Top 10 Uses of Remote Sensing in Agriculture

by HI-GLCI on December 31, 2014

Remote Sensing Applications and Uses

Thanks to GISGeography, below is a list of the Top 10 Uses of Remote Sensing Applications below. They reported 100 Top Uses, but I’ve shortened it to 10 here. I don’t know about you, but I have a rather short attention span….

I am continuously amazed at the creative things people can do with satellite imagery, weather and soil data, and cropland/grazing land vegetation data.

Many of you have already had an introduction to Google Earth, and mapping your ranch resources using Google Earth. That’s a rather obvious use of satellite imagery data.

But how’d you like to see a list of some of the more amazing remote sensing applications and uses? Whether you are beginner or advanced, this list will change the way you feel about how this industry is changing our world and the way we think.

1. Soil Moisture. Determining soil moisture content using active and passive sensors from space.
Soil moisture contributes so much to understanding Earth sciences… the water cycle, weather forecasting, drought and floods. But did you know there are two ways to derive soil moisture from space? 1) Active sensors like Radarsat-2 illuminate their target and measures backscatter – resulting in high spatial resolution but low accuracy. 2) Passive sensors like SMOS measures naturally emitted microwave radiation – highly accurate but poor spatial resolution. How can we get the best of both worlds? This is what SMAP is trying to achieve – Soil Moisture Active Passive. Learn more: NASA’s Soil Moisture Active Passive (SMAP) Mission

2. LiDAR. Mapping with laser precision using Light Detection and Ranging technology.
If Dr. Evil was a geographer, LiDAR would be his weapon of choice. I can see it now… pinky in the mouth saying “bring out the laser“. LiDAR measures the distance from the airborne platform to the earth surface using laser beams. This is how LiDAR got its name – “Light Detection and Ranging”. What makes LiDAR so special is its densely sampled points at laser accuracy. Digital surface models, digital elevation models and light intensity models can all be derived from LiDAR. Learn more: Open Topography

3. Crop Insurance. Doing the detective work for fraudulent crop insurance claims.
As climate becomes less predictable and more destructive (such as droughts and floods), farmers have to adapt to this new reality. In these cases, crop insurance can help farmers supplement their income when their fields don’t get seeded. Insurance companies and the United States Geological Survey (USGS) are teaming to up to fight crop insurance fraud. The USGS measures vegetation growth using Landsat’s red, infrared channels in combination with NDVI. Using this information, crop insurance companies can verify seeded crops and catch fraud. Learn more: Landsat Helps Fight Crop Insurance Fraud: Saving Millions in Government Dollars

4. Forest Stands. Identifying forest stands and tallying their area to estimate forest supplies.
Global forest supplies are being monitored because they not only provide valuable materials (think construction, paper, packaging…) but they also absorb roughly one-third of carbon dioxide emissions. AVHRR, MODIS and SPOT quantitatively measure the loss and gain of our global forests.

5. Wind Speed. Measuring wind speed and direction for wind farms, weather forecasting and surfers.
Golfers, farmers, pilots, engineers and wind turbine planners need accurate wind information. Weather balloons and GPS are a good way to do this. But it’s not the only way. NASA’s QuickSCAT scatterometer and wind LiDAR are making these large-scale wind observations too. Learn more: LiDAR Wind Measurements – Wind Speed at Light Speed

6. Weather Forecast. Forecasting weather to warn about natural disasters.
Remote sensing applications like weather forecasting and monitoring are fundamentally important for businesses, athletes and tourists. In 1975, the Geostationary Operational Environment Satellite (GOES-1) was launched to collect wind, temperature and other atmospheric data. But GOES-1 was limited to a small portion of the Earth. A lot has changed since then. We are now on GOES-12, 13, 14 and 15 with improving temporal, spectral, spatial and radiometric resolution.

7. Land Cover/Use. Detecting land cover/use types for decision making.
‘Land cover’ is the physical property of the surface. ‘Land use’ explains how land is being utilized. When a mayor of a city targets a 50% urban tree canopy, spatial resolution matters. A Landsat pixel spans multiple parcel boundaries and is not a realistic representation of tree canopy. The Spatial Analysis Laboratory (SAL) of Vermont compared the National Land Cover with object-based classification and found it was significantly underestimated (11% vs 39%). A mayor would be very embarrassed to know their objective is almost exceeded. Learn more: University of Vermont Spatial Analysis Lab

8. Vegetation Conditions. Quantifying forage and crop conditions with Normalized Difference Vegetation Index (NDVI).
The global food supply is being monitored with satellite imagery and the Normalized Difference Vegetation Index (NDVI). Near-infrared radiation is being used to detect healthy vegetation in agriculture. Healthy vegetation reflects green light and absorbs red and blue light. The green light that our eyes see is chlorophyll created by plants during photosynthesis. Chlorophyll will reflect more light in the green and near infrared spectrum compared to other wavelengths. This is why near infrared radiation in combination with NDVI is one of the primary remote sensing applications in agriculture and the environment.

9. Sediment Transport. Tracking sediment transport into rivers, lakes, oceans.
Sediment loading is one of the most profound anthropogenic factors on aquatic systems. It affects industries like tourism, fisheries and ecological functioning. It would be useful to understand exactly where suspended solids enter and leave. The reflectance of water in satellite imagery increases with more suspended solids. But in order to monitor nutrient loading, there needs to be repeated coverage and temporal analysis.

10. Wetland Location and Extent. Preventing the degradation and loss of wetland ecosystems.
Once seen as a nuisance in agriculture, wetlands were being drained and lost. Now, they have become a rare precious resource. Wetlands serve many purposes. They help purify water, control flooding and improve shoreline stability. This is why remote sensing applications to inventory wetlands have grown so much over the years.

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Satellite information is fundamentally important if we are going to solve some of the major challenges of our time. For issues like climate change, natural resources, disaster management and the environment, remote sensing provides a wealth of information at a global scale. What we get are answers to these problems so we can make informed decisions.

There are endless possibilities of benefits to society from remote sensing. With higher spatial, spectral and temporal resolution, the future of remote sensing is promising. If we are going to take on some of the biggest challenges of Earth in the near future, we need remote sensing to cover that much ground.

Other remote sensing applications and uses resources:
Digital Globe
Earth Observatory

Special thanks to GISGeography for authoring the above, with limited content edits by Hawaii Grazing Lands Coalition.

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