure type (Wang and Tenhunen 2004). In other words,
healthy vegetation (more chlorophyll pigment) or high greenness vegetation tends to
have a high NDVI mean.
5.6.4 Case Study on Tropical Peatland Mapping
Tropical peatlands serve as important carbon pools and form unique ecosystems.
The total area of tropical peatlands is nearly 441,025 km
2 (Page et al. 2011).
Indonesia has the largest area at 206,950 km
2
, and Peru has the second largest area
at approximately 50,000 km
2 . The Ministry of Environment (MINAM) of Peru
reported the total area of wetlands as 63,167 km
2 (MINAM 2017), and tropical peatland areas were not reported separately. Although it is estimated that
21,929 km
2 of tropical peatlands are present in the “Pastaza-Maranon” area, one
of the largest Peruvian Amazon basins (Lahteenoja et al. 2011), other tropical
peatland areas in the Peruvian Amazon have not yet been reported due to limited
accessibility. Peatlands in the Amazon are dominated by Mauritia flexuosa (“aguaje”
in Peruvian local language, Fig. 5.11) which is likely a dominant producer of peat
(Virapongse et al. 2017).
Peatland mapping was conducted using the aguaje features of optical and microwave images in the San Martin Department, which is located in the highland
Peruvian Amazon. Aguaje has a unique spectral reflectance in the visible to nearinfrared (VNIR) and shortwave-infrared (SWIR) regions of the optical images from
Landsat and Sentinel-2 and higher backscatter signals for the L-band microwave
182
N. Tsuji et al.