Application of Geographic Information System to Predict Land Use Change for Maximum Flow Rate Calculation

2019 ◽  
pp. 96-108
Author(s):  
Yutthana Chaona ◽  
Teerawate Limkomonvilas ◽  
Sathaporn Monprapussorn
Keyword(s):  
Land Use ◽  
Information System ◽  
Geographic Information System ◽  
Land Use Change ◽  
Flow Rate ◽  
Maximum Flow ◽  
Geographic Information ◽  
Maximum Flow Rate ◽  
Rate Calculation

scholarly journals Agricultural Land Conversion and Land Use Change Dynamics in North Bandung Area

2007 ◽  
Vol 9 (2) ◽  
pp. 63-70 ◽  
Author(s):  
Agus Ruswandi ◽  
Ernan Rustiadi ◽  
Kooswardhono Mudikdjo
Keyword(s):  
Land Use ◽  
Information System ◽  
Geographic Information System ◽  
Land Use Change ◽  
Agricultural Land ◽  
Geographic Information ◽  
Land Conversion ◽  
Change Dynamics

Agricultural land conversion is considered as one of an important issus in the developing areas. In spite of theimportance of informations on the quantity and the rate of land conversion as the basis of formulating the agricultural landconversion policy, those informations are limited. This research was conducted at Lembang and Parongpong Sub-District,Bandung District. The objectives of research are to identify the rate of agricultural land conversion and to measure thedynamic change of land use. Land use in 1992 and 2002 was evaluated by interpretating the result of 1992 and 2002 landsatimage using Geographic Information System (GIS) program. Shift Share analysis was conducted to know the dynamic changeof land use. Results of the study indicated that land conversion at Lembang and Parongpong Sub-District during the period of1992-2002 (ten years) about 3,134.49 ha (25%) or 313.5 ha (2,96%) per year. Forestland reduced the most, from 5,470 ha in 1992 to 1,746 ha in 2002 or reduced about 3,732.12 ha (68%) in ten years. While area of the bush was increased about2,780.20 ha (1,326%) during the same period, from 210 ha in 1992 to 2,990 ha in 2002. Low land was decreasedfrom 252 hain 1992 to 95 ha in 2002, up land was decreased from 3,856 ha in 1992 to 2,736 ha in 2002, mix farming was increasedfrom2,491 ha in 1992 to 4,358 ha in 2002, resettlement was increased from 359 ha in 1992 to 1,612 ha in 2002, bare wasdecreasedfrom 1,115 ha in 1992 to 217 ha in 2002, lake was decreasedfrom 52 ha in 1992 to 50 ha in 2002.

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.  

scholarly journals The Use of Remote Sensing and Geographic Information System Techniques to Determine Relationships between Land Use and Landform

2014 ◽  
Vol 3 (2) ◽  
Author(s):  
Tülay TUNÇAY ◽  
İlhami BAYRAMİN ◽  
Hasan Sabri ÖZTÜRK ◽  
Mümtaz KİBAR ◽  
Oğuz BAŞKAN
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Information System ◽  
Geographic Information System ◽  
Geographic Information

Calculation of Land Consolidation Potential Based on GIS

2014 ◽  
Vol 580-583 ◽  
pp. 2769-2773
Author(s):  
Yan Hua Liu ◽  
Wei Qing Chen
Keyword(s):  
Land Use ◽  
Information System ◽  
Geographic Information System ◽  
Geographic Information ◽  
Land Consolidation ◽  
Cultivated Land ◽  
Thematic Maps ◽  
Residential Land ◽  
Rural Residential Land ◽  
In Virtue Of

Through the analysis of land use actuality, this paper summarizes the characteristics of land use, in virtue of geographic information system (GIS) platform, the database of land consolidation is constructed, combining with different calculation models of cultivated land and rural residential land consolidation potential, the consolidation potentials of cultivated land and rural residential land are calculated, and the thematic maps about land consolidation potential of each village and town in study area are mapped out. The results show that the land consolidation areas are mainly concentrated in the middle of study area.

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