Bridging the national data gap with Google earth engine and landsat imagery by developing annual land cover for Afghanistan.

The national-level land cover database is essential to sustainable landscape management, environmental protection, and food security. In Afghanistan, the existing national-level land cover data from 1972, 1993, and 2010 relied on satellite data from diverse sensors adopted three different land cover classification systems. This inconsistent land cover map across the various years leads to the challenge of assessing landscape changes that are crucial for management efforts. To address this challenge, a 19-year national-level land cover dataset from 2000 to 2018 was developed for the first time to aid policy development, settlement planning, and the monitoring of forests and agriculture across time. In the development of the 19 year span of land cover data products, a state-of-the-art remote sensing approach, employing a harmonized classification scheme was implemented through the utilization of Google Earth Engine (GEE). Publicly accessible Landsat imagery and additional geospatial covariates were integrated to produce an annual land cover database for Afghanistan. The generated dataset bridges historical data gaps and facilitates robust land cover change information. The annual land cover database is now accessible through https://rds.icimod.org/. This repository ensures that the annual land cover data is readily available to all users interested in comprehending the dynamic land cover changes happening in Afghanistan.

"Don't Have A Cow, Man!": Recognizing Herd Share Agreements for Raw Milk.

Dissatisfaction with the industrial model of food production has caused many consumers to seek out food produced on local, family-scale farms that use U.S. Department of Agriculture certified organic or other sustainable practices to grow their food and raise their livestock. While almost all of the types of food that are available at the grocery store can also be found at the local farmers market, one food that is difficult to find in many states is raw milk­that is, milk that has not undergone pasteurization (heat treatment). This difficulty lies in the fact that most states prohibit the direct retail sale of raw milk to the final consumer because public health officials and state legislators fear that raw milk may contain bacteria harmful to human health such as E. coli, Campylobacter, and Listeria. However, some consumers reject these warnings and instead believe that raw milk possesses both nutritional and medicinal qualities. Indeed, an ever-increasing body of scientific research published in peer-reviewed journals supports the claim that raw milk consumption can mitigate or prevent some allergies and infections, especially in young children. In order for consumers to obtain raw milk in states where its sale is prohibited, some consumers have entered into arrangements with farmers known as "herd sharing," through which the consumer effectively becomes an owner of the herd of cows or goats. For the price of the share and a monthly boarding fee, the shareholder can receive a weekly distribution of the herd's primary dividend, namely the raw milk. Several states expressly permit this practice while most are silent and still a few prohibit it outright. The three courts in the United States that have ruled on herd share agreements have split, with two courts rejecting the agreements as a circumvention of the state's prohibition on the sale of raw milk, and the other court assuming the agreement's validity in light of the state's failure to adequately define "sale." I argue that courts should consistently uphold properly written herd share agreements where such agreements are not prohibited because such agreements are deeply rooted in the longstanding practice of shared ownership agreements for livestock found throughout the agriculture industry. Furthermore, raw milk has been found by some researchers to be a low-risk food that may actually have some nutritional and even medicinal qualities not found in pasteurized milk. And to the extent that raw milk consumption could cause harm, the risk of a large-scale outbreak from milk obtained through a herd share is slight considering how few participants are in any given herd share.

Evaluating climate variability and pumping effects in statistical analyses.

As development of ground water resources reaches the limits of sustainability, it is likely that even small changes in inflow, outflow, or storage will have economic or environmental consequences. Anthropogenic impacts of concern may be on the scale of natural variability, making it difficult to distinguish between the two. Under these circumstances, we believe that it is important to account for effects from both ground water development and climate variability. We use several statistical methods, including trend analysis, cluster analysis, and time series analysis with seasonal decomposition, to identify climate and anthropogenic effects in regional ground water levels and spring discharge in southern Nevada. We discuss the parameterization of climate and suggest that the relative importance of various measures of climate provides information about the aquifer system response to climate. In our system, which may be characteristic of much of the arid southwestern United States, ground water levels are much more responsive to wet years than to dry years, based on the importance of selected climate parameters in the regression. Using cluster analysis and time series seasonal decomposition, we relate differences in amplitude and phase in the seasonal signal to two major forcings--climate and pumping--and distinguish between a regional recharge response to an extremely wet year and a seasonal pumping/evapotranspiration response that decays with distance from the pumping center. The observed spring discharge data support our hypothesis that regional spring discharge, particularly at higher elevation springs, is sensitive to relatively small ground water level changes.