Satellite Change Detection, Land Cover & Radar Monitoring Reports

Five report products covering land, coast, vegetation, and all-weather radar. A person processes each one by hand, then delivers a finished PDF you can put straight to work.

What is satellite-derived bathymetry, and when does it beat a boat survey?

If you manage a coastal site, an oyster lease, a marina basin, or a channel, you eventually need to know how deep the water is and how that depth is changing. The traditional answer is a boat-based hydrographic survey: accurate, thorough, and expensive, often costing several thousand to tens of thousands of dollars for a small site. Satellite-derived bathymetry, or SDB, takes a different route. In clear, shallow water, the color a satellite records depends on water depth. Light penetrates, reflects off the bottom, and returns to the sensor, changed by the depth it traveled through. With the right processing and a handful of known depth points for calibration, that relationship can be used to generate a depth map across an entire area at once. That last part is where the real work lives. Getting a usable depth map out of an image means correcting for the water surface, sun glint, and atmosphere, calibrating the result against independent depth references, and having an analyst check it against what is physically plausible for the site. The imagery is the easy part; the processing and the judgment are what make the number trustworthy, and that is the part you are paying a specialist for.

SDB is not a replacement for a survey in every case. A boat survey still wins when you need engineering-grade precision, when the water is deep or persistently turbid, or when a regulator requires a specific survey standard. SDB wins when you need a broad, affordable, current picture: scouting a site before you commit to a full survey, monitoring how a basin or channel is shoaling over time, or comparing this year to last across a large area. 

The practical way to think about it is this: SDB tells you where to look and whether a problem is developing. A boat survey, when you still need one, can then be aimed precisely instead of sweeping the whole site blind. For many coastal operators, an SDB report once or twice a year, with a targeted boat survey only when imagery flags an issue, is far less expensive than surveying everything on a fixed schedule. 

That is the whole idea behind our BottomBee product line. Give the folks who work the water an affordable, repeatable first look, so the expensive tools get used only where they are actually needed. We farm a lease ourselves, so we built the thing we wished we had.  

Reading an NDVI map without a remote-sensing degree.

NDVI is the single most common map you will see in vegetation and crop work, and it looks more intimidating than it is. Here is everything you need to read with confidence.

NDVI stands for Normalized Difference Vegetation Index. It is built from two kinds of light. Healthy green plants absorb most of the visible red light that hits them and strongly reflect near-infrared light, which the human eye cannot see but a satellite sensor can. NDVI is a simple comparison of those two: a lot of reflected near-infrared and very little reflected red means dense, healthy vegetation. The result is a single number between -1 and 1 for every point on the map. 

Values near zero or below mean bare soil, pavement, or water, with no living vegetation. Values from roughly 0.2 to 0.4 mean sparse or stressed vegetation. Values of about 0.6 or higher indicate dense, vigorous growth. Most NDVI maps color this scale so that red and orange mark the low, stressed values, and deep green marks the high, healthy ones. 

The mistake people make is treating one NDVI map as a verdict. A single map is a snapshot, and a low value can simply mean that a field was recently harvested or has not yet emerged. NDVI becomes genuinely useful in two ways. First, as a comparison across one property on one date: the stressed corner of a field stands out clearly against the healthy rest of it, and that tells you where to walk. Second, as a comparison of the same field across time, a downward NDVI trend through a season is a real early warning. 

So when you look at one of our Crop & Land Vegetation Analysis maps, do not try to read the absolute number. Read the pattern. Where is this property different from itself? Where has it changed since last month? That is where the decision is. A map cannot tell you why a zone is stressed, only that it is, and exactly where. That is still enormously valuable. It turns a whole-property problem into a small, specific place you can go stand in.

When radar beats optical, and when it does not. 

Two of our products perform change detection: Construction & Land Change Detection with optical satellite imagery and Storm & Flood Radar Change Detection with radar imagery. People often ask which is better. The honest answer is that they are built for different conditions, and the smart move is knowing which one your situation calls for. 

Optical imagery is what most people picture when they think of a satellite photo. It records sunlight reflected off the ground, in colors close to what the eye would see, plus a few extra bands. It is detailed, intuitive, and excellent for vegetation and land-cover work. It has one hard limitation. It cannot see through clouds, and it cannot see at night. In a cloudy region or a stormy season, that limitation is not minor. Whether it is hurricane season on the Gulf, a wet Atlantic-Canada winter, or a long grey stretch over northern Europe, the exact moment you most need a picture is often the moment the sky is solid cloud. 

Radar works on a completely different principle. The satellite sends down its own microwave signal and measures what bounces back. Because it provides its own energy and uses a wavelength that passes through clouds, radar works in darkness, through overcast skies, and during a storm. It is the tool that can image a coastline the day after a hurricane, when optical imagery would show nothing but cloud tops. 

Radar has its own trade-offs. The imagery is less intuitive to read; it lacks natural color and answers a slightly different set of questions. It is strong in water extent, and subtle vegetation health. 

So the rule is straightforward. For routine vegetation, crop, and land-cover change on clear days, optical Construction & Land Change Detection is the right tool. For storm response, flood mapping, winter monitoring, and any time-critical job under cloud, radar Storm & Flood Radar Change Detection is the right tool. And for the highest-stakes work, a disputed claim, a major storm assessment, running both and cross-referencing them gives you a picture neither could give alone. That is why we offer them as a pair, not as competitors. The weather decides which one you need.