scholarly journals Remote Sensing Monitoring and Evaluation of Vegetation Restoration in Grassland Mining Areas—A Case Study of the Shengli Mining Area in Xilinhot City, China

Land ◽  
2021 ◽  
Vol 10 (7) ◽  
pp. 743
Author(s):  
Jiawei Hui ◽  
Zhongke Bai ◽  
Baoying Ye ◽  
Zihao Wang
Keyword(s):  
Vegetation Index ◽  
Vegetation Indices ◽  
Monitoring And Evaluation ◽  
Mining Area ◽  
Vegetation Restoration ◽  
Coal Production ◽  
Vegetation Monitoring ◽  
Mining Areas ◽  
Restoration Work

Coal production will cause serious damage to regional vegetation, especially in ecologically fragile grasslands. It is the consensus of all major countries to conduct vegetation restoration and management monitoring in areas damaged by coal production. This paper compares the adaptability of different data sources and different vegetation indices to grassland mining areas and proposes a normalized environmental vegetation index (NEVI) suitable for vegetation monitoring in grassland mining areas. Based on the Landsat and Sentinel data from 2005 to 2019, this paper uses NEVI to monitor the vegetation destruction and restoration of the Shengli mining area. The main result is that the vegetation restoration work in the Shengli mining area started in 2007 and was gradually carried out in subsequent years. The restoration effect of vegetation is significantly better in the east than in the west. The NEVI of the vegetation in the east can reach, or exceed, the level of natural vegetation in the same period. The restoration of vegetation degradation in some areas requires strengthening of management and maintenance measures.

scholarly journals THEORETICAL MODELLING STUDY ON THE RELATIONSHIP BETWEEN MULTI-FREQUENCY MICROWAVE VEGETATION INDEX AND VEGETATION PROPERTIES (OPTICAL DEPTH AND SINGLE SCATTERING ALBEDO)

2018 ◽  
Vol XLII-3 ◽  
pp. 1623-1627
Author(s):  
S. Talebi ◽  
J. Shi ◽  
T. Zhao
Keyword(s):  
Optical Depth ◽  
Vegetation Index ◽  
Vegetation Indices ◽  
Soil Surface ◽  
Single Scattering ◽  
Single Scattering Albedo ◽  
Theoretical Modelling ◽  
Vegetation Monitoring ◽  
Scattering Effects ◽  
The Relationship

This paper presents a theoretical study of derivation Microwave Vegetation Indices (MVIs) in different pairs of frequencies using two methods. In the first method calculating MVI in different frequencies based on Matrix Doubling Model (to take in to account multi scattering effects) has been done and analyzed in various soil properties. The second method was based on MVI theoretical basis and its independency to underlying soil surface signals. Comparing the results from two methods with vegetation properties (single scattering albedo and optical depth) indicated partial correlation between MVI from first method and optical depth, and full correlation between MVI from second method and vegetation properties. The second method to derive MVI can be used widely in global microwave vegetation monitoring.

scholarly journals Evaluation and Normalization of Topographic Effects on Vegetation Indices

2020 ◽  
Vol 12 (14) ◽  
pp. 2290
Author(s):  
Rui Chen ◽  
Gaofei Yin ◽  
Guoxiang Liu ◽  
Jing Li ◽  
Aleixandre Verger
Keyword(s):  
Vegetation Index ◽  
Near Infrared ◽  
Vegetation Indices ◽  
Topographic Effects ◽  
Terrestrial Vegetation ◽  
Mountainous Areas ◽  
Near Infrared Reflectance ◽  
Illumination Condition ◽  
Vegetation Monitoring ◽  
Local Illumination

The normalization of topographic effects on vegetation indices (VIs) is a prerequisite for their proper use in mountainous areas. We assessed the topographic effects on the normalized difference vegetation index (NDVI), the enhanced vegetation index (EVI), the soil adjusted vegetation index (SAVI), and the near-infrared reflectance of terrestrial vegetation (NIRv) calculated from Sentinel-2. The evaluation was based on two criteria: the correlation with local illumination condition and the dependence on aspect. Results show that topographic effects can be neglected for the NDVI, while they heavily influence the SAVI, EVI, and NIRv: the local illumination condition explains 19.85%, 25.37%, and 26.69% of the variation of the SAVI, EVI, and NIRv, respectively, and the coefficients of variation across different aspects are, respectively, 8.13%, 10.46%, and 14.07%. We demonstrated the applicability of existing correction methods, including statistical-empirical (SE), sun-canopy-sensor with C-correction (SCS + C), and path length correction (PLC), dedicatedly designed for reflectance, to normalize topographic effects on VIs. Our study will benefit vegetation monitoring with VIs over mountainous areas.

scholarly journals Influence of Varying Solar Zenith Angles on Land Surface Phenology Derived from Vegetation Indices: A Case Study in the Harvard Forest

2021 ◽  
Vol 13 (20) ◽  
pp. 4126
Author(s):  
Yang Li ◽  
Ziti Jiao ◽  
Kaiguang Zhao ◽  
Yadong Dong ◽  
Yuyu Zhou ◽  
...  
Keyword(s):  
Time Series ◽  
Land Surface ◽  
Vegetation Index ◽  
Vegetation Indices ◽  
Mean Difference ◽  
Land Surface Phenology ◽  
Harvard Forest ◽  
Ndvi Time Series ◽  
Bidirectional Reflectance Distribution

Vegetation indices are widely used to derive land surface phenology (LSP). However, due to inconsistent illumination geometries, reflectance varies with solar zenith angles (SZA), which in turn affects the vegetation indices, and thus the derived LSP. To examine the SZA effect on LSP, the MODIS bidirectional reflectance distribution function (BRDF) product and a BRDF model were employed to derive LSPs under several constant SZAs (i.e., 0°, 15°, 30°, 45°, and 60°) in the Harvard Forest, Massachusetts, USA. The LSPs derived under varying SZAs from the MODIS nadir BRDF-adjusted reflectance (NBAR) and MODIS vegetation index products were used as baselines. The results show that with increasing SZA, NDVI increases but EVI decreases. The magnitude of SZA-induced NDVI/EVI changes suggests that EVI is more sensitive to varying SZAs than NDVI. NDVI and EVI are comparable in deriving the start of season (SOS), but EVI is more accurate when deriving the end of season (EOS). Specifically, NDVI/EVI-derived SOSs are relatively close to those derived from ground measurements, with an absolute mean difference of 8.01 days for NDVI-derived SOSs and 9.07 days for EVI-derived SOSs over ten years. However, a considerable lag exists for EOSs derived from vegetation indices, especially from the NDVI time series, with an absolute mean difference of 14.67 days relative to that derived from ground measurements. The SOSs derived from NDVI time series are generally earlier, while those from EVI time series are delayed. In contrast, the EOSs derived from NDVI time series are delayed; those derived from the simulated EVI time series under a fixed illumination geometry are also delayed, but those derived from the products with varying illumination geometries (i.e., MODIS NBAR product and MODIS vegetation index product) are advanced. LSPs derived from varying illumination geometries could lead to a difference spanning from a few days to a month in this case study, which highlights the importance of normalizing the illumination geometry when deriving LSP from NDVI/EVI time series.

scholarly journals Optimal Spatial Resolution for the Detection and Discrimination of Archaeological Proxies in Areas with Spectral Heterogeneity

2020 ◽  
Vol 12 (1) ◽  
pp. 136 ◽  
Author(s):  
Athos Agapiou
Keyword(s):  
Spatial Resolution ◽  
Vegetation Index ◽  
Near Infrared ◽  
Normalized Difference Vegetation Index ◽  
Spectral Band ◽  
Vegetation Indices ◽  
Archaeological Site ◽  
Area Of Interest ◽  
First Case

Subsurface targets can be detected from space-borne sensors via archaeological proxies, known in the literature as cropmarks. A topic that has been limited in its investigation in the past is the identification of the optimal spatial resolution of satellite sensors, which can better support image extraction of archaeological proxies, especially in areas with spectral heterogeneity. In this study, we investigated the optimal spatial resolution (OSR) for two different cases studies. OSR refers to the pixel size in which the local variance, of a given area of interest (e.g., archaeological proxy), is minimized, without losing key details necessary for adequate interpretation of the cropmarks. The first case study comprises of a simulated spectral dataset that aims to model a shallow buried archaeological target cultivated on top with barley crops, while the second case study considers an existing site in Cyprus, namely the archaeological site of “Nea Paphos”. The overall methodology adopted in the study is composed of five steps: firstly, we defined the area of interest (Step 1), then we selected the local mean-variance value as the optimization criterion of the OSR (Step 2), while in the next step (Step 3), we spatially aggregated (upscale) the initial spectral datasets for both case studies. In our investigation, the spectral range was limited to the visible and near-infrared part of the spectrum. Based on these findings, we determined the OSR (Step 4), and finally, we verified the results (Step 5). The OSR was estimated for each spectral band, namely the blue, green, red, and near-infrared bands, while the study was expanded to also include vegetation indices, such as the Simple Ratio (SR), the Atmospheric Resistance Vegetation Index (ARVI), and the Normalized Difference Vegetation Index (NDVI). The outcomes indicated that the OSR could minimize the local spectral variance, thus minimizing the spectral noise, and, consequently, better support image processing for the extraction of archaeological proxies in areas with high spectral heterogeneity.

scholarly journals Rehabilitation of Post-Mining Areas in the Bohumin City Area (Czech Republic). Case Study

2020 ◽  
Vol 3 (1) ◽  
pp. 367-378
Author(s):  
Witold Biały ◽  
Vlastimil Moni ◽  
Beata Gibesova ◽  
Barbara Stalmachova ◽  
Milan Mikolas
Keyword(s):  
Czech Republic ◽  
Residential Buildings ◽  
Land Development ◽  
Mining Area ◽  
Hard Coal ◽  
Mining Areas ◽  
Hard Coal Mining ◽  
Mining Works ◽  
Post Industrial

AbstractRehabilitation of post-industrial areas involves many areas. The area after hard coal mines, requires many specific actions and funds in order to eliminate any remnants of the former infrastructure that is located in this area. The area of Upper Silesia, which includes areas on both the Polish and Czech borders, belongs to the area where the process of underground hard coal mining is being extinguished. As a result of the completion of mining works, the mine areas and adjacent sites begin to undergo transformations. Thus, the landscape of this area changes, various types of land, residential buildings and roads are destroyed. The activities related to restoring the utility value to degraded areas should be carried out consistently, primarily from their inhabitants’ perspective. The rehabilitation of post-mining area and its proper management can bring great benefits to the city and its inhabitants in the future. The publication presents a proposal for land development solutions for the former hard coal mine in Bohumin, Vrbice district in the Czech Republic.

scholarly journals Study on soil pollution caused by heavy metals in coal mining areas and vegetation restoration in surrounding areas

2021 ◽  
Author(s):  
Xun Wang
Keyword(s):  
Heavy Metals ◽  
Heavy Metal ◽  
Coal Mining ◽  
Metal Pollution ◽  
Heavy Metal Pollution ◽  
Soil Layer ◽  
Mining Area ◽  
Vegetation Restoration ◽  
Mining Areas ◽  
Ligustrum Lucidum

Abstract In this study, taking a coal mining area as an example, three vegetation restoration modes were designed: Populus L., Ligustrum lucidum Ait., and Amygdalus persica L., and soil and plant samples were collected to determine and evaluate the heavy metals. It was found that all the three modes were effective in eliminating heavy metal pollution in the soil, especially Populus L. and Ligustrum lucidum Ait.; in the soil layer at a depth of 0–20 cm, the content of Cd was the lowest (2.68 mg/kg) in Populus L., and the content of Cr and Pb was the lowest (58.64 mg/kg and 95.36 mg/kg) in Ligustrum lucidum Ait., which was significantly lower than that in the bare land. The evaluation results demonstrated that the pollution under Populus L. and Ligustrum lucidum Ait. modes was moderate. In the aspect of the heavy metal content in plants, the content of Cd was the lowest, and the content of Cr and Pb was high. In the same plant, the content of heavy metals in the leaf was the lowest, followed by the stem and root. The experimental results show that the vegetation restoration mode can relieve the heavy metal pollution, which makes some contributions to solve the ecological restoration problem in coal mining areas.

scholarly journals Comparative study on Hydrogeological conditions of Huaihe mining area

2018 ◽  
Vol 1 (1) ◽  
Author(s):  
Xiaolin Cheng ◽  
Meichen Yu ◽  
Jiayun Zhang
Keyword(s):  
Pore Water ◽  
Quaternary System ◽  
Water Inrush ◽  
Fine Sand ◽  
Mining Area ◽  
Coal Production ◽  
Water Group ◽  
Mining Areas ◽  
Hydrogeological Conditions ◽  
Similarities And Differences

Lianghuai Mining Area is one of the 13 large coal bases in China. It is an important coal and coal production base in China. Mine water inrush accidents occur frequently, resulting in economic and human resource losses, reflecting the importance of the study of hydrogeology in mining areas. In this paper, the hydrogeological conditions of Bozhou and Huainan Panxie mine are analyzed, and the similarities and differences between the hydrogeological conditions of the two mines are summarized. The shallow pore water group in the Bozhou area is composed of the Quaternary system of the Quaternary system (Q4d) and the upper part of the upper part of the Mao Tong group (Q3m). The lithology of the aquifer is silt, silt and fine sand. The shallow pore water group of the Panxian Pancho Formation in Huainan is composed of the Upper Pleistocene of the Quaternary system and the Holocene strata. The lithology is mainly composed of fine sand. The main sources of shallow pore water supply in the two areas are precipitation infiltration, mainly for evaporation, lateral runoff, artificial mining and deep flow and discharge to the river.

scholarly journals Dynamic monitoring and evaluation of ecological restoration in mining area based on GNSS+RS technology

2022 ◽  
Vol 355 ◽  
pp. 02068
Author(s):  
Qiang Wang
Keyword(s):  
Machine Learning ◽  
Ecological Restoration ◽  
Vegetation Index ◽  
Net Primary Productivity ◽  
Dynamic Assessment ◽  
Monitoring And Evaluation ◽  
Mining Area ◽  
Least Square ◽  
Dynamic Monitoring ◽  
Ecological Environment

The continuous development of mineral resources is increasingly damaging the ecological environment, so it is of great significance to ecological restoration and dynamic monitoring of the mining area. In this paper, dynamic monitoring and evaluation method of ecological restoration in the mining area are proposed, which integrates GNSS + RS (Global Navigation Satellite System + Remote Sensing) technology. According to the Precipitable Water Vapor (PWV) retrieved by GNSS and NDVI (Normalized Vegetation Index) can monitor the ecological environment and introduce machine learning to improve the accuracy of the model. The dynamic assessment of ecological restoration was carried out by using temperature, rainfall, NPP (Net Primary Productivity), NDVI and PWV. The results show that: (1) the modeling effect of machine learning is better than that of the least square regression. (2) The comprehensive ecological evaluation index proposed can better reflect the ecological situation of the mining area. Therefore, the environmental monitoring and assessment of mining area based on GNNS + RS technology proposed in this paper have important reference significance.

scholarly journals Developing a p-NDVI Map for Highland Kimchi Cabbage Using Spectral Information from UAVs and a Field Spectral Radiometer

Agronomy ◽  
2020 ◽  
Vol 10 (11) ◽  
pp. 1798
Author(s):  
Dong-Ho Lee ◽  
Hyoung-Sub Shin ◽  
Jong-Hwa Park
Keyword(s):  
Spectral Analysis ◽  
Vegetation Index ◽  
Spatial Information ◽  
Vegetation Indices ◽  
Soil Conditions ◽  
Maturity Stage ◽  
Good Growth ◽  
Vegetation Monitoring ◽  
Reflectance Measurement ◽  
The Difference

Kimchi cabbage grows in South Korea and is an essential ingredient for making kimchi with the kimjang method. The technique of accurately managing and monitoring crops such as kimchi cabbage plays an important role in stabilizing consumer prices. Unmanned aerial vehicles (UAVs) are expected to be used more widely in global and local agriculture. The agricultural sites at which kimchi cabbages are cultivated are affected by various climatic, terrain, and soil conditions, requiring technologies that can accurately and quickly acquire such information. UAVs and sensors are able to provide some of these data. In this study, we set up a cultivation environment for kimchi cabbage and investigated the correlation between a UAV-attached multispectral sensor and a field-portable spectroradiometer. Reflectance measurement using a spectroradiometer was performed on 99 kimchi cabbages in a Mt. Maebong testbed. We aimed to find a method for obtaining accurate vegetation information by combining the high spatial and temporal resolution information of the UAV observation with the spectral resolution of the spectroradiometer. Spectral analysis was used to identify the difference between healthy and poorly growing cabbage and to find the wavelength that most affected the growth. The hyperspectrum of the spectroradiometer reflected the accurate vegetation characteristics and contributed greatly to the identification of vegetation indices. A method for correcting the errors that occurred in the ground and UAV monitoring and the difference arising from the application of the broadband wavelength of the UAV and the single wavelength of the spectroradiometer through correlation analysis is presented. The calibration equation method was applied to UAV spatial information and was used to create a precise normalized distribution vegetation index (p-NDVI) map. The p-NDVI map was organized into four categories for the selection of cabbages with healthy (good) growth. Our results show that (1) the merged spectral analysis method was found to be more accurate and distinct than conventional methods, and (2) methods for estimating cabbage growth status showed a higher significant correlation than the UAV-based NDVI. At the maturity stage, high accuracy (R2 = 0.7816, RMSE = 0.06) was achieved for NDVI. Although this map is the result of the limited vegetation monitoring of UAV images taken during the maturity stage, it could be of great help for managing the quality and production of cabbage. However, the efficient management of highland kimchi cabbage requires continuous research under various conditions to enable periodic and systematic monitoring using UAVs and sensors.

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