Strategy For Assessment Of Land And Complex Fields Type Analysis Through GIS In Bangladesh

TL;DR

This paper presents a GIS-based system for assessing and mapping cultivable land in Bangladesh to aid in food security and land management, utilizing digital mapping, object detection, and real-time analysis.

Contribution

It introduces a new interactive GIS system that integrates Google Earth data with object detection and user feedback for accurate land classification in Bangladesh.

Findings

GIS mapping reveals land loss over years

System enables real-time land analysis

Supports agricultural planning and food security

Abstract

Bangladesh is an over populated developing country where crisis of food is a major issue, it faces different infrastructure problem in every sector. For Poverty Alleviation from the country we have to confirm cultivable land to increase the crop production for feeding the over population of the country. This paper focuses on the measurement of cultivable land for cultivation. The main purpose of this paper is to briefly describe how the GIS, Digital Mapping, Internet concepts and tools can effectively contribute in the modeling, analysis and visualization phases within an engineering or research project according to the crops by using object detection, object tracking and field mapping in Bangladesh. Through GIS mapping of the agricultural lands, the statistics can be made of how much land is cultivable and each year how much land we are losing. Mapping the cultivation land will tell us how much crop we have to import from other countries. Enabling real-time GIS analysis anytime, anywhere, the implementation of the GIS information to a wider aspect. Automation is the indicator of the modern civilizations. The system will benefit the food stock of the country according to the harvest. For this research we developed a new interactive system. The system will integrate with GIS project data in Google Earth, first finds highly accurate cluster images and partial images, obtains user feedback to merge or correct these digests, and then the supplementary visual analysis complete the partitioning of the data. This study was conducted at the software laboratory, Computer Science and Engineering department, Jahangirnagar University, Dhaka, Bangladesh in 2013.