How Coastal Ecology Institute Improved Data Accuracy by 40%

The Challenge

Coastal Ecology Institute is a nonprofit research organization monitoring ecological health across 12 coastal wetland sites. Their field researchers conduct quarterly surveys tracking water quality, vegetation health, wildlife populations, and invasive species presence.

For years, the team relied on a patchwork of tools:

• Paper datasheets for field observations
• Handheld GPS units to log waypoints
• Separate cameras for photo documentation
• Excel spreadsheets for data entry and analysis

This fragmented workflow created significant problems:

Data Entry Errors

Researchers would spend hours transcribing handwritten field notes into Excel. Transcription errors were common—a pH reading of 6.8 might become 8.6, or GPS coordinates would be entered in the wrong format. Data validation happened weeks after collection, making it impossible to re-measure questionable values.

A 2024 internal audit found that approximately 12% of all field observations contained transcription errors or missing data.

Disconnected Data

Photos, GPS waypoints, and observation notes were stored in separate systems. Matching a photo to the exact observation point required cross-referencing photo timestamps with GPS logs and handwritten notes. This manual matching process was tedious and error-prone.

No Quality Control in the Field

Researchers couldn't validate data while still on-site. If a pH reading seemed unusually high, they wouldn't know until days later when someone reviewed the spreadsheet. By then, returning to re-measure was often impractical.

Limited Collaboration

Multiple researchers would visit the same site on different days. There was no way to see what observations had already been collected without calling the office or checking a shared drive later. This led to duplicate efforts and missed coverage.

GIS Export Was Manual and Slow

To create maps showing spatial patterns (e.g., invasive species distribution), a GIS specialist had to manually import GPS coordinates from text files, join them with observation data from Excel, and create point layers. This process took 2-3 days per survey round.

The research director knew that the team was losing valuable time and data quality due to the disconnected workflow. They needed a solution that would work reliably in remote locations without internet access.

The Solution

After evaluating several options, Coastal Ecology Institute chose Mapalyze for its combination of offline reliability, GIS integration, and flexible form design.

True Offline Capability

Most of the institute's monitoring sites are in remote coastal areas with no cell coverage. Researchers needed a tool that would work 100% offline for multi-day field sessions.

Mapalyze's offline-first architecture meant researchers could:

• Pre-load site maps and previous observation data before heading into the field
• Collect data for days without connectivity
• Automatically sync everything when they returned to the office

"The offline capability is non-negotiable for our work," says Dr. Sarah L., the lead research scientist. "Most of our monitoring sites have zero cell coverage. Mapalyze just works."

Custom Forms for Each Monitoring Protocol

The team built specialized forms for different survey types:

Water Quality Monitoring

• Temperature, pH, dissolved oxygen, salinity
• Turbidity readings, field observations
• GPS-stamped sample collection points

Vegetation Surveys

• Species identification, percent coverage
• Condition ratings (healthy, stressed, dead)
• Photo documentation with automatic GPS tagging

Wildlife Observations

• Species, count, behavior notes
• Habitat type, weather conditions
• Point or polygon capture (e.g., nesting area boundaries)

Forms included built-in validation rules. If a pH reading was outside the expected range (4.0-9.0), the researcher received an immediate warning and could re-measure on the spot.

Integrated Photo Documentation

Photos were now captured directly within the observation record. Each photo was automatically tagged with:

• GPS coordinates
• Timestamp
• The specific observation record
• Researcher name

No more manual photo matching. When the data was exported, photos were linked directly to their associated observations.

Real GIS Geometry Capture

Mapalyze allowed researchers to capture not just points, but lines and polygons. This was essential for mapping:

• Invasive species patches (polygons)
• Vegetation transects (lines)
• Wildlife movement corridors (lines)
• Specific observation points (points)

Data could be exported directly to GeoJSON or Shapefile and opened in QGIS without any manual data processing.

Quality Control in the Field

With Mapalyze, researchers could review previous observations at the same location before leaving the site. If a new water quality reading diverged significantly from historical values, they could re-measure immediately rather than discovering the discrepancy weeks later.

The Results

Coastal Ecology Institute rolled out Mapalyze to all field researchers over a two-month pilot period. The improvement in data quality and efficiency was significant:

40% Improvement in Data Accuracy

Post-deployment data validation found that observation errors dropped from 12% to under 5%. The combination of in-field validation, reduced transcription steps, and real-time quality checks made data more reliable.

For a research organization, this was transformative. Published findings were now based on cleaner, more trustworthy data.

3x Faster Data Processing

What used to take 2-3 days of GIS work now took 30 minutes. Researchers exported data from Mapalyze to GeoJSON, loaded it into QGIS, and generated spatial visualizations immediately.

Report turnaround time dropped from 3 weeks to 1 week. The team could now deliver findings to stakeholders and grant funders much faster.

Consistent Monitoring Across Sites

All 12 coastal sites were now surveyed using identical protocols and forms. This standardization made it possible to compare ecological trends across sites and identify regional patterns.

Before Mapalyze, each site used slightly different datasheets, making cross-site analysis difficult.

Better Collaboration

Researchers could see what their colleagues had already surveyed. If one researcher covered the north section of a wetland, another could focus on the south without overlap. This improved field coverage and reduced wasted effort.

More Observations Per Field Day

Eliminating manual GPS logging and photo matching meant researchers could complete 30-40% more observations per field day. Over a year, this translated to hundreds of additional data points without increasing field time.

Grant Reporting Became Easier

Grant funders often required detailed maps showing where monitoring occurred and what was found. With Mapalyze, the team could generate these maps in minutes, complete with photo documentation and observation summaries.

One researcher noted: "We used to dread grant report season because pulling together all the maps and data was so tedious. Now it's actually straightforward."

What's Next

Coastal Ecology Institute has expanded Mapalyze use to additional research programs, including:

• Coastal erosion monitoring (tracking shoreline change over time)
• Bird nesting surveys (polygon capture of nesting areas)
• Invasive species removal tracking (before/after photo documentation)

The team is also exploring the use of Mapalyze's data export API to automatically push field observations into their research database, eliminating even the final manual export step.

"Mapalyze has fundamentally changed how we do field research," says Dr. Sarah L. "The data is cleaner, the workflow is faster, and our researchers can focus on science instead of data wrangling."