scholarly journals A Framework to Automatic Detect Center Pivots Using Land Use and Land Cover Data

2021 ◽  
Vol 73 (4) ◽  
pp. 1048-1070
Author(s):  
Marcos Lima Rodrigues ◽  
Thales Sehn Körting ◽  
Gilberto Ribeiro de Queiroz
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Vegetation Indices ◽  
Irrigated Agriculture ◽  
Landsat 8 ◽  
Land Cover Data ◽  
Machine Learning Approach ◽  
Center Pivot ◽  
Shape Characteristics ◽  
Consumptive Water

Water management is a key field to support life and economic activity nowadays. The greatly increased mechanization of agriculture, mainly through center pivot irrigation systems, represents a big challenge to control this resource. Irrigated agriculture makes up the large majority of consumptive water use, therefore it is important to identify and quantify these systems. Currently, with 6.95x10⁶ ha, Brazil is among the 10 largest countries in irrigation areas in the world. In this study, a combined Computer Vision and Machine Learning approach is proposed for the identification of center pivots in remote sensing images. The methodology is based on Circular Hough Transform (CHT) and Balanced Random Forest (BRF) classifier using vegetation indices NDVI/SAVI generated from Landsat 8 images and Land Use and Land Cover (LULC) data provided by project MapBiomas. The candidate's circles of pivots identified on images are filtered based on vegetation behavior and shape characteristics of these areas. Our approach was able to detect 7358 pivots, reaching 83.86% of Recall for 52 scenes analyzed overall Brazil compared with mapping done by the Brazilian National Water and Sanitation Agency (ANA). In some scenes, the Recall reaches up to 100%.

scholarly journals A comparative analysis of Resourcesat-2 LISS-3 and Landast-8 OLI imagery

2014 ◽  
Vol XL-8 ◽  
pp. 987-989 ◽  
Author(s):  
E. Venkateswarlu ◽  
T. Sivannarayana ◽  
K. V. Ratna Kumar
Keyword(s):  
Land Use ◽  
Comparative Analysis ◽  
Land Cover ◽  
Andhra Pradesh ◽  
Vegetation Indices ◽  
Land Cover Classification ◽  
Landsat 8 ◽  
Electromagnetic Spectrum ◽  
Data Gaps ◽  
Spectral Vegetation Indices

Linear Imaging Self Scanning Sensor (LISS-3) onboard Resoucesat-1 and 2 Satellites have been used extensively for various land cover-land use applications. In this study, we examined the potential of using Resourcesat-2 LISS-3 images in the absence of LANDSAT-8 Operational Land Imager (OLI) images. This paper compares the capabilities of LISS-3 sensor with OLI sensor. LISS-3 images were selected for comparison because of their close resemblance in electromagnetic spectrum range with LS-8 OLI images. Images of LS-8 OLI and RS-2 LISS-3 of the same area in Andhra Pradesh were used to evaluate the comparative performances based on the intra-inter band correlation, spectral vegetation indices and land cover classification. The results showed that in most cases the LS-8 OLI and the RS-2 LISS-3 images are comparable. This study also indicated that LISS-3 images could fill the data gaps in OLI images for land-cover studies, vice versa.

scholarly journals Spatial-Temporal Land Use and Land Cover Changes in Urban Areas Using Remote Sensing Images and GIS Analysis: The Case Study of Opole, Poland

Geosciences ◽  
2021 ◽  
Vol 11 (8) ◽  
pp. 312
Author(s):  
Barbara Wiatkowska ◽  
Janusz Słodczyk ◽  
Aleksandra Stokowska
Keyword(s):  
Remote Sensing ◽  
Land Use ◽  
Land Cover ◽  
Satellite Imagery ◽  
Urban Areas ◽  
Agricultural Land ◽  
Urban Expansion ◽  
Landsat 8 ◽  
Rate Of Increase ◽  
Management Procedures

Urban expansion is a dynamic and complex phenomenon, often involving adverse changes in land use and land cover (LULC). This paper uses satellite imagery from Landsat-5 TM, Landsat-8 OLI, Sentinel-2 MSI, and GIS technology to analyse LULC changes in 2000, 2005, 2010, 2015, and 2020. The research was carried out in Opole, the capital of the Opole Agglomeration (south-western Poland). Maps produced from supervised spectral classification of remote sensing data revealed that in 20 years, built-up areas have increased about 40%, mainly at the expense of agricultural land. Detection of changes in the spatial pattern of LULC showed that the highest average rate of increase in built-up areas occurred in the zone 3–6 km (11.7%) and above 6 km (10.4%) from the centre of Opole. The analysis of the increase of built-up land in relation to the decreasing population (SDG 11.3.1) has confirmed the ongoing process of demographic suburbanisation. The paper shows that satellite imagery and GIS can be a valuable tool for local authorities and planners to monitor the scale of urbanisation processes for the purpose of adapting space management procedures to the changing environment.

scholarly journals A Comparative Analysis of Spatial Data and Land Use/Land Cover Classification in Urbanized Areas and Areas Subjected to Anthropogenic Pressure for the Example of Poland

2021 ◽  
Vol 13 (6) ◽  
pp. 3070
Author(s):  
Patrycja Szarek-Iwaniuk
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Land Cover Classification ◽  
Classification Systems ◽  
Anthropogenic Pressure ◽  
Land Use Land Cover ◽  
Land Use Classification ◽  
Land Cover Data ◽  
Spatial Changes ◽  
Land Use Types

Urbanization processes are some of the key drivers of spatial changes which shape and influence land use and land cover. The aim of sustainable land use policies is to preserve and manage existing resources for present and future generations. Increasing access to information about land use and land cover has led to the emergence of new sources of data and various classification systems for evaluating land use and spatial changes. A single globally recognized land use classification system has not been developed to date, and various sources of land-use/land-cover data exist around the world. As a result, data from different systems may be difficult to interpret and evaluate in comparative analyses. The aims of this study were to compare land-use/land-cover data and selected land use classification systems, and to determine the influence of selected classification systems and spatial datasets on analyses of land-use structure in the examined area. The results of the study provide information about the existing land-use/land-cover databases, revealing that spatial databases and land use and land cover classification systems contain many equivalent land-use types, but also differ in various respects, such as the level of detail, data validity, availability, number of land-use types, and the applied nomenclature.

scholarly journals Monitoring the Spatial Variation of Aerosol Optical Depth and Its Correlation with Land Use/Land Cover in Wuhan, China: A Perspective of Urban Planning

2021 ◽  
Vol 18 (3) ◽  
pp. 1132
Author(s):  
Qijiao Xie ◽  
Qi Sun
Keyword(s):  
Land Use ◽  
Air Quality ◽  
Urban Planning ◽  
Land Cover ◽  
Aerosol Optical Depth ◽  
Optical Depth ◽  
Water Bodies ◽  
Landsat 8 ◽  
Land Use Land Cover ◽  
The Impact

Aerosols significantly affect environmental conditions, air quality, and public health locally, regionally, and globally. Examining the impact of land use/land cover (LULC) on aerosol optical depth (AOD) helps to understand how human activities influence air quality and develop suitable solutions. The Landsat 8 image and Moderate Resolution Imaging Spectroradiometer (MODIS) aerosol products in summer in 2018 were used in LULC classification and AOD retrieval in this study. Spatial statistics and correlation analysis about the relationship between LULC and AOD were performed to examine the impact of LULC on AOD in summer in Wuhan, China. Results indicate that the AOD distribution expressed an obvious “basin effect” in urban development areas: higher AOD values concentrated in water bodies with lower terrain, which were surrounded by the high buildings or mountains with lower AOD values. The AOD values were negatively correlated with the vegetated areas while positively correlated to water bodies and construction lands. The impact of LULC on AOD varied with different contexts in all cases, showing a “context effect”. The regression correlations among the normalized difference vegetation index (NDVI), normalized difference built-up index (NDBI), normalized difference water index (NDWI), and AOD in given landscape contexts were much stronger than those throughout the whole study area. These findings provide sound evidence for urban planning, land use management and air quality improvement.

Making Of Classification Land Cover Through Result Of Visual Data Satellite Image Analysis Landsat 8 OLI : Case Study in Tapaktuan District, South Aceh District

2021 ◽  
Vol 6 (1) ◽  
pp. 59-65
Author(s):  
Safridatul Audah ◽  
Muharratul Mina Rizky ◽  
Lindawati
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Image Classification ◽  
Satellite Image ◽  
Landsat 8 ◽  
Landsat 8 Oli ◽  
Sensing Technology ◽  
Open Land ◽  
Cover Class ◽  
Satellite Image Analysis

Tapaktuan is the capital and administrative center of South Aceh Regency, which is a sub-district level city area known as Naga City. Tapaktuan is designated as a sub-district to be used for the expansion of the capital's land. Consideration of land suitability is needed so that the development of settlements in Tapaktuan District is directed. The purpose of this study is to determine the level of land use change from 2014 to 2018 by using remote sensing technology in the form of Landsat-8 OLI satellite data through image classification methods by determining the training area of the image which then automatically categorizes all pixels in the image into land cover class. The results obtained are the results of the two image classification tests stating the accuracy of the interpretation of more than 80% and the results of the classification of land cover divided into seven forms of land use, namely plantations, forests, settlements, open land, and clouds. From these classes, the area of land cover change in Tapaktuan is increasing in size from year to year.

scholarly journals Land use and land cover mapping and identification of misuse in the permanent preservation areas in the Tailândia Municipality - PA

2017 ◽  
Vol 38 (3) ◽  
pp. 1145 ◽  
Author(s):  
Rosana Sumiya Gurgel ◽  
Paulo Roberto Silva Farias ◽  
Sandro Nunes de Oliveira
Keyword(s):  
Land Use ◽  
Land Cover ◽  
Palm Oil ◽  
Regulatory Agencies ◽  
Visual Interpretation ◽  
Livestock Farming ◽  
Land Cover Data ◽  
The Government ◽  
Remote Sensing Techniques ◽  
Bodies Of Water

The objective of this study is to expand the mapping of land use and land cover, as well as of the permanent preservation areas (PPAs), and identify land misuse areas in the PPAs in the Tailândia municipality in the state of Pará, which is part of the Amazon biome. Remote sensing techniques and geographic information systems (GIS) were used to achieve these goals. Mapping and classification for the year 2012 were made by visual interpretation of images obtained from the RapidEye satellite, which has a 5 m spatial resolution. In this work, we identified nine classes of land use and land cover. From the hydrography vectors it was possible to determinate the Permanent Preservation Areas of the bodies of water according to the environmental legislation. Analysis of misuse in the PPAs was made by crossing-checking the land use and land cover data with that of the PPAs. The results show that 53 % of the municipality (2,347.64 km²) is occupied by human activities. Livestock farming is the activity that has most increased the use of area (30 %), followed by altered vegetation (14.6 %) and palm oil (7.2 %). The PPAs have a high percentage of misuse (47.12 %), with livestock being the largest contributor, occupying 26.65 % of the PPAs, followed by altered vegetation (12.64 %) and palm oil (4.29 %). Therefore, the main objective in Tailândia is to reconcile economic activity with sustainable development. It is important to emphasize the partnerships between the government, research institutions, regulatory agencies, states departments and local communities, else it would be impossible to monitor or control an area as vast as the Amazon.

scholarly journals Predicting Land Use/Land Cover Changes Using a CA-Markov Model under Two Different Scenarios

2018 ◽  
Vol 10 (10) ◽  
pp. 3421 ◽  
Author(s):  
Rahel Hamad ◽  
Heiko Balzter ◽  
Kamal Kolo
Keyword(s):  
Land Use ◽  
Markov Chain ◽  
Land Cover ◽  
Land Use Changes ◽  
Landsat 8 ◽  
Chain Model ◽  
Land Use Land Cover ◽  
Kurdistan Region ◽  
The Past ◽  
Past Trend

Multi-temporal Landsat images from Landsat 5 Thematic Mapper (TM) acquired in 1993, 1998, 2003 and 2008 and Landsat 8 Operational Land Imager (OLI) from 2017, are used for analysing and predicting the spatio-temporal distributions of land use/land cover (LULC) categories in the Halgurd-Sakran Core Zone (HSCZ) of the National Park in the Kurdistan region of Iraq. The aim of this article was to explore the LULC dynamics in the HSCZ to assess where LULC changes are expected to occur under two different business-as-usual (BAU) assumptions. Two scenarios have been assumed in the present study. The first scenario, addresses the BAU assumption to show what would happen if the past trend in 1993–1998–2003 has continued until 2023 under continuing the United Nations (UN) sanctions against Iraq and particularly Kurdistan region, which extended from 1990 to 2003. Whereas, the second scenario represents the BAU assumption to show what would happen if the past trend in 2003–2008–2017 has to continue until 2023, viz. after the end of UN sanctions. Future land use changes are simulated to the year 2023 using a Cellular Automata (CA)-Markov chain model under two different scenarios (Iraq under siege and Iraq after siege). Four LULC classes were classified from Landsat using Random Forest (RF). Their accuracy was evaluated using κ and overall accuracy. The CA-Markov chain method in TerrSet is applied based on the past trends of the land use changes from 1993 to 1998 for the first scenario and from 2003 to 2008 for the second scenario. Based on this model, predicted land use maps for the 2023 are generated. Changes between two BAU scenarios under two different conditions have been quantitatively as well as spatially analysed. Overall, the results suggest a trend towards stable and homogeneous areas in the next 6 years as shown in the second scenario. This situation will have positive implication on the park.

scholarly journals Assessment of land cover on soil erosion in Lam Phra Phloeng watershed by USLE model

2018 ◽  
Vol 192 ◽  
pp. 02017 ◽  
Author(s):  
Jatuwat Wattanasetpong ◽  
Uma Seeboonruang ◽  
Uba Sirikaew ◽  
Walter Chen
Keyword(s):  
Land Use ◽  
Soil Erosion ◽  
Land Cover ◽  
Soil Loss ◽  
Land Development ◽  
Developed Countries ◽  
Surface Erosion ◽  
Agricultural Field ◽  
Land Cover Data

Soil loss due to surface erosion has been a global problem not just for developing countries but also for developed countries. One of the factors that have greatest impact on soil erosion is land cover. The purpose of this study is to estimate the long-term average annual soil erosion in the Lam Phra Phloeng watershed, Nakhon Ratchasima, Thailand with different source of land cover by using the Universal Soil Loss Equation (USLE) and GIS (30 m grid cells) to calculate the six erosion factors (R, K, L, S, C, and P) of USLE. Land use data are from Land Development Department (LDD) and ESA Climate Change Initiative (ESA/CCI) in 2015. The result of this study show that mean soil erosion by using land cover from ESA/CCI is less than LDD (29.16 and 64.29 ton/ha/year respectively) because soil erosion mostly occurred in the agricultural field and LDD is a local department that survey land use in Thailand thus land cover data from this department have more details than ESA/CCI.

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