scholarly journals PEMANFAATAN INDERAJA DAN SISTEM INFORMASI GEOGRAFIS (SIG) DALAM INVENTARISASI LAHAN KRITIS DI KABUPATEN KOLAKA UTARA

PERENNIAL ◽  
2010 ◽  
Vol 6 (2) ◽  
pp. 83 ◽  
Author(s):  
. Baharuddin
Keyword(s):  
Remote Sensing ◽  
Forest Area ◽  
Director General ◽  
Social Forestry ◽  
Land Resources ◽  
Suitability Analysis ◽  
Degraded Land ◽  
Productivity Data ◽  
Land Condition ◽  
Potential Land

At this time the technology required to conduct a study of land mainly related to land change and land condition analysis. To anticiapate this need for technology Remote Sensing and Geographic Information System (GIS) that can quickly and accurately to conduct a study on land resources. Critical land is a condition of land which is the result of an error in the maintenance and land management. Kolaka Utara Regency a new district which has the problem of land mainly biophysical and social condition.In this case the methode used is to land suitability analysis approach based on FAO and determination based on the rules Director General Land Rehabilitation and Social Forestry – DEPHUT, SK.167/V-SET/2004, combined with productivity data field based on their utilization. Based on the analysis with Remote Sensing and GIS in Kolaka Utara Regency result that is dominated by protected forest area of 163.376,51 ha (53,0 %), followed by limited production forest 65.887,63 ha (21 %), cultivation area 60.977,75 ha. (19,6 %) and production forest convertion 20.258,94 ha (6.5 %). Land use and land cover largest is forest area of 177.850,02 ha (57,3 %), cocoa palantation area 91.066.80 ha (29,3 %), garden mixed area18.517,76 ha (6,0 %), shrub area 11.615,40 ha (3,7 %), and clove plantation area 4.067,93 ha ( 1,3 %). Potential land critical area is 39.040,96 ha (12,6 %), land rather critical is 13.513,43 ha (4,4 %), critical land is 47.534,21 ha, (15,3 %) and land critical immensely is 19.509,42 ha (6,3 %), and land while the rest is not critical is 190.902,81 ha (61,5 %). Degraded land spread in all areas well outside the region (cultivate area) and within region (forest area). Key words: Inderaja, SIG, critical land

scholarly journals ANALISIS LAHAN KRITIS DAN ARAHAN LAHAN DALAM PENGEMBANGAN WILAYAH PADA SUBDAS DI KABUPATEN KAYONG UTARA MENGGUNAKAN TEKNIK PENGINDERAAN JAUH DAN SISTEM INFORMASI GEOGRAFIS

2019 ◽  
Vol 9 (1) ◽  
Author(s):  
Murti Anom Suntoro ◽  
Dwi Astiani ◽  
Wiwik Ekyastuti
Keyword(s):  
Remote Sensing ◽  
Information System ◽  
Geographic Information System ◽  
Spatial Data ◽  
Geographic Information ◽  
Director General ◽  
Landsat 8 ◽  
Degraded Land ◽  
Technical Guidance

Critical land is a damaged land, thus losing or decreasing its function to the specified or expected limits. The identification and critical lands mapping is essential for the planning and determination of priority watersheds in order to the utilization and development of natural resources and land rehabilitation and soil conservation. Remote sensing is a technique that enable people to collect data without direct field measurement. The using of Landsat 8 image then analyzed by using Geographic Information System (GIS) is being expected to improve the ability to classify land cover, the map was then overlad with parameter map based on Regulation of Director General of Management of Watershed and Social Forestry Number P. 4 / V-Set / 2013 about technical guidance on the preparation of spatial data of other critical lands to identify critical lands in Kayong Utara Regency.Keywords: Degraded land, Geographic Information System (GIS), Remote sensing, overlay

scholarly journals ANALISIS KESESUAIAN LAHAN DI KAWASAN HUTAN DENGAN TUJUAN KHUSUS (KHDTK) BULUH CINA, RIAU

2021 ◽  
Vol 16 (2) ◽  
pp. 113-127
Author(s):  
Hanifah Ikhsani ◽  
Azwin Azwin ◽  
Muhammad Ikhwan
Keyword(s):  
Land Cover ◽  
Plant Species ◽  
Aerial Photography ◽  
Soil Samples ◽  
Forest Area ◽  
Land Suitability ◽  
Overlay Analysis ◽  
Suitability Analysis ◽  
Land Suitability Analysis ◽  
Potential Land

Forest Area with Special Purposes (KHDTK) Buluh Cina requires a land suitability analysis so that the development of plant species can be carried out optimally. This study aims to map land units and determine land suitability classes. This study uses aerial photography to classify land cover and take soil samples. Furthermore, overlay analysis and species matching were carried out for 7 types of plants including durian, rambutan, sengon, mango, cacao, pineapple, and corn. The land suitability class is divided into 4 levels namely, very suitable (S1), suitable (S2), marginally suitable (S3), and not suitable (N). Based on the results, the actual land suitability class at KHDTK Buluh Cina class S1 was rambutan at SPL I and III. Land suitability class S2 is rambutan at SPL II and IV. S3 land suitability classes are durian, sengon, mango, cocoa, pineapple, and corn in SPL I, II, III, and IV. The potential land suitability class at KHDTK Buluh Cina class S1 is rambutan at SPL I, II, III and IV. Land suitability class S2 is durian, sengon, and cocoa at SPL I, II, III, and IV. S3 land suitability class is mango, pineapple, and corn in SPL I, II, III, and IV.

scholarly journals Rapid Evaluation and Validation Method of Above Ground Forest Biomass Estimation Using Optical Remote Sensing in Tundi Reserved Forest Area, India

2021 ◽  
Vol 10 (1) ◽  
pp. 29
Author(s):  
Praveen Kumar ◽  
Akhouri P. Krishna ◽  
Thorkild M. Rasmussen ◽  
Mahendra K. Pal
Keyword(s):  
Remote Sensing ◽  
Vegetation Cover ◽  
Remote Sensing Data ◽  
Test Site ◽  
Forest Area ◽  
Relational Model ◽  
Biomass Estimation ◽  
Optical Remote Sensing ◽  
Ground Sample ◽  
Sensing Data

Optical remote sensing data are freely available on a global scale. However, the satellite image processing and analysis for quick, accurate, and precise forest above ground biomass (AGB) evaluation are still challenging and difficult. This paper is aimed to develop a novel method for precise, accurate, and quick evaluation of the forest AGB from optical remote sensing data. Typically, the ground forest AGB was calculated using an empirical model from ground data for biophysical parameters such as tree density, height, and diameter at breast height (DBH) collected from the field at different elevation strata. The ground fraction of vegetation cover (FVC) in each ground sample location was calculated. Then, the fraction of vegetation cover (FVC) from optical remote sensing imagery was calculated. In the first stage of method implementation, the relation model between the ground FVC and ground forest AGB was developed. In the second stage, the relational model was established between image FVC and ground FVC. Finally, both models were fused to derive the relational model between image FVC and forest AGB. The validation of the developed method was demonstrated utilizing Sentinel-2 imagery as test data and the Tundi reserved forest area located in the Dhanbad district of Jharkhand state in eastern India was used as the test site. The result from the developed model was ground validated and also compared with the result from a previously developed crown projected area (CPA)-based forest AGB estimation approach. The results from the developed approach demonstrated superior capabilities in precision compared to the CPA-based method. The average forest AGB estimation of the test site obtained by this approach revealed 463 tons per hectare, which matches the previous estimate from this test site.

scholarly journals THE INVESTIGATION INTO THE LAND CONDITION OF KASEGAWA DAM RESERVOIR BASIN BY USING THE REMOTE-SENSING DATA AND THE ESTIMATE OF ITS SEDIMENT YIELD VOLUME

2001 ◽  
Vol 45 ◽  
pp. 805-810
Author(s):  
Haruyuki HASHIMOTO ◽  
Katsutoshi WATANABE ◽  
Byungdug JUN ◽  
Kenji UENO ◽  
Minoru YAMANAKA ◽  
...  
Keyword(s):  
Remote Sensing ◽  
Sediment Yield ◽  
Remote Sensing Data ◽  
Dam Reservoir ◽  
Sensing Data ◽  
Land Condition ◽  
Reservoir Basin

scholarly journals Efficient Patch-Wise Semantic Segmentation for Large-Scale Remote Sensing Images

Sensors ◽  
2018 ◽  
Vol 18 (10) ◽  
pp. 3232 ◽  
Author(s):  
Yan Liu ◽  
Qirui Ren ◽  
Jiahui Geng ◽  
Meng Ding ◽  
Jiangyun Li
Keyword(s):  
Remote Sensing ◽  
High Resolution ◽  
Large Scale ◽  
Semantic Segmentation ◽  
Remote Sensing Image ◽  
Training Data ◽  
Land Resources ◽  
Remote Sensing Images ◽  
Training Strategy ◽  
The Impact

Efficient and accurate semantic segmentation is the key technique for automatic remote sensing image analysis. While there have been many segmentation methods based on traditional hand-craft feature extractors, it is still challenging to process high-resolution and large-scale remote sensing images. In this work, a novel patch-wise semantic segmentation method with a new training strategy based on fully convolutional networks is presented to segment common land resources. First, to handle the high-resolution image, the images are split as local patches and then a patch-wise network is built. Second, training data is preprocessed in several ways to meet the specific characteristics of remote sensing images, i.e., color imbalance, object rotation variations and lens distortion. Third, a multi-scale training strategy is developed to solve the severe scale variation problem. In addition, the impact of conditional random field (CRF) is studied to improve the precision. The proposed method was evaluated on a dataset collected from a capital city in West China with the Gaofen-2 satellite. The dataset contains ten common land resources (Grassland, Road, etc.). The experimental results show that the proposed algorithm achieves 54.96% in terms of mean intersection over union (MIoU) and outperforms other state-of-the-art methods in remote sensing image segmentation.

scholarly journals Problems and areas to improve a land monitoring system in Ukraine

2020 ◽  
pp. 81-88
Author(s):  
A. V. Lyusak ◽  
K. M. Nikolaichuk
Keyword(s):  
Land Use ◽  
Monitoring System ◽  
The State ◽  
Monitoring Data ◽  
Land Resources ◽  
Single Observation ◽  
International Monitoring ◽  
Monitoring Procedure ◽  
Land Condition ◽  
Standards And Regulations

Relevance of the research. A scientific and theoretical analysis of the legislation in the field of monitoring of land use and protection was carried out. The problem of information imperfection on the quantitative and qualitative state of land resources, which is the basis of land monitoring, was identified. The problem of land monitoring is the imperfection of the monitoring system itself, namely the collection of information on the land state, the spread of degradation processes by various entities of monitoring. The current Regulations on land monitoring were considered and it is proposed to provide for the expansion of the types of analytical work, to adapt the European standards in the selection, transportation and storage of soil samples, to impose mandatory quality control on all works. According to the current legislation of Ukraine, the main task of monitoring is to monitor the dynamics of the processes taking place in the field of land management. Monitoring data are used in making decisions on construction, establishing permitted types of land use, which help prevent land degradation. The updated monitoring data enable public administration bodies to make appropriate demands to land users to eliminate the violations in the field of land use and protection, as well as to bring to justice those responsible for these violations. To ensure the effective functioning of the unified monitoring system, it is necessary to solve a number of organizational, technical and other problems. The main disadvantages of this system are the obsolescence of technical, methodological and information equipment of the monitoring system centers used during observations; lack of a single observation network; inconsistency of separate information technologies used by different entities of monitoring; inconsistency of normative-technical and normative-legal provision with modern requirements. These problems can be solved by creating a new network of observations, but it requires a large amount of funding. The Concepts of the State Target Program for the development of land relations in Ukraine and the Concepts of the State Program for Environmental Monitoring were considered, which provide for the improvement of the land monitoring by maximizing the existing potential and gradual improvement of organizational, legal, methodological and technical support of the monitoring system, taking into account current information needs and the recommendations of the UN Economic Commission for Europe. A necessary requirement for the effective counteraction to violations of land legislation and non-compliance with the norms of rational land use is the improvement of the regulatory framework for land monitoring. It is necessary to clearly specify the following: the purpose and objectives of monitoring as well as the methods of its implementation; main stages and steps of the land monitoring procedure; powers of the implementation entities of this procedure; basic criteria and standards for evaluating the state of land resources and crisis detection. It is also necessary to develop and legislate the procedure for Ukraine's participation in international monitoring studies on land conditions, etc. Currently in Ukraine there is no single methodology for conducting observations, due to the lack of monitoring networks, as well as a modern information system on the state of natural resources, in particular - land. According to scientists, the monitoring requirements are currently met only by agrochemical inspection of agricultural land, however, it is not monitoring: certification does not give a complete picture of land condition; it is not carried out on permanent plots and by a very limited list of indicators and focuses only on the evaluation of individual characteristics, without identifying numerous other physical, chemical and biological indicators. Conclusions. According to the current legislation, the land monitoring system is improved by defining and developing standards and regulations in the field of land use and protection, including protection and reproduction of soil fertility. Improving the land monitoring procedure in Ukraine requires the development and implementation of a set of mechanisms for coordinating the interaction and coordination of all monitoring entities using a single system of methods and technologies in planning, organizing and conducting observations and joint activities, which will facilitate the rapid response of local executive bodies and governments to the occurrence or threat of emergencies and proper control over their development and elimination of consequences. The main areas of developing the land monitoring system include: improving organizational and legal support of monitoring; establishing a single integrated monitoring system; optimizing land monitoring methods, determining and developing standards and regulations in the field of land use and protection; ensuring the integration of information resources; strengthening the coordination of the activities of monitoring entities and data management within the state system of land monitoring in Ukraine; participating in international monitoring studies on land condition and harmonization of national standards with the international ones in order to integrate the national land monitoring system in the international systems.

scholarly journals Beyond Bioproductivity: Engaging Local Perspectives in Land Degradation Monitoring and Assessment

2018 ◽  
Author(s):  
Stefanie Herrmann ◽  
Abdoul Aziz Diouf ◽  
Ibrahima Sall
Keyword(s):  
Remote Sensing ◽  
Land Degradation ◽  
Vegetation Indices ◽  
Temporal Trends ◽  
Photo Elicitation ◽  
Field Observations ◽  
Crowd Sourcing ◽  
Vegetative Cover ◽  
Degradation Monitoring ◽  
Land Condition

Land degradation monitoring and assessment in the Sahel zone takes advantage of and relies substantially on temporal trends of remote sensing-based vegetation indices, which are proxies for the bioproductivity of the land. However, prior studies have shown that negative or positive trends in bioproductivity are not necessarily associated with degradation or improvement of land condition. We argue that remote sensing-based indices, while having contributed much to dismantling an outdated desertification narrative, are themselves falling short of capturing the whole picture and need to be accompanied by field observations that are relevant to local land users. We used the participatory photo elicitation method in three sites in order to elicit local pastoralists’ perspectives on land degradation and identify the indicators that they use to characterize pasture quality, while empowering them to lead the discussion. The discussion revealed indicators far beyond bioproductivity, including livestock performance as well as composition and quality of the herbaceous and woody vegetative cover, invasive species, soil quality and water availability. We found that the pastoralists’ interest, knowledge and field observations could potentially be harnessed using a crowd-sourcing approach in order to produce a geospatially explicit dataset of land degradation, which would be complementary to the remote sensing-based maps of trends in bioproductivity and could serve as a reference for the development of more targeted remote sensing-based indicators of land degradation

Wildlife Habitat Evaluation

2019 ◽  
pp. 143-148
Author(s):  
Peeyush Gupta ◽  
Swati Goyal
Keyword(s):  
Remote Sensing ◽  
Protected Areas ◽  
Natural Resource ◽  
Habitat Suitability ◽  
Wildlife Habitat ◽  
Suitability Analysis ◽  
Habitat Alterations ◽  
Complex Interactions ◽  
Basic Concepts ◽  
Management Recommendations

Before an individual can evaluate wildlife habitat and make management recommendations, some basic concepts about habitat and its relationships to different wildlife species should be understood. In this chapter, some of the basic concepts will be described; mainly analyzing of habitat alterations, landscape analysis, networking and creation of corridor between protected areas, wildlife habitat suitability analysis using Remote Sensing & GIS. Since most of the contest will be based on these concepts. Like other natural resource fields, wildlife management is both an art and science that deals with complex interactions in the environment. This means that management includes art or judgment based on experience as well as sound factual information based on scientific studies.

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