SPATIAL TECHNOLOGIES IN PASTURE AND RANGE MANAGEMENT: A REVIEW

2021 ◽  
Vol 19 (1) ◽  
pp. 168-185
Author(s):  
J.A. OYEDEPO ◽  
O.S. ONIFADE
Keyword(s):  
Remote Sensing ◽  
Information Science ◽  
Vegetation Indices ◽  
Rangeland Management ◽  
Geographical Information ◽  
Specific Reference ◽  
Range Management ◽  
Grazing Land ◽  
Hyper Spectral ◽  
Complex Models

This paper looked at practical ways in which pasture and range management (P&RM) can benefit from application of spatial technologies; namely Satellite Remote Sensing, Global Positioning System and Geographical Information Science. Brief mention of these spatial technologies’ components and ways of their integrations (linear, interactive, hierarchical and complex models) were discussed with specific reference to P&RM. The paper also dwells on salient principles of applied remote sensing and geospatial technics in P&RM using examples and case studies revolving around rangeland management, spatial decision support and resource conservation. Specifically, the relevance of hyper spectral imageries and vegetation indices in cattle population and range roaming determination, grazing land and paddock site-specific management were demonstrated. It is hoped that the review will create awareness for the inclusion and use of remote sensing and geospatial technics in many areas of livestock management in Nigeria.      

scholarly journals A study on deforestation in hilly areas of Haryana using Remote Sensing and GIS technique

2020 ◽  
pp. 69-77
Author(s):  
Anju Jangra ◽  
Anurag Airon ◽  
Ram Niwas
Keyword(s):  
Remote Sensing ◽  
Forest Cover ◽  
Vegetation Indices ◽  
Remote Sensing Data ◽  
Geographical Information ◽  
Special Focus ◽  
Landsat 8 ◽  
Deforestation Rate ◽  
Gis Technique ◽  
Prime Concern

Forest is an essential part or backbone of the earth ecological system. In a country like India, the people and the economy of nation is mainly relies on the diversity of natural resources. In today's world degradation of forest resources is a prime concern for many of the scientists and environmentalists because the canvas had been transformed from last few decades to cultivated and non-cultivated land. In India, Haryana state has lowest forest cover i.e. 3.59% followed by Punjab 3.65%. Over the several decades, the advancement of Remote Sensing and Geographical Information System (GIS) technique has emerged as an efficient tool to monitor and analyse deforestation rate in hilly areaor over a variety of location. Remote sensing based vegetation indices show better sensitivity than individual band reflectance and hence are more preferred for assessment and monitoring of tress. The aim of the present study was to analyse the deforestation in hilly areas in Haryana State (India) by remote sensing data with a special focus on Panchkula and Yamunanagar. The information was collected through the LANDSAT 8 satellite of NASA. The result revealed that the deforestation rate is high in Hilly areas of Haryana. The study shows that the forest cover in hilly areas of Haryana in 2013 was 50,879.07 hectares and in 2019 it was 44,445.51 hectares of land. Thereby decrease in forest cover of 6,433.56 hectares had been observed in the study period of 2013-2019 i.e. 6 years. Spatial variations in deforestation were also mapped in GIS for the hilly areas in Panchkula and Yamunanagar districts of Haryana.  

The Development Process and Prospects of Mine Surveying in China

2011 ◽  
Vol 71-78 ◽  
pp. 1311-1317 ◽  
Author(s):  
Gang Wang ◽  
Guang Li Guo ◽  
Jian Feng Zha ◽  
Bing Fang Liu
Keyword(s):  
Remote Sensing ◽  
Development Process ◽  
Information Science ◽  
Rapid Development ◽  
Geographical Information ◽  
Mine Safety ◽  
Transit Times ◽  
Basic Work ◽  
Safety Production ◽  
Mine Surveying

Mine surveying is an important part and infrastructure protection of mine production and mine construction, and it is also very important basic work of coal mine safety production. This article summarized the development process of China's mine surveying for 60 years, the development process of China's mine surveying was from Transit Times which angling and distancing separately to Electronic Total Time which angling and distancing combo. Today, China's mine surveying has developed into an information science which combines with measurement and optoelectronic technology, computer technology, global positioning system (GPS), geographical information system (GIS) , remote sensing (RS) , D-InSAR and Unmanned Aerial Vehicle Remote Sensing with the rapid development of science and technology. This paper also analyzed the development status, opportunities and challenges-digital of China's mine surveying , and pointed out its development direction and what measures should be taken.

ANALISIS KESESUAIAN LAHAN DAN EVALUASI JENIS TANAH DALAM BUDIDAYA TANAMAN TEBU UNTUK PENGEMBANGAN DAERAH KABUPATEN TEGAL

2013 ◽  
Vol 13 (2) ◽  
Author(s):  
Daru Mulyono
Keyword(s):  
Remote Sensing ◽  
Information System ◽  
Spatial Analysis ◽  
Geographical Information System ◽  
Plant Productivity ◽  
Saccharum Officinarum ◽  
Geographical Information ◽  
Sugarcane Plant ◽  
Plant Cultivation ◽  
Suitability Map

The objectives of the research were to make land suitability map for sugarcane plant (Saccharum officinarum), to give recommendation of location including area for sugarcane plant cultivation and to increase sugarcane plant productivity. The research used maps overlay and Geographical Information System (GIS) which used Arch-View Spatial Analysis version 2,0 A in Remote Sensing Laboratory, Agency for the Assessment and Application of Technology (BPPT), Jakarta. The research was carried out in Tegal Regency starting from June to October 2004.The results of the research showed that the suitable, conditionally suitable, and not suitable land for sugarcane cultivation in Tegal Regency reached to a high of 20,227 ha, 144 ha, and 81,599 ha respectively. There were six most dominant kind of soil: alluvial (32,735 ha), grumosol 5,760 ha), mediteran (17,067 ha), latosol   (18,595 ha), glei humus (596 ha), and regosol (22,721 ha).

Analysis of Remote Sensing based Vegetation Indices (VIs) for Unmanned Aerial System (UAS): A Review

2020 ◽  
Vol 3 (2) ◽  
pp. 58-73
Author(s):  
Vijay Bhagat ◽  
Ajaykumar Kada ◽  
Suresh Kumar
Keyword(s):  
Remote Sensing ◽  
Spatial Data ◽  
Satellite Remote Sensing ◽  
Vegetation Indices ◽  
Unmanned Aerial System ◽  
Sustainable Land Management ◽  
Efficient Tool ◽  
Site Specific ◽  
The Earth ◽  
Interesting Area

Unmanned Aerial System (UAS) is an efficient tool to bridge the gap between high expensive satellite remote sensing, manned aerial surveys, and labors time consuming conventional fieldwork techniques of data collection. UAS can provide spatial data at very fine (up to a few mm) and desirable temporal resolution. Several studies have used vegetation indices (VIs) calculated from UAS based on optical- and MSS-datasets to model the parameters of biophysical units of the Earth surface. They have used different techniques of estimations, predictions and classifications. However, these results vary according to used datasets and techniques and appear very site-specific. These existing approaches aren’t optimal and applicable for all cases and need to be tested according to sensor category and different geophysical environmental conditions for global applications. UAS remote sensing is a challenging and interesting area of research for sustainable land management.

Worldview-2 and Landsat 8 Satellite Data for Seaweed Mapping along Karachi Coast

2016 ◽  
Vol 5 (2) ◽  
Author(s):  
Muhammad Danish Siddiqui ◽  
Arjumand Z Zaidi
Keyword(s):  
Satellite Data ◽  
Spatial Scales ◽  
Economic Value ◽  
Vegetation Indices ◽  
Cost Effective ◽  
Geographical Information ◽  
Landsat 8 ◽  
Coverage Area ◽  
Breeding Sites ◽  
Marine Plant

<span>Seaweed is a marine plant or algae which has economic value in many parts of the world. The purpose of <span>this study is to evaluate different satellite sensors such as high-resolution WorldView-2 (WV2) satellite <span>data and Landsat 8 30-meter resolution satellite data for mapping seaweed resources along the coastal<br /><span>waters of Karachi. The continuous monitoring and mapping of this precious marine plant and their <span>breeding sites may not be very efficient and cost effective using traditional survey techniques. Remote <span>Sensing (RS) and Geographical Information System (GIS) can provide economical and more efficient <span>solutions for mapping and monitoring coastal resources quantitatively as well as qualitatively at both <span>temporal and spatial scales. Normalized Difference Vegetation Indices (NDVI) along with the image <span>enhancement techniques were used to delineate seaweed patches in the study area. The coverage area of <span>seaweed estimated with WV-2 and Landsat 8 are presented as GIS maps. A more precise area estimation <span>wasachieved with WV-2 data that shows 15.5Ha (0.155 Km<span>2<span>)of seaweed cover along Karachi coast that is <span>more representative of the field observed data. A much larger area wasestimated with Landsat 8 image <span>(71.28Ha or 0.7128 Km<span>2<span>) that was mainly due to the mixing of seaweed pixels with water pixels. The <span>WV-2 data, due to its better spatial resolution than Landsat 8, have proven to be more useful than Landsat<br /><span>8 in mapping seaweed patches</span></span></span></span></span></span></span></span></span></span></span></span></span></span><br /><br class="Apple-interchange-newline" /></span></span></span></span></span>

scholarly journals Mapping Groundwater Potential for Irrigation, by Geographical Information System and Remote Sensing Techniques: A Case Study of District Lower Dir, Pakistan

Atmosphere ◽  
2021 ◽  
Vol 12 (6) ◽  
pp. 669
Author(s):  
Abid Sarwar ◽  
Sajid Rashid Ahmad ◽  
Muhammad Ishaq Asif Rehmani ◽  
Muhammad Asif Javid ◽  
Shazia Gulzar ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Water Table ◽  
Groundwater Potential ◽  
Geographical Information ◽  
Groundwater Potential Zone ◽  
Potential Zone ◽  
Relative Significance ◽  
High Good ◽  
Groundwater Potentiality ◽  
Very High

The changing climate and global warming have rendered existing surface water insufficient, which is projected to adversely influence the irrigated farming systems globally. Consequently, groundwater demand has increased significantly owing to increasing population and demand for plant-based foods especially in South Asia and Pakistan. This study aimed to determine the potential areas for groundwater use for agriculture sector development in the study area Lower Dir District. ArcGIS 10.4 was utilized for geospatial analysis, which is referred to as Multi Influencing Factor (MIF) methodology. Seven parameters including land cover, geology, soil, rainfall, underground faults (liniment) density, drainage density, and slope, were utilized for delineation purpose. Considering relative significance and influence of each parameter in the groundwater recharge rating and weightage was given and potential groundwater areas were classified into very high, high, good, and poor. The result of classification disclosed that the areas of 113.10, 659.38, 674.68, and 124.17 km2 had very high, high, good, and poor potential for groundwater agricultural uses, respectively. Field surveys for water table indicated groundwater potentiality, which was high for Kotkay and Lalqila union councils having shallow water table. However, groundwater potentiality was poor in Zimdara, Khal, and Talash, characterized with a very deep water table. Moreover, the study effectively revealed that remote sensing and GIS could be developed as potent tools for mapping potential sites for groundwater utilization. Furthermore, MIF technique could be a suitable approach for delineation of groundwater potential zone, which can be applied for further research in different areas.

scholarly journals Semantics of Voids within Data: Ignorance-Aware Machine Learning

2021 ◽  
Vol 10 (4) ◽  
pp. 246
Author(s):  
Vagan Terziyan ◽  
Anton Nikulin
Keyword(s):  
Spatial Data ◽  
Information Science ◽  
Nearest Neighbor ◽  
Geographical Information ◽  
Two Dimensional ◽  
Prototype Selection ◽  
Data Space ◽  
Important Concern ◽  
Traditional Classification ◽  
Nearest Neighbor Classifiers

Operating with ignorance is an important concern of geographical information science when the objective is to discover knowledge from the imperfect spatial data. Data mining (driven by knowledge discovery tools) is about processing available (observed, known, and understood) samples of data aiming to build a model (e.g., a classifier) to handle data samples that are not yet observed, known, or understood. These tools traditionally take semantically labeled samples of the available data (known facts) as an input for learning. We want to challenge the indispensability of this approach, and we suggest considering the things the other way around. What if the task would be as follows: how to build a model based on the semantics of our ignorance, i.e., by processing the shape of “voids” within the available data space? Can we improve traditional classification by also modeling the ignorance? In this paper, we provide some algorithms for the discovery and visualization of the ignorance zones in two-dimensional data spaces and design two ignorance-aware smart prototype selection techniques (incremental and adversarial) to improve the performance of the nearest neighbor classifiers. We present experiments with artificial and real datasets to test the concept of the usefulness of ignorance semantics discovery.

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