Operational cases for monitoring crop pattern and status using remote sensing are
reviewed in this chapter.
Chapter 11, Crop Growth Modeling and Yield Forecasting, by Pan and Chen,
introduces the comparison of statistical modeling, crop growth models, and the
remote sensing data-dependent models for crop monitoring and yield forecasting.
Chapter 12, Spatial and Temporal Monitoring System for Agriculture, by Yue
and Hu, reviews state-of-the-art operational agriculture monitoring systems at international, national, and regional levels. The requirements of current agricultural data
systems are discussed, and the capabilities of spatial and temporal monitoring
systems are analyzed.
Quality and proper acquisition planning of spatial data are important for efficient
use of agricultural information systems. Chapter 13, Spatial Data Usage in Turkish
Agriculture, by Erden and Aslan, presents an overview of spatial and geo-statistical
data characteristics, acquisition, and processing methods in agriculture with some
example applications in Turkey. This chapter also explains service level compliance
to political and regional data and process standards that enable comparative performance reports as in the EU cases of LPIS, IACS, and FADN applications.
Chapter 14, Geospatial Land Use and Land Cover Data for Improving Agricultural Area Sampling Frames, by Boryan and Yang, presents and assesses an automatic stratification method and its integration with a traditional stratification method.
Here, the results of the automatic stratification of NASS area frame PSUs of Arizona,
Georgia, Ohio, Oklahoma, and Virginia indicated that the automated stratification
method was more accurate in determining the US percent cultivation in intensively
cropped areas and weaker in low agricultural areas. In addition, this chapter introduces a hybrid operational process that integrates the automated stratification
method with traditional area frame construction manual editing/review procedures
in order to increase the operational area frame accuracy. It has been demonstrated
that the proposed operational hybrid area frame construction process, based on
available geospatial data, is easily applicable to the operations of other agencies or
countries that conduct area frame-based surveys and have available geospatial
cropland cover data.
Agricultural drought is one of the major disasters in the twenty-first century as the
world population continues to grow exponentially. Monitoring and predicting the
droughts accurately is necessary for informing the governments, farmers, and
decision-makers so that proper actions can be taken on time to mitigate their
devastating effects. Chapter 15, Mapping and Monitoring of Soil Moisture, Evapotranspiration, and Agricultural Drought, by Yagci and Yilmaz, explains drought as
the interconnected phenomena between evapo transpiration (ET) and the soil moisture. Three robust and proven methods to map soil moisture, ET, and agricultural
drought based on satellite data and methods are discussed in Chap. 15. A model is
proposed here to estimate ET through evaporative fraction (EF), tracking the agricultural drought by using remote sensing data.
Flood is one of the devastating natural disasters for agricultural production.
Chapter 16, Flood Monitoring and Crop Damage Assessment, by Shrestha and
Rahman, discusses the advancement of geoinformation flood monitoring system,
1 Introduction to Agro-Geoinformatics: Theory and Practices
5
reviewed in this chapter.
Chapter 11, Crop Growth Modeling and Yield Forecasting, by Pan and Chen,
introduces the comparison of statistical modeling, crop growth models, and the
remote sensing data-dependent models for crop monitoring and yield forecasting.
Chapter 12, Spatial and Temporal Monitoring System for Agriculture, by Yue
and Hu, reviews state-of-the-art operational agriculture monitoring systems at international, national, and regional levels. The requirements of current agricultural data
systems are discussed, and the capabilities of spatial and temporal monitoring
systems are analyzed.
Quality and proper acquisition planning of spatial data are important for efficient
use of agricultural information systems. Chapter 13, Spatial Data Usage in Turkish
Agriculture, by Erden and Aslan, presents an overview of spatial and geo-statistical
data characteristics, acquisition, and processing methods in agriculture with some
example applications in Turkey. This chapter also explains service level compliance
to political and regional data and process standards that enable comparative performance reports as in the EU cases of LPIS, IACS, and FADN applications.
Chapter 14, Geospatial Land Use and Land Cover Data for Improving Agricultural Area Sampling Frames, by Boryan and Yang, presents and assesses an automatic stratification method and its integration with a traditional stratification method.
Here, the results of the automatic stratification of NASS area frame PSUs of Arizona,
Georgia, Ohio, Oklahoma, and Virginia indicated that the automated stratification
method was more accurate in determining the US percent cultivation in intensively
cropped areas and weaker in low agricultural areas. In addition, this chapter introduces a hybrid operational process that integrates the automated stratification
method with traditional area frame construction manual editing/review procedures
in order to increase the operational area frame accuracy. It has been demonstrated
that the proposed operational hybrid area frame construction process, based on
available geospatial data, is easily applicable to the operations of other agencies or
countries that conduct area frame-based surveys and have available geospatial
cropland cover data.
Agricultural drought is one of the major disasters in the twenty-first century as the
world population continues to grow exponentially. Monitoring and predicting the
droughts accurately is necessary for informing the governments, farmers, and
decision-makers so that proper actions can be taken on time to mitigate their
devastating effects. Chapter 15, Mapping and Monitoring of Soil Moisture, Evapotranspiration, and Agricultural Drought, by Yagci and Yilmaz, explains drought as
the interconnected phenomena between evapo transpiration (ET) and the soil moisture. Three robust and proven methods to map soil moisture, ET, and agricultural
drought based on satellite data and methods are discussed in Chap. 15. A model is
proposed here to estimate ET through evaporative fraction (EF), tracking the agricultural drought by using remote sensing data.
Flood is one of the devastating natural disasters for agricultural production.
Chapter 16, Flood Monitoring and Crop Damage Assessment, by Shrestha and
Rahman, discusses the advancement of geoinformation flood monitoring system,
1 Introduction to Agro-Geoinformatics: Theory and Practices
5