A Review of the Application of Remote Sensing Data for Abandoned Agricultural Land Identification with Focus on Central and Eastern Europe

This study aims to analyze and assess studies published from 1992 to 2019 and listed in the Web of Science (WOS) and Current Contents (CC) databases, and to identify agricultural abandonment by application of remote sensing (RS) optical and microwave data. We selected 73 studies by applying structured queries in a field tag form and Boolean operators in the WOS portal and by expert analysis. An expert assessment yielded the topical picture concerning the definitions and criteria for the identification of abandoned agricultural land (AAL). The analysis also showed the absence of similar field research, which serves not only for validation, but also for understanding the process of agricultural abandonment. The benefit of the fusion of optical and radar data, which supports the application of Sentinel-1 and Sentinel-2 data, is also evident. Knowledge attained from the literary sources indicated that there exists, in the world literature, a well-covered problem of abandonment identification or biomass estimation, as well as missing works dealing with the assessment of the natural accretion of biomass in AAL.

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Evolution of Surge-Type Glaciers in the Yangtze River Headwater Using Multi-Source Remote Sensing Data

Remote Sensing ◽

10.3390/rs11242991 ◽

2019 ◽

Vol 11 (24) ◽

pp. 2991 ◽

Cited By ~ 1

Author(s):

Jin Yan ◽

Mingyang Lv ◽

Zhixing Ruan ◽

Shiyong Yan ◽

Guang Liu

Keyword(s):

Remote Sensing ◽

Flow Velocity ◽

Yangtze River ◽

Stable State ◽

Remote Sensing Data ◽

Radar Data ◽

Series Data ◽

The Yangtze River ◽

Glacier Surges ◽

Short Time

A surge-type glacier is a special and dangerous type of glacier, which can advance quickly in a short-time with cycles. Glaciers in the Yangtze River headwater are generally acknowledged to be in a stable state. However, not all of those glaciers are stable. In this paper, five glaciers from the Yangtze River headwater glacier were selected as the experimental subjects, and multi-source remote sensing images were used to study and analyze the surge behavior over the past 30 years. Based on the Landsat series data, ERS-2, and ENVISAT radar data, this paper extracts the glacier centerline information, glacial area information, and glacial flow velocity during different time periods from 1988 to 2018, which are used to monitor the active periods of glacier surges. We found three surge-type glaciers in the study area. The glacial characteristics of the three glaciers showed some drastic changes, they can advance quickly nearly 800 m in active periods, their area change can reach 2.0 × 106 m2, and their flow velocity can suddenly increase by dozens of times. Surging periods and the initiated time of the three glaciers are different, which are locked in 1997, 2003, and 1997–1998. All those surges ended within one to two years. We suggest that the surges in this paper are dominated by hydrological conditions.

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

ISPRS International Journal of Geo-Information ◽

10.3390/ijgi10010029 ◽

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.

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Study of Ancient Land Boundaries at Tauric Chersonesos Using Satellite Images

Ancient Civilizations from Scythia to Siberia ◽

10.1163/15700577-12341342 ◽

2019 ◽

Vol 25 (1) ◽

pp. 44-58 ◽

Cited By ~ 1

Author(s):

Edgar A. Terekhin ◽

Tatiana N. Smekalova

Keyword(s):

Remote Sensing ◽

Information Systems ◽

Geographic Information Systems ◽

Satellite Images ◽

Agricultural Land ◽

Remote Sensing Data ◽

Field Surveys ◽

The 1960S ◽

Better Than ◽

Made In

Abstract The near chora (agricultural land) of Tauric Chersonesos was investigated using multiyear remote sensing data and field surveys. The boundaries of the land plots were studied with GIS (Geographic Information Systems) technology and an analysis of satellite images. Reliable reconstruction of the borders has been done for 231 plots (from a total of about 380), which is approximately 53% of the Chersonesean chora. During the last 50 years, most of the ancient land plots have been destroyed by modern buildings, roads, or forests. However, in the 1960s, a significant part of the chora was still preserved. Changes in preservation with time were studied with the aid of satellite images that were made in 1966 and 2015. During that period, it was found that the number of plots with almost-complete preservation decreased from 47 to 0. Those land plots whose preservation was better than 50% dropped from 104 to 4. A temporal map shows this decline in preservation. It was found that the areas of land plots could be determined accurately with satellite images; compared to field surveys, this accuracy was about 99%.

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REMOTE SENSING AND GIS FOR LAND COVER CLASSIFICATION AND CHANGE DETECTION IN GAZIPUR SADAR, BANGLADESH DURING 1973-2017

Geoplanning Journal of Geomatics and Planning ◽

10.14710/geoplanning.5.2.215-228 ◽

2018 ◽

Vol 5 (2) ◽

pp. 215

Author(s):

Md Arafat Hassan ◽

Rakibul Islam ◽

Rehnuma Mahjabin

Keyword(s):

Remote Sensing ◽

Supervised Classification ◽

Agricultural Land ◽

Satellite Image ◽

Remote Sensing Data ◽

Remote Sensing And Gis ◽

Vegetation Coverage ◽

Accurate Information ◽

Sal Forest ◽

Shed Light

This paper has been developed to capture the land coverage change in Gazipur Sadar Upazila with the help of remote sensing data of 44 years from 1973 to 2017. After acquiring the study area image of 1973, 1991, 2006 and 2017 supervised classification method has been used to get the accurate information from the satellite image and the whole outcome has been transformed into measurable unit (sq km) and graphs. The accuracy of land coverage was ranged from 85% to 89%. The outcome says that the acceleration of economic growth and pressure of huge population took a heavy toll on the vegetation coverage which decreased -199.7%. People are destroying vegetation coverage for building up settlements and infrastructure. In the year 2017, the map shows that the built-up area increased 312.9% for industry, settlement and agricultural purpose. Moreover agricultural land also drops down from 42% to 32%. The rapid rate of decreasing vegetation coverage and small amount of existing vegetation coverage only 57 sq km (in 2017) is a red alert for the region. The Sal forest and other special flora species of that region is valuable resource for environment. This paper shed light on the fact that it is urgent to protect vegetation coverage so it will help the authority to make good policies and use other techniques to save vegetation coverage.

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Application of optical and radar data for lineaments mapping in Kerdous inlier of the Anti Atlas belt, Morocco

10.5194/egusphere-egu21-7895 ◽

2021 ◽

Author(s):

Amine Jellouli ◽

Abderrazak El Harti ◽

Zakaria Adiri ◽

Mohcine Chakouri ◽

Jaouad El Hachimi ◽

...

Keyword(s):

Remote Sensing ◽

Remote Sensing Data ◽

Radar Data ◽

Ore Deposits ◽

Landsat 8 ◽

Landsat 8 Oli ◽

Alos Palsar ◽

Geological Map ◽

Color Composite ◽

Manual Extraction

Lineament mapping is an important step for lithological and hydrothermal alterations mapping. It is considered as an efficient research task which can be a part of structural investigation and mineral ore deposits identification. The availability of optical as well as radar remote sensing data, such as Landsat 8 OLI, Terra ASTER and ALOS PALSAR data, allows lineaments mapping at regional and national scale. The accuracy of the obtained results depends strongly on the spatial and spectral resolution of the data. The aim of this study was to compare Landsat 8 OLI, Terra ASTER, and radar ALOS PALSAR satellite data for automatic and manual lineaments extraction. The module Line of PCI Geomatica software was applied on PC1 OLI, PC3 ASTER and HH and HV polarization images to automatically extract geological lineaments. However, the manual extraction was achieved using the RGB color composite of the directional filtered images N - S (0&#176;), NE - SW (45&#176;) and E - W (90&#176;) of the OLI panchromatic band 8. The obtained lineaments from automatic and manual extraction were compared against the faults and photo-geological lineaments digitized from the existing geological map of the study area. The extracted lineaments from PC1 OLI and ALOS PALSAR polarizations images showed the best correlation with faults and photo-geological lineaments. The results indicate that the lineaments extracted from HH and HV polarizations of ALOS PALSAR radar data used in this study, with 1499 and 1507 extracted lineaments, were more efficient for structural lineament mapping, as well as the PC1 OLI image with 1057 lineaments.Keywords Remote Sensing . OLI. ALOS PALSAR . ASTER . Kerdous Inlier . Anti Atlas

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Geoecological assessment of the state of postagrogenic lands of the Moscow village soviet council of the Republic of Khakassia on the basis of remote sensing data

E3S Web of Conferences ◽

10.1051/e3sconf/202014903006 ◽

2020 ◽

Vol 149 ◽

pp. 03006 ◽

Cited By ~ 1

Author(s):

Ekaterina V. Pavlova ◽

Anastasiia I. Volkova ◽

Ekaterina A. Demina

Keyword(s):

Remote Sensing ◽

Agricultural Land ◽

Remote Sensing Data ◽

Point Of View ◽

Economic Point ◽

Fallow Lands ◽

Village Council ◽

Qualitative State ◽

The Republic ◽

Map Scale

Currently, the consequences which take place in Khakassia expansion of tree-shrub vegetation on fallow lands have not been properly assessed neither from an ecological nor economic point of view. Based on the analysis of the agricultural map scale 1: 100 000 decoding images Landsat 4–5, 7, 8 and Sentinel 1, and 2, as well as subsatellite ground researches were carried out the identification, the description and assessment of the qualitative state of postagrogenic lands of Khakassia exposed to the processes of overgrowth of tree-shrub vegetation. As an example, this article analyzes the processes of overgrowth of agricultural land on the example of the territory of the Moscow village council of Ust-Abakan district. A geoinformation project of spatial distribution of postagrogenic lands within the Moscow village council of Ust-Abakan district of Khakassia was developed. The results of the research showed that in the studied area in the structure of agricultural land 67204 hectares of land belongs to the fallows located at different stages of recovery of which 77 % exposed to overgrowth processes. The obtained data indicate the need for the formation of management decisions in the field of land use.

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DISTRIBUTION OF RESTORATION SUCCESSIONS IN TAIGA AND FOREST-STEPPE LANDSCAPES OF THE PERMSKY PRIKAMYE (ON THE EXAMPLE OF AGRICULTURAL LANDS)

Bulletin of Udmurt University. Series Biology. Earth Sciences ◽

10.35634/2412-9518-2021-31-4-416-424 ◽

2021 ◽

Vol 31 (4) ◽

pp. 416-424

Author(s):

A.P. Belousova ◽

N.N. Nazarov

Keyword(s):

Remote Sensing ◽

Soil Fertility ◽

Forest Cover ◽

Agricultural Land ◽

Remote Sensing Data ◽

Forest Steppe ◽

Landscape Changes ◽

Agricultural Lands ◽

Natural Factors ◽

Agricultural Use

The research of forest cover development on agricultural lands in the Perm Prikamye was carried the example of taiga and forest-steppe types of landscapes. The Babkinsko-Yugovskoy and Irensko-Kungursky landscapes were select for research. Received information about the geosystem condition in different years using remote sensing data. All landscape changes were record during the formed stable snow cover. As a result, was divide into two classes - forested and treeless areas. Established, the main natural factors of land differentiation by an areas and a pace of withdrawal from agricultural use are the small contours of agricultural land and differences in soil fertility. The growth pace of forest geosystems within the forest-steppe landscape was 2.5 times higher than of the taiga. The research of the dynamics of forest cover showed that in the Perm Prikamye in the forest-steppe landscape substitution of anthropogenic geosystems with natural-anthropogenic ("wild") accompanied by the development of forest biogeocenosis, not steppe.

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Improved representation of agricultural land use and crop management for large-scale hydrological impact simulation in Africa using SWAT+

Hydrology and Earth System Sciences ◽

10.5194/hess-26-71-2022 ◽

2022 ◽

Vol 26 (1) ◽

pp. 71-89

Author(s):

Albert Nkwasa ◽

Celray James Chawanda ◽

Jonas Jägermeyr ◽

Ann van Griensven

Keyword(s):

Remote Sensing ◽

Management Practices ◽

Agricultural Land ◽

Remote Sensing Data ◽

Hydrological Models ◽

Multiple Cropping ◽

Crop Phenology ◽

Cropping Season ◽

Cropping Seasons ◽

Global Datasets

Abstract. To date, most regional and global hydrological models either ignore the representation of cropland or consider crop cultivation in a simplistic way or in abstract terms without any management practices. Yet, the water balance of cultivated areas is strongly influenced by applied management practices (e.g. planting, irrigation, fertilization, and harvesting). The SWAT+ (Soil and Water Assessment Tool) model represents agricultural land by default in a generic way, where the start of the cropping season is driven by accumulated heat units. However, this approach does not work for tropical and subtropical regions such as sub-Saharan Africa, where crop growth dynamics are mainly controlled by rainfall rather than temperature. In this study, we present an approach on how to incorporate crop phenology using decision tables and global datasets of rainfed and irrigated croplands with the associated cropping calendar and fertilizer applications in a regional SWAT+ model for northeastern Africa. We evaluate the influence of the crop phenology representation on simulations of leaf area index (LAI) and evapotranspiration (ET) using LAI remote sensing data from Copernicus Global Land Service (CGLS) and WaPOR (Water Productivity through Open access of Remotely sensed derived data) ET data, respectively. Results show that a representation of crop phenology using global datasets leads to improved temporal patterns of LAI and ET simulations, especially for regions with a single cropping cycle. However, for regions with multiple cropping seasons, global phenology datasets need to be complemented with local data or remote sensing data to capture additional cropping seasons. In addition, the improvement of the cropping season also helps to improve soil erosion estimates, as the timing of crop cover controls erosion rates in the model. With more realistic growing seasons, soil erosion is largely reduced for most agricultural hydrologic response units (HRUs), which can be considered as a move towards substantial improvements over previous estimates. We conclude that regional and global hydrological models can benefit from improved representations of crop phenology and the associated management practices. Future work regarding the incorporation of multiple cropping seasons in global phenology data is needed to better represent cropping cycles in areas where they occur using regional to global hydrological models.

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Assessment of Change in the Built-Up Index of Uyo Metropolis and Its Environs Using Remote Sensing

European Journal of Engineering Research and Science ◽

10.24018/ejers.2019.4.6.1349 ◽

2019 ◽

Vol 4 (6) ◽

pp. 84-89 ◽

Cited By ~ 1

Author(s):

Aniekan Effiong Eyoh ◽

Akwaowo Ekpa

Keyword(s):

Remote Sensing ◽

Land Use ◽

Quantitative Analysis ◽

Land Cover ◽

Agricultural Land ◽

Remote Sensing Data ◽

Land Use Land Cover ◽

Positive Growth ◽

Bare Land ◽

Erdas Imagine

The research was aim at assessing the change in the Built-up Index of Uyo metropolis and its environs from 1986 to 2018, using remote sensing data. To achieve this, a quantitative analysis of changes in land use/land cover within the study area was undertaken using remote sensing dataset of Landsat TM, ETM+ and OLI sensor images of 1986, 2000 and 2018 respectively. Supervised classification, using the maximum likelihood algorithm, was used to classify the study area into four major land use/land cover types; built-up land, bare land/agricultural land, primary swamp vegetation and secondary vegetation. Image processing was carried out using ERDAS IMAGINE and ArcGIS software. The Normalised Difference Built-up Index (NDBI) was calculated to obtain the built-up index for the study area in 1986, 2000 and 2018 as -0.20 to +0.45, -0.13 to +0.55 and -0.19 to +0.63 respectively. The result of the quantitative analysis of changes in land use/land cover indicated that Built-up Land had been on a constant and steady positive growth from 6.76% in 1986 to 11.29% in 2000 and 44.04% in 2018.

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