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21 pages, 5739 KiB

Open AccessArticle

Extracting Information on Rocky Desertification from Satellite Images: A Comparative Study

by Junwei Pu, Xiaoqing Zhao, Pinliang Dong, Qian Wang and Qifa Yue

Remote Sens. 2021, 13(13), 2497; https://doi.org/10.3390/rs13132497 - 26 Jun 2021

Cited by 26 | Viewed by 2994

Abstract

Rocky desertification occurs in many karst terrains of the world and poses major challenges for regional sustainable development. Remotely sensed data can provide important information on rocky desertification. In this study, three common open-access satellite image datasets (Sentinel-2B, Landsat-8, and Gaofen-6) were used [...] Read more.

Rocky desertification occurs in many karst terrains of the world and poses major challenges for regional sustainable development. Remotely sensed data can provide important information on rocky desertification. In this study, three common open-access satellite image datasets (Sentinel-2B, Landsat-8, and Gaofen-6) were used for extracting information on rocky desertification in a typical karst region (Guangnan County, Yunnan) of southwest China, using three machine-learning algorithms implemented in the Python programming language: random forest (RF), bagged decision tree (BDT), and extremely randomized trees (ERT). Comparative analyses of the three data sources and three algorithms show that: (1) The Sentinel-2B image has the best capability for extracting rocky desertification information, with an overall accuracy (OA) of 85.21% using the ERT method. This can be attributed to the higher spatial resolution of the Sentinel-2B image than that of Landsat-8 and Gaofen-6 images and Gaofen-6’s lack of the shortwave infrared (SWIR) bands suitable for mapping carbonate rocks. (2) The ERT method has the best classification results of rocky desertification. Compared with the RF and BDT methods, the ERT method has stronger randomness in modeling and can effectively identify important feature factors for extracting information on rocky desertification. (3) The combination of the Sentinel-2B images and the ERT method provides an effective, efficient, and free approach to information extraction for mapping rocky desertification. The study can provide a useful reference for effective mapping of rocky desertification in similar karst environments of the world, in terms of both satellite image sources and classification algorithms. It also provides important information on the total area and spatial distribution of different levels of rocky desertification in the study area to support decision making by local governments for sustainable development. Full article

(This article belongs to the Special Issue Advances of Remote Sensing in Environmental Geoscience)

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21 pages, 11017 KiB

Open AccessArticle

Analysis of Spatial and Temporal Changes and Expansion Patterns in Mainland Chinese Urban Land between 1995 and 2015

by Chuanzhou Cheng, Xiaohuan Yang and Hongyan Cai

Remote Sens. 2021, 13(11), 2090; https://doi.org/10.3390/rs13112090 - 26 May 2021

Cited by 15 | Viewed by 2246

Abstract

China has experienced greater and faster urbanization than any other country, and while coordinated regional development has been promoted, urbanization has also introduced various problems, such as an increased scarcity of land resources, uncontrolled demand for urban land, and disorderly development of urban [...] Read more.

China has experienced greater and faster urbanization than any other country, and while coordinated regional development has been promoted, urbanization has also introduced various problems, such as an increased scarcity of land resources, uncontrolled demand for urban land, and disorderly development of urban fringes. Based on GIS, remote sensing data, and spatial statistics covering the period 1995–2015, this study identified the patterns, as well as spatial and temporal changes, with respect to urban land expansion in 367 mainland Chinese cities. Over this study period, the area of urban land in mainland China increased from 3.05 to 5.07 million km², at an average annual growth rate of 2.56%. This urban land expansion typically occurred the fastest in medium-sized cities, followed by large cities, and then small cities, with megacities and megalopolises exhibiting the slowest expansion rates. Nearly 70% of the new urban land came from arable land, 11% from other built land, such as pre-existing rural settlements, and 15% from forests and grasslands. When considering marginal-, enclave-, and infill-type expansion patterns, growth in >80% of the 367 cities surveyed was dominated by marginal expansion patterns. Marginal and enclave expansion patterns were found to be becoming more prevalent, with infill-type expansion being seen less. The results of this study provide a theoretical basis and data support for urban spatial planning, the protection of farmland, and the promotion of urban land use efficiency, and can be used as guidance for regional urbanization planning. Full article

(This article belongs to the Special Issue Advances of Remote Sensing in Environmental Geoscience)

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16 pages, 6410 KiB

Open AccessArticle

Topographic Evolution Involving Co-Seismic Landslide, Deformation, Long-Term Folding and Isostatic Rebound: A Case Study on the 2004 Chuetsu Earthquake

by Jinghao Lei, Zhikun Ren, Takashi Oguchi, Peizhen Zhang and Shoichiro Uchiyama

Remote Sens. 2021, 13(6), 1073; https://doi.org/10.3390/rs13061073 - 11 Mar 2021

Cited by 2 | Viewed by 2475

Abstract

Co-seismic landslide volume information is critical to understanding the role of strong earthquakes in topographic and geological evolution. The availability of both pre- and post-earthquake high-resolution digital elevation models (DEMs) provides us with the opportunity to develop a new approach to obtain robust [...] Read more.

Co-seismic landslide volume information is critical to understanding the role of strong earthquakes in topographic and geological evolution. The availability of both pre- and post-earthquake high-resolution digital elevation models (DEMs) provides us with the opportunity to develop a new approach to obtain robust landslide volume information. Here, we propose a method for landslide volume estimation and test it in the Chuetsu region, where a Mw 6.6 earthquake occurred in 2004. First, we align the DEMs by reconstructing the horizontal difference. Then, we quantitatively obtain the landslide volume in the epicentral area by differencing the pre- and post-earthquake DEMs. We convert the landslide volume into the distribution of average catchment-scale denudation and the resulting long-term crustal rebound. Our findings reveal that the Chuetsu earthquake mainly roughens the topography in the low-elevation Chuetsu region. Our results indicate that the preserved topography not only is due to the uplift caused by fault-related folding on the hanging wall of the Muikamachi fault but also undergoes erosion caused by seismically induced landslides and crustal rebound also modifies the topography in the long term. This study confirms that the differential DEM method is a valuable approach for quantitative analysis of topographic and geological evolution. Full article

(This article belongs to the Special Issue Advances of Remote Sensing in Environmental Geoscience)

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24 pages, 10562 KiB

Open AccessArticle

Fractal and Multifractal Characteristics of Lineaments in the Qianhe Graben and Its Tectonic Significance Using Remote Sensing Images

by Zhiheng Liu, Ling Han, Chengyan Du, Hongye Cao, Jianhua Guo and Haiyang Wang

Remote Sens. 2021, 13(4), 587; https://doi.org/10.3390/rs13040587 - 07 Feb 2021

Cited by 11 | Viewed by 3071

Abstract

The distribution and characteristics of geological lineaments in areas with active faulting are vital for providing a basis for regional tectonic identification and analyzing the tectonic significance. Here, we extracted the lineaments in the Qianhe Graben, an active mountainous area on the southwest [...] Read more.

The distribution and characteristics of geological lineaments in areas with active faulting are vital for providing a basis for regional tectonic identification and analyzing the tectonic significance. Here, we extracted the lineaments in the Qianhe Graben, an active mountainous area on the southwest margin of Ordos Block, China, by using the tensor voting algorithm after comparing them with the segment tracing algorithm (STA) and LINE algorithm in PCI Geomatica Software. The main results show that (1) the lineaments in this area are mostly induced by the active fault events with the main trending of NW–SE, (2) the box dimensions of all lineaments, NW–SE trending lineaments, and NE–SW trending lineaments are 1.60, 1.48, and 1.44 (R² > 0.9), respectively, indicating that the faults exhibit statistical self-similarity, and (3) the lineaments have multifractal characteristics according to the mass index τ(q), generalized fractal dimension D(q), fractal width (Δα = 2.25), fractal spectrum shape (f(α) is a unimodal left-hook curve), and spectrum width (Δf = 1.21). These results are related to the tectonic activity in this area, where a higher tectonic activity leads to more lineaments being produced and a higher fractal dimension. All of these results suggest that such insights can be beneficial for providing potential targets in reconstructing the tectonic structure of the area and trends of plate movement. Full article

(This article belongs to the Special Issue Advances of Remote Sensing in Environmental Geoscience)

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21 pages, 9103 KiB

Open AccessArticle

Airborne LiDAR Intensity Correction Based on a New Method for Incidence Angle Correction for Improving Land-Cover Classification

by Qiong Wu, Ruofei Zhong, Pinliang Dong, You Mo and Yunxiang Jin

Remote Sens. 2021, 13(3), 511; https://doi.org/10.3390/rs13030511 - 01 Feb 2021

Cited by 3 | Viewed by 3621

Abstract

Light detection and range (LiDAR) intensity is an important feature describing the characteristics of a target. The direct use of original intensity values has limitations for users, because the same objects may have different spectra, while different objects may have similar spectra in [...] Read more.

Light detection and range (LiDAR) intensity is an important feature describing the characteristics of a target. The direct use of original intensity values has limitations for users, because the same objects may have different spectra, while different objects may have similar spectra in the overlapping regions of airborne LiDAR intensity data. The incidence angle and range constitute the geometric configuration of the airborne measurement system, which has an important influence on the LiDAR intensity. Considering positional shift and rotation angle deviation of the laser scanner and the inertial measurement unit (IMU), a new method for calculating the incident angle is presented based on the rigorous geometric measurement model for airborne LiDAR. The improved approach was applied to experimental intensity data of two forms from a RIEGL laser scanner system mounted on a manned aerial platform. The results showed that the variation coefficient of the intensity values after correction in homogeneous regions is lower than that obtained before correction. The overall classification accuracy of the corrected intensity data of the first form (amplitude) is significantly improved by 30.01%, and the overall classification accuracy of the corrected intensity data of second form (reflectance) increased by 18.21%. The results suggest that the correction method is applicable to other airborne LiDAR systems. Corrected intensity values can be better used for classification, especially in more refined target recognition scenarios, such as road mark extraction and forest monitoring. This study provides useful guidance for the development of future LiDAR data processing systems. Full article

(This article belongs to the Special Issue Advances of Remote Sensing in Environmental Geoscience)

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35 pages, 19842 KiB

Open AccessArticle

A Rapid and High-Precision Mountain Vertex Extraction Method Based on Hotspot Analysis Clustering and Improved Eight-Connected Extraction Algorithms for Digital Elevation Models

by Zhenqi Zheng, Xiongwu Xiao, Zhi-Chao Zhong, Yufu Zang, Nan Yang, Jianguang Tu and Deren Li

Remote Sens. 2021, 13(1), 81; https://doi.org/10.3390/rs13010081 - 28 Dec 2020

Cited by 2 | Viewed by 2407

Abstract

Digital Elevation Model (DEM)-based mountain vertex extraction is one of the most useful DEM applications, providing important information to properly characterize topographic features. Current vertex-extraction techniques have considerable limitations, such as yielding low-accuracy results and generating false mountain vertices. To overcome these limitations, [...] Read more.

Digital Elevation Model (DEM)-based mountain vertex extraction is one of the most useful DEM applications, providing important information to properly characterize topographic features. Current vertex-extraction techniques have considerable limitations, such as yielding low-accuracy results and generating false mountain vertices. To overcome these limitations, a new approach is proposed that combines Hotspot Analysis Clustering and the Improved Eight-Connected Extraction algorithms that would quickly and accurately provide the location and elevation of mountain vertices. The use of the elevation-based Hotspot Analysis Clustering Algorithm allows the fast partitioning of the mountain vertex area, which significantly reduces data and considerably improves the efficiency of mountain vertex extraction. The algorithm also minimizes false mountain vertices, which can be problematic in valleys, ridges, and other rugged terrains. The Eight-Connected Extraction Algorithm also hastens the precise determination of vertex location and elevation, providing a better balance between accuracy and efficiency in vertex extraction. The proposed approach was used and tested on seven different datasets and was compared against traditional vertex extraction methods. The results of the quantitative evaluation show that the proposed approach yielded higher efficiency, considerably minimized the occurrence of invalid points, and generated higher vertex extraction accuracy compared to other traditional methods. Full article

(This article belongs to the Special Issue Advances of Remote Sensing in Environmental Geoscience)

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20 pages, 9862 KiB

Open AccessArticle

Active Tectonics of the Frontal Himalayas: An Example from the Manzai Ranges in the Recess Setting, Western Pakistan

by Kamil A. Qureshi and Shuhab D. Khan

Remote Sens. 2020, 12(20), 3362; https://doi.org/10.3390/rs12203362 - 15 Oct 2020

Cited by 10 | Viewed by 4503

Abstract

The Himalayan main frontal thrust (MFT) accommodates most of the present-day Indo–Asia convergence with related periodic earthquakes. The seismicity and deformation mechanism varies considerably across the frontal Himalayas. We mapped a segment (Manzai Ranges) of the MFT at the western margin of the [...] Read more.

The Himalayan main frontal thrust (MFT) accommodates most of the present-day Indo–Asia convergence with related periodic earthquakes. The seismicity and deformation mechanism varies considerably across the frontal Himalayas. We mapped a segment (Manzai Ranges) of the MFT at the western margin of the Himalayas and analyzed its deformation mechanism and active tectonics using geomorphic indices and the Interferometric Synthetic Aperture Radar (InSAR) Small Baseline Subset (SBAS) technique. Two frontal thrust faults (Khirgi and Jandola) were mapped using Sentinel-2B band ratios in the study area. Water gaps were present in the form of deflected streams at the tip of the growing anticlines. The C-band RADAR interferometry (Sentinel-1A) showed an average uplift of 5–9 mm/year in the satellite line of sight (LOS) from May 2018 to October 2019. The velocity profiles show an uplift variation across the anticlines and may be related to the displacement transfer from the zone of compression in the Manzai Ranges to the zone of transpression in the Pezu–Bhittani Ranges. Four types of morphometric analyses were carried out to assess the relative tectonic activity, namely mountain front sinuosity index (Smf), valley floor width to height ratio (V_f), normalized longitudinal river profile, and normalized channel steepness index (Ksn). The landscape response to active tectonics in the study area was recorded as a deep fluvial incision in V-shaped valleys, convex river profiles, topographic breaks as knickpoints, and a high Ksn index. The geomorphic parameters show a relative increase in tectonic uplift and deformation from the Kundi anticline to the Khirgi and Manzai anticline. We concluded that the frontal structures in the western Himalayas are still going through an active phase of deformation and landscape development with both seismic and aseismic creep. Full article

(This article belongs to the Special Issue Advances of Remote Sensing in Environmental Geoscience)

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17 pages, 6365 KiB

Open AccessArticle

Joint Use of Spaceborne Microwave Sensor Data and CYGNSS Data to Observe Tropical Cyclones

by Shiwei Wang, Shuzhu Shi and Binbin Ni

Remote Sens. 2020, 12(19), 3124; https://doi.org/10.3390/rs12193124 - 23 Sep 2020

Cited by 5 | Viewed by 2337

Abstract

The joint use of spaceborne microwave sensor data and Cyclone Global Navigation Satellite System (CYGNSS) data to observe tropical cyclones (TCs) is presented in this paper. The Soil Moisture Active and Passive (SMAP) radiometer was taken as an example of a spaceborne microwave [...] Read more.

The joint use of spaceborne microwave sensor data and Cyclone Global Navigation Satellite System (CYGNSS) data to observe tropical cyclones (TCs) is presented in this paper. The Soil Moisture Active and Passive (SMAP) radiometer was taken as an example of a spaceborne microwave sensor, and its data and the CYGNSS data were fused to fix the center of a TC and to measure the maximum wind speed around the TC inner core. This process included data preprocessing, image fusion, determination of the TC center position, and the estimation of the TC’s intensity. For all of the observed hurricanes, the experimental results demonstrated that the proposed method obtains a more complete structure of the TC and can measure the surface wind speed around the TC inner core at more frequent intervals compared to the case where the SMAP radiometer data or the CYGNSS data are employed alone. Furthermore, when comparing the TC tracks obtained by the proposed method with the best tracks provided by the National Hurricane Center (NHC), we found that the mean absolute error values ranged between 18.4 and 46 km, the standard deviation varied between 15.1 and 28.2 km, and both of these were smaller than the values obtained by only using the CYGNSS data. In addition, when comparing the maximum wind speed around the TC inner core obtained by the proposed method with the best track peak winds estimated by the NHC, we found that the mean absolute error values ranged between 7.7 and 15.7 m/s, the root-mean-square difference values varied between 8.6 and 18 m/s, the correlation coefficients varied between 0.1782 and 0.9877, the bias values varied between −8.5 and 4.5 m/s, and all of these values were smaller in most cases, than those obtained by only using the CYGNSS data. Full article

(This article belongs to the Special Issue Advances of Remote Sensing in Environmental Geoscience)

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18 pages, 4784 KiB

Open AccessArticle

Detection of Tailings Dams Using High-Resolution Satellite Imagery and a Single Shot Multibox Detector in the Jing–Jin–Ji Region, China

by Qingting Li, Zhengchao Chen, Bing Zhang, Baipeng Li, Kaixuan Lu, Linlin Lu and Huadong Guo

Remote Sens. 2020, 12(16), 2626; https://doi.org/10.3390/rs12162626 - 14 Aug 2020

Cited by 21 | Viewed by 6251

Abstract

The timely and accurate mapping and monitoring of mine tailings dams is crucial to the improvement of management practices by decision makers and to the prevention of disasters caused by failures of these dams. Due to the complex topography, varying geomorphological characteristics, and [...] Read more.

The timely and accurate mapping and monitoring of mine tailings dams is crucial to the improvement of management practices by decision makers and to the prevention of disasters caused by failures of these dams. Due to the complex topography, varying geomorphological characteristics, and the diversity of ore types and mining activities, as well as the range of scales and production processes involved, as they appear in remote sensing imagery, tailings dams vary in terms of their scale, color, shape, and surrounding background. The application of high-resolution satellite imagery for automatic detection of tailings dams at large spatial scales has been barely reported. In this study, a target detection method based on deep learning was developed for identifying the locations of tailings ponds and obtaining their geographical distribution from high-resolution satellite imagery automatically. Training samples were produced based on the characteristics of tailings ponds in satellite images. According to the sample characteristics, the Single Shot Multibox Detector (SSD) model was fine-tuned during model training. The results showed that a detection accuracy of 90.2% and a recall rate of 88.7% could be obtained. Based on the optimized SSD model, 2221 tailing ponds were extracted from Gaofen-1 high resolution imagery in the Jing–Jin–Ji region in northern China. In this region, the majority of tailings ponds are located at high altitudes in remote mountainous areas. At the city level, the tailings ponds were found to be located mainly in Chengde, Tangshan, and Zhangjiakou. The results prove that the deep learning method is very effective at detecting complex land-cover features from remote sensing images. Full article

(This article belongs to the Special Issue Advances of Remote Sensing in Environmental Geoscience)

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20 pages, 15765 KiB

Open AccessArticle

Application of Beamforming Technology in Ionospheric Oblique Backscatter Sounding with a Miniaturized L-Array

by Tongxin Liu, Guobin Yang, Zhengyu Zhao, Chunhua Jiang and Yaogai Hu

Remote Sens. 2020, 12(3), 499; https://doi.org/10.3390/rs12030499 - 04 Feb 2020

Cited by 5 | Viewed by 2751

Abstract

In this paper, a new dedicated multi-channel ionospheric oblique backscatter sounder is described. A miniaturized L-shaped antenna array was employed for the receiving of the oblique backscatter echoes in the present system. Firstly, two typical adaptive beamforming algorithms were introduced to improve the [...] Read more.

In this paper, a new dedicated multi-channel ionospheric oblique backscatter sounder is described. A miniaturized L-shaped antenna array was employed for the receiving of the oblique backscatter echoes in the present system. Firstly, two typical adaptive beamforming algorithms were introduced to improve the anti-jamming ability. Then, simulations were carried out to verify the beamforming performance in azimuth and elevation simultaneously. Furthermore, the experimental results by the present sounding system were used to test the performance of the adaptive beamformers. Results show that the radio frequency interference and the interference of the vertical echoes can be effectively suppressed by the adaptive beamformers. In particular, the use value of the beamforming in the receiving of the ionospheric oblique backscatter sounding is described in detail through the analysis of the signal sequences in several typical frequencies. And after the constant false-alarm rate processing, the oblique backscatter ionograms processed by the adaptive beamforers have clearer and continuous leading edge compared with the original ionograms. As a result, the adaptive beamformers of great significance to improve the detection ability of the ionospheric oblique backscatter sounding. Full article

(This article belongs to the Special Issue Advances of Remote Sensing in Environmental Geoscience)

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20 pages, 3450 KiB

Open AccessArticle

Cross-Comparison between Landsat 8 (OLI) and Landsat 7 (ETM+) Derived Vegetation Indices in a Mediterranean Environment

by Giuseppe Mancino, Agostino Ferrara, Antonietta Padula and Angelo Nolè

Remote Sens. 2020, 12(2), 291; https://doi.org/10.3390/rs12020291 - 16 Jan 2020

Cited by 64 | Viewed by 8241

Abstract

Landsat 8 is the most recent generation of Landsat satellite missions that provides remote sensing imagery for earth observation. The Landsat 7 Enhanced Thematic Mapper Plus (ETM+) images, together with Landsat-8 Operational Land Imager (OLI) and Thermal Infrared sensor (TIRS) represent fundamental tools [...] Read more.

Landsat 8 is the most recent generation of Landsat satellite missions that provides remote sensing imagery for earth observation. The Landsat 7 Enhanced Thematic Mapper Plus (ETM+) images, together with Landsat-8 Operational Land Imager (OLI) and Thermal Infrared sensor (TIRS) represent fundamental tools for earth observation due to the optimal combination of the radiometric and geometric images resolution provided by these sensors. However, there are substantial differences between the information provided by Landsat 7 and Landsat 8. In order to perform a multi-temporal analysis, a cross-comparison between image from different Landsat satellites is required. The present study is based on the evaluation of specific intercalibration functions for the standardization of main vegetation indices calculated from the two Landsat generation images, with respect to main land use types. The NDVI (Normalized Difference Vegetation Index), NDWI (Normalized Difference Water Index), LSWI (Land Surface Water Index), NBR (Normalized Burn Ratio), VIgreen (Green Vegetation Index), SAVI (Soil Adjusted Vegetation Index), and EVI (Enhanced Vegetation Index) have been derived from August 2017 ETM+ and OLI images (path: 188; row: 32) for the study area (Basilicata Region, located in the southern part of Italy) selected as a highly representative of Mediterranean environment. Main results show slight differences in the values of average reflectance for each band: OLI shows higher values in the near-infrared (NIR) wavelength for all the land use types, while in the short-wave infrared (SWIR) the ETM+ shows higher reflectance values. High correlation coefficients between different indices (in particular NDVI and NDWI) show that ETM+ and OLI can be used as complementary data. The best correlation in terms of cross-comparison was found for NDVI, NDWI, SAVI, and EVI indices; while according to land use classes, statistically significant differences were found for almost all the considered indices calculated with the two sensors. Full article

(This article belongs to the Special Issue Advances of Remote Sensing in Environmental Geoscience)

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18 pages, 8233 KiB

Open AccessTechnical Note

A New Method for Automated Measurement of Sand Dune Migration Based on Multi-Temporal LiDAR-Derived Digital Elevation Models

by Pinliang Dong, Jisheng Xia, Ruofei Zhong, Zhifang Zhao and Shucheng Tan

Remote Sens. 2021, 13(16), 3084; https://doi.org/10.3390/rs13163084 - 06 Aug 2021

Cited by 4 | Viewed by 2371

Abstract

While remote sensing methods have long been used for coastal and desert sand dune studies, few methods have been developed for the automated measurement of dune migration in large dune fields. To overcome a major limitation of an existing method named “pairs of [...] Read more.

While remote sensing methods have long been used for coastal and desert sand dune studies, few methods have been developed for the automated measurement of dune migration in large dune fields. To overcome a major limitation of an existing method named “pairs of source and target points (PSTP)”, this paper proposes a toe line tracking (TLT) method for the automated measurement of dune migration rate and direction using multi-temporal digital elevation models (DEM) derived from light detection and ranging (LiDAR) data. Based on a few simple parameters, the TLT method automatically extracts the base level of a dune field and toe lines of individual dunes. The toe line polygons derived from two DEMs are processed using logical operators and other spatial analysis methods implemented in the Python programming language in a geographic information system. By generating thousands of random sampling points along source toe lines, dune migration distances and directions are calculated and saved with the sampling point feature class. The application of the TLT method was demonstrated using multi-temporal LiDAR-derived DEMs for a 9 km by 2.4 km area in the White Sands Dune Field in New Mexico (USA). Dune migration distances and directions for three periods (24 January 2009–26 September 2009, 26 September 2009–6 June 2010, and 24 January 2009–6 January 2010) were calculated. Sensitivity analyses were carried out using different window sizes and toe heights. The results suggest that both PSTP and TLT produce similar sand dune migration rates and directions, but TLT is a more generic method that works for dunes with or without slipfaces that reach the angle of repose. Full article

(This article belongs to the Special Issue Advances of Remote Sensing in Environmental Geoscience)

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15 pages, 8363 KiB

Open AccessTechnical Note

Mapping Dragon Fruit Croplands from Space Using Remote Sensing of Artificial Light at Night

by Ruirui Wang, Wei Shi and Pinliang Dong

Remote Sens. 2020, 12(24), 4139; https://doi.org/10.3390/rs12244139 - 17 Dec 2020

Cited by 2 | Viewed by 3870

Abstract

The nighttime light (NTL) on the surface of Earth is an important indicator for the human transformation of the world. NTL remotely sensed data have been widely used in urban development, population estimation, economic activity, resource development and other fields. With the increasing [...] Read more.

The nighttime light (NTL) on the surface of Earth is an important indicator for the human transformation of the world. NTL remotely sensed data have been widely used in urban development, population estimation, economic activity, resource development and other fields. With the increasing use of artificial lighting technology in agriculture, it has become possible to use NTL remote sensing data for monitoring agricultural activities. In this study, National Polar Partnership (NPP)-Visible Infrared Imaging Radiometer Suite (VIIRS) NTL remote sensing data were used to observe the seasonal variation of artificial lighting in dragon fruit cropland in Binh Thuan Province, Vietnam. Compared with the statistics of planted area, area having products and production of dragon fruit by district in the Statistical Yearbook of Binh Thuan Province 2018, values of the mean and standard deviation of NTL brightness have significant positive correlations with the statistical data. The results suggest that the NTL remotely sensed data could be used to reveal some agricultural productive activities such as dragon fruits production accurately by monitoring the seasonal artificial lighting. This research demonstrates the application potential of NTL remotely sensed data in agriculture. Full article

(This article belongs to the Special Issue Advances of Remote Sensing in Environmental Geoscience)

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