OGC Disasters Resilience Pilot User Guide: Rapid Assessment for Flood, Hurricane, and Agriculture Condition

Flooding is one of the most frequent natural disasters in the world. According to the Organization for Economic Cooperation and Development, on average, floods cause over $40 billion in damage worldwide. U.S. alone account 20% of the global loss.

Floods cause more than $40 billion in damage worldwide annually, according to the Organization for Economic Cooperation and Development cite:[OECD2016]. In the U.S., losses average close to $8 billion a year cite:[OECD2016]. Significant death tolls have increased in recent decades.

For example, Hurricane Harvey in 2017 was the largest hurricane in past decade. Flooding account one of the largest damages from the storm.

Objectives: The flood scenario tries to provide a cost-effective, objective, rapid assessment of impact from extreme weather disasters. Deliver the results to information consumers quickly through an automated, geospatial processing workflow in the Web that accomplish the process from data to information, including data preparation, processing, computation, and product dissemination.

Disaster cases: Texas Hurricane Harvey FEMA DR-4332

User: Resource Planner

Use scenario: Use Sentinel and MODIS/VIIRS to quickly extract the extent map of flooded area and calculate Disaster Vegetation Difference Index (DVDI) - an indicator of disaster impact. Resource planners uses the information to efficiently allocate the resources in respond to flooding events.

A hurricane is one of the major natural hazards around coastal areas. Because of the low-pressure oceanic condition, a hurricane event causes high precipitation during its landfall. The agriculture sector especially crops are damaged because of the heavy precipitation due to hurricane events. Recent examples are Hurricane Harvey,and Hurricane Irma-induced flooding in 2017, which accounted for a million-dollar crop loss in the south-eastern parts of the US cite:[davidpike2018,quealy2017cost]. Therefore, it is important to monitor the impact of the hurricane on crop fields. Soil saturation is one of the indicators to monitor the impact of hurricane landfall. Crop condition and growth primarily depend on the balance of primary resources: soil, water, heat, and nutrients. Any extreme condition such as water shortage or extra water in the soil is detrimental to crop growth and yield. Plant water stress condition, agriculture drought, takes place when soil moisture goes below the wilting point because there is no water for plant uptake. Similarly, soil moisture at saturation level can significantly damage the crop, since crop roots are unable to adequately respire due to the insufficient oxygen in the soil pores cite:[rahman2017agriculture,universityofcaliforniadavis]. Therefore, monitoring of soil saturation can be helpful for crop damage assessment during hurricane landfall. It is impossible to monitor soil saturation with high frequency for the vast agricultural area by field-based measurement. Thus, satellite remote sensing-based soil moisture measurement is useful to monitor soil saturation over vast areas. Soil Moisture Active Passive (SMAP), a NASA’s satellite mission, launched on January 2015, consisting of L-band microwaves Radar and Radiometer systems. It aims to provide global maps of soil moisture and freeze/thaw state every 2–3 days with high accuracy cite:[o2010nasa]. One of the key science applications of SMAP is to develop improved flood prediction and drought monitoring capabilities cite:[entekhabi2009soil]. SMAP level 4 (L4) represents the model-driven value-added data products, which provides surface soil moisture, root zone soil moisture, and carbon net ecosystem exchange to support SMAP key applications cite:[o2010nasa]. Catchment model soil porosity data of the SMAP soil moisture land model constant dataset is available from the National Snow and Ice Data Center cite:[reichle2018soil]. Thus, soil moisture content greater than effective soil porosity can be mapped as saturated soil. Moreover, cropland coverage and crop types data are available from national landcover data and cropland data layer (CDL). Hurricane impacted cropland information can be generated by combining cropland information, saturated soil maps, and county level boundary information. This information can quickly be disseminated through web mapping and cyberinfrastructure for the quick assessment of hurricane impact on croplands.

Disaster cases: Texas Hurricane Harvey FEMA DR-4332 and Louisiana Severe Storms and Flooding (DR-4277)

User: Resource Planner

Use scenario: Use SMAP data to quickly produce soil-moisture-statured area maps to give a quick lead where the landfall of hurricane events. A quick guide and information retrieval would provide resource planner with information of counties and people affected by hurricanes.

Weather extremes have significant impact on agricultural productivity. Severe storms could damage crops immediately. In rain-fed area, severe drought could also cause immediate damage to crops in a large area. In irrigated area, an extended, long drought period could exhaust ground water resources and lead to unrepairable crop damage and yield reduction. Crops grow differently under different extreme weathers. The impacts are different with different crops and different events, as shown in Figure 1. Rapid and accurate information on how many acres cropland are affected and how serious the impact on yield after each of such severe weather events would greatly help resource planners in allocating resources to provide adequate, much-needed support to farmers.

Remote sensing technologies integrated with geospatial information of human dimensions have been proven to be among the most efficient and cost-effective means to deliver the information products of disaster impacts on crops and assess their impacts on agricultural productivity. Studies showed that vegetation index values and their fluctuation over time series can be used to indicate crop yield and yield change respectively. The indices are effective means for quick assessment of disaster impacts on crop and its yield. The calculation of vegetation indices can be easily automated which make the process of estimating the impact to be readily processed and assessed with machine-to-machine processes under predefined workflows. The impact can be assessed and reported shortly after severe weather disasters happened by leveraging the standard interfaces and the automated chained processes of Web processing services.

In this pilot, a system, VegScape, is demonstrated in producing the crop condition maps automatically. Two types of severe weather disasters, severe storm and drought, were showcased with applications of such technologies in providing much-needed information to resource planners with impact area and assessment.

Disaster cases: Louisiana Severe Storms and Flooding (DR-4277) and Severe Drought in Kansas state during the North America Drought events

User: Resource Planner

Use scenario: Use MODIS/VIIRS to quickly produce crop condition maps. Resource planners use the crop condition data to quickly assess the impact of severe weather conditions on acgricultural productivity and allocate resources efficiently in responding to food security under pressure of disasters.

Major data providers are as follows:

Major catalogs are as follows:

Resource planners are the primary user groups for all the scenarios to be demonstrated. Resources, in this context, are related to agriculture and cropland and their recovery.

All disasters may impact agricultural productivity. The extent and degree of impact are two of the most impact factors as resource planners efficiently allocate necessary resources for recovering and mediating the impact of disasters on agriculture.

Produce and publish the following data:

Register the maps in the catalogs (CSW at GMU, CKAN and Geoplatform.gov)

The following catalogs are consulted to find relevant services and data:

Access data through standard interfaces. The following data interfaces are primarily used in downloading products.

Integration of data with human-dimension data sources to relate the disaster impacts to resources - people, crop, and farms.

Publish the integrated results as standard geospatial services (WMS, WCS, and WFS) and register into catalogs:

Interactively produce the maps for resource planners on demand with their specific areas of interest and summation levels. OGC Styled Layer Descriptor (SLD) was used in defining and rendering different maps. They are released through OGC WMS.

When registering the data products in a catalogue, tagging the data with proper themes and topics would greatly enhance the chance of finding the correct data by the right user. When users find the data, they may special requirements on areas of interest, temporal ranges, aggregation of information, and format of presentation. These special requirements can be accommodated by refined definition of styles, projection, or format in output. In VegScape and RF-CLASS, specialized on-demand customization is supported with OGC standard encoding schema. For example, area of interests can be uploaded by users if they provide maps in OGC standard formats - Geography Markup Language (GML) or GeoJSON. In Figure 3, a GML file was uploaded and used as area of interest to compute the statistic summary.