Satellite-Based Monitoring of Primary Production in a Mediterranean Islet Post Black Rat Eradication

Invasive rodents have a detrimental impact on terrestrial ecosystem functioning, this is often exacerbated on small islands. Rat eradication campaigns are often used to deal with this environmental perturbation given their classification as invasive species. Studies assessing the effects of rodent control at ecosystem scale are scarce and thus little is known about the subsequent functional response of vegetation subsequent to rat control. In this work, we use remote sensing to assess the effects of black rat (Rattus rattus) eradication on Mediterranean vegetation productivity in the Sa Dragonera Islet, Mallorca (Spain). Rats feed on seeds, sprouts, and leaves of woody vegetation and hence we expect primary production to increase nine years after the rodenticide campaign. The Break Detection approach for additive season and trend (BFAST method) was adopted to examine changes in vegetation density before and after the eradication campaign in Sa Dragonera Islet (Balearic Islands), using a temporal series of monthly NDVI data extracted from Landsat imagery. The same temporal trends were examined for a control zone where no rat eradication took place, in order to control for weather-driven changes. The results of this study revealed changes across the 21-year monthly NDVI time series. However, the dates, magnitude, and trend of these changes could not be explicitly attributed to the action of rats, when compared to the historical changes on the islet and the changes found to co-occur within the control zone. These finding could, perhaps, be explained by the high resilience of Mediterranean shrubs to browsing including that of rat invasion. However, the results from the study appear to show that rat damage on specific plant species, with little contribution to global NDVI values, would be overshadowed by the effects of broader environmental factors in this remote sensing approach. The results suggest that the current passive restoration scheme imposed following eradication is not sufficient for effective ecosystem restoration.

Assessment of Recent Flow, and Calving Rate of the Perito Moreno Glacier Using LANDSAT and SENTINEL2 Images

We mapped flow velocity and calving rates of the iconic Perito Moreno Glacier (PMG), belonging to the Southern Patagonian Icefield (SPI) in the Argentinian Patagonia. We tracked PMG from 2001 to 2017, focusing mostly upon the latest images from 2016–2017. PMG delivers about ca. 106 m3 day−1 of ice in the Lago Argentino, and its front periodically reaches the Peninsula Magallanes. Therein, the PMG causes an ice-dam, clogging Brazo Rico channel, and lifting water level by about 10 m, until ice-dam failure, normally occurring in March. Here, we used 36 pairs of satellite images with a resolution of 10 m (SENTINEL2, visible, 9 pairs of images) and 15 m (LANDSAT imagery, panchromatic, 27 pairs of images) to calculate surface velocity (VS). We used Orientation Correlation technique, implemented via the ImGRAFT® TemplateMatch tool. Calving rates were then calculated with two methods, namely, (i) M1, by ice flow through the glacier front, and (ii) M2, by ice flow at 7.5 km upstream of the front minus ablation losses. Surface velocity ranged from about 4 m day−1 in the accumulation area to about 2 m day−1 in the calving front, but it is variable seasonally with maxima in the summer (December–January–February). Calving rate (CRM) ranges from 7.72 × 105 ± 32% to 8.76 × 105 ± 31% m3 day−1, in line with recent studies, also with maxima in the summer. We found slightly lower flow velocity and calving rates than previously published values, but our estimates cover a different period, and a generally large uncertainty in flow assessment suggests a recent overall stability of the glacier.

A Diachronic Analysis of a Changing Landscape on the Duero River Borderlands of Spain and Portugal Combining Remote Sensing and Ethnographic Approaches

The Arribes del Duero region spans the border of both Spain and Portugal along the Duero River. On both sides of the border, the region boasts unique human-influenced ecosystems. The borderland landscape is dotted with numerous villages that have a history of maintaining and managing an agrosilvopastoral use of the land. Unfortunately, the region in recent decades has suffered from massive outmigration, resulting in significant rural abandonment. Consequently, the once-maintained landscape is evolving into a more homogenous vegetative one, resulting in a greater propensity for wildfires. This study utilizes an interdisciplinary, integrated approach of “bottom up” ethnography and “top down” remote sensing data from Landsat imagery, to characterize and document the diachronic vegetative changes on the landscape, as they are perceived by stakeholders and satellite spectral analysis. In both countries, stakeholders perceived the current changes and threats facing the landscape. Remote sensing analysis revealed an increase in forest cover throughout the region, and more advanced, drastic change on the Spanish side of the study area marked by wildfire and a rapidly declining population. Understanding the evolution and history of this rural landscape can provide more effective management and its sustainability.

GISD30: global 30-m impervious surface dynamic dataset from 1985 to 2020 using time-series Landsat imagery on the Google Earth Engine platform

Accurately mapping impervious surface dynamics has great scientific significance and application value for urban sustainable development research, anthropogenic carbon emission assessment and global ecological environment modeling. In this study, a novel and accurate global 30 m impervious surface dynamic dataset (GISD30) for 1985 to 2020 was produced using the spectral generalization method and time-series Landsat imagery, on the Google Earth Engine cloud-computing platform. Firstly, the global training samples and corresponding reflectance spectra were automatically derived from prior global 30 m land-cover products after employing the multitemporal compositing method and relative radiometric normalization. Then, spatiotemporal adaptive classification models, trained with the migrated reflectance spectra of impervious surfaces from 2020 and pervious surface samples in the same epoch for each 5° × 5° geographical tile, were applied to map the impervious surface in each period. Furthermore, a spatiotemporal consistency correction method was presented to minimize the effects of independent classification errors and improve the spatiotemporal consistency of impervious surface dynamics. Our global 30 m impervious surface dynamic model achieved an overall accuracy of 91.5 % and a kappa coefficient of 0.866 using 18,540 global time-series validation samples. Cross-comparisons with four existing global 30 m impervious surface products further indicated that our GISD30 dynamic product achieved the best performance in capturing the spatial distributions and spatiotemporal dynamics of impervious surfaces in various impervious landscapes. The statistical results indicated that the global impervious surface has doubled in the past 35 years, from 5.116 × 105 km2 in 1985 to 10.871 × 105 km2 in 2020, and Asia saw the largest increase in impervious surface area compared to other continents, with a total increase of 2.946 × 105 km2. Therefore, it was concluded that our global 30 m impervious surface dynamic dataset is an accurate and promising product, and could provide vital support in monitoring regional or global urbanization as well as in related applications. The global 30 m impervious surface dynamic dataset from 1985 to 2020 generated in this paper is free to access at http://doi.org/10.5281/zenodo.5220816 (Liu et al., 2021b).

Watershed Health Changes based on Vegetated Land Cover in the Upper Citarum Watershed, West Java, Province, Indonesia

The increase in built-up land and the decrease in vegetated land due to human activities have worsened watershed health from time to time. This study aims to assess the watershed’s health and changes every ten years based on the percentage of vegetated land cover except agricultural land in the Upper Citarum watershed, West Java. Land cover information was obtained from the processing of Landsat imagery in 1990, 2000, 2010, and 2020 based on remote sensing using the supervised classification method. The watershed health level is determined by calculating the percentage of vegetated land cover of 173 catchments. The results show that the area of the vegetated land cover decreased from 1990 to 2000, then increased from 2000 to 2010, and decreased again from 2010 to 2020. Changes in the area of vegetated land in each period of the year affect the health level of the watershed in a spatiotemporal manner. Although these changes occur in a fluctuating manner, the number of unhealthy catchments in the Upper Citarum watershed is increasing, especially in the Ci Kapundung sub-watershed in the north and Ci Sangkuy in the south.

Remote Sensing in Predicting Development Patterns of Built-up Land

Indonesia is a developing country whose construction and development are centered on the island of Java, especially in West Java Province. Sukabumi City is one of the areas in West Java. The development of urban areas is expanding due to various human needs to carry out the construction of buildings. Remote sensing that can be used to store developments with multi-temporal analysis with materials is Landsat imagery from 2001 to 2020. The method used is the Normalized Difference Built-up Index (NDBI). The purpose of this study is to map the development of the built-up land from year to year and predict the following years. The results of the research on the significant changes in built-up land occurred between 2013-2020, while from 2001 to 2013 there was not much change. Based on the research results, the total growth of built-up land was 1.539% per year with a population growth rate of 1.4% per year. The results of the analysis show that the area of ​​land built in Sukabumi City in 2028 is 186,7194 km2 or has increased by 21,2808 km2 since 2020.

The Response of Brewster Glacier to Five Decades of Climate

<p>Small perturbations in climate can produce measurable changes to the size of a glacier. Documenting such changes is important for quantifying water storage changes, and understanding glacier-climate interactions. By using all available geodetic data, such as Landsat imagery, Shuttle Radar Topography Mission, GNSS and photogrammetric techniques, as well as ground penetrating radar for the construction of a bed DEM, it is found that Brewster Glacier decreased in volume from 1967 to 2017, losing ∼56% of its volume, with a period of volume increase of ∼10% from 1986 to 1997. The overall pattern of geodetic mass balance is similar to the glaciological mass balance record, however, the geodetic method tends to show more negative values by an average of ∼0.6 m w.e. Contrary to many other New Zealand glaciers, which experienced an advance from 1983 to 2008, Brewster Glacier continued to retreat by 390 m during the study period, at an average rate of 7.8 m a⁻¹, but at a significantly reduced rate of ∼2 m a⁻¹ from 1997 until 2005. By comparing the records of Brewster Glacier and Fox and Franz Josef glaciers, we explore the differences in response and reaction times resulting from glacier area-altitude distribution, and climatic setting. Furthermore, DEMs produced by this study are now available for use by a New Zealand wide glacier monitoring programme.</p>