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A special issue of Remote Sensing (ISSN 2072-4292). This special issue belongs to the section "Remote Sensing in Geology, Geomorphology and Hydrology".

Deadline for manuscript submissions: closed (31 May 2018) | Viewed by 63950

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Special Issue Editors

Dr. Magaly Koch

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Guest Editor

Center for Remote Sensing, Boston University, Boston, MA 02215, USA
Interests: hydrogeology; geomorphology; natural hazards; land use/cover changes; optical/radar remote sensing
Special Issues, Collections and Topics in MDPI journals

Dr. Brian F. Thomas

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Guest Editor

Dept. Geology and Environmental Science, University of Pittsburgh, Pittsburgh, PA 15260, USA
Interests: hydrogeology; Gravity Recovery and Climate Experiment (GRACE); hydrologic modeling; land use/cover changes; statistical hydrology; time series analysis

Dr. Ahmed Gaber

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Guest Editor

Geology Dept., Faculty of Science, Port Said University, 23 December Street, Port Said 42522, Egypt
Interests: Synthetic Aperture Radar (SAR); Ground Penetrating Radar (GPR); hydrogeology; natural hazards; land use/cover changes

Special Issue Information

Dear Colleagues,

Arid and semiarid lands are ecologically fragile environments with limited water resources and vegetation cover. They encompass a range of very unique habitats—whether desert plains, savanna, seasonal wetlands, or arid mountain ranges—adapted to harsh and changing climatic conditions. After prolonged periods of droughts, the sparse vegetation in these regions often show a tremendous resilience capacity when rains return. At the same time they are very susceptible to surface disturbances and water resources changes, and, thus, may serve as excellent indicators of the onset of climate change. Arid/semiarid regions are usually characterized by their remoteness and low population density. However, as population pressure increases, these regions are undergoing rapid changes with significant impact on their natural resources. Remote sensing offers an important tool to assess, monitor, and manage such resources and their changes.

This Special Issue seeks to compile the latest development in the field of remote sensing technology, algorithm development and applications specifically addressing issues affecting arid/semiarid lands. Tools and methods may encompass a range of platforms (satellite, airborne, UAV, ground based), sensors (multispectral, thermal, radar, Lidar) and techniques (time series analysis, data fusion, machine learning, spectroscopy, polarimetric SAR, InSAR). Topics may include the use of remote sensing for assessing groundwater depletion or diversion of surface water for irrigated agriculture, land subsidence due to changes in water fluxes, soil salinization, evapotranspiration, land use changes (e.g., desert reclamation, agriculture expansion, urbanization), crop water productivity/consumption, ecosystem health, mineral resources, soil erosion, and other forms of geohazards.

Dr. Magaly Koch
Dr. Brian F. Thomas
Dr. Ahmed Gaber
Guest Editors

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Keywords

Agriculture
Water resources
Soil erosion/degradation/salinization
Arid land geomorphology
Drought monitoring
Land subsidence
Dryland ecosystem change
Geohazards (aeolian/fluvial)
Subsurface investigation

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Published Papers (9 papers)

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Research

20 pages, 4684 KiB

Open AccessArticle

Assessing Water Availability in Mediterranean Regions Affected by Water Conflicts through MODIS Data Time Series Analysis

by Gema Marco-Dos Santos, Ignacio Melendez-Pastor, Jose Navarro-Pedreño and Magaly Koch

Remote Sens. 2019, 11(11), 1355; https://doi.org/10.3390/rs11111355 - 5 Jun 2019

Cited by 8 | Viewed by 3882

Abstract

Water scarcity is a widespread problem in arid and semi-arid regions such as the western Mediterranean coastal areas. The irregularity of the precipitation generates frequent droughts that exacerbate the conflicts among agriculture, water supply and water demands for ecosystems maintenance. Besides, global climate models predict that climate change will cause Mediterranean arid and semi-arid regions to shift towards lower rainfall scenarios that may exacerbate water conflicts. The purpose of this study is to find a feasible methodology to assess current and monitor future water demands in order to better allocate limited water resources. The interdependency between a vegetation index (NDVI), land surface temperature (LST), precipitation (current and future), and surface water resources availability in two watersheds in southeastern Spain with serious difficulties in meeting water demands was investigated. MODIS (Moderate Resolution Imaging Spectroradiometer) NDVI and LST products (as proxy of drought), precipitation maps (generated from climate station records) and reservoir storage gauging information were used to compute times series anomalies from 2001 to 2014 and generate regression images and spatial regression models. The temporal relationship between reservoir storage and time series of satellite images allowed the detection of different and contrasting water management practices in the two watersheds. In addition, a comparison of current precipitation rates and future precipitation conditions obtained from global climate models suggests high precipitation reductions, especially in areas that have the potential to contribute significantly to groundwater storage and surface runoff, and are thus critical to reservoir storage. Finally, spatial regression models minimized spatial autocorrelation effects, and their results suggested the great potential of our methodology combining NDVI and LST time series to predict future scenarios of water scarcity. Full article

(This article belongs to the Special Issue Remote Sensing of Arid/Semiarid Lands)

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14 pages, 10628 KiB

Open AccessArticle

Evaluation of Manning’s n Roughness Coefficient in Arid Environments by Using SAR Backscatter

by Yuval Sadeh, Hai Cohen, Shimrit Maman and Dan G. Blumberg

Remote Sens. 2018, 10(10), 1505; https://doi.org/10.3390/rs10101505 - 20 Sep 2018

Cited by 21 | Viewed by 5985

Abstract

The prediction of arid region flash floods (magnitude and frequency) is essential to ensure the safety of human life and infrastructures and is commonly based on hydrological models. Traditionally, catchment characteristics are extracted using point-based measurements. A considerable improvement of point-based observations is offered by remote sensing technologies, which enables the determination of continuous spatial hydrological parameters and variables, such as surface roughness, which significantly influence runoff velocity and depth. Hydrological models commonly express the surface roughness using Manning’s roughness coefficient (n) as a key variable. The objectives were thus to determine surface roughness by exploiting a new high spatial resolution spaceborne synthetic aperture radar (SAR) technology and to examine the correlation between radar backscatter and Manning’s roughness coefficient in an arid environment. A very strong correlation (R² = 0.97) was found between the constellation of small satellites for Mediterranean basin observation (COSMO)-SkyMed SAR backscatter and surface roughness. The results of this research demonstrate the feasibility of using an X-band spaceborne sensor with high spatial resolution for the evaluation of surface roughness in flat arid environments. The innovative method proposed to evaluate Manning’s n roughness coefficient in arid environments with sparse vegetation cover using radar backscatter may lead to improvements in the performance of hydrological models. Full article

(This article belongs to the Special Issue Remote Sensing of Arid/Semiarid Lands)

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18 pages, 20606 KiB

Open AccessFeature PaperArticle

Using InSAR Coherence for Investigating the Interplay of Fluvial and Aeolian Features in Arid Lands: Implications for Groundwater Potential in Egypt

by Ahmed Gaber, Mohamed Abdelkareem, Ismail S. Abdelsadek, Magaly Koch and Farouk El-Baz

Remote Sens. 2018, 10(6), 832; https://doi.org/10.3390/rs10060832 - 25 May 2018

Cited by 35 | Viewed by 6820

Abstract

Despite the fact that the Sahara is considered the most arid region on Earth, it has witnessed prolonged fluvial and aeolian depositional history, and might harbor substantial fresh groundwater resources. Its ancient fluvial surfaces are, however, often concealed by aeolian deposits, inhibiting the discovery and mapping of potential groundwater recharge areas. However, recent advances in synthetic aperture radar (SAR) imaging offer a novel approach for detecting partially hidden and dynamic landscape features. Interferometry SAR coherence change detection (CCD) is a fairly recent technique that allows the mapping of very slight surface changes between multidate SAR images. Thus, this work explores the use of the CCD method to investigate the fluvial and aeolian morphodynamics along two paleochannels in Egypt. The results show that during wetter climates, runoff caused the erosion of solid rocks and the rounding of sand-sized grains, which were subsequently deposited in depressions further downstream. As an alternating dry climate prevailed, the sand deposits were reshaped into migrating linear dunes. These highly dynamic features are depicted on the CCD image with very low coherence values close to 0 (high change), while the deposits within the associated ephemeral wadis show low to moderate coherence values ranging from 0.2 to 0.4 (high to moderate change), and the country rocks show a relative absence of change with high coherence values close to 1. These linear dunes crossed their parent’s stream courses and dammed the runoff to form lakes during rainy seasons. Part of the dammed surface water would have infiltrated the ground to recharge the permeable wadi deposits. The alternation of fluvial and aeolian depositional environments produced unique hydromorphometrically trapped lakes that are very rare in arid regions, but of great interest because of their significance to groundwater recharge. Full article

(This article belongs to the Special Issue Remote Sensing of Arid/Semiarid Lands)

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15 pages, 9929 KiB

Open AccessArticle

Spatiotemporal Analysis of Landsat-8 and Sentinel-2 Data to Support Monitoring of Dryland Ecosystems

by Neal J. Pastick, Bruce K. Wylie and Zhuoting Wu

Remote Sens. 2018, 10(5), 791; https://doi.org/10.3390/rs10050791 - 19 May 2018

Cited by 49 | Viewed by 8145

Abstract

Drylands are the habitat and source of livelihood for about two fifths of the world’s population and are highly susceptible to climate and anthropogenic change. To understand the vulnerability of drylands to changing environmental conditions, land managers need to effectively monitor rates of past change and remote sensing offers a cost-effective means to assess and manage these vast landscapes. Here, we present a novel approach to accurately monitor land-surface phenology in drylands of the Western United States using a regression tree modeling framework that combined information collected by the Operational Land Imager (OLI) onboard Landsat 8 and the Multispectral Instrument (MSI) onboard Sentinel-2. This highly-automatable approach allowed us to precisely characterize seasonal variations in spectral vegetation indices with substantial agreement between observed and predicted values (R² = 0.98; Mean Absolute Error = 0.01). Derived phenology curves agreed with independent eMODIS phenological signatures of major land cover types (average r-value = 0.86), cheatgrass cover (average r-value = 0.96), and growing season proxies for vegetation productivity (R² = 0.88), although a systematic bias towards earlier maturity and senescence indicates enhanced monitoring capabilities associated with the use of harmonized Landsat-8 Sentinel-2 data. Overall, our results demonstrate that observations made by the MSI and OLI can be used in conjunction to accurately characterize land-surface phenology and exclusion of imagery from either sensor drastically reduces our ability to monitor dryland environments. Given the declines in MODIS performance and forthcoming decommission with no equivalent replacement planned, data fusion approaches that integrate observations from multispectral sensors will be needed to effectively monitor dryland ecosystems. While the synthetic image stacks are expected to be locally useful, the technical approach can serve a wide variety of applications such as invasive species and drought monitoring, habitat mapping, production of phenology metrics, and land-cover change modeling. Full article

(This article belongs to the Special Issue Remote Sensing of Arid/Semiarid Lands)

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21 pages, 14664 KiB

Open AccessArticle

Water Loss Due to Increasing Planted Vegetation over the Badain Jaran Desert, China

by Xunhe Zhang, Nai’ang Wang, Zunyi Xie, Xuanlong Ma and Alfredo Huete

Remote Sens. 2018, 10(1), 134; https://doi.org/10.3390/rs10010134 - 18 Jan 2018

Cited by 21 | Viewed by 7000

Abstract

Water resources play a vital role in ecosystem stability, human survival, and social development in drylands. Human activities, such as afforestation and irrigation, have had a large impact on the water cycle and vegetation in drylands over recent years. The Badain Jaran Desert (BJD) is one of the driest regions in China with increasing human activities, yet the connection between human management and the ecohydrology of this area remains largely unclear. In this study, we firstly investigated the ecohydrological dynamics and their relationship across different spatial scales over the BJD, using multi-source observational data from 2001 to 2014, including: total water storage anomaly (TWSA) from Gravity Recovery and Climate Experiment (GRACE), normalized difference vegetation index (NDVI) from Moderate Resolution Imaging Spectroradiometer (MODIS), lake extent from Landsat, and precipitation from in situ meteorological stations. We further studied the response of the local hydrological conditions to large scale vegetation and climatic dynamics, also conducting a change analysis of water levels over four selected lakes within the BJD region from 2011. To normalize the effect of inter-annual variations of precipitation on vegetation, we also employed a relationship between annual average NDVI and annual precipitation, or modified rain-use efficiency, termed the RUE_mo. A focus of this study is to understand the impact of the increasing planted vegetation on local ecohydrological systems over the BJD region. Results showed that vegetation increases were largely found to be confined to the areas intensely influenced by human activities, such as croplands and urban areas. With precipitation patterns remaining stable during the study period, there was a significant increasing trend in vegetation greenness per unit of rainfall, or RUE_mo over the BJD, while at the same time, total water storage as measured by satellites has been continually decreasing since 2003. This suggested that the increased trend in vegetation and apparent increase in RUE_mo can be attributed to the extraction of ground water for human-planted irrigated vegetation. In the hinterland of the BJD, we identified human-planted vegetation around the lakes using MODIS observations and field investigations. Four lake basins were chosen to validate the relationship between lake levels and planted vegetation. Our results indicated that increasing human-planted vegetation significantly increased the water loss over the BJD region. This study highlights the value of combining observational data from space-borne sensors and ground instruments to monitor the ecohydrological dynamics and the impact of human activities on water resources and ecosystems over the drylands. Full article

(This article belongs to the Special Issue Remote Sensing of Arid/Semiarid Lands)

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4447 KiB

Open AccessArticle

Photochemical Reflectance Index (PRI) for Detecting Responses of Diurnal and Seasonal Photosynthetic Activity to Experimental Drought and Warming in a Mediterranean Shrubland

by Chao Zhang, Iolanda Filella, Daijun Liu, Romà Ogaya, Joan Llusià, Dolores Asensio and Josep Peñuelas

Remote Sens. 2017, 9(11), 1189; https://doi.org/10.3390/rs9111189 - 20 Nov 2017

Cited by 40 | Viewed by 8600

Abstract

Climatic warming and drying are having profound impacts on terrestrial carbon cycling by altering plant physiological traits and photosynthetic processes, particularly for species in the semi-arid Mediterranean ecosystems. More effective methods of remote sensing are needed to accurately assess the physiological responses and seasonal photosynthetic activities of evergreen species to climate change. We evaluated the stand reflectance in parallel to the diurnal and seasonal changes in gas exchange, fluorescence and water contents of leaves and soil for a Mediterranean evergreen shrub, Erica multiflora, submitted to long-term experimental warming and drought. We also calculated a differential photochemical reflectance index (ΔPRI, morning PRI subtracted from midday PRI) to assess the diurnal responses of photosynthesis (ΔA) to warming and drought. The results indicated that the PRI, but not the normalized difference vegetation index (NDVI), was able to assess the seasonal changes of photosynthesis. Changes in water index (WI) were consistent with seasonal foliar water content (WC). In the warming treatment, ΔA value was higher than control in winter but ΔYield was significantly lower in both summer and autumn, demonstrating the positive effect of the warming on the photosynthesis in winter and the negative effect in summer and autumn, i.e., increased photosynthetic midday depression in summer and autumn, when temperatures were much higher than in winter. Drought treatment increased the midday depression of photosynthesis in summer. Importantly, ΔPRI was significantly correlated with ΔA both under warming and drought, indicating the applicability of ΔPRI for tracking the midday depression of photosynthetic processes. Using PRI and ΔPRI to monitor the variability in photosynthesis could provide a simple method to remotely sense photosynthetic seasonality and midday depression in response to ongoing and future environmental stresses. Full article

(This article belongs to the Special Issue Remote Sensing of Arid/Semiarid Lands)

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11336 KiB

Open AccessArticle

Assessing a Multi-Platform Data Fusion Technique in Capturing Spatiotemporal Dynamics of Heterogeneous Dryland Ecosystems in Topographically Complex Terrain

by Peter J. Olsoy, Jessica Mitchell, Nancy F. Glenn and Alejandro N. Flores

Remote Sens. 2017, 9(10), 981; https://doi.org/10.3390/rs9100981 - 22 Sep 2017

Cited by 13 | Viewed by 6185

Abstract

Water-limited ecosystems encompass approximately 40% of terrestrial land mass and play a critical role in modulating Earth’s climate and provisioning ecosystem services to humanity. Spaceborne remote sensing is a critical tool for characterizing ecohydrologic patterns and advancing the understanding of the interactions between atmospheric forcings and ecohydrologic responses. Fine to medium scale spatial and temporal resolutions are needed to capture the spatial heterogeneity and the temporally intermittent response of these ecosystems to environmental forcings. Techniques combining complementary remote sensing datasets have been developed, but the heterogeneous nature of these regions present significant challenges. Here we investigate the capacity of one such approach, the Spatial and Temporal Adaptive Reflectance Fusion Model (STARFM) algorithm, to map Normalized Difference Vegetation Index (NDVI) at 30 m spatial resolution and at a daily temporal resolution in an experimental watershed in southwest Idaho, USA. The Dry Creek Experimental Watershed captures an ecotone from a sagebrush steppe ecosystem to evergreen needle-leaf forests along an approximately 1000 m elevation gradient. We used STARFM to fuse NDVI retrievals from the MODerate-resolution Imaging Spectroradiometer (MODIS) and Landsat during the course of a growing season (April to September). Specifically we input to STARFM a pair of Landsat NDVI retrievals bracketing a sequence of daily MODIS NDVI retrievals to yield daily estimates of NDVI at resolutions of 30 m. In a suite of data denial experiments we compared these STARFM predictions against corresponding Landsat NDVI retrievals and characterized errors in predicted NDVI. We investigated how errors vary as a function of vegetation functional type and topographic aspect. We find that errors in predicting NDVI were highest during green-up and senescence and lowest during the middle of the growing season. Absolute errors were generally greatest in tree-covered portions of the watershed and lowest in locations characterized by grasses/bare ground. On average, relative errors in predicted average NDVI were greatest in grass/bare ground regions, on south-facing aspects, and at the height of the growing season. We present several ramifications revealed in this study for the use of multi-sensor remote sensing data for the study of spatiotemporal ecohydrologic patterns in dryland ecosystems. Full article

(This article belongs to the Special Issue Remote Sensing of Arid/Semiarid Lands)

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3345 KiB

Open AccessArticle

Estimating Daily Reference Evapotranspiration in a Semi-Arid Region Using Remote Sensing Data

by Peshawa M. Najmaddin, Mick J. Whelan and Heiko Balzter

Remote Sens. 2017, 9(8), 779; https://doi.org/10.3390/rs9080779 - 29 Jul 2017

Cited by 33 | Viewed by 7998

Abstract

Estimating daily evapotranspiration is challenging when ground observation data are not available or scarce. Remote sensing can be used to estimate the meteorological data necessary for calculating reference evapotranspiration ETₒ. Here, we assessed the accuracy of daily ETₒ estimates derived from remote sensing (ETₒ_-RS) compared with those derived from four ground-based stations (ETₒ_-G) in Kurdistan (Iraq) over the period 2010–2014. Near surface air temperature, relative humidity and cloud cover fraction were derived from the Atmospheric Infrared Sounder/Advanced Microwave Sounding Unit (AIRS/AMSU), and wind speed at 10 m height from MERRA (Modern-Era Retrospective Analysis for Research and Application). Four methods were used to estimate ETₒ: Hargreaves–Samani (HS), Jensen–Haise (JH), McGuinness–Bordne (MB) and the FAO Penman Monteith equation (PM). ETₒ_-G (PM) was adopted as the main benchmark. HS underestimated ETₒby 2%–3% (R² = 0.86 to 0.90; RMSE = 0.95 to 1.2 mm day⁻¹ at different stations). JH and MB overestimated ETₒby 8% to 40% (R²= 0.85 to 0.92; RMSE from 1.18 to 2.18 mm day⁻¹). The annual average values of ETₒ estimated using RS data and ground-based data were similar to one another reflecting low bias in daily estimates. They ranged between 1153 and 1893 mm year⁻¹ for ETₒ_-G and between 1176 and 1859 mm year⁻¹ for ETₒ_-RS for the different stations. Our results suggest that ETₒ_-RS(HS)can yield accurate and unbiased ETₒestimates for semi-arid regions which can be usefully employed in water resources management. Full article

(This article belongs to the Special Issue Remote Sensing of Arid/Semiarid Lands)

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7776 KiB

Open AccessFeature PaperArticle

Minimizing the Residual Topography Effect on Interferograms to Improve DInSAR Results: Estimating Land Subsidence in Port-Said City, Egypt

by Ahmed Gaber, Noura Darwish and Magaly Koch

Remote Sens. 2017, 9(7), 752; https://doi.org/10.3390/rs9070752 - 21 Jul 2017

Cited by 25 | Viewed by 7304

Abstract

The accurate detection of land subsidence rates in urban areas is important to identify damage-prone areas and provide decision-makers with useful information. Meanwhile, no precise measurements of land subsidence have been undertaken within the coastal Port-Said City in Egypt to evaluate its hazard in relationship to sea-level rise. In order to address this shortcoming, this work introduces and evaluates a methodology that substantially improves small subsidence rate estimations in an urban setting. Eight ALOS/PALSAR-1 scenes were used to estimate the land subsidence rates in Port-Said City, using the Small BAse line Subset (SBAS) DInSAR technique. A stereo pair of ALOS/PRISM was used to generate an accurate DEM to minimize the residual topography effect on the generated interferograms. A total of 347 well distributed ground control points (GCP) were collected in Port-Said City using the leveling instrument to calibrate the generated DEM. Moreover, the eight PALSAR scenes were co-registered using 50 well-distributed GCPs and used to generate 22 interferogram pairs. These PALSAR interferograms were subsequently filtered and used together with the coherence data to calculate the phase unwrapping. The phase-unwrapped interferogram-pairs were then evaluated to discard four interferograms that were affected by phase jumps and phase ramps. Results confirmed that using an accurate DEM (ALOS/PRISM) was essential for accurately detecting small deformations. The vertical displacement rate during the investigated period (2007–2010) was estimated to be −28 mm. The results further indicate that the northern area of Port-Said City has been subjected to higher land subsidence rates compared to the southern area. Such land subsidence rates might induce significant environmental changes with respect to sea-level rise. Full article

(This article belongs to the Special Issue Remote Sensing of Arid/Semiarid Lands)

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