Estimation of instantaneous air temperature above vegetation and soil surfaces from Landsat 7 ETM+ data in northern Germany

The temperature–vegetation index method (TVX method, also called contextual method) for the area-wide mapping of instantaneous air temperature is adopted for use with Landsat 7 Enhanced Thematic Mapper Plus (ETM+) data. The method requires multispectral data consisting of bands in the red, near-infrared and thermal spectral regions, and no additional data. The approach is complemented with an iterative filtering routine for eliminating outliers and an interpolation algorithm for filling data gaps. The adopted method is applied to a multi-temporal dataset of nine ETM+ scenes, covering large parts of north-eastern Germany including the Durable Environmental Multidisciplinary Monitoring Information Network (DEMMIN) test site. Thus, for the first time the TVX method is applied to fine spatial resolution data and a central European region. The satellite-derived air temperatures (60 m spatial resolution) are compared with in situ measurements, showing an average error of about 3 K (root mean square, RMS), whereas the mean error in land surface temperature (LST) estimation is about 2 K. The results compare well with the in situ values throughout all seasons. The accuracy of about 3 K is in line with previously reported results for the TVX method (employing medium spatial resolution data) as well as for physically based approaches (ecosystem- or energy-balance models). Only remote sensing models incorporating in situ air temperature (as training data for neural networks or in multiple regression analysis) are reported to perform better in terms of RMS deviations. In the past, overestimation of air temperature by the TVX method was repeatedly observed. It is shown that the remote sensing approach tends to under- or overestimate the in situ air temperatures, depending on the in situ measurement heights. In conjunction with the attempt to assign the satellite-derived air temperature to a certain height above ground, the possibility of a simple correction for reference height is investigated. Over- and underestimations larger than 2 K seem to reflect existing differences in temperature rather than calculation errors. Furthermore, the dependence of the derived air temperature spatial pattern on different moving window sizes is shown. Possible sources of errors and limitations of the approach are discussed in detail

Beiträge aus der Fernerkundung zur Bestimmung der Energiebilanz vegetationsbedeckter Landoberflächen

Die flächendeckende, räumlich differenzierte Modellierung der Energie- und Stoffflüsse an der Erdoberfläche erfordert flächendeckende Eingangsdaten wie z. B. zur Oberflächen- und Lufttemperatur sowie dem Bodenwärmestrom. Die kleinräumige Variabilität dieser Parameter kann mit konventionellen meteorologischen Messnetzen infolge der geringen Messpunktdichte nicht erfasst werden. Hier bietet die Fernerkundung neue Ansätze. Der vorliegende Beitrag demonstriert die Ableitung dieser Größen auf der Grundlage von Landsat 7 ETM+ Daten aus dem Jahre 2000

Drivers and Implications of Land Use/Land Cover Dynamics in Finchaa Catchment, Northwestern Ethiopia

Understanding the trajectories and extents of land use/land cover change (LULCC) is important to generate and provide helpful information to policymakers and development practitioners about the magnitude and trends of LULCC. This study presents the contributing factors of LULCC, the extent and implications of these changes for sustainable land use in the Finchaa catchment. Data from Landsat images 1987, 2002, and 2017 were used to develop the land use maps and quantify the changes. A supervised classification with the maximum likelihood classifier was used to classify the images. Key informant interviews and focused group discussions with transect walks were used for the socio-economic survey. Over the past three decades, agricultural land, commercial farm, built-up, and water bodies have increased while forestland, rangeland, grazing land, and swampy areas have decreased. Intensive agriculture without proper management practice has been a common problem of the catchment. Increased cultivation of steep slopes has increased the risk of erosion and sedimentation of nearby water bodies. Multiple factors, such as biophysical, socio-economic, institutional, technological, and demographic, contributed to the observed LULCC in the study area. A decline in agricultural yield, loss of biodiversity, extended aridity and drought, land and soil degradation, and decline of water resources are the major consequences of LULCC in the Finchaa catchment. The socio-economic developments and population growth have amplified the prolonged discrepancy between supply and demand for land and water in the catchment. More comprehensive and integrated watershed management policies will be indispensable to manage the risks

Prioritization of Sub-Watersheds to Sediment Yield and Evaluation of Best Management Practices in Highland Ethiopia, Finchaa Catchment

Excessive soil loss and sediment yield in the highlands of Ethiopia are the primary factors that accelerate the decline of land productivity, water resources, operation and function of existing water infrastructure, as well as soil and water management practices. This study was conducted at Finchaa catchment in the Upper Blue Nile basin of Ethiopia to estimate the rate of soil erosion and sediment loss and prioritize the most sensitive sub-watersheds using the Soil and Water Assessment Tool (SWAT) model. The SWAT model was calibrated and validated using the observed streamflow and sediment data. The average annual sediment yield (SY) in Finchaa catchment for the period 1990–2015 was 36.47 ton ha−1 yr−1 with the annual yield varying from negligible to about 107.2 ton ha−1 yr−1. Five sub-basins which account for about 24.83% of the area were predicted to suffer severely from soil erosion risks, with SY in excess of 50 ton ha−1 yr−1. Only 15.05% of the area within the tolerable rate of loss (below 11 ton ha−1yr−1) was considered as the least prioritized areas for maintenance of crop production. Despite the reasonable reduction of sediment yields by the management scenarios, the reduction by contour farming, slope terracing, zero free grazing and reforestation were still above the tolerable soil loss. Vegetative contour strips and soil bund were significant in reducing SY below the tolerable soil loss, which is equivalent to 63.9% and 64.8% reduction, respectively. In general, effective and sustainable soil erosion management requires not only prioritizations of the erosion hotspots but also prioritizations of the most effective management practices. We believe that the results provided new and updated insights that enable a proactive approach to preserve the soil and reduce land degradation risks that could allow resource regeneration

Beiträge aus der Fernerkundung zur Bereitstellung von Parametern für die agrarmeteorologische Prozessmodellierung

Die für eine Modellierung von Wasser- und Stoffkreisläufen benötigten Parameter unterliegen räumlich und zeitlich starken Schwankungen. Während durch in-situ Messungen die zeitliche Variabilität sehr gut erfasst werden kann, ist mit konventionellen Messnetzen eine räumlich ausreichend hoch aufgelöste Betrachtung nicht möglich. Hier kann die Fernerkundung flächenhafte Informationen beisteuern. Klimatologisch relevante Parameter können aus Fernerkundungsdaten abgeleitet werden. Mit geeigneten Algorithmen ist darüber hinaus die Bestimmung von Prozessgrößen, wie z.B. der Verdunstung, und damit die Entwicklung prozessorientierter Regionalisierungsansätze möglich. Schwerpunktmäßig werden Algorithmen zur Ableitung der Oberflächentemperatur und der Lufttemperatur aus Daten des Landsat 7 / ETM+ vorgestellt. Für die Berechnungen sind keine zusätzlichen in-situ Messdaten erforderlich, sie bilden jedoch die Validationsgrundlage. Die Vorgehensweise bei der Validierung der Berechnungsansätze wird erläutert. Erste Ergebnisse zeigen die perspektivisch erreichbaren Genauigkeiten einer derartigen Parametergewinnung. Für die Zukunft ist eine automatische Prozessierung von Satellitendaten zur Bereitstellung von agrarmeteorologischen Parametern geplant

Nitrate Occurrence in Groundwater: A Case Study from Haryana

Groundwater and soil samples were collected to determine NO)\u27 and N Level at different locations in two villages and to investigate probable reasons for the occurrence of high nitrate concentration in groundwater. The soil of the study area was loamy sand throughout the profile up to 15 m except sandy loam at depth of 8. I to 10.8 m. All the groundwater samples collected during different time periods (pre-monsoon and post-monsoon) showed nitrate concentration of about more than twice the maximum acceptable nitrate concentration for drinking water standards (45 mg L·\u27). Water quality with respect to nitrate concentration in the pumped groundwater was determined for different pumping rates and time periods after the start of pumping. The nitrate concentration did not change considerably with the discharge and time during the pumping. Lower nitrate concentration (1.44 me L\u27) in groundwater was observed at shallow depth (5.45- 8.1 m) as compared to 1.56 me L-\u27 in relatively deep (10.8 to 15 m) groundwater. Total nitrogen content in subsurface profile to a depth of 15 m was found to vary from 0.13 to 0.18%. Wide variation in nitrate content (56.19 to 91.36 mg L-t) was observed among tubewell water of two contiguous villages