functionalities such as statistics. For each operation, HTTP GET/POST requests are
supported. On the server side of VegScape, Apache 2 and Tomcat 6 are used as the
server containers for their popularity and being free. MapServer deployed in
Apache’s Common Gateway Interface (CGI) is used as the server of WMS, WFS,
and WCS for its good robustness on all major platforms (e.g., Linux, Mac OS X, and
Windows). On the client side, OpenLayers and ExtJS are used to develop an Ajaxbased rich Web application which can easily display a dynamic map on any Web
page. The communication between the server side and the client side is through the
messages in XML or JavaScript Object Notation (JSON) format. Through the
VegScape system, agricultural vegetation condition information and knowledge
could be easily discovered, customized, and further integrated by a broad range of
users.
12.3.3 Web Service–Based Near-Real-Time US Flood
and Progress Monitoring System
The Remote-sensing-based Flood Crop Loss Assessment Service System
(RF-CLASS), funded by NASA Applied Science Program (NNX12AQ31G,
NNX14AP91G, PI: Prof. Liping Di), is a remote-sensing-based, near-real-time US
flood crop loss assessment cyber-service system for supporting crop statistics and
insurance decision-making (Yu et al. 2013; Di et al. 2017). It aims to provide a
Web-based service system for research scientists, decision-makers, and agricultural
markets to monitor the US flood status and to analyze and predict the flood crop loss
conditions.
Among the most natural hazards, flooding always causes tremendous crop loss
over large agricultural areas in the United States (Smith and Katz 2013). Floodrelated information is crucial to flood loss assessment, US economics, and agriculture sustainable development. The World Meteorological Organization (WMO) and
the Global Water Partnership (GWP) have taken some measures for the flood
assessment model definition. To fulfill the imperative demands of relief and monetary compensation relies on the flood loss knowledge, RF-CLASS provides
on-demand and near-real-time post-flood prediction and decision-making for the
concerned agencies. With the RF-CLASS system, the users can efficiently access
and download and analyze the flood-related products for crop flood insurance
policy-making. Especially for some government agencies, such as USDA NASS
and Risk Management Agency (RMA). USDA NASS collects the flooded acreage
and flood duration and records annual crop loss due to the flood; RMA carries out the
USDA crop insurance policy, investigates crop policy compliance, and checks
prevented planting claims.
The RF-CLASS system provides various flood-related data products. Continuous, near-real-time, MODIS sensor-based, flood map products (daily raster maps at
250 m spatial resolution, and daily water polygons) from NASA Goddard Space
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supported. On the server side of VegScape, Apache 2 and Tomcat 6 are used as the
server containers for their popularity and being free. MapServer deployed in
Apache’s Common Gateway Interface (CGI) is used as the server of WMS, WFS,
and WCS for its good robustness on all major platforms (e.g., Linux, Mac OS X, and
Windows). On the client side, OpenLayers and ExtJS are used to develop an Ajaxbased rich Web application which can easily display a dynamic map on any Web
page. The communication between the server side and the client side is through the
messages in XML or JavaScript Object Notation (JSON) format. Through the
VegScape system, agricultural vegetation condition information and knowledge
could be easily discovered, customized, and further integrated by a broad range of
users.
12.3.3 Web Service–Based Near-Real-Time US Flood
and Progress Monitoring System
The Remote-sensing-based Flood Crop Loss Assessment Service System
(RF-CLASS), funded by NASA Applied Science Program (NNX12AQ31G,
NNX14AP91G, PI: Prof. Liping Di), is a remote-sensing-based, near-real-time US
flood crop loss assessment cyber-service system for supporting crop statistics and
insurance decision-making (Yu et al. 2013; Di et al. 2017). It aims to provide a
Web-based service system for research scientists, decision-makers, and agricultural
markets to monitor the US flood status and to analyze and predict the flood crop loss
conditions.
Among the most natural hazards, flooding always causes tremendous crop loss
over large agricultural areas in the United States (Smith and Katz 2013). Floodrelated information is crucial to flood loss assessment, US economics, and agriculture sustainable development. The World Meteorological Organization (WMO) and
the Global Water Partnership (GWP) have taken some measures for the flood
assessment model definition. To fulfill the imperative demands of relief and monetary compensation relies on the flood loss knowledge, RF-CLASS provides
on-demand and near-real-time post-flood prediction and decision-making for the
concerned agencies. With the RF-CLASS system, the users can efficiently access
and download and analyze the flood-related products for crop flood insurance
policy-making. Especially for some government agencies, such as USDA NASS
and Risk Management Agency (RMA). USDA NASS collects the flooded acreage
and flood duration and records annual crop loss due to the flood; RMA carries out the
USDA crop insurance policy, investigates crop policy compliance, and checks
prevented planting claims.
The RF-CLASS system provides various flood-related data products. Continuous, near-real-time, MODIS sensor-based, flood map products (daily raster maps at
250 m spatial resolution, and daily water polygons) from NASA Goddard Space
228
L. Hu and P. Yue