scholarly journals Use of Remote Sensing and Geographic Information System for the Classification of Agricultural Land Uses and Land Cover in the Al-Sad Al-Adhim sub District – Iraq

2018 ◽  
Vol 225 (2) ◽  
pp. 245-273
Author(s):  
Assist. Prof. Dr. Saleem Y. Jamal
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Information System ◽  
Geographic Information System ◽  
Land Cover ◽  
Agricultural Land ◽  
Geographic Information ◽  
Land Uses ◽  
Barren Land

     Land use refers to the human activity associated with a particular area of land. The land cover refers to the pattern of appearances located on the surface of the earth. Survey, inventory, monitoring and classification of land use and land cover are a fundamental step in the land use planning process, in evaluating and comparing alternatives and in choosing the best and sustainable use of land for development, accomplishment economic and social well-being. Remote sensing and Geographic Information System provided advantages that conventional methods could not provide for surveys and monitoring of natural and human resources, and classification of agricultural land uses and land cover in the area of the Al-Sad Al-Adhim sub District – Iraq. Depending on the Anderson system and others to classify land uses and land cover, through the integration of digital interpretation with the use of Digital Image Processing (ERDAS IMAGINE) software, and visual interpretation using ArcGIS software. Classification of agricultural land use and land cover up to the third level, with over all accuracy of the map 90%. the percentage distribution of the areas shows that the agricultural lands ranked first and occupy 52%, then grassland occupies 19%, barren land is occupied 17%, urban areas and built up occupy 9% water is ranked last occupy 3% of the total area of the study area.

scholarly journals Analysis Transfer of the Function Cover of Agricultural Land Become a Housing Area and Industry in the Semarang City with Approach of Remote Sensing and Geographic Information System

2019 ◽  
Vol 3 (2) ◽  
pp. 204-210
Author(s):  
Harnawan Nurul Asna ◽  
Frederik Samuel Papilaya
Keyword(s):  
Remote Sensing ◽  
Information System ◽  
Geographic Information System ◽  
Land Cover ◽  
Land Cover Change ◽  
Agricultural Land ◽  
Unsupervised Classification ◽  
Geographic Information ◽  
Classification Technique ◽  
Housing Area

The purpose of this study was to find out how much area of agricultural land was converted because of the high property business activities in Semarang City, the data used for this study were taken from 1999 to 2018. The classification method used in this study was the remote sensing method using the unsupervised classification technique. Output of this study is the extensive data of agricultural land cover change obtained from 1999 to 2018. The results of this study can prove that the Geographic Information System can be used to find out how much agricultural land cover change in Semarang City from 1999 to 2018. The area of agricultural land that has been converted is from 1999 to 2009 around 3072 ha and from 2009 to 2018 around 1071.4 ha.

scholarly journals Modeling Land Use and Land Cover Dynamic Using Geographic Information System and Markov-CA

2020 ◽  
Vol 5 (2) ◽  
pp. 210
Author(s):  
Millary Agung Widiawaty ◽  
Arif Ismail ◽  
Moh. Dede ◽  
N. Nurhanifah
Keyword(s):  
Land Use ◽  
Information System ◽  
Geographic Information System ◽  
Land Cover ◽  
Agricultural Land ◽  
Dynamic Models ◽  
Geographic Information ◽  
Google Earth ◽  
Road Density ◽  
Lulc Change

The need for built-up area increases along with a rise in population growth in many regions. This phenomenon leads to a tremendous change in agricultural land and decrease in the environmental carrying capacity. Therefore, this study aims to determine Land Use and Land Cover (LULC) dynamics and the drivers used for its modeling in 2030. This is a quantitative study, which uses the dynamic models of Geographic Information System (GIS) and Markov-CA. Data were obtained from the CNES-Airbus satellite imageries in 2009, 2014, and 2019 by using Google Earth at East Cirebon. The drivers include road density, distance to CBD, total population, distance to settlements, land slope and distance to rivers. The interaction between drivers and LULC change was analyzed using binary logistic regression. The results showed that the rise of built-up area reached 36.4 percent and causes the loss of 0.78 km2 of agricultural land from 2009 to 2019. The LULC simulation in 2030 shows an increase in the built-up area by 82.85 percent with probabilities above 0.6. Meanwhile the significant drivers for changes include road density and distance to settlements. In conclusion, efforts to reduce LULC change in agricultural land into built-up area is by re-strengthening spatial planning-based environmental awareness for the community. Keywords: Built-up area; GIS; LULC; Markov-CA; Spatial modeling   Copyright (c) 2020 Geosfera Indonesia Journal and Department of Geography Education, University of Jember This work is licensed under a Creative Commons Attribution-Share A like 4.0 International License

scholarly journals CHANGE DETECTION IN LAND USE AND LAND COVER OF DISTRICT CHARSADDA PAKISTAN ALONG RIVER KABUL (2010 FLOOD): TAKING ADVANTAGE OF GEOGRAPHIC INFORMATION SYSTEM AND REMOTE SENSING

2021 ◽  
Vol 5 (2) ◽  
pp. 40-46
Author(s):  
Misbah Fida ◽  
Irshad Hussain ◽  
Abdur Rashid ◽  
Syed Amir Ali Shah ◽  
Sardar Khan
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Water Body ◽  
Agricultural Land ◽  
Geographic Information ◽  
Land Cover Changes ◽  
Barren Land ◽  
Gis And Remote Sensing ◽  
Kabul River

This study aims to quantify land use and land cover changes before and after the 2010 flood in district Charsadda, Pakistan. Advanced geographic information systems (GIS) and remote sensing techniques (RST) evaluate land use and land cover changes. The purpose of this research is to estimate and compare the pre-and post-flood changes and their influences on land use and land cover changes. Land use land cover data studies are important for sustainable management of natural resources; they are becoming increasingly important for assessing the environmental impacts of economic development. Moreover, some remedial measures are adopted to develop the area’s land cover to overcome future problems. Land use and land cover changes are measured using satellite images. Two instances, i.e., pre-flood and post-flood, are compared to analyze the change in land use and land cover of district Charsadda within 5 km along the Kabul River. Comparative analysis of pre-flood and post-flood imageries highlighted some drastic changes over the water body, built-up area, agricultural land, and bare land during flood instances. The study area is rural and agricultural land is dominant as compared to other land uses. We evaluated the percentage of different land use and land cover within our study area. The agricultural land found about 68.5%, barren land 22.5%, and the water body 8.8% before the flood. After inundation, the water body raised to 16.4%, bare soil increased to 26.3%, agricultural land degraded up to 57.0%, and settlements (villages) along the Kabul River were severely damaged and finished by this flood. 2010’s flood heavily damaged approximately four villages in district Nowshera, six in district Peshawar, and twenty-seven Charsadda District villages.

scholarly journals Automated Classification of Agricultural Lands Using GIS and NES

2018 ◽  
Vol 7 (4.38) ◽  
pp. 1146
Author(s):  
V. K. Kalichkin ◽  
A. I. Pavlova ◽  
A. F. Petrov ◽  
V. A. Smolyakov
Keyword(s):  
Land Use ◽  
Information System ◽  
Geographic Information System ◽  
Interpolation Method ◽  
Ground Surface ◽  
Geographic Information ◽  
Automated Classification ◽  
Stream Power ◽  
Stream Power Index

The article proposes the methodology for the automated classification of uplands using Geographic Information System (GIS) and Neural Expert System (NES). Quantitative indicators of topography are used as the basis of the proposed classification. A database consisting of topographic, soil, and land use maps was created using ArcGIS 10 geographic information system. A topologically correct digital elevation model (DEM) was created by the ANUDEM interpolation method. The DEM contains the following maps: hypsometric, steepness and slopes exposure, plan, profile, common curvature of the ground surface, and cumulative runoff maps. The boundaries of elementary surfaces (ES), which are homogeneous morphological formations, are established. Parameters characterizing the Stream Power Index (SPI) are taken into account. The essence of the proposed classification consists in attributing of ES to a certain group of lands based on aggregate of features. To do this, partial scales were created, containing indicators of topography, soil cover, land drainage conditions, as well as the degree of erosion development. The authors formed knowledge base for traning the NES using GIS database and partial scales of estimates. Teaching of neural network was carried out. The classification and topology of land was carried out by means of the NES. The uplands are distributed in flat and slightly convex areas. They are characterized by the following indicators: the curvature of the ground surface: plan curvature (0 – 0.03), profile curvature (0 – 0.15), common curvature (0 – 0.22); slope angles (less than 1.5о); horizontal dissection in elevation (less than 0.5 km/km2), vertical dissection (less than 5 m); and SPI (from -13.80 to -6.47). Electronic map of uplands of LLC «Salair» land-use area was created in the ArcGIS 10 environment.  

Sign in / Sign up

Export Citation Format

Share Document