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Project Experience · Remote Sensing / Land Cover

Kafr El-Sheikh LCCS Analysis

Land-cover analysis presented through mapped views for 2006, 2013 and 2018.

Kafr El-Sheikh LCCS project overview map

Project overview

This project presents LCCS analysis for Kafr El-Sheikh through an authentic overview map and dated map outputs for 2006, 2013 and 2018.

LocationKafr El-Sheikh, Egypt
Documented map dates2006 · 2013 · 2018
Project typeLCCS analysis
Project evidenceOverview plus 3 dated maps

Technologies & capabilities

  • Remote sensing
  • LCCS analysis
  • Land-cover mapping

Authentic project visuals

Before & after

Kafr El-Sheikh multi-temporal map comparison

Comparison of Kafr El-Sheikh land-cover maps from 2006 and 2018 — 2006
Comparison of Kafr El-Sheikh land-cover maps from 2006 and 2018 — 2018
20062018

Current capability

From Dated Land-Cover Maps to Continuous Change Intelligence

For comparable requirements today, Start For IT can structure a transparent land-cover workflow around the approved classification scheme, imagery dates, validation data and reporting needs.

Current capability — separate from historical project scope

Land-Cover Classification

Prepare imagery and mapped classes using a project-appropriate classification framework, documented class definitions and validation workflow.

  • LCCS
  • Classification
  • Validation

Multi-Date Change Analysis

Compare consistent dated outputs to identify mapped transitions and produce reviewable change summaries.

  • Time Series
  • Change Matrix
  • Change Maps

AI-Assisted Mapping

Where labelled samples and image quality support it, machine learning can assist classification and feature extraction under human quality control.

  • GeoAI
  • Feature Extraction
  • Quality Control

Web GIS & Reporting

Deliver approved maps, comparisons and statistics through a responsive Web GIS or reporting dashboard.

  • Web GIS
  • Reports
  • Decision Support

Land-cover intelligence architecture

Imagery & reference dataClassificationChange analysisMaps / dashboard
Traceable classification and change outputs for environmental, agricultural and planning decisions.

Discuss your land-cover analysis requirement.

Plan a transparent Remote Sensing workflow around the required dates, classes, imagery, validation and delivery format.

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