Science Excursion:


* From Aspen Global Change Institute 1992–Ground Truth Studies


Students will recognize and explain the differences between satellite images and topographic maps; identify different land cover types on satellite images and relate them to the corresponding areas on the topographic maps; and explain the relationship between cover types, water flow, and water quality.


Land cover, in remote sensing, refers to the primary reflective or emitting surface detected by sensors. Land cover differs from forest or vegetative cover in that it is all inclusive of everything detected by the sensors: Trees, fields, houses, lawns, lakes, roads and parking lots, etc. Land cover significantly influences water flow and water quality. Because vegetation intercepts precipitation with its many surfaces, it slows and decreases runoff–the flow of water across the land surface. Runoff is faster and greater on bare ground or paved surfaces. Vegetation cover permits more infiltration, or soaking of precipitation into the ground, because root channels keep the soil loose and decaying organic material acts as a sponge. Impermeable paved surfaces do not allow infiltration for recharge of the soil moisture and groundwater reserves.

Because land cover influences water flow across a watershed, it directly impacts water quality in the water-course. If vegetation is removed, precipitation hits the soil surface more energetically and runs off more quickly, carrying with it greater amounts of soil and plant nutrients. This results in increased erosion, watercourse turbidity, and decreased water quality. Eventually, the suspended soil particles settle to the bottom of the water-course as sediment, perhaps suffocating riverbed organisms or filling in reservoirs behind dams. On the other hand, sediments may settle during receding seasonal floods renewing the fertility of riverside agricultural fields. Runoff may enter a watercourse at a different temperature than the water already there. A temperature change may benefit some organisms living in the water while making it less suitable for others. For example, trout require cold water, but catfish prefer warmer water. Runoff may bring bacteria, pesticides, or toxic chemicals from the land into watercourses, thus decreasing water quality. Mining, road construction, housing develop-ments, industrial expansion, and the conversion of forests to crop land all decrease the amount of vegetative land cover. Reforestation, mine reclamation, residential landscaping laws, soil conservation ordinances, the creation of parklands, and the cultivation of perennial instead of annual crops all increase vegetative land cover. Converting land cover near a watercourse can directly affect water quality. Removing trees shading a watercourse will increase water temperature, while planting trees will decrease water temperature, wind speed, and evaporation.

In this activity, students will use remotely sensed images and topographic maps to classify land cover types in their watershed. A field trip to specific sites will allow the students to “ground truth” cover types found on the remotely sensed images and infer that information to other sites not visited. The purpose of this activity is to teach students how information gained from a small sample of sites can be used to interpret remotely sensed images and to make educated guesses as to the extent of similar types of land cover within their watershed.

Maps are generalizations of reality, often containing numerical or alphabetical information, as well as selected and adjusted graphical detail. Within limits, different objects, such as areas of different land cover, can be distinguished on remotely sensed images because they each have a unique spectral signature. That is, each type of vegetation or material covering the land reflects or emits a unique radiation pattern that is sensed and re-corded. To a certain degree, then, it is possible to differentiate between different types of land cover, thus corn fields, pine forests, open water and concrete building may all appear differently on remotely sense images. There are limitations to what can be interpreted from any remotely sensed image, however. While it will almost always be possible to tell a paved parking lot from an agricultural field, it may be difficult to determine whether a field contains corn, barley,or wheat, or to distinguish a marsh from a rice field without more information than one satellite photo contains.

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