Remote Sensing and Precision Agriculture in Physical Geography

Running head: PHYSICAL GEOGRAPHY
Remote Sensing
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PHYSICAL GEOGRAPHY
Table of Contents
Introduction......................................................................................................................................2
Precision agriculture........................................................................................................................2
Remote sensing and its applications in agriculture..........................................................................3
Precision crop protection.................................................................................................................5
Thermography..............................................................................................................................5
Fluorescence measurements........................................................................................................6
Hyperspectral techniques.............................................................................................................6
Precision agriculture for measuring the crop productivity..............................................................6
Identified knowledge gaps...............................................................................................................7
Conclusion.......................................................................................................................................7
Reference.........................................................................................................................................8
Appendix........................................................................................................................................11

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PHYSICAL GEOGRAPHY
Introduction
Agricultural production systems are facing difficulties due to the variation in the
topography and the climate of the different regions. For the purpose of sustainable management
of agricultural all the factors are needed to be analyzed and on a spatiotemporal basis. Advanced
techniques like the geographical information system, global positioning system (GPS) and the
remote sensing are used for their effective management and assessment. These technologies have
the multifaceted benefits and utilities like yield prediction, crop acreage estimation, precise
agriculture/site-specific management, computation crop evapotranspiration, soil moisture
estimation, crop inventory, stress detection, crop growth detection, and crop discrimination
(Hunt et al., 2014). These data provide the reliable information and timely information that are
beneficial both for the policymakers and the farmers. Such information on a regional basis is
provided through the GIS techniques and remote sensing. Both the GIS and the remote sensing
are used effectively for the analysis of land cover and its use. Remote sensing can be described
as a cheap alternative that provides a large amount of data over a large geographical area. In
remote sensing, the basic concept that is used for the data acquisition is the through the remote
sensing and this includes the measuring the characteristics of spectral reflectance from the
various surface areas. The invention of both the hyperspectral and the multispectral remote
sensing technology has broadened its application in the different fields and areas (Kingra,
Majumder & Singh 2016). This study is based on the usage of the remote sensing for measuring
the productivity and the health of the agricultural practices which is also called precision
agriculture.
Precision agriculture
Precision agriculture was developed during the middle of 1980s. The application of the
remote sensing in the field of precision agriculture initially started with the sensors for the soil
organic matter. This, however, later diversified into tractor mounted sensors or handheld sensors,
aerial sensors and satellite sensors. Initially, the wavelengths of the electromagnetic radiation
focused on the near or visible infrared regions. However, nowadays the electronic magnetic
radiation include the wavelengths that range from the microwave to the ultraviolet spectrum.
Thus, enabling the usage of the advanced applications of the thermal spectroscopy, fluorescence
spectroscopy and light detection and ranging (LiDAR), and this also includes the traditional

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PHYSICAL GEOGRAPHY
applications of the near infrared and the visible spectrum (Wei et al., 2012). With the advent of
the hyperspectral spectroscopy, the spectral bandwidth has decreased dramatically and this
allows the improved analysis of the crop biochemical and the biophysical characteristics, crop
stress, molecular interactions and the improved analysis of some of the compounds. Currently,
rather than the normalized difference vegetation indices, the spectral indices exist for the
different types of applications in the precision agriculture. The satellite remote sensing and its
spatial resolution along with the aerial imagery have now improved from 100 of meters to just a
sub-meter accuracy. Thus, this allows the evaluation of the crop and the soil properties at the
finest spatial resolution that only utilizes an extra amount of storage and the other processing
essentials. Temporal frequency has also developed to great extent presently. Presently there is a
significant amount of interest in collecting the data of remote sensing at various intervals for
conducting pest management, crop and real-time soil management (Barnhart & Crosby, 2013).
Precision agriculture involves the collection of data, analysis of the data and the
information management. This also includes the sensor design, remote sensing, yield monitoring,
and field positioning and technological advances in the field of computer processing. It has been
found that the more than the 30 percent of the agribusiness in Agriculture came from the
precision agriculture adoption by the farmers (Santesteban et al., 2013).
Remote sensing and its applications in agriculture
Remote sensing application in agriculture is entirely dependent on the interaction
between electromagnetic radiation with the plant and soil material. This includes measurement of
the reflected radiation instead of absorbed and transmitted radiation. It utilizes the non-contact
measurements of the emitted and the reflected from the agricultural fields. In addition, it is
important to mention that apart from absorption, transmittance and reflectance that the plant
leaves emit the energy via the thermal emission or fluorescence. Thermal remote sensing is used
to measuring the water stress of the plants is entirely based on radiation of the emission with
respect to the temperature of the canopy and the leaf that varies with the rate of
evapotranspiration and air temperature (Peng & Gitelson 2012). The amount of that is absorbed
by the plant's pigments is inversely related to the radiation that is absorbed by the plants and this
radiation varies with the incident radiation wavelength. Chlorophyll is a plant pigment and it
absorbs the radiation strongly in the range of the visible spectrum of 400- 700 nm. For the