active microwave remote sensing provide a unique capability for mapping soil
moisture (Calvet et al. 2011). Various low frequencies (X, C, and L bands) have
been used to estimate bare or vegetated soil moisture content.
Early microwave remote sensing was conducted on the airborne platform. Many
sensors have been launched to space to provide microwave signals for operational
uses. The Advanced Microwave Scanning Radiometer for the Earth Observing
System (AMSR-E) aboard the Aqua spacecraft includes C (4–8 GHz) and X
(8–12 GHz) band sensors and provides global daily soil moisture product at
25-km spatial resolution from June 2002 to October 2011. Several satellites carrying
L (1–2 GHz) band sensors have been launched. The ESA Soil Moisture and Ocean
Salinity (SMOS) satellite was launched in November 2009. The goal of the SMOS
mission is to provide surface soil moisture with an accuracy of 4% at 35–50-km
spatial resolution. The NASA Soil Moisture Active Passive (SMAP) satellite was
launched in January 2015. It includes passive and active L band sensors. While the
SMAP active radar sensor (1–3-km resolution) have failed after 3 months of
operation, the passive radiometer sensor still provides coarse-resolution products
(L2 and L3 products at 36-km and L4 value-added products at 9-km spatial resolution) at a global scale from 2015 to present. The SMAP data products are available
from the National Snow and Ice Data Center (NSIDC: https://nsidc.org/data/smap/
smap-data.html). ESA’s Sentinel-1A and Sentinel-1B satellites carry a C band
synthetic-aperture radar instrument. Recently, the L band radiometer measurements
from SMAP and the C band radar measurements from Sentinel-1 are combined to
produce high-spatial-resolution soil moisture estimates (Das et al. 2018). A beta
version of the combined product at 3-km spatial resolution is available from the
NASA NSIDC DAAC (Distributed Active Archive Center). Soil moisture estimates
are affected by surface roughness and vegetation coverage. The accuracy of soil
moisture estimates depends on the surface conditions.
2.4 Summary
This chapter introduces basic remote sensing concepts and applications in agriculture. Remote sensing characteristics such as spatial, temporal, and spectral resolutions are discussed. The major agricultural-related and freely available remote
sensing data sources (e.g., Landsat, MODIS, VIIRS, and Sentinel-2) and the data
products are presented. Remote sensing applications in crop type classification, crop
phenology monitoring, crop yield estimation, crop water use, and soil moisture
estimation are introduced.
2 Remote Sensing for Agriculture
21
moisture (Calvet et al. 2011). Various low frequencies (X, C, and L bands) have
been used to estimate bare or vegetated soil moisture content.
Early microwave remote sensing was conducted on the airborne platform. Many
sensors have been launched to space to provide microwave signals for operational
uses. The Advanced Microwave Scanning Radiometer for the Earth Observing
System (AMSR-E) aboard the Aqua spacecraft includes C (4–8 GHz) and X
(8–12 GHz) band sensors and provides global daily soil moisture product at
25-km spatial resolution from June 2002 to October 2011. Several satellites carrying
L (1–2 GHz) band sensors have been launched. The ESA Soil Moisture and Ocean
Salinity (SMOS) satellite was launched in November 2009. The goal of the SMOS
mission is to provide surface soil moisture with an accuracy of 4% at 35–50-km
spatial resolution. The NASA Soil Moisture Active Passive (SMAP) satellite was
launched in January 2015. It includes passive and active L band sensors. While the
SMAP active radar sensor (1–3-km resolution) have failed after 3 months of
operation, the passive radiometer sensor still provides coarse-resolution products
(L2 and L3 products at 36-km and L4 value-added products at 9-km spatial resolution) at a global scale from 2015 to present. The SMAP data products are available
from the National Snow and Ice Data Center (NSIDC: https://nsidc.org/data/smap/
smap-data.html). ESA’s Sentinel-1A and Sentinel-1B satellites carry a C band
synthetic-aperture radar instrument. Recently, the L band radiometer measurements
from SMAP and the C band radar measurements from Sentinel-1 are combined to
produce high-spatial-resolution soil moisture estimates (Das et al. 2018). A beta
version of the combined product at 3-km spatial resolution is available from the
NASA NSIDC DAAC (Distributed Active Archive Center). Soil moisture estimates
are affected by surface roughness and vegetation coverage. The accuracy of soil
moisture estimates depends on the surface conditions.
2.4 Summary
This chapter introduces basic remote sensing concepts and applications in agriculture. Remote sensing characteristics such as spatial, temporal, and spectral resolutions are discussed. The major agricultural-related and freely available remote
sensing data sources (e.g., Landsat, MODIS, VIIRS, and Sentinel-2) and the data
products are presented. Remote sensing applications in crop type classification, crop
phenology monitoring, crop yield estimation, crop water use, and soil moisture
estimation are introduced.
2 Remote Sensing for Agriculture
21